text
stringlengths 14
5.77M
| meta
dict | __index_level_0__
int64 0
9.97k
⌀ |
|---|---|---|
{"url":"http:\/\/openstudy.com\/updates\/506074b9e4b02e139410c8f2","text":"1. andriod09 Group Title\n\n|dw:1348498599367:dw| ik what the answers are, i just need help finding how to get them They are 5\", 12\", and 13\"\n\nThe Theorem is a^2 + b^2 = c^2 Where a and b are sides of the right triangle and c is the hypotenuse of the right triangle.\n\n3. andriod09 Group Title\n\nik the thirum, i just havn't done it in about 3 years.\n\nOk. Let a = x and b = x+7 therefore, (x)^2 + (x+7)^2 = (8+x)^2\n\n5. andriod09 Group Title\n\nokay, then what?\n\n6. andriod09 Group Title\n\n7. andriod09 Group Title\n\n@cshalvey @Callisto @Yahoo!\n\n8. Yahoo! Group Title\n\n$(x+8)^2 = x^2 + (x+7)^2$\n\n9. Yahoo! Group Title\n\nnw expand this....... $(a+b)^2 = a^2 + 2ab + b^2$\n\n10. andriod09 Group Title\n\nplease do not use the equation button i have a mathjax error and it annoys me. i see the slashes and brackets and braces.\n\n11. erica.d Group Title\n\n(x+8)^2=x^2+(x+7)^2\n\n12. Yahoo! Group Title\n\nlol.... ) (x)^2 + (x+7)^2 = (8+x)^2\n\n13. andriod09 Group Title\n\nokay?? then you do??????\n\n14. Callisto Group Title\n\nExpand the terms for both sides of the question, then simplify it. As Yahoo! mentioned, you can expand the term (a+b)^2 by using the identity (a+b)^2 = a^2 + 2ab + b^2. If you don't know where this identity comes from, you can simply perform multiplication for the term, i.e. (a+b)^2 = (a+b)(a+b), now expand it. What have you got for now?\n\n15. andriod09 Group Title\n\n|dw:1348501546848:dw|\n\n16. andriod09 Group Title\n\n@Callisto that made no sense to me. :c\n\n17. Callisto Group Title\n\nMay I know what made no sense to you?\n\n18. andriod09 Group Title\n\n\"Expand the terms for both sides of the question, then simplify it. As Yahoo! mentioned, you can expand the term (a+b)^2 by using the identity (a+b)^2 = a^2 + 2ab + b^2. If you don't know where this identity comes from, you can simply perform multiplication for the term, i.e. (a+b)^2 = (a+b)(a+b), now expand it.\"\n\n19. Callisto Group Title\n\nWhich part you don't understand?\n\n20. andriod09 Group Title\n\nthe expansion parts.\n\n21. Callisto Group Title\n\nDo you know how to expand (a+b)^2?\n\n22. andriod09 Group Title\n\nno. im homeschooled, i havn't even done pythagereum theory much.\n\n23. erica.d Group Title\n\nx^2+16x+64=x^2+x^2+14x+49\n\n24. Callisto Group Title\n\nThat is not Pyth. Thm. It's just simple multiplication of some factors. For instance, $x^2 = x \\times x$$x^3 = x \\times x \\times x$ Similarly, $(a+b)^2 = (a+b) \\times (a+b)$It can be expanded in this way: $(a+b)^2 = (a+b) \\times (a+b) = a(a+b) + b(a+b)$Can you further expand and simplify it?\n\n25. andriod09 Group Title\n\ni can not see the equations from the eqtation button!!!!!!!!!!\n\n26. Callisto Group Title\n\nequation button is for you to type latex...\n\n27. Callisto Group Title\n\n*type in latex\n\n28. andriod09 Group Title\n\nyes, but i see: $\\$$\\\\$][\\\\]$\\$ thats what i see, i see evey single slash, all the brackets, the braces, everything\n\n29. Callisto Group Title\n\n\\sqrt{x} = $$\\sqrt{x}$$ and so on.. You can try these on the equation button. Though, back to your question, are you still having trouble with your question?\n\n30. andriod09 Group Title\n\nyes. and i see the \\sqrt{x} = $$\\sqrt{x}$$ like i see all the braces, the terms for them, and everything like that. my mathjax thing isn't working atm\n\n31. Callisto Group Title\n\nCan you see what I've typed in latex?\n\n32. andriod09 Group Title\n\nno. i see the equation as if you write it with out the button, like i don't see the (x)^2 i see the ()^{} and things like that. and yes, i still am having problems with my problem\n\n33. Callisto Group Title\n\n|dw:1348503516047:dw|\n\n34. andriod09 Group Title\n\nyes.\n\n35. Callisto Group Title\n\nNow, can you expand a(a+b) +b(a+b) ?\n\n36. andriod09 Group Title\n\nhow?\n\n37. Callisto Group Title\n\nDistributing a into a+b and b into a+b\n\n38. andriod09 Group Title\n\nthen??\n\n39. Callisto Group Title\n\nExpand it first.\n\n40. andriod09 Group Title\n\nhow?\n\n41. Callisto Group Title\n\na(a+b) = a(a) + a(b) = a^2 + ab Can you try b(a+b) now?\n\n42. andriod09 Group Title\n\nis it: b(a+b)=b(a)+b(b)=b^2+ba?\n\n43. Callisto Group Title\n\nYes! Now combine them What is a(a+b) + b(a+b) ?\n\n44. andriod09 Group Title\n\n(a(a+b) = a(a) + a(b) = a^2 + ab)+(b(a+b)=b(a)+b(b)=b^2+ba)?\n\n45. Callisto Group Title\n\nNope not really.. can you try again?\n\n46. andriod09 Group Title\n\nwhat would it be then?\n\n47. andriod09 Group Title\n\n@ash2326\n\n48. andriod09 Group Title\n\n@ganeshie8\n\n49. andriod09 Group Title\n\n@Callisto\n\n50. andriod09 Group Title\n\n@ash2326\n\n51. andriod09 Group Title\n\n52. andriod09 Group Title\n\n|dw:1348510329568:dw|","date":"2014-07-23 08:02:40","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.8861767053604126, \"perplexity\": 8000.881079522854}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 5, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2014-23\/segments\/1405997877644.62\/warc\/CC-MAIN-20140722025757-00105-ip-10-33-131-23.ec2.internal.warc.gz\"}"}
| null | null |
Education to take spotlight at 17th COHSOD meeting
Oct 15, 2008 News 0
On 18-19 November, 2008, the Caribbean Community (CARICOM) Secretariat will again, after ten years, bring together Ministers of Education and their technical advisors for a comprehensive evaluation of the last ten years of the Community's work in education.
This Seventeenth Meeting of the CARICOM Council for Human and Social Development (COHSOD) with special focus on education has been described as "a meeting for frank discussion on how we can do things better in education within the Region."
The first COHSOD on education was held in 1998 under the Revised Treaty of Chaguaramas and, according to Dr Edward Greene, CARICOM Assistant Secretary-General for Human and Social Development, this COHSOD would be one with a difference.
"The difference is that we would not only be looking at the achievements over the last ten years but also looking at those things that did not get implemented for one reason or the other; and in so doing examine how we can expedite the rate of implementation…by understanding some of the reasons why some things did not get done in the first place," explained Dr Greene.
Dr Greene, who was briefing the Public Information Unit of the CARICOM Secretariat, further explained that since the first COHSOD on education in 1998, a number of policies and programmes in education had evolved and it was now time to assess their impact on the Community.
He added that every effort would be made to ensure that all Ministers of Education attend the meeting. He noted that with the change of Governments over the past ten years, there were seven new Ministers of Education who should view this as an opportune time to be engaged in action-planning for the future of education in the Region.
"There is a general perception that the Secretariat does not do things quickly," Dr Greene noted, "but sometimes the reasons are rooted at the country level, hence the necessity to engage the Ministers at the country level in meetings such as the COHSOD," he continued.
Besides the comprehensive evaluation to be undertaken, the COHSOD will engage Education Ministers in critically examining the implications of various components of the Economic Partnership Agreement (EPA) for education as well as ways in which the education sector could tap into the opportunities it holds for the Region.
Scheduled to be held here, the 17th COHSOD, Dr Greene stated, would also identify and discuss the elements in education that could help to promote the CARICOM Single Market and Economy, (CSME).
He cited the establishment of the Caribbean Vocation Qualification (CVQ) which was launched in 2007 as one of the standards which would help to facilitate the movement of skilled persons other than University graduates within the Region.
Teacher education and training will also be one of the agenda items Dr Greene anticipates will generate much discussion. The COHSOD is expected to examine the treatment of teacher education and training, especially in this age of New Information technologies: "We developed and promoted a science and technology policy in 1998 and we now need to assess how we have advanced on that and to address its relevance of those recommendations from 1998 to what we have to do in 2008," the Assistant Secretary-General explained.
In addition, Dr Greene noted that "the new dimension of teacher education means coming to grips with the sociology of the environment and exploring distance education to reach the perceived 'un-reachable." As a result, the 17th COHSOD will also review the work of the Caribbean Knowledge Learning Network (CKLN) which was established in 2004 to foster the upgrading of tertiary institutions across the Region in an effort to increase their ability to use modern approaches to learning; and make recommendations on how this tool could be further maximized in facilitating greater collaboration between tertiary institutions in reaching a wider cross-section of the Community's students.
Also at the COHSOD, the New Vision for the Caribbean Examinations Council (CXC) as proposed by the new Director Dr Didacus Jules will also be presented. According to Dr Greene, "we are hoping that this new vision will engender vigorous discussion among Ministers and provide useful insights on where the Council goes from here as a credible institution making a greater contribution to learning and education in the Region."
> Stakeholder engagement is important to tourism development
> Vendors and M&CC clean up Stabroek Bazaar and...
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 2,392
|
{"url":"https:\/\/www.nature.com\/articles\/s41467-018-07085-1\/?error=cookies_not_supported&code=6757b816-b40e-40b0-97b1-ebe76ab1a9b8","text":"Article | Open | Published:\n\n# An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling\n\n## Abstract\n\nMany components of signaling pathways are functionally pleiotropic, and signaling responses are marked with substantial cell-to-cell heterogeneity. Therefore, biochemical descriptions of signaling require quantitative support to explain how complex stimuli (inputs) are encoded in distinct activities of pathways effectors (outputs). A unique perspective of information theory cannot be fully utilized due to lack of modeling tools that account for the complexity of biochemical signaling, specifically for multiple inputs and outputs. Here, we develop a modeling framework of information theory that allows for efficient analysis of models with multiple inputs and outputs; accounts for temporal dynamics of signaling; enables analysis of how signals flow through shared network components; and is not restricted by limited variability of responses. The framework allows us to explain how identity and quantity of type I and type III interferon variants could be recognized by cells despite activating the same signaling effectors.\n\n## Introduction\n\nBiochemical signaling is a key mechanism to coordinate an organism in all aspects of its function. In a typical example, cells detect extracellular stimuli (input), e.g., growth factors, cytokines, or chemokines, with specific transmembrane receptors binding a ligand, which results in a biochemical activity on the inside of the cell, for example, the activation of a receptor-associated kinase1. The initial stimuli are processed in an intracellular relay mechanism and culminate in effectors (output), which might be transcription factors. The effectors carry information about the identity and intensity of the stimuli in order to initiate distinct cellular responses, which might involve gene transcription, or any other cellular process. Biochemical descriptions do not directly lead to understanding how the stimuli are translated into distinct responses as signaling processes are immensely complex2,3. Many components of signaling pathways are functionally pleiotropic:4,5,6 (i) a single stimulus often activates multiple effectors, (ii) a distinct effector can be activated by numerous stimuli, and (iii) signals triggered by different stimuli often travel through shared network components. Besides, (iv) biochemical signaling processes are intrinsically stochastic and responding cells exhibit quite varied behaviors when examined individually7,8, and (v) temporal dynamics of signaling in individual cells is correlated with physiological responses6,9,10. In light of these observations, understanding of how information about a complex mixture of extracellular stimuli is processed and translated into distinct cellular responses remains deficient2,3. For instance, human type I and type III interferons (IFNs) signal through distinct cell-surface receptors that appear to induce a shared signaling pathway. Yet, they can evoke different physiological effects11. The mechanism mediating this differential activity and signaling through common pathways remains largely unknown11,12,13,14,15.\n\nUnderstanding how cellular signaling processes can derive a variety of distinct outputs from complex inputs appears to be beyond solely experimental treatment. Therefore, an adequate modeling formalism is required. Following Berg and Purcell16, probabilistic modeling has been applied to examine fidelity of receptors as well as more complex biochemical signaling systems19. Specifically, information theory has been deployed as an integrated measure of signaling accuracy, a term known as information capacity, C*. Information capacity is expressed in bits, and generaly speaking, $$2^{C^ \\ast }$$ represents the maximal number of different inputs that a system can effectively resolve (e.g. different ligand concentrations)17. So far, both experimental and computational analysis of biochemical signaling within information theory revealed several unique aspects of how signaling pathways transmit information18,19,20,21,22,23,24. A tangible obstacle to further utilize the potential of information theory is the lack of computationally efficient tools that can account for complexities of biochemical signaling. Existing techniques are based on Blahut\u2013Arimoto algorithm18,25, small noise approximation19,26, or density estimation22 and their application so far has been limited to relatively simple systems, usually with one input and one output only. As analysis of systems with multiple inputs and outputs appears to be essential for deciphering of biochemical signaling27,28,29, we currently need new tools to study such systems. Here, we developed a computational framework of information theory that alleviates several drawbacks of existing tools, primarily by allowing efficient analysis of complex models with multiple inputs and multiple outputs. The method allowed us to provide an insight to one of the long-standing problems in signaling: how type I and type III interferon signaling can be recognized by cells despite activating the same signaling effectors.\n\n## Results\n\n### Quantification of information transfer in signaling systems\n\nWithin information theory, a signaling system is typically considered as a probability distribution P(Y|X\u2009=\u2009x) that for a given level of input, x, elicits output, Y. In a typical example, the input is the concentration of a ligand that activates a receptor, and the output is the activity of a signaling effector, which might be the nuclear concentration of an activated transcription factor. The output, Y, carries information about the level of the input, x. How much information is transferred depends on the signaling system itself, i.e., on its noise levels and sensitivity to changes of input values, as well as on how frequently different input values are transmitted. To illustrate the latter, consider two possible sets of input values. One set of input values generates similar and\/or irreproducible outputs, while the other generates distinct and reproducible outputs. If a pathway encounters signals from the first set more frequently than from the second one, its information transfer will be on average lower. The mutual information, I(X,Y), quantifies information transfer of a given signaling system, P(Y|X\u2009=\u2009x), that encounters input values following a given distribution, P(X) (see Methods). The maximal mutual information, with respect to all input distributions, termed information capacity, C*, quantifies information transfer under the most favorable distribution of input values\n\n$$C^ \\ast = \\begin{array}{*{20}{c}} {} \\\\ {{\\mathrm {max}}} \\\\ {P(X)} \\end{array}I(X,Y).$$\n(1)\n\nThe distribution for which the maximum of mutual information is achieved is called the optimal input distribution and denoted as P*(X). The information capacity, C*, is expressed in bits, and $$2^{C^ \\ast }$$ can be interpreted, within the Shannon\u2019s coding theorem17,30,31, as the number of input values that the system can effectively resolve based on the information contained in the output. For instance, if C*\u2009=\u20092, there exist four concentrations that can be distinguished with, on average, negligible error. Available approaches to compute information capacity are briefly described in Methods, whereas more background on information theory is provided in Section 1 of Supplementary information (SI).\n\n### Efficient calculation of information capacity in complex models\n\nIn a general setting, calculation of the information capacity, C*, is computationally expensive, if not prohibitive. Here, we propose a framework to study information flow in biochemical signaling models that alleviate several of the important drawbacks related to available approaches19,22,25,32. Specifically, the proposed framework is based on analytical solutions. This, in turn, leads to an efficient computational algorithm that accounts for the complexity of signaling, most importantly multidimensional inputs and outputs.\n\nWe propose to calculate the information capacity, using an asymptotic approach. Precisely, we consider a system with an output, YN\u2009=\u2009(Y(1),...,Y(N)), that consists of N independent copies of $$Y\\sim P( \\cdot |X = x)$$, where Y itself can be multidimensional, e.g., a time series of induced levels of transcription factors. Biologically, N can be interpreted as the number of cells that independently sense the signal, X. The corresponding information capacity problem is then written as\n\n$$C_N^ \\ast = \\begin{array}{*{20}{c}} {} \\\\ {{\\mathrm {max}}} \\\\ {P_N(X)} \\end{array}I(X,Y_N).$$\n(2)\n\n$$C_N^ \\ast$$ quantifies information about the input, X, jointly stored in N cells. For large N, Eq. (2) has an exact and computationally efficient solution based on the Fisher information matrix (FIM),\n\n$${\\mathrm{FIM}}_{ij}(x) = {\\Bbb E}\\left[ {\\frac{{\\partial {\\mathrm{log}}P(Y|X = x)}}{{\\partial x_i}}\\frac{{\\partial {\\mathrm{log}}P(Y|X = x)}}{{\\partial x_j}}} \\right],$$\n(3)\n\nwhere i and j refer to elements of the vector x\u2009=\u2009(x1,\u2026,xk), i.e., multidimensional input. Specifically, it has been shown in the statistical theory of reference priors30,33 that if FIM is non-singular, i.e., all inputs have a non-redundant impact on the output, then\n\n$$P_N^ \\ast (x)\\mathop{\\longrightarrow}\\limits_{{N \\to \\infty }}P_{{\\mathrm{JP}}}^ \\ast (x),$$\n(4)\n\nwhere\n\n$$P_{{\\mathrm{JP}}}^ \\ast (x) \\propto \\sqrt {|{\\mathrm{FIM}}(x)|} ,$$\n(5)\n\nand || denotes the matrix determinant. The distribution $$P_{{\\mathrm{JP}}}^ \\ast (x)$$ is known as the Jeffrey prior (JP). Similarly, it can be shown, see Section 1.4 SI and ref. 30, that\n\n$$C_N^ \\ast - \\frac{k}{2}{\\mathrm{log}}_2(N)\\mathop{\\longrightarrow}\\limits_{{N \\to \\infty }}C_{\\mathrm{A}}^ \\ast ,$$\n(6)\n\nwhere k is the dimension of input, and\n\n$$C_{\\mathrm{A}}^ \\ast = {\\mathrm{log}}_2\\left( {(2\\pi e)^{ - \\frac{k}{2}}{\\int}_{\\hskip -5pt \\mathscr{X}} \\sqrt {|{\\mathrm{FIM}}(x)|} {\\mathrm d}x} \\right),$$\n(7)\n\nwhere $${\\mathscr{X}}$$ is the space of signal values, x.\n\nAs suggested by Eq. (6), we will call $$C_{\\mathrm{A}}^ \\ast$$ as the asymptotic information capacity, where asymptotics is meant with respect to the number of cells, N. Equation (6) implies that $$C_{\\mathrm{A}}^ \\ast$$ can be used to approximate the joint capacity of N cells\n\n$$C_N^ \\ast \\approx C_{\\mathrm{A}}^ \\ast + \\frac{k}{2}{\\mathrm{log}}_2(N).$$\n(8)\n\nThe approximation demonstrates that the joint capacity of N cells depends on the baseline, asymptotic, capacity, $$C_{\\mathrm{A}}^ \\ast$$, and on the number of cells via $$\\frac{k}{2}{\\mathrm{log}}_2(N)$$, where the latter term vanishes for N\u2009=\u20091. Therefore, in terms of Eq. (8), the asymptotic capacity $$C_{\\mathrm{A}}^ \\ast$$ can be interpreted as the contribution of an individual cell to the capacity of an ensemble of N cells. Equivalently, the number of inputs resolvable by N cells increases linearly with $$N^{\\frac{k}{2}}$$ at the rate $$2^{C_{\\mathrm{A}}^ \\ast }$$\n\n$$2^{C_N^ \\ast } \\approx 2^{C_{\\mathrm{A}}^ \\ast } \\cdot N^{\\frac{k}{2}}.$$\n(9)\n\nIn terms of Eq. (9), the asymptotic capacity $$C_{\\mathrm{A}}^ \\ast$$ defines a rate, at which the number of resolvable states increases with N.\n\nImportantly, asymptotic capacity, $$C_{\\mathrm{A}}^ \\ast$$, can take negative values, which has a precise interpretation. The scaling law of Eqs. (8) and (9), which is warranted to be correct by convergence in Eq. (6), implies that $$C_{\\mathrm{A}}^ \\ast$$ must be allowed to take negative values. If $$C_{\\mathrm{A}}^ \\ast$$ was guaranteed to be positive then, any signaling system composed of N cells would be guaranteed to have the capacity $$C_N^ \\ast$$ larger than $$\\frac{k}{2}{\\mathrm{log}}_2(N)$$, which obviously is not the case. In other words, if the number of resolvable inputs $$2^{C_N^ \\ast }$$ increases slowly with N then $$2^{C_{\\mathrm{A}}^ \\ast }$$ must be accordingly small, which means negative $$C_{\\mathrm{A}}^ \\ast$$. For illustration, consider two systems with asymptotic capacities, $$C_{\\mathrm{A}}^ \\ast$$, of, say, \u22121 bit and 1 bit. Then, the capacity $$C_N^ \\ast$$, of the first is smaller by 2 bits compared to the second, for large N. Equivalently, the number of resolvable inputs of the first systems increases at the fourth of the rate of the latter. Besides, Eq. (7), implies that for systems with low Fisher information the number of resolvable inputs increases slowly with N.\n\nConveniently, $$C_{\\mathrm{A}}^ \\ast$$ reduces the problem of calculating the information capacity to the problem of calculating the FIM and we propose to take advantage of this. Fisher information can be calculated for systems with multiple inputs and outputs, and therefore the above approach allows simple computation of information capacity for such systems. To the best of our knowledge, this method has not been used to analyze biochemical signaling, most likely due to technical difficulties in calculating the FIM, which was, to a considerable degree, alleviated by methods recently developed34,35. In Section 6 of SI we discuss in details how FIM can be calculated in different scenarios.\n\n### Asymptotic capacity does not deviate substantially from non-asymptotic capacity in the test model\n\nThe asymptotic capacity, $$C_{\\mathrm{A}}^ \\ast$$, and the capacity of an individual cell, $$C_1^ \\ast$$, are related but not the same quantities. As we discuss in Section 1 of SI, differences arise from non-identical optimal input distributions of single cells and population of cells as well as the way in which information from different cells adds up. In the literature, so far, the interest in $$C_1^ \\ast$$ is dominating. Therefore, even though $$C_{\\mathrm{A}}^ \\ast$$ has a meaningful interpretation on its own, we have compared values of $$C_{\\mathrm{A}}^ \\ast$$ and $$C_1^ \\ast$$ in a test model. Blahut\u2013Arimoto algorithm was used to calculate the exact $$C_1^ \\ast$$. In the comparison we have also included the established, and virtually the only available method to approximate $$C_1^ \\ast$$, i.e., the small noise approximation19, denoted here as $$C_{{\\mathrm{SN}}}^ \\ast$$. We have designed a test model, for which all methods are computationally feasible, and which challenges the assumption of our method, i.e., asymptotics, and of the small noise approximation, i.e., limited stochasticity. Precisely, we considered a model of a biochemical sensor described by the binomial distribution $$Y\\sim {\\mathrm{Bin}}(h(S),L)$$ with the output Y being the number of active sensors and L being the copy number of sensors. The probability of the sensor being active was assumed to be the Michaelis\u2013Menten function, h(S)\u2009=\u2009S\/H\/(1\u2009+\u2009S\/H), with S\u2009=\u2009X + XF\/\u03bb, where X is the concentration of a cognate and XF of a non-cognate ligand, and \u03bb is the selectivity factor (the ratio of the binding affinities, Kd\u2019s, of the non-cognate and cognate ligands, $$\\lambda = \\frac{{H_{\\mathrm{F}}}}{H}$$). The higher the value of \u03bb, the less likely the receptor binds the false ligand. We have assumed that the concentration of the true ligand, X, is the input of the system and varies according to the optimal input distribution, P*(X), whereas the variability of the non-cognate ligand, modeled as the probability distribution P(XF), is the source of noise that leads to information loss. For calculation of $$C_1^ \\ast$$ with Blahut\u2013Arimoto algorithm, we used a complete model without any approximations.\n\nChanging the settings of this model allowed us to challenge the tested methods thoroughly. In total, we have considered 27 different scenarios by combining different variants of the probability distributions P(XF); sensor copy number, L; and of the selectivity factor, \u03bb. In each scenario, we have calculated capacities as a function of the standard deviation of the distribution P(XF), denoted as $$\\sigma _{X_{\\mathrm{F}}}$$. Relative deviations of $$C_{\\mathrm{A}}^ \\ast$$ and $$C_{{\\mathrm {SN}}}^ \\ast$$ from $$C_1^ \\ast$$, averaged over all considered scenarios of the test model, are presented in Fig.\u00a01, whereas comparison for each scenario is presented in Supplementary Figures 1\u20133. For limited variability, i.e., small $$\\sigma _{X_{\\mathrm{F}}}$$, both methods have similar accuracy. When the variability increases both methods become less accurate; however, $$C_{\\mathrm{A}}^ \\ast$$ has half lower error compared to $$C_{\\mathrm{SN}}^ \\ast$$. High variability violates the assumption of the small noise approximation, which explains higher error for high $$\\sigma _{X_{\\mathrm{F}}}$$. Lower approximation accuracy of $$C_{\\mathrm{A}}^ \\ast$$ results from the lack of asymptotics, i.e., N\u2009=\u20091. When using $$C_{\\mathrm{A}}^ \\ast$$ or $$C_{\\mathrm{SN}}^ \\ast$$ as approximations of $$C_1^ \\ast$$, which is a positive quantity, one should monitor for negative values and set approximation to zero. Supplementary Figure\u00a01 shows that in the test model both approximations fell below zero for several model settings, specifically these corresponding to low copy number and highest considered $$\\sigma _{X_{\\mathrm{F}}}$$. In Section 1.5 of SI we present an auxiliary approximation of $$C_1^ \\ast$$ that is guaranteed to be positive, but is computationally not as efficient as $$C_{\\mathrm{A}}^ \\ast$$.\n\nIn summary, our numerical analysis demonstrates that $$C_{\\mathrm{A}}^ \\ast$$ provided a more accurate approximation of $$C_1^ \\ast$$ than $$C_{{\\mathrm {SN}}}^ \\ast$$. The approximation error is at the order of maximum 30%, which indicates that the asymptotic capacity, $$C_{\\mathrm{A}}^ \\ast$$, served as a reliable approximation of the capacity of an individual cell, $$C_1^ \\ast$$.\n\n### Information transmission is maximized when frequent signals are recognized with high precision\n\nHow much information is transferred in a given signaling system depends on three factors: (i) sensitivity of the output to changes in the input, (ii) variability of output given input, and (iii) how frequently do different inputs occur. The first two are modeled by the input\u2013output distribution, P(Y|X\u2009=\u2009x), and the third is represented by the maximization problem in Eq. (2). Here we show that our approach allows for an insightful interpretation of the input distribution that is optimal for signaling. Precisely, consider an asymptotically efficient estimator, $$\\hat x(Y_N)$$ value, x, i.e., an estimator that achieves lowest possible variance for large data, e.g., maximum likelihood estimator. Then, the variance of this estimator, $$\\Sigma (\\hat x(Y_N))$$, is asymptotically described by the inverse of the Fisher information\n\n$$\\Sigma (\\hat x(Y_N))\\mathop{\\longrightarrow}\\limits^{{N \\to \\infty }}(N \\cdot {\\mathrm{FIM}}(x))^{ - 1}.$$\n(10)\n\nGiven the above, the optimal distribution of inputs, $$P_{{\\mathrm{JP}}}^ \\ast (x) \\propto \\sqrt {|{\\mathrm {FIM}}(x)|}$$, is defined in terms of the uncertainty of inferences, $$\\Sigma \\left( {\\hat x(Y_N)} \\right)$$, that cells can draw about the input value, x. Precisely, for large N, $$P_{{\\mathrm{JP}}}^ \\ast (x) \\propto 1\/\\sqrt {\\left| {\\Sigma \\left( {\\hat x(Y_N)} \\right)} \\right|}$$. Therefore, the optimal distribution, $$P_{{\\mathrm{JP}}}^ \\ast (x)$$, states that the system performs best in terms of the information capacity if frequent values are recognized and processed with high precision, whereas more rarely occurring signals need not be transmitted with similarly high accuracy. This is visualized in Fig.\u00a02 for a scenario with a one-dimensional input: in the optimal scenario signals occur at a frequency that is proportional to the inverse of the uncertainty measured as the standard deviation of the estimate of the signal, $$\\sqrt {\\Sigma (\\hat x(Y_N))}$$.\n\nSignaling precision is also closely related to the discrimination error. This is relevant as the information capacity per se does not indicate which exact states can be effectively discriminated. Precisely, consider two close input values x0 and x1, and the probability, \u03b5(x0, x1, YN), of not detecting the change x0\u2009\u2192\u2009x1 based on observations YN. Within the statistical framework of hypothesis testing, the probability \u03b5(x0, x1, YN) is approximated as17\n\n$$\\varepsilon (x_0,x_1,Y_N) \\approx {\\mathrm e}^{- N(x_1 - x_0){\\mathrm {FIM}}(x_0)(x_1 - x_0)^{T}}.$$\n(11)\n\nTherefore, changes in input concentrations that are easily recognized are these along sensitive directions of the FIMs. These directions and can be determined in our framework.\n\n### Signaling dynamics allows discrimination between identity and quantity of type I and type III interferons\n\nIn order to demonstrate how our method can be applied to provide a unique insight regarding the functioning of signaling pathways, we have addressed the problem of the type I and type III interferons signaling. Both IFN types induce the same signaling effectors and it is currently not clear how their identity and quantity is recognized by cells to induce distinct physiological responses12,13,14,15,36. Both IFN types have several variants and here we have selected IFN-\u03b1 and IFN-\u03bb1 as representatives of type I and type III IFNs, respectively. IFN-\u03b1 exerts its action through cognate two subunits receptor complex IFNAR1\/IFNAR2, whereas IFN-\u03bb1 signals through two subunit receptor complex IFNLR1\/IL10R\u03b1. Simplistically, receptor ligand binding induces a cascade of events. The cascade culminates with phosphoryled forms of STAT1 and STAT2 proteins translocating to the nucleus as homodimers (p-STAT1\/1) and heterodimers (p-STAT1\/2), where they bind DNA to specific cognate sites (Fig.\u00a03a). The mechanism that explains the differential physiological effect of IFN-\u03b1 and IFN-\u03bb1 despite inducing the same signaling effectors is largely unknown12,13,14. Recent data12,13,14,37, however, support the hypothesis that a differential temporal profile, understood as time series of the copy numbers of nuclear p-STAT1\/1 homodimers and p-STAT1\/2 heterodimers, carries information about identity and quantity of both IFNs and is further propagated by the gene expression machinery into distinct physiological responses. For instance, western blot experiments show a prolonged phosphorylation in response to IFN-\u03bb1 compared to IFN-\u03b114.\n\nOur framework provides a natural, and computationally feasible, framework to address IFN discrimination problem. As four resolvable states are required to distinguish between presence and absence of two stimuli, the capacity $$C_N^ \\ast \\ge 2$$ can be interpreted as the potential of a population of N cells to distinguish both identity and quantity of the two IFNs. Moreover, Eqs. (8) and (11) imply that if FIM is non-singular the capacity $$C_N^ \\ast$$ can be arbitrarily increased and the discrimination error \u03b5(x0, x1, YN) arbitrarily decreased with the population size N. Therefore, information capacity and FIMs constitute suitable tools to determine how information about identity and quantity of both IFN is encoded in signaling responses.\n\nTo this end, we have built a probabilistic model of the pathway\u2019s input\u2013output relationship, P(Y|X\u2009=\u2009x). Construction of the model was accomplished by assembling and refining model components of the JAK-STAT signaling available in literature38,39,40 (Fig.\u00a03a and Section 3 of SI). The input x\u2009=\u2009(x\u03b1, x\u03bb1) consists of concentrations of IFN-\u03b1 and IFN-\u03bb1, respectively. We assumed that the pathway is exposed for 30\u2009min to stimulation with a mixture of IFNs specified by the input. The output is defined as Y\u2009=\u2009(Y1\/2(t1), Y1\/1(t1),...,Y1\/2(tn), Y1\/1(tn)), where Y1\/2(ti) and Y1\/1(ti) denote copy numbers of nuclear of p-STAT1\/2 heterodimers and p-STAT1\/1 homodimers, respectively, at time ti. Times t1,\u2026,tn serve as a proxy of the complete temporal profile. To account for signaling noise, we assumed that the stochasticity results from: (i) randomness of individual reactions and (ii) also cell-to-cell variability in the copy numbers of STAT1 and STAT2 molecules as well as type I, RI, and type III, RIII, receptor complexes. The two noise sources are seen as main contributors of cell-to-cell heterogeneity in general41 and IFN signaling, specifically42. The copy numbers of the above entities per cell was assumed variable with the same coefficient of variation\n\n$$c_{\\mathrm{v}} = \\frac{{\\sigma _i}}{{\\mu _i}},$$\n(12)\n\nwhere \u03bci is the mean copy number per cell, and \u03c3i is its standard deviation, for i{STAT1,STAT2,RI,RIII}. Further, we considered coefficient of variation from 0.3 to 1.5 to reflect typically measured values43. Importantly, the model is in line with the present biochemical knowledge14,37 by allowing the only difference in responses to arise from the different kinetics of both receptor complexes. We quantified the difference in receptor kinetics using the ratio of deactivation rates of the type III and type I receptor complexes, $$k_{{\\bar{R}}_{{\\mathrm {III}}}}$$ and $$k_{{\\bar{R}}_{\\mathrm I}}$$, respectively (see Sections 3.2\u20133.3 of SI),\n\n$$\\delta = \\frac{{k_{{\\bar{R}}_{III}} }}{{k_{{\\bar{R}}_I}}},$$\n(13)\n\nwhich we call the differential kinetics coefficient. For a given value of \u03b4 (e.g. 0.5), upon activation, the type I receptor complex remains active on average 1\/\u03b4 (e.g. 2) times shorter than the type III receptor. As responses to IFN-\u03bb1 are prolonged compared to IFN-\u03b114, we have considered \u03b4(0, 1). Values close to 0 and 1 denote dissimilar and similar receptor kinetics, respectively. The model was numerically simulated within the framework of the linear noise approximation that allows efficient calculation of the FIMs34,35 using literature values of kinetic parameters (see Supplementary Table\u00a02). As shown in Fig.\u00a03b the model provides responses qualitatively consistent with experiments that show prolonged responses to IFN-\u03bb1 compared to IFN-\u03b114. The strength of this effect is controlled by the parameter \u03b4. Low \u03b4 implies a significantly longer response to IFN-\u03bb1, whereas for \u03b4 close to 1 responses to both IFNs appear to be indistinguishable.\n\nFirst, we examined the potential of the differential signaling dynamics to discriminate between identity and quantity of IFNs under noise limited to stochasticity of individual reactions, cv\u2009=\u20090. To this end, we considered outputs, Y, with different end time points, tn\u2019s, so that they contain only the information available to the cell until time tn. For the values of \u03b4 used in Fig.\u00a03b, we plotted the information capacity, $$C_{\\mathrm{A}}^ \\ast$$, as a function of tn (Fig.\u00a04a) as well as corresponding representative FIMs (Fig.\u00a04b). For early times, the capacities, $$C_{\\mathrm{A}}^ \\ast$$ are below 0, further, with increasing tn, raise over 2 bits, and finally plateau. The time-windows of rapid increase coincide with times, at which stimulation with different combinations of the two IFNs generates distinguishable output trajectories (compare with Fig.\u00a03b and Supplementary Figures 4 and 5). Correspondingly, FIM is singular only for early tn and high \u03b4. Also, it becomes close to orthogonal for late tn and small \u03b4.\n\nThese results indicate that for limited signaling noise, differential signaling dynamics has a potential to ensure discriminability between the two IFNs. Precisely, for all \u03b4\u2019s and late tn, $$C_{\\mathrm{A}}^ \\ast$$ reaches high values, and FIMs are non-singular. Therefore, at the population level, both capacity, $$C_N^ \\ast$$, arbitrarily increases (Eq.\u00a08), and the discrimination error arbitrarily decreases (Eq.\u00a011), with N. Moreover, using $$C_{\\mathrm{A}}^ \\ast$$ as an approximation of $$C_1^ \\ast$$, which can be safely done for high values of $$C_{\\mathrm{A}}^ \\ast$$, we can also conclude that the differential signaling dynamics results with the single-cell capacity, $$C_1^ \\ast$$, significantly higher than 2 bits. Two bits is a minimum necessary condition to encode four input values, e.g., presence and absence of two stimuli. However, Shannon information alone does not tell us which exact input values can be discriminated. Therefore, we can conclude only that individual cells can resolve at least four combinations of both IFN concentrations.\n\n### Population level discrimination is possible even at high noise and with minor kinetic differences\n\nThe above analysis demonstrated that with limited noise signaling dynamics ensures discrimination between both IFNs. Interestingly, the discrimination is possible even with modest differences in the kinetics of both receptors, i.e., \u03b4\u2009=\u20090.9, which corresponds to 10% difference in the receptors deactivation rates. Noise in signaling processes is, however, not limited to stochasticity of signaling reactions. In mammalian signaling, the noise is thought to be dominated by the copy number variability of signaling components8. Therefore, we have considered several noise levels, and examined how the information content of the complete temporal profile, tn\u2009=\u2009180, depends on the values of the differential kinetics coefficient, \u03b4. Fig.\u00a04c presents the capacity, $$C_{\\mathrm{A}}^ \\ast$$, as a function of \u03b4 for a range of biologically feasible43 values of cv. Fig.\u00a04d shows corresponding FIMs. Not surprisingly, both noise and lack of kinetic differences can severely compromise the information transfer (Fig.\u00a04c). $$C_{\\mathrm{A}}^ \\ast$$ falls substantially below 2 bits, reaching negative values for high noise and similar kinetics. On the other hand, representative FIMs are non-singular for all noise levels and values of \u03b4.\n\nThe above results primarily show that discriminability at the population level can be achieved even with minor differences in kinetic rates, and despite high noise levels. This is implied by Eqs. (8) and (11). As indicated by Eq. (8), high population capacity, $$C_N^ \\ast$$, can be ensured by large N, as long as $$C_{\\mathrm{A}}^ \\ast$$ is not prohibitively low. Similarly, Eq. (11) shows that low discrimination error, \u03b5(x0, x1, YN), can be ensured by large N, as long as FIMs are non-singular. Both conditions are satisfied in the considered scenarios as shown in Fig.\u00a04c, d. In addition, negative values of $$C_{\\mathrm{A}}^ \\ast$$, for high \u03b4 and cv, indicate slow increase of the overall number of resolvable input values with N (Eq.\u00a09).\n\nMoreover, our analysis demonstrates that discriminability at the population level does not require discriminability at the single-cell level. This conclusion can be made on the following ground. The capacity of two bits is a necessary condition to encode four input values, e.g., presence or absence of both IFNs. In other words, a system with capacity lower than two bits does not have a sufficient discriminatory power to resolve presence and absence of the two IFNs. Therefore if $$C_1^ \\ast < 2$$ the discrimination at the single-cell level is not possible. Here, we calculated $$C_{\\mathrm{A}}^ \\ast$$ not $$C_1^ \\ast$$, which can only serve as an approximation of $$C_1^ \\ast$$. However, $$C_{\\mathrm{A}}^ \\ast$$ falls substantially below two bits. Therefore, even if $$C_{\\mathrm{A}}^ \\ast$$ was not a very accurate of approximation of $$C_1^ \\ast$$, low values of $$C_{\\mathrm{A}}^ \\ast$$ strongly indicate that $$C_1^ \\ast$$ is smaller than two bits, which demonstrates that there is no discriminability at the single-cell level. On the other hand, as argued in the previous paragraph, discriminability at the population can be achieved by increasing N.\n\nInterestingly, our analysis also highlights the role of kinetic rates in efficient information transfer. Primarily, the model predicts that at the population level, the discriminability between the two IFNs can be achieved even at high noise with differences in kinetic rates at the order of 10%. This suggest that even minor divergence of evolutionary related receptors might suffice to augment information transfer. This prediction is in line with the highly cross-wired architecture of signaling pathways29,44. Secondly, Fig.\u00a04c shows that loss of information due to noise can be compensated by stronger kinetic differences, and vice versa. This trade-off emphasizes the divergence of kinetic rates as an easily accessible evolutionary strategy of increasing information transfer. Reduction of noise level requires an increase in the number of signaling molecules or\/and sophisticated control mechanisms. On the other hand, alteration of receptor kinetic rates can be caused by a single mutation45.\n\nOverall, our model predicts that the population can correctly decode information even in cases where single cells cannot, due to high noise or similar receptor kinetics. The question, however, arises how the population should be able to make correct decisions based on low capacity in single cells. To illustrate this, consider the expression of IFNs induced genes as a downstream output. Both IFNs induce expression of hundreds of gene, including several chemokines from CXCL and CCL family12,46,47. Specifically, it has been shown that temporal profiles of CXCL10 expression differ in response to both considered IFNs12.\n\nOne of the main function of these chemokines is to attract different types of leukocytes to a site of an infection. Therefore, concentration and timing of these chemoattractants can be seen as a decision of cellular population regarding which and how many leukocytes are needed at a given time. Concentration and timing are controlled jointly by a large number of cells due to averaging of secretions in the intercellular space. In consequence, the chemokine concentration depends on the information encoded in nuclear levels of the p-STAT1\/1 and p-STAT1\/2 dimers in multiple cells. Therefore, even if the capacity of individual cells is low, and as a result expression of the chemokine can be only vaguely controlled by IFNs level, the high joint capacity of N cells may lead to a finely tuned level of the chemokine in the intercellular space, as the differences in secretion of individual cells would average out. To further hypothesize how the high capacity of a population and low individual capacity may be utilized, one can also anticipate a different scenario. An initial stimulus leads to subsequent rounds of cell-to-cell communication through paracrine signaling. Low individual capacity implies that initially the stimulus is recognized with low precision. In subsequent rounds of communication information is exchanged between cells, and as a result, the initial stimulus may lead to finely tuned responses at later times.\n\nAlthough the above hypothetical mechanisms are in line with current understanding of IFN signaling, they imply the need for more detailed experimental testing. They also rise an essential questions regarding signaling processes: does effective information transfer require discriminability of IFNs, and signaling ligands more generally, at the single-cell level, or population level suffices? So far, differential IFNs signaling dynamics have been observed at the population level12,13,14,15,36. Experimental confirmation of our theoretical prediction would be of high relevance for reconciling the single-cell stochasticity with fine-tuned tissue level responses.\n\n## Discussion\n\nInformation theory appears to have a potential to promote further understanding of how cells translate information about complex stimuli into distinct activities of the pathway\u2019s effectors using pleiotropic and stochastic mechanisms. Our theoretical methodology establishes a general and computationally efficient framework that enables analysis of models with multiple inputs and outputs. Importantly, it also accounts for the temporal aspect of signaling. Here, we have shown that even in the presence of significant noise information about identity and quantity of IFN-\u03b1 and IFN-\u03bb1 can be transmitted despite shared network components. Discriminability at the population level can be achieved without discriminability at the single-cell level, and with only small differences in receptor kinetic rates. So far, signaling responses to both IFNs have been measured at the population level only12,13,14,15,36. Our analysis suggests that further verification at the single-cell level could provide interesting conclusions regarding how information processing differs between single cells and cellular populations. Scenarios of pleiotropic signaling, similar to IFNs, are common in signaling, e.g., Wnt, BMP29, as well as in GPCR signaling48,49. Therefore, our framework seems to offer an attractive opportunity to gain further insight into the functioning of many complex signaling systems.\n\n## Methods\n\n### Mutual information\n\nWithin information theory, quantification of information transfer of a given signaling system, P(Y|X\u2009=\u2009x), is performed in reference to the distribution of input values P(X). Although, randomness of output, Y, prevents the system from resolving a precise value of the input, x, the uncertainty regarding input values cannot be higher than the uncertainty associated with the input distribution, P(X). Uncertainty is usually quantified by entropy\n\n$$H(X) = - {\\int}_{\\hskip -5pt \\mathscr{X}} \\mathop {{{\\mathrm {log}}}}\\nolimits_2 (P(x))P(x){\\mathrm d}x,$$\n(14)\n\nwhere $${\\mathscr{X}}$$ is the space of possible values of the signal, X.\n\nObservation of output has a potential to reduce uncertainty regarding input value. Via the Bayes formula, plausible inputs that generated a specific output value, y, are represented as the probability distribution $$P(X|Y = y) = \\frac{{P(Y = y|X)P(X)}}{{P(Y = y)}}$$. Uncertainty regarding input value can be then quantified by the entropy of the distribution P(X|Y\u2009=\u2009y)\n\n$$H(X|Y = y) = {\\int}_{\\hskip -5pt \\mathscr{X}} {\\mathrm{log}}_2(P(x|Y = y))P(x|Y = y){\\mathrm d}x.$$\n(15)\n\nAs the output is random, averaging H(X|Y\u2009=\u2009y) over all possible outputs quantifies the average uncertainty regarding the input, given the output, H(X|Y)\n\n$$H(X|Y) = - {\\int}_{\\hskip -5pt \\mathscr{Y}} H(X|Y = y)P(y){\\mathrm d}y,$$\n(16)\n\nwhere is $${\\mathscr{Y}}$$ the space of possible values of the output, Y. The difference between H(X) and H(X|Y) measures the average reduction in uncertainty regarding the input resulting from observing an output and is referred to as mutual information, I(X,Y), between the input and the output\n\n$$I(X,Y) = H(X) - H(X|Y).$$\n(17)\n\nMore background on information theory is provided in Section 1 of Supplementary methods.\n\n### Existing methods to compute information capacity\n\nThree main approaches are available to calculate C* and P*(X). The state-of-the-art Blahut\u2013Arimoto algorithm is based on convex optimization25,32 and for systems with continuous variables it requires discretization of input and output values18. Although it works efficiently for systems with one-dimensional input and output, optimization may become computationally prohibitive for higher dimensionalities. An alternative approach is offered by the small noise (SN) approximation method19, which offers an analytical solution, and therefore avoids heavy computations. However, it assumes a limited stochasticity within the analyzed system. Recently, a method based on density approximation was proposed in ref. 22 to account for temporarily resolved outputs.\n\n### Code availability\n\nComputer code used to generate reported results is available from authors upon request.\n\n## Data availability\n\nThe study did not involve any datasets.\n\nPublisher\u2019s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\n\n## References\n\n1. 1.\n\nKholodenko, B. N. Cell-signalling dynamics in time and space. Nat. Rev. Mol. Cell Biol. 7, 165 (2006).\n\n2. 2.\n\nNurse, P. Life, logic and information. Nature 454, 424\u2013426 (2008).\n\n3. 3.\n\nTawfik, D. S. Messy biology and the origins of evolutionary innovations. Nat. Chem. Biol. 6, 692 (2010).\n\n4. 4.\n\nRu\u00e9, P. & Arias, A. M. Cell dynamics and gene expression control in tissue homeostasis and development. Mol. Syst. Biol. 11, 792 (2015).\n\n5. 5.\n\nLim, W. A. Designing customized cell signalling circuits. Nat. Rev. Mol. Cell Biol. 11, 393\u2013403 (2010).\n\n6. 6.\n\nBehar, M., Barken, D., Werner, S. L. & Hoffmann, A. The dynamics of signaling as a pharmacological target. Cell 155, 448\u2013461 (2013).\n\n7. 7.\n\nRand, U. et al. Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response. Mol. Syst. Biol. 8, 584 (2012).\n\n8. 8.\n\nTay, S. et al. Single-cell NF-\u03baB dynamics reveal digital activation and analogue information processing. Nature 466, 267\u2013271 (2010).\n\n9. 9.\n\nPurvis, J. E. & Lahav, G. Encoding and decoding cellular information through signaling dynamics. Cell 152, 945\u2013956 (2013).\n\n10. 10.\n\nPurvis, J. E. et al. p53 dynamics control cell fate. Science 336, 1440\u20131444 (2012).\n\n11. 11.\n\nOlagnier, D. & Hiscott, J. Type I and type III interferon-induced immune response: it\u2019s a matter of kinetics and magnitude. Hepatology 59, 1225\u20131228 (2014).\n\n12. 12.\n\nBolen, C. R., Ding, S., Robek, M. D. & Kleinstein, S. H. Dynamic expression profiling of type I and type III interferon-stimulated hepatocytes reveals a stable hierarchy of gene expression. Hepatology 59, 1262\u20131272 (2014).\n\n13. 13.\n\nJilg, N. et al. Kinetic differences in the induction of interferon stimulated genes by interferon-\u03b1 and interleukin 28B are altered by infection with hepatitis C virus. Hepatology 59, 1250\u20131261 (2014).\n\n14. 14.\n\nMaher, S. G. et al. IFN-\u03b1 and IFN-\u03bb differ in their antiproliferative effects and duration of JAK\/STAT signaling activity. Cancer Biol. Ther. 7, 1109\u20131115 (2008).\n\n15. 15.\n\nVoigt, E. A. & Yin, J. Kinetic differences and synergistic antiviral effects between type I and type III interferon signaling indicate pathway independence. J. Interferon Cytokine Res. 35, 734\u2013747 (2015).\n\n16. 16.\n\nBerg, H. C. & Purcell, E. M. Physics of chemoreception. Biophys. J. 20, 193\u2013219 (1977).\n\n17. 17.\n\nCover, T. M. & Thomas, J. A. Elements of Information Theory (John Wiley & Sons, New York, 2012).\n\n18. 18.\n\nCheong, R., Rhee, A., Wang, C. J., Nemenman, I. & Levchenko, A. Information transduction capacity of noisy biochemical signaling networks. Science 334, 354\u2013358 (2011).\n\n19. 19.\n\nTka\u010dik, G., Callan, C. G. & Bialek, W. Information flow and optimization in transcriptional regulation. Proc. Natl. Acad. Sci. USA 105, 12265\u201312270 (2008).\n\n20. 20.\n\nVoliotis, M., Perrett, R. M., McWilliams, C., McArdle, C. A. & Bowsher, C. G. Information transfer by leaky, heterogeneous, protein kinase signaling systems. Proc. Natl. Acad. Sci. USA 111, E326\u2013E333 (2014).\n\n21. 21.\n\nSuderman, R., Bachman, J. A., Smith, A., Sorger, P. K. & Deeds, E. J. Fundamental trade-offs between information flow in single cells and cellular populations. Proc. Natl. Acad. Sci. USA 114, 5755\u20135760 (2017).\n\n22. 22.\n\nSelimkhanov, J. et al. Accurate information transmission through dynamic biochemical signaling networks. Science 346, 1370\u20131373 (2014).\n\n23. 23.\n\nMartins, B. M. & Swain, P. S. Trade-offs and constraints in allosteric sensing. PLoS Comput. Biol. 7, e1002261 (2011).\n\n24. 24.\n\nMarzen, S., Garcia, H. G. & Phillips, R. Statistical mechanics of Monod-Wyman-Changeux (MWC) models. J. Mol. Biol. 425, 1433\u20131460 (2013).\n\n25. 25.\n\nArimoto, S. An algorithm for computing the capacity of arbitrary discrete memoryless channels. IEEE Trans. Inf. Theory 18, 14\u201320 (1972).\n\n26. 26.\n\nTka\u010dik, G. & Walczak, A. M. Information transmission in genetic regulatory networks: a review. J. Phys. Condens. Matter 23, 153102 (2011).\n\n27. 27.\n\nWaltermann, C. & Klipp, E. Information theory based approaches to cellular signaling. Biochim. Biophys. Acta 1810, 924\u2013932 (2011).\n\n28. 28.\n\nMehta, P., Goyal, S., Long, T., Bassler, B. L. & Wingreen, N. S. Information processing and signal integration in bacterial quorum sensing. Mol. Syst. Biol. 5, 325 (2009).\n\n29. 29.\n\nAntebi, Y. E. et al. Combinatorial signal perception in the BMP pathway. Cell 170, 1184\u20131196 (2017).\n\n30. 30.\n\nClarke, B. S. & Barron, A. R. Jeffreys\u2019 prior is asymptotically least favorable under entropy risk. J. Stat. Plan. Infer. 41, 37\u201360 (1994).\n\n31. 31.\n\nShannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379\u2013657 (1948).\n\n32. 32.\n\nBlahut, R. Computation of channel capacity and rate-distortion functions. IEEE Trans. Inf. Theory 18, 460\u2013473 (1972).\n\n33. 33.\n\nBernardo, J. M. Reference posterior distributions for Bayesian inference. J. R. Stat. Soc. Ser. B (Methodol.) 41, 113\u2013147 (1979).\n\n34. 34.\n\nKomorowski, M., Costa, M. J., Rand, D. A. & Stumpf, M. P. Sensitivity, robustness, and identifiability in stochastic chemical kinetics models. Proc. Natl. Acad. Sci. USA 108, 8645\u20138650 (2011).\n\n35. 35.\n\nKomorowski, M., \u017durauskien\u0117, J. & Stumpf, M. P. StochSens\u2014matlab package for sensitivity analysis of stochastic chemical systems. Bioinformatics 28, 731\u2013733 (2012).\n\n36. 36.\n\nWack, A., Terczy\u0144ska-Dyla, E. & Hartmann, R. Guarding the frontiers: the biology of type III interferons. Nat. Immunol. 16, 802\u2013809 (2015).\n\n37. 37.\n\nNovatt, H. et al. Distinct patterns of expression of transcription factors in response to interferon \u03b2 and interferon \u03bb1. J. Interferon Cytokine Res. 36, 589\u2013598 (2016).\n\n38. 38.\n\nVanlier, J., Tiemann, C. A., Hilbers, P. A. J. & van Riel, N. A. W. An integrated strategy for prediction uncertainty analysis. Bioinformatics 28, 1130\u20131135 (2012).\n\n39. 39.\n\nSmieja, J., Jamaluddin, M., Brasier, A. R. & Kimmel, M. Model-based analysis of interferon-induced signaling pathway. Bioinformatics 24, 2363\u20132369 (2008).\n\n40. 40.\n\nSwameye, I., M\u00fcller, T. G., Timmer, J., Sandra, O. & Klingm\u00fcller, U. Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling. Proc. Natl. Acad. Sci. USA 100, 1028\u20131033 (2003).\n\n41. 41.\n\nSymmons, O. & Raj, A. What?s luck got to do with it: single cells, multiple fates, and biological nondeterminism. Mol. Cell 62, 788\u2013802 (2016).\n\n42. 42.\n\nLevin, D., Harari, D. & Schreiber, G. Stochastic receptor expression determines cell fate upon interferon treatment. Mol. Cell Biol. 31, 3252\u20133266 (2011).\n\n43. 43.\n\nBar-Even, A. et al. Noise in protein expression scales with natural protein abundance. Nat. Genet. 38, 636\u2013643 (2006).\n\n44. 44.\n\nAmit, I., Wides, R. & Yarden, Y. Evolvable signaling networks of receptor tyrosine kinases: relevance of robustness to malignancy and to cancer therapy. Mol. Syst. Biol. 3, 151 (2007).\n\n45. 45.\n\nTawfik, D. S. Accuracy-rate tradeoffs: how do enzymes meet demands of selectivity and catalytic efficiency? Curr. Opin. Chem. Biol. 21, 73\u201380 (2014).\n\n46. 46.\n\nGarcin, G. et al. Differential activity of type I interferon subtypes for dendritic cell differentiation. PLoS ONE 8, e58465 (2013).\n\n47. 47.\n\nBauer, J. W. et al. Elevated serum levels of interferon-regulated chemokines are biomarkers for active human systemic lupus erythematosus. PLoS Med. 3, e491 (2006).\n\n48. 48.\n\nRajagopal, S., Rajagopal, K. & Lefkowitz, R. J. Teaching old receptors new tricks: biasing seven-transmembrane receptors. Nat. Rev. Drug. Discov. 9, 373 (2010).\n\n49. 49.\n\nKenakin, T. Theoretical aspects of GPCR\u2013ligand complex pharmacology. Chem. Rev. 117, 4\u201320 (2016).\n\n50. 50.\n\nZhou, Z. et al. Type III interferon (IFN) induces a type I IFN-like response in a restricted subset of cells through signaling pathways involving both the Jak-STAT pathway and the mitogen-activated protein kinases. J. Virol. 81, 7749\u20137758 (2007).\n\n51. 51.\n\nDoyle, S. E. et al. Interleukin-29 uses a type 1 interferon-like program to promote antiviral responses in human hepatocytes. Hepatology 44, 896\u2013906 (2006).\n\n## Acknowledgements\n\nT.J. was supported by his own funds and the European Commission Research Executive Agency under grant CIG PCIG12-GA-2012-334298, M.K. and K.N. by the Polish National Science Centre under grant 2015\/17\/B\/NZ2\/03692. We thank Stefan Gr\u00fcnert, Marek Kocha\u0144czyk, Margaritis Voliotis, and Christopher Zechner for their helpful comments during the preparation of this manuscript. The model of biochemical sensor exposed to non-cognate ligand was inspired by discussions with Prof. Dan S. Tawfik.\n\n## Author information\n\n### Affiliations\n\n1. #### Institute of Fundamental Technological Research, Polish Academy of Sciences, Warszawa, 02-106, Poland\n\n\u2022 Tomasz Jetka\n\u2022 ,\u00a0Karol Niena\u0142towski\n\u2022 \u00a0&\u00a0Micha\u0142 Komorowski\n2. #### Department of Mathematics and School of Public Health, Imperial College London, London, SW7 2AZ, UK\n\n\u2022 Sarah Filippi\n3. #### Melbourne Integrative Genomics, School of BioSciences and School of Mathematics and Statistics, University of Melbourne, Parkville, 3010, VIC, Australia\n\n\u2022 Michael P. H. Stumpf\n\n### Contributions\n\nT.J. and M.K. designed research; T.J., K.N., and M.K. performed research; T.J., K.N., S.F., M.P.H.S. and M.K. analyzed data; and T.J., K.N., M.P.H.S. and M.K. wrote the paper.\n\n### Competing interests\n\nThe authors declare no competing interests.\n\n### Corresponding author\n\nCorrespondence to Micha\u0142 Komorowski.","date":"2018-11-17 15:40:41","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 0, \"mathjax_display_tex\": 2, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.6536663174629211, \"perplexity\": 2007.9405009388408}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2018-47\/segments\/1542039743714.57\/warc\/CC-MAIN-20181117144031-20181117170031-00530.warc.gz\"}"}
| null | null |
I wish some UK Government/Establishment figure would explain why these type of characters were, and still are, essential to the "National security" of the UK ???????????
What made them SO important that the MSM had to be silenced regarding them?
I can only presume this guy is essential to "National security" as well?
Is the alleged "Demon Pastor" really James Bond in disguise?
"National security!" Update 1 Murdered boys probe.
We really must ask the question, "How many of the present Kincora Old Boy Association aka the DUP MPs are essential to "National security" ??????
Perhaps Jeffrey Donaldson aka Jeffrey Lundy or Willie Mcrea aka "Willie McLundy could tell us?
The "secret" of "National security" is revealed below.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 4,516
|
Q: DNS_ANY working but DNS_TXT not working for DS_GET_RECORD php function I am trying to debug dns_get_record since it isn't working for me as expected.
I created a Text DNS record "laramon_59939919ec899.glibix.com." with value "dd678f947384ed8d3531465439ff852e01e6eb1d"
With:
$result=dns_get_record('laramon_59939919ec899.glibix.com.',DNS_TXT);
print_r($result);
I get:
Array
(
)
But with:
$result=dns_get_record('laramon_59939919ec899.glibix.com.',DNS_ANY);
print_r($result);
I get:
Array
(
[0] => Array
(
[host] => laramon_59939919ec899.glibix.com
[class] => IN
[ttl] => 86182
[type] => TXT
[txt] => dd678f947384ed8d3531465439ff852e01e6eb1d
[entries] => Array
(
[0] => dd678f947384ed8d3531465439ff852e01e6eb1d
)
)
)
The record I have added is of TXT type. Can someone help me understand why do I not get the correct record when I am specifically looking for TXT record?
A: Thanks to @NickCoons
The DNS record was being returned from cache. I fixed it by changing DNS_TXT to DNS_ALL. Somehow, it seems like only DNS_TXT is returning the cached result.
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 3,508
|
{"url":"https:\/\/leetcode.ca\/2021-07-26-1898-Maximum-Number-of-Removable-Characters\/","text":"Formatted question description: https:\/\/leetcode.ca\/all\/1898.html\n\n# 1898. Maximum Number of Removable Characters\n\nMedium\n\n## Description\n\nYou are given two strings s and p where p is a subsequence of s. You are also given a distinct 0-indexed integer array removable containing a subset of indices of s (s is also 0-indexed).\n\nYou want to choose an integer k (0 <= k <= removable.length) such that, after removing k characters from s using the first k indices in removable, p is still a subsequence of s. More formally, you will mark the character at s[removable[i]] for each 0 <= i < k, then remove all marked characters and check if p is still a subsequence.\n\nReturn the maximum k you can choose such that p is still a subsequence of s after the removals.\n\nA subsequence of a string is a new string generated from the original string with some characters (can be none) deleted without changing the relative order of the remaining characters.\n\nExample 1:\n\nInput: s = \u201cabcacb\u201d, p = \u201cab\u201d, removable = [3,1,0]\n\nOutput: 2\n\nExplanation: After removing the characters at indices 3 and 1, \u201cabcacb\u201d becomes \u201caccb\u201d.\n\n\u201cab\u201d is a subsequence of \u201caccb\u201d.\n\nIf we remove the characters at indices 3, 1, and 0, \u201cabcacb\u201d becomes \u201cccb\u201d, and \u201cab\u201d is no longer a subsequence.\n\nHence, the maximum k is 2.\n\nExample 2:\n\nInput: s = \u201cabcbddddd\u201d, p = \u201cabcd\u201d, removable = [3,2,1,4,5,6]\n\nOutput: 1\n\nExplanation: After removing the character at index 3, \u201cabcbddddd\u201d becomes \u201cabcddddd\u201d.\n\n\u201cabcd\u201d is a subsequence of \u201cabcddddd\u201d.\n\nExample 3:\n\nInput: s = \u201cabcab\u201d, p = \u201cabc\u201d, removable = [0,1,2,3,4]\n\nOutput: 0\n\nExplanation: If you remove the first index in the array removable, \u201cabc\u201d is no longer a subsequence.\n\nConstraints:\n\n\u2022 1 <= p.length <= s.length <= 10^5\n\u2022 0 <= removable.length < s.length\n\u2022 0 <= removable[i] < s.length\n\u2022 p is a subsequence of s.\n\u2022 s and p both consist of lowercase English letters.\n\u2022 The elements in removable are distinct.\n\n## Solution\n\nUse binary search. Initially, low = 0 and high = removable.length. Each time, let mid be the mean of low and high and check whether p is still a subsequence of s after removing mid characters from s according to removable. The maximum possible k can be found in this way.\n\nclass Solution {\npublic int maximumRemovals(String s, String p, int[] removable) {\nint low = 0, high = removable.length;\nwhile (low < high) {\nint mid = (high - low + 1) \/ 2 + low;\nif (isPossible(s, p, removable, mid))\nlow = mid;\nelse\nhigh = mid - 1;\n}\nreturn low;\n}\n\npublic boolean isPossible(String s, String p, int[] removable, int k) {\nint[] removes = new int[k];\nfor (int i = 0; i < k; i++)\nremoves[i] = removable[i];\nArrays.sort(removes);\nStringBuffer sb = new StringBuffer(s);\nfor (int i = k - 1; i >= 0; i--)\nsb.deleteCharAt(removes[i]);\nreturn isSubsequence(p, sb.toString());\n}\n\npublic boolean isSubsequence(String s, String t) {\nif (s.length() == 0)\nreturn true;\nif (s.length() > t.length())\nreturn false;\nint sLength = s.length(), tLength = t.length();\nint sIndex = 0, tIndex = 0;\nwhile (sIndex < sLength && tIndex < tLength) {\nchar sChar = s.charAt(sIndex), tChar = t.charAt(tIndex);\nif (sChar == tChar)\nsIndex++;\ntIndex++;\n}\nreturn sIndex == sLength;\n}\n}","date":"2022-05-17 16:52:45","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 0, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 1, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.23440030217170715, \"perplexity\": 6080.53336580443}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": false}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2022-21\/segments\/1652662519037.11\/warc\/CC-MAIN-20220517162558-20220517192558-00184.warc.gz\"}"}
| null | null |
In organic chemistry, cyclopentanonide is a functional group which is composed of a cyclic ketal of a diol with cyclopentanone. It is seen in amcinonide (triamcinolone acetate cyclopentanonide).
See also
Acetonide
Acetophenide
Acroleinide
Aminobenzal
Pentanonide
References
Cyclopentanonides
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 5,406
|
Sometimes things don't go as planned. Sony released Driveclub for the PlayStation 4 in October of 2014. At the time, a companion came out for Android, but Sony quickly pulled the app after less than a day on the site. The servers struggled to handle the load of everyone trying to play, so Sony delayed the PlayStation Plus Edition and mobile companion app in order to reduce the strain.
Now it's March 2016, and version 1.0 of the Driveclub companion app has returned to Google Play. The software has undergone a name change (it was originally MyDriveclub), and the developers have updated the interface into something that looks more at home on Android Lollipop and Marshmallow.
The app provides a space to track challenges and take on new ones. You can also pick up fame points if you're looking for something else to brag about.
The app is free to use. Hopefully this time the servers are good to go.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 321
|
Q: Where all List values are equal to column List Hello I have a problem and i cant solve it for 3 days. I've red many posts here and in google, but I cant find the solution.
In db I have column "Gener" - nvarchar(350) which contains for example this:
row 1: 1,4,32,11
row 2: 32,11
row 3: 1
row 4: 4,56,1,23
row 5: 4
From checkboxlist I check this values: 1,4 which add to
List<string> gnr = new List<string>();
The result which I want is row 1 and row 4.
I've made (take from stackoverflow) code which result is row 3 and row 4:
var result = from m in db.Movies
where gnr.Contains(m.Gener)
select m;
And code which result is row 1, row 3, row 4 and row 5:
foreach (string term in gnr)
{
var trb = db.movies.Where(o => o.Gener.Contains(term));
}
With Ole DB I can make it, but with LINQ I can't here is the code there:
List<string> Gener = new List<string>();
Gener = Action,Comedy
StringBuilder builder = new StringBuilder();
string lastItem = Gener[Gener.Count - 1];
// Here I made string Which I'll add to cmd string
foreach (string safePrime in Gener)
{
if (safePrime != lastItem)
{
builder.Append("((gener LIKE '%" + safePrime + "%')) AND").Append(" ");
}
else
{
builder.Append("((gener LIKE '%" + safePrime + "%')) ORDER By ID DESC").Append(" ");
}
}
string dbSelect = builder.ToString();
//The result from loop
dbSelect = "((GenerLIKE '%Action%')) AND ((GenerLIKE '%Comedy%')) ORDER By ID"
//Add dbSelect to exist cmd
Cmd1.CommandText = "SELECT * FROM movies WHERE " + dbSelect;
And the result here is what I want with LINQ, select all movies that are Action and Comedy
Thanks for the time you red this, I'll be very thankful for some help. Sorry for my english I hope it is readable.
A: String.Split does not work with Entity Framework, so you can move splitting Gener column value in memory:
var result = from m in db.movies.ToList()
let movieGnr = m.Gener.Replace(" ", "").Split(',')
where m.Gener != null && !gnr.Except(movieGnr).Any()
select m;
Returns rows 1 and 4.
UPDATE: As stated above, this solution will load all movies data into memory. What I suggest to you is changing DB structure - create MovieGeners table, which will contain Geners for each movie. And add navigation property to Movie which will contain list of Geners. This solution will allow to move all query to the database side.
int[] gnr;
var result = from m in db.movies.Include("Geners")
where gnr.All(g => m.Geners.Any(x => x.Id == g))
select m;
A: Below used query would returns row 1 and row 4 data.We need to use where clause and check the row data length. row1 and row 4 data length is 9.This query would work.
var result= db.Movies.Where(mv => mv.Gener.Length > 8).Select(mv => mv.Gener);
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 4,484
|
{"url":"http:\/\/www.math.unist.ac.kr\/news\/5746066179751936\/view","text":"When: Jan. 15th 2020, 16:00.\nWhere: Building 108, Room 318.\n\nSpeaker: Lee Wan (\uc774\uc644), Yonsei University.\n\nTitle: On capitulation map of global fields.\n\nAbstract: For a finite Galois extension L\/K of global fields, let C(L) and C(K) denote the Galois groups of maximal S-ramified T-split abelian extensions of L and M, respectively (where S and T are sets of places). There is a natural map Ver from C(K) to C(L) induced from the transfer homomorphism. Since Artin's principal ideal theorem, to determine the kernel and the cokernel of Ver has been an interesting problem. They can be described by Galois cohomology groups of unit groups. As a corollary, we get the strict cohomological dimension of the Galois group of the S-ramified T-split maximal extension of a global field is equal to 2 when S has Dirichlet density 1 and T is finite.","date":"2020-01-18 21:28:18","metadata":"{\"extraction_info\": {\"found_math\": false, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 0, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.8707513809204102, \"perplexity\": 1076.980315214245}, \"config\": {\"markdown_headings\": true, \"markdown_code\": false, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 10, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2020-05\/segments\/1579250593937.27\/warc\/CC-MAIN-20200118193018-20200118221018-00175.warc.gz\"}"}
| null | null |
Everybody's All-American is a 1988 American sports drama film, released internationally as When I Fall in Love, directed by Taylor Hackford and based on the 1981 novel Everybody's All-American by longtime Sports Illustrated contributor Frank Deford.
The film covers 25 years in the life of a college football hero. It stars Dennis Quaid, Jessica Lange, Timothy Hutton and John Goodman.
Plot
Gavin Grey is a 1950s star athlete known by the moniker "The Grey Ghost," who plays football at the [fictional] University of Louisiana. His campus girlfriend Babs Rogers, nephew Donnie "Cake" McCaslin, and teammate Ed Lawrence adore his personality and charm. During the Sugar Bowl game, Gavin's play, defining his competitiveness throughout his career, causes a player from the opposing team to fumble the ball, which he returns to score a game-winning touchdown.
As his college days come to an end, Gavin ends up marrying Babs, starts a family, and gets drafted by the Washington Redskins. Lawrence opens a popular sports bar in Baton Rouge. Everyone is pleased for Gavin, including his friendly rival Narvel Blue, who might have achieved professional stardom had he chosen an athletic career path. Reality quickly sets in for Gavin as life in the NFL is difficult, the competition is fierce, and the schedule is grueling. Gavin is a respectable running back for the Redskins, but hardly the idol worshipped by everyone back home during his school years. Concurrently, Lawrence has accrued a number of gambling debts. He is later murdered by unidentified attackers, creating more debts for Gavin and Babs, who had invested in Lawrence's business.
Babs does her best to keep up with her husband's career and mood swings, and in doing so inherits the role of the wage earner in their household after he briefly retires. A sympathetic Donnie finds her frustrated and lonely, as his lifetime attraction to her brings them together for a brief extramarital affair. Gavin's financial setbacks encourage Babs to seek a job from Narvel to manage his restaurant.
During his retirement, money issues convince Gavin to accept a comeback offer from the Denver Broncos. The new NFL has passed him by, though, and Gavin is forced to accept that his playing days are over. He enters a failed business relationship with entrepreneur Bolling Kiely, whom he despises, spending countless hours telling old college football stories to clients. Donnie moves on with his life, becoming an author and getting engaged to a sophisticated woman named Leslie Stone, while supporting Gavin and Babs through a marital breakdown. A lost and pathetic figure, in the end, Gavin mends his relationship with Babs as he spends his withdrawal from professional sports reminiscing about his famed athletic youth.
Cast
Jessica Lange as Babs Rogers Grey
Dennis Quaid as Gavin "Grey Ghost" Grey
Timothy Hutton as Donnie "Cake" McCaslin
John Goodman as Ed "Bull" Lawrence
Carl Lumbly as Narvel Blue
Ray Baker as Bolling Kiely
Savannah Smith Boucher as Darlene Kiely
Patricia Clarkson as Leslie Stone
Wayne Knight as Fraternity Pisser
Production
Filming was stopped for weeks when Dennis Quaid had his collarbone broken by former New England Patriots cornerback Tim Fox during Footage of Quaid rolling in pain on the sidelines of the snow game appears in the finished film. A key scene featuring a candlelight parade involving large numbers of extras was filmed, on the steps of the Louisiana State Capitol, when snow started falling. Despite the beauty of the scene, director Taylor Hackford elected to reshoot the scene, as snow in Baton Rouge in November was such a rare event that he was worried it would be seen as a special effects goof in the film.
The game scenes were shot in LSU's Tiger Stadium during the halftimes of actual LSU games in 1987. The goalposts were altered to resemble the vintage "H" posts as needed during filming. Vertical posts were moved in place for the bottom portion of the H, and a multi-colored fabric covering was used to conceal the "modern" center support post. Upon completion of filming, the vertical posts and fabric were retracted so as not to interfere with the LSU games. In late 1993, LSU installed an updated model of the vintage posts permanently in the stadium. Some of the filming of the football scenes took place during halftime of the LSU-Alabama game on The producers wanted to continue shooting some scenes following the game, so they requested that the LSU fans remain after the game so that they could finish the scenes. However, Alabama won in and ten minutes after the game, the only fans still in the bleachers were wearing crimson, forcing the producers to finish shooting the following week (November 14) following LSU's game with Mississippi State,
Michael Apted was all set to direct Thomas Rickman's script in 1982 until Warner Bros. balked at the $16 million price tag, leading man Tommy Lee Jones and the fact that American football movies never do any business overseas. During its six years in development hell, Warren Beatty, Robert Redford, and Robert De Niro all circled the project.
Despite the fact that the novel was written about the University of North Carolina (which refused to allow filming because they suspected the story defamed campus legend Charlie "Choo Choo" Justice), when it was filmed at LSU, rumors started that Gavin Grey was based on the former LSU All-American Billy Cannon. He won the Heisman Trophy in 1959 and played eleven seasons for three professional teams, but served two and a half years in federal prison in the mid-1980s for his role in a counterfeiting ring. Deford himself denies this, saying: "Never met Cannon and knew nothing about him personally," he says. "Gavin was strictly a composite of many athletes from several sports that I had covered."
The film contains a much more hopeful and upbeat ending than the book, where Gavin takes his own life after trying to kill Babs as well.
Reception
Reaction to the film was mostly mixed. Review aggregator Rotten Tomatoes gives it a 44% rating based on 32 reviews, with an average rating of 5.2/10. Audiences polled by CinemaScore gave the film an average grade of "B+" on an A+ to F scale.
References
External links
Interview with Dennis Quaid from Everybody's All-American press junket at Texas Archive of the Moving Image
1988 films
1988 drama films
1980s sports drama films
American football films
American sports drama films
Films based on American novels
Films directed by Taylor Hackford
Films scored by James Newton Howard
Films set in the 1950s
Films set in the 1960s
Films set in Louisiana
Films shot in Colorado
Films shot in Louisiana
Warner Bros. films
1980s English-language films
1980s American films
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 2,523
|
On Campus: Franklin's Chris Rodgers carries on the family hoops legacy
By Tim Whelan Jr./Daily News Correspondent
The Boston Celtics brought the Rodgers family to Massachusetts in 1979. In 2017, the family legacy is still strong on the court.
Raised in Franklin, Chris Rodgers is a junior standout for the men's basketball team at Worcester Polytechnic Institute. He also happens to be the grandson of former Celtics assistant and head coach Jimmy Rodgers.
In the 1980s, members of the Rodgers family shined at Walpole High. Tim Rodgers, Chris' dad, went on to play football at Tufts University, while Tim's younger brother Matt played quarterback at Iowa.
Chris Rodgers is carving out his own niche. The industrial engineering major is a member of the NEWMAC Academic All-Conference team, and his on-court work has been an asset as well.
"I knew this school would be the perfect fit for me," Rodgers said last week. "It's hard to believe I'm already a junior looking ahead at my senior year."
This weekend, the WPI men's basketball team did what it does every year, finding itself among the final four in the conference.
It wasn't to be, however. On Saturday, the Engineers' season came to an end in a hard-fought 63-61 defeat to MIT in the NEWMAC semifinal. Rodgers played 38 minutes, scoring 12 points to go with five rebounds. The Engineers finish at 17-9, breaking a streak of 13 straight seasons finishing with 20 or more victories.
"We wanted to be playing our best basketball as we entered the NEWMAC tournament," Rodgers said just days after he recorded the first double-double of his college career (13 points, 10 rebounds) in a Feb. 15 win at Wheaton.
Rodgers has been integral to keeping the team near the top of the NEWMAC standings the last few years. A starting guard, his 9.5 points per game were third on the team. The 6-foot-2 swingman also averaged 4.8 rebounds and 2.2 assists per contest.
The second of Tim and Carolyn's four kids, with an older sister Sarah and younger brothers Patrick and Jack, inherited the basketball gene from a staple of the Larry Bird-era Celtics.
Jimmy Rodgers was quite a familiar face around the area in the 1980s. After arriving as an assistant with head coach Bill Fitch in 1979, Rodgers was a part of three NBA champions. He was the Celtics' head coach for two seasons, from 1988 through 1990.
He went on to be the head coach of the expansion Minnesota Timberwolves and was a Chicago Bulls assistant for five years, where he was part of the final three Michael Jordan-led title teams.
"Having somebody like my grandfather to talk to, him knowing how college basketball works, he's a great help," Rodgers said. "More than anyone, though, my dad's been so supportive."
His grandfather's time growing up in the Chicago suburbs, playing at the University of Iowa, then having a 34-year coaching career that began at the University of North Dakota and was followed by four NBA stops lends itself to some memorable tales.
For most of the year, Rodgers' grandparents live in Naples, Fla. For the summer, though, they come up and stay with the Franklin branch of the Rodgers clan.
"He's got some of the best stories," his grandson said. "Really funny stuff."
Growing up in Franklin, Rodgers felt the tight bond between the community and its student-athletes from an early age.
"As early as sixth grade, we were learning to run the offense that Franklin High ran," Rodgers said. "I took a lot of pride playing for Franklin, thinking about everybody who came before me, and we wanted to keep that success going."
Rodgers recalled a particularly fun moment when he was a junior at Franklin in 2013 and the Panthers beat a powerful Mansfield team at the old Franklin Field House on Senior Night.
As a senior during the last season of the field house before it was torn down, the late venue will always have a soft spot for him and other Panthers.
"I miss it so much," Rodgers said. "It was the best, especially for big games. Just an amazing environment to have for a home court."
The college game, as with any sport, provided a wake-up call for Rodgers. Division III basketball is a big jump up from the Hockomock League.
"You come to college, and you're not faster than others on the court anymore," he said. "You have to hone your technique, like getting two feet in paint to get a rebound. You're not jumping over everyone — they can jump with you.
"But the game has slowed down. I'm thinking the game even more."
Rodgers has one more college offseason to prepare to get WPI back near the top of the NEWMAC. A familiar name in New England basketball lore is carrying on a family tradition.
Natick's Young ends swimming career on high note
Several months back, we wrote about Natick's Alex Young in this space. The Catholic Memorial product was a part of a Holy Cross record in the 400-yard (4x100) freestyle relay in each of Young's first three years as a Crusader.
Last weekend, the senior co-captain Young and his teammates made it four-for-four.
At the Patriot League Championships at Bucknell University in Lewisburg, Pa., Young managed to swim his fastest-ever split in the 100 — 47.91 seconds — despite being treated for pneumonia. His performance was part of the team-record pace of 3:08.39, narrowly breaking last year's mark of 3:09.61.
Hopkinton's Bolick shines at New Englands
Bentley University senior Tim Bolick, a 2013 Hopkinton graduate, had one of the highest individual finishes for the Falcons' indoor track team during the New England Intercollegiate Amateur Athletic Association Championships on Saturday at the Reggie Lewis Center.
Bolick was 10th of 32 in the 800 meters (1:54.13), achieving a new personal best by 1.26 seconds. His performance elevated him to sixth on Bentley's all-time list. Bolick was also part of Bentley's 4x800 relay that placed ninth overall and second among Division II participants in 7:56.43.
Tim Whelan Jr. can be reached at whelan.timothy@gmail.com. Follow him on Twitter @thattimwhelan.
Millis
Milford Daily News ~ 197 Main St., Milford, MA 01757 ~ Do Not Sell My Personal Information ~ Cookie Policy ~ Do Not Sell My Personal Information ~ Privacy Policy ~ Terms Of Service ~ Your California Privacy Rights / Privacy Policy
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 6,237
|
{"url":"https:\/\/math.stackexchange.com\/questions\/886909\/int-0-infty-frac-sin2xx2x21-dx","text":"$\\int_0^\\infty \\frac{\\sin^2(x)}{x^2(x^2+1)} dx$ =?\n\nAfter reading articles on differentiation under the integral sign, I hit this post from mit, where after introducing the power tool, it challenges reader to do\n\n$$\\int_0^\\infty \\frac{\\sin^2(x)}{x^2(x^2+1)} dx$$\n\nObviously I have no clue where to start. Could any one give a hint?\n\n\u2022 I think you can simplify first the integral using partial fractions since $\\frac{1}{x^2 \\left(x^2+1\\right)}=\\frac{1}{x^2}-\\frac{1}{x^2+1}$. The first integral is simple; the second one is more problematic to me. Good luck. \u2013\u00a0Claude Leibovici Aug 4 '14 at 7:18\n\u2022 The definite integral of $\\frac{1}{x^2+1}$ is simple: it is $\\arctan(x)$. Remember that $\\arctan(0)=0$ and $\\arctan(\\infty)=\\pi\/2$. \u2013\u00a0Steven Van Geluwe Aug 4 '14 at 7:27\n\u2022 This question is the same as the problem in this link math.stackexchange.com\/questions\/691798\/\u2026 \u2013\u00a0xpaul Aug 4 '14 at 23:46\n\nThis is a possible way to evaluate the integral. Partial fraction decomposition and the double angle formula yield $$\\int^\\infty_0\\frac{\\sin^2{x}}{x^2(1+x^2)}dx=\\frac{1}{2}\\int^\\infty_0\\frac{1-\\cos{2x}}{x^2}dx-\\frac{1}{2}\\int^\\infty_0\\frac{1-\\cos{2x}}{1+x^2}dx$$ The first integral can be evaluated in many ways, differentiation under the integral sign is one of them. I prefer to proceed with a simple fact that follows from the definition of the gamma function. $$\\int^{\\infty}_0t^{n-1}e^{-xt} \\ dt=\\frac{\\Gamma(n)}{x^n}$$ Hence the first integral is \\begin{align} \\frac{1}{2}\\int^\\infty_0\\frac{1-\\cos{2x}}{x^2}dx &=\\frac{1}{2}\\int^\\infty_0(1-\\cos{2x})\\int^\\infty_0te^{-xt} \\ dt \\ dx\\\\ &=\\frac{1}{2}\\int^\\infty_0t\\int^\\infty_0e^{-xt}(1-\\cos{2x}) \\ dx \\ dt\\\\ &=\\int^\\infty_0\\left(\\int^\\infty_0e^{-xt}\\sin{2x} \\ dx\\right)dt\\\\ &=\\int^\\infty_0\\frac{2}{t^2+4}dt\\\\ &=\\frac{\\pi}{2}\\\\ \\end{align} The second integral can be broken up further and evaluated using the residue theorem. \\begin{align} \\frac{1}{2}\\int^\\infty_0\\frac{1-\\cos{2x}}{1+x^2}dx &=\\frac{\\pi}{4}-\\frac{1}{4}\\Re\\oint_{\\Gamma}\\frac{e^{2iz}}{1+z^2}dz\\\\ &=\\frac{\\pi}{4}-\\frac{1}{2}\\Re\\left(\\pi i\\operatorname{Res}(f,i)\\right)\\\\ &=\\frac{\\pi}{4}-\\frac{1}{2}\\Re\\left(\\pi i\\frac{e^{-2}}{2i}\\right)\\\\ &=\\frac{\\pi}{4}-\\frac{\\pi}{4e^2} \\end{align} Hence $$\\int^\\infty_0\\frac{\\sin^2{x}}{x^2(1+x^2)}dx=\\frac{\\pi}{4}\\left(1+e^{-2}\\right)$$\n\n\u2022 thanks a lot and.. the trick with $\\int^{\\infty}_0t^{n-1}e^{-xt} \\ dt=\\frac{\\Gamma(n)}{x^n}$ is brilliant! i only saw $n=1$ case before, never realized that could utilize $n>1$! \u2013\u00a0athos Aug 4 '14 at 10:35\n\nCould any one give a hint?\n\nPartial fraction decomposition, together with the fact that\n\n\u2022 $\\displaystyle\\int_0^\\infty\\frac{\\sin^2x}{x^2}dx=\\frac\\pi2$\n\n\u2022 $\\sin^2x=\\dfrac{1-\\cos2x}2$\n\n\u2022 $\\displaystyle\\int_0^\\infty\\frac{\\cos x}{x^2+a^2}dx=\\frac\\pi{2a~e^a}$","date":"2019-06-17 12:35:45","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 0, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 1, \"mathjax_display_tex\": 1, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 2, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.9855247735977173, \"perplexity\": 691.3001209810684}, \"config\": {\"markdown_headings\": false, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.3, \"absolute_threshold\": 20, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2019-26\/segments\/1560627998475.92\/warc\/CC-MAIN-20190617123027-20190617145027-00143.warc.gz\"}"}
| null | null |
Development notes
=================
In here are a few notes about how the code is organized, used concepts, etc.
The main code is all pure Python. It is highly modular. The main playing engine is implemented in C/C++ as a Python module ([`ffmpeg.c`](https://github.com/albertz/music-player/blob/master/ffmpeg.c) and related). It uses [FFmpeg](http://ffmpeg.org/) for decoding and [PortAudio](http://www.portaudio.com/) for output.
A basic principle is to keep the code as simple as possible so that it works. I really want to avoid to overcomplicate things.
The main entry point is [`main`](https://github.com/albertz/music-player/blob/master/main.py). It initializes all the modules. The list of modules is defined in [`State.modules`](https://github.com/albertz/music-player/blob/master/State.py). It contains for example `queue`, `tracker`, `mediakeys`, `gui`, etc.
## Module
A module is controlled by the `utils.Module` class. It refers to a Python module (for example `queue`).
When you start a module (`Module.start`), it starts a new thread and executes the `<modulename>Main` function.
A module is supposed to be reloadable. There is the function `Module.reload` and `State.reloadModules` is supposed to reload all modules. This is mostly only used for/while debugging, though and is probably not stable and not well tested.
## Multithreading and multiprocessing
The whole code makes heavy use of multithreading and multiprocessing. Every module already runs in its own thread. But some modules itself spawn also other threads. The GUI module spawns a new thread for most actions. Heavy calculations should be done in a seperate process so that the GUI and the playing engine (which run both in the main process) are always responsive. There is `utils.AsyncTask` and `utils.asyncCall` for an easy and stable way to do something in a seperate process.
## Playing engine
This is all the [Python native-C/C++ module](https://github.com/albertz/music-player-core/).
The `player` module creates the player object as `State.state.player`. It setups the queue as `queue.queue`. `State.state` provides also some functions to control the player state (`playPause`, `nextSong`).
## GUI
The basic idea is that Python objects are directly represented in the GUI. The main window corresponds to the `State.state` object. Attributes of an object which should be shown in the GUI are marked via the `utils.UserAttrib` decorator. There, you can specify some further information to specify more concretely how an attribute should be displayed.
The GUI has its own module [`gui`](https://github.com/albertz/music-player/blob/master/gui.py). At the moment, only an OSX Cocoa interface ([`guiCocoa`](https://github.com/albertz/music-player/blob/master/guiCocoa.py)) is implemented but a PyQt implementation is planned. There is some special handling for this module as it needs to be run in the main thread in most cases. See `main` for further reference.
## Database
This is the module [`songdb`](https://github.com/albertz/music-player/blob/master/songdb.py).
The database is intended to be an optional system which stores some extra data/statistics about a song and also caches some data which is heavy to calculate (e.g. the fingerprint).
It provides several ways to identify a song:
- By the SHA1 of its path name (relative to the users home dir).
- By the SHA1 of its file.
- By the SHA1 of its AcoustId fingerprint.
This is so that the database stays robust in case the user moves a song file around or changes its metadata.
It uses [SQLite](http://www.sqlite.org/) as its backend. (As it is used mostly as a key/value store with optional external indexing, a complex SQL-like DB is not strictly needed. Earlier, I tried other DBs. For a history, see the [comment in the source](https://github.com/albertz/music-player/blob/master/songdb.py).)
It uses [binstruct](https://github.com/albertz/binstruct) for the serialization.
## Song attribute knowledge system
Some of the initial ideas are presented in [`attribs.txt`](https://github.com/albertz/music-player/blob/master/attribs.txt). This is implemented now mostly for the [`Song` class](https://github.com/albertz/music-player/blob/master/Song.py).
There are several sources where we can get some song attribute from:
- The local `song.__dict__`.
- The database.
- The file metadata (e.g. artist, title, duration).
- Calculate it from the file (e.g. duration, fingerprint, ReplayGain).
- Look it up from some Internet service like MusicBrainz.
To have a generic attribute read interface which captures all different cases, there is the function:
Song.get(self, attrib, timeout, accuracy)
For each attrib, there might be functions:
- `Song._estimate_<attrib>`, which is supposed to be fast. This is called no matter what the `timeout` is, in case we did not get it from the database.
- `Song._calc_<attrib>`, which is supposed to return the exact value but is heavy to call. If this is needed, it will be executed in a seperate process.
See [`Song`](https://github.com/albertz/music-player/blob/master/Song.py) for further reference.
## Playlist queue
The playlist queue is managed by the [`queue`](https://github.com/albertz/music-player/blob/master/queue.py) module. It has the logic to autofill the queue if there are too less songs in it. The algorithm to automatically select a new song uses the random file queue generator. This is a lazy directory unfolder and random picker, implemented in [`RandomFileQueue`](https://github.com/albertz/music-player/blob/master/RandomFileQueue.py). Every time, it looks at a few songs and selects some song based on
- the song rating,
- the current recently played context (mostly the song genre / tag map).
## Debugging
The module [`stdinconsole`](stdinconsole.py), when started with `--shell`, provides a handy IPython shell to the running application (in addition to the GUI which is still loaded). This is quite helpful to play around. In addition, as said earlier, all the modules are reloadable. I made this so I don't need to interrupt my music playing when playing with the code.
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 1,111
|
Proving it is possible to close the pay gap between women and men in the workforce, enterprise software company Salesforce, under chairman and CEO Marc Benioff, has effectively bridged that disparity for its 28,000 global employees.
Salesforce's cloud-based, customer relationship management program allows businesses to manage their sales, service and marketing online rather than spending on IT infrastructure. The San Francisco-headquartered company has a market value of more than $66 billion; Benioff is not only an entrepreneur, but also a philanthropist committed to using his and his company's business acumen for the greater good. He recently spoke at the U.N. and participated in the World Economic Forum's Sustainable Development Impact Summit.
It was a concerted effort to accomplish parity, says Cindy Robbins, Salesforce's president and chief people officer. Beginning in 2015, Benioff established a program within the company to identify female executives with promise and mandating that these "high-potential" women would be included in quarterly operational review meetings.
The next step became, "How can we be more overt about bringing women's issues to table?" says Robbins, who along with a colleague broached the issue of equal pay. Benioff quickly agreed that equality had to be a core value of the company. "It turns out, getting his support was the easy part," says Robbins.
A company-wide audit and evaluation began: compensation was analyzed by employee groups in comparable roles to determine pay scale differences. Initially the company spent close to $3 million to reduce salary differences to ensure that those employees performing similar work at the same level were paid consistently. In 2017, the company conducted a second assessment and spent another $3 million to address variances.
Robbins explains that pay gaps exist for a variety of reasons from hiring and promotional practices to women carrying a gap from previous employment. Per the U.S. Census Bureau's latest stats, women on average earn 21% less than male counterparts in the same job.
Champions for equal pay include actress Patricia Arquette, who famously called for wage equality during her supporting actress acceptance speech at the 2015 Oscars. Benioff is among the first CEOs to address the issue.
"Our employees and company have responded really well as a whole," says Robbins, who credits Benioff for doing the right thing. "The CEO sets the tone and vision and we could not have done this without Marc. He drives the message," says the HR exec. She explains other companies can follow suit by closely examining compensation data; despite numerous variables (such as job level), an inspection will most likely yield discrepancies.
Variety's EmPOWerment Award is given to a male executive who uses his influence to further gender equality in the workplace. Previous recipients include Lucian Grainge, CEO of Universal Music Group, and Jim Gianopulos, Paramount Pictures CEO.
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 4,698
|
Q: Animating Fragment causes other view to "jump" Short Question:
When using animation on FragmentTransactions, how can I animate other views with the animation?
Long Question:
Hi,
I am new to fragments and so on, and i am trying to animate them i a single activity so I created the following xml file for the activity:
<LinearLayout
android:id="@+id/run_select_fragment_container"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:keepScreenOn="true"
android:orientation="vertical">
<FrameLayout
android:id="@+id/activity_run_search_fragmentHeaderPlaceholder"
android:layout_width="match_parent"
android:layout_height="wrap_content" />
<FrameLayout
android:id="@+id/activity_run_search_fragmentPlaceholder"
android:layout_width="match_parent"
android:layout_height="0dp"
android:layout_weight="1"/>
</LinearLayout>
Then I definded the res/anim files i want to use for the animation:
fade_in_from_top.xml
<?xml version="1.0" encoding="utf-8"?>
<set xmlns:android="http://schemas.android.com/apk/res/android"
android:shareInterpolator="false">
<alpha android:fromAlpha="0.0" android:toAlpha="1.0"
android:duration="@android:integer/config_longAnimTime" />
<translate
android:fromXDelta="0%" android:toXDelta="0%"
android:fromYDelta="-100%" android:toYDelta="0%"
android:duration="1000" />
</set>
fade_in_from_bottom.xml
<?xml version="1.0" encoding="utf-8"?>
<set xmlns:android="http://schemas.android.com/apk/res/android"
android:shareInterpolator="false">
<alpha android:fromAlpha="0.0" android:toAlpha="1.0"
android:duration="@android:integer/config_longAnimTime" />
<translate
android:fromXDelta="0%" android:toXDelta="0%"
android:fromYDelta="100%" android:toYDelta="0%"
android:duration="1000"/>
</set>
fade_out_to_bottom.xml
<?xml version="1.0" encoding="utf-8"?>
<set xmlns:android="http://schemas.android.com/apk/res/android"
android:shareInterpolator="false">
<alpha
android:duration="@android:integer/config_longAnimTime"
android:fromAlpha="1.0"
android:toAlpha="0.0" />
<translate
android:duration="700"
android:fromXDelta="0%"
android:fromYDelta="0%"
android:toXDelta="0%"
android:toYDelta="100%" />
</set>
fade_out_to_top.xml
<?xml version="1.0" encoding="utf-8"?>
<set xmlns:android="http://schemas.android.com/apk/res/android"
android:shareInterpolator="false">
<alpha
android:duration="@android:integer/config_longAnimTime"
android:fromAlpha="1.0"
android:toAlpha="0.0" />
<translate
android:duration="700"
android:fromXDelta="0%"
android:fromYDelta="0%"
android:toXDelta="0%"
android:toYDelta="-100%" />
</set>
In detail:
The lower fragment contains always a listview with several items. I do change the fragments based on what to search by a toggle button. thats no problem. When the user clicks on a specific listentry the headerFragment will be filled with additional data and displayed with a fade in animation like:
First show loading fragment while loading the data:
final RSBaseFragment headerFragment = (RSBaseFragment) getSupportFragmentManager().findFragmentById(R.id.activity_run_search_fragmentHeaderPlaceholder);
FragmentTransaction ft = getSupportFragmentManager().beginTransaction();
LoadingFragment fragment = new LoadingFragment();
if (headerFragment != null) {
ft.setCustomAnimations(R.anim.fade_in_from_bottom, R.anim.fade_out_to_top, R.anim.fade_in_from_top, R.anim.fade_out_to_bottom);
ft.replace(R.id.activity_run_search_fragmentHeaderPlaceholder, fragment, HEADER_FRAGMENT_TAG);
} else {
ft.setCustomAnimations(R.anim.fade_in_from_top, R.anim.fade_out_to_bottom, R.anim.fade_in_from_bottom, R.anim.fade_out_to_top);
ft.add(R.id.activity_run_search_fragmentHeaderPlaceholder, fragment, HEADER_FRAGMENT_TAG);
}
ft.commit();
After data was loaded show the data in a new fragment replacing the loading fragment
HeaderFragment fragment = new HeaderFragment();
ft.setCustomAnimations(R.anim.fade_in_from_top, R.anim.fade_out_to_bottom, R.anim.fade_in_from_bottom, R.anim.fade_out_to_top);
ft.replace(R.id.activity_run_search_fragmentHeaderPlaceholder, fragment, HEADER_FRAGMENT_TAG);
The problem ist that the headerfragment is fading and sliding in from the top or bottom direction, while the fragment holding the listview ist "jumping" to the bottom Y of the headerfragment before it's even there. How can I animate the lower fragment to slide with the header fragment to create a smooth user experience?
Sorry for the long question. If searched for 3 days and did not found anything helping with my problem.
A: I nearly solved it by adding to the LinearLayout (run_select_fragment_container)
android:animateLayoutChanges="true"
And in the onCreate of the Activity I have done this
LinearLayout mainLayout = (LinearLayout) findViewById(R.id.run_select_fragment_container);
LayoutTransition layoutTransition = mainLayout.getLayoutTransition();
layoutTransition.enableTransitionType(LayoutTransition.CHANGING);
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 5,226
|
var Benchmark = require('benchmark');
var suite = new Benchmark.Suite();
var Mustache = require('mustache');
var Plates = require('../lib/plates');
suite
.add('mustache', function() {
var view = { "foo": "Hello, World" };
var template = '<div id="foo">{{foo}}</div><div class="foo">';
Mustache.to_html(template, view);
})
.add('plates', function() {
var view = { "foo": "Hello, World" };
var template = '<div id="foo"></div><div class="foo">';
Plates.bind(template, view);
})
.on('cycle', function(event, bench) {
console.log(String(bench));
})
.on('complete', function() {
console.log('Fastest is ' + this.filter('fastest').pluck('name'));
})
.add('mustache iterations', function() {
var view = {
"stooges": [
"Moe",
"Larry",
"Curly"
]
};
var template = '{{#stooges}}<b>{{name}}</b>{{/stooges}}';
Mustache.to_html(template, view);
})
.add('plates iterations', function() {
var view = {
"stooges": [
"Moe",
"Larry",
"Curly"
]
};
var template = '<b class="stooges">Name</b>';
Plates.bind(template, view);
})
.run(true);
|
{
"redpajama_set_name": "RedPajamaGithub"
}
| 6,388
|
Classifieds Currency exchange Newsletter
Login / Register BASKET
Helpguides
French Facts
Bilingual Crosswords
Amazing France
About Us / Legal Information
Featured links to other websites
The Connexion Shop
French news ×
If you have refined your search by clicking on one of the terms in the left-hand panel you can remove the filter by clicking on the × beside the category used to filter the results.
Search for "" in the "French news" category returned 173 matches.
French town with Australia link raises €18k for fires
A small French town with links to Australia going back to World War One has raised more than €18,000 for the fire-ravaged country.
Author: Connexion journalist
French town with Australia link sends wildfire support
A French school with links to Australia dating back to World War One is raising money and organising events in solidarity as the country continues to be devastated by deadly wildfires.
Paris museum welcomes 'Instagram artist in residence'
The Musée d'Orsay in Paris is to welcome a French "artist in residence" on its Instagram social media account, who will each week highlight one of the museum's great artists as if they were still alive today.
France celebrates with traditional galette des rois
It is galette des rois season in France, as the country marks Epiphany on January 6, and bakers compete to make the best, most original versions of the popular patisserie.
Bacon, money, proud...9 words English took from French
Any English speaker who has tried to learn French will know that it is not always easy to master, but a new book has shown that some surprising words are more similar than you might think.
New Paris show tells history of France...in Playmobil
More than 3,000 figures from children's toy brand Playmobil are now on public display at the army museum at Les Invalides in Paris, arranged in scenes from French history.
French Bordeaux guide recreates 15th century monuments
Monuments dating back to the 15th century have "reappeared" in the city of Bordeaux (Gironde, Nouvelle-Aquitaine) thanks to a 3D virtual reality project created by a local guide.
French chocolatier marks Berlin Wall fall in chocolate
A French chocolatier has celebrated 30 years since the fall of the Berlin Wall by replicating part of the infamous structure - using one tonne of solid chocolate.
Planet Mercury Sun event to be visible from France
The planet Mercury is to pass in front of the Sun early next week, in a rare sight that will be partly visible from mainland France.
French family keepsake up for auction at €24m
Small artwork recognised as lost 13th-century masterpiece
© English Language Media 2020, All rights reserved. Privacy policy Terms and conditions
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 2,388
|
Home/Travel/3 most popular festivals of Kenya
3 most popular festivals of Kenya
Paul watson November 3, 2020
Kenya is one of the richest countries with strong cultural diversity, as the country possess more that seventy tribal group within it. Kenya is the only African land in which different people from different parts of the continent migrated and settled in throughout the African history. This makes the land more peculiar as each and every group of people have their own style of living including their culture, tradition and festivals. Kenya is the land of colorful festivals, that sprinkles the individual culture of each clan on you during each festival. Every Kenyan festival brings people together to celebrate with joy and energy which is the secret of the unity of the communities till date.
Lamu Cultural Festival (November)
Lamu Cultural festival is celebrated by the Lamu community people and the people living in the island of Lamu of Kenya including other community members to celebrate their peaceful lifestyle from the past to the present and to the future. The Lamu people have their own cultural heritage and beliefs that is loved and attracted by number of tourists who take part in the celebration. According to their belief, every year, Lamu gains life during the Lamu Cultural festival. During this festival, the entire group of Kenyans gets gathered in the place to celebrate their beliefs and life styles that the Lamu people consider their soul and life. The cultural festival takes over with numbers of competitions and different races like donkey races (the highlight of the Lamu festival including endearing symbol the culture and tradition of the community), henna painting, Swahili poetry, dhow sailing and so on, in which the people participate with enthusiasm and joy. One of the oldest games played during this festival is the Boa competition which has some archeological evidences of playing it from thousands of years ago by the African people. The Lamu Cultural festival teaches every one about the insight of life, how life was led by their ancestors along with peaceful and loving lifestyle and architecture. Visiting Kenya during the festival is considered as the best time to visit Lamu,as the lessons of life can be learned in simple and attractive manner.
The entire life style of the Lamu people can be seen during this festival, including Lamu weddings, special henna paintings, and special dishes of Swahili. Their beliefs are followed from their ancestral ages and are engraved deeply in the heart and soul of every local in Kenya. The Lamu Island is located off the coastal area of Kenya that gets alive every year during the Lamu cultural festival. Along with the culture and beliefs, the festival also promotes the beauty and uniqueness of the island of Lamu as well as its people. The festival is usually celebrated at the end of November, from 21 to 24th of the month on which thousands of tourists from all over the world enjoy their trip to Kenya. Being 700 years old, the Lamu Island is declared as one of the Heritage Sites of the World. As Lamu was ruled by the Oman, most of the people of the Island are Muslims, and Islam plays an important role in the Lamu cultural festival. The festival was launched in 2001 that is supported and sponsored by various private and international embassies. The old skills of the Swahili culture like reading and storytelling is also greatly encouraged during the festival. The festival astonishes the foreigners with its magic of new life, and things turning old as you can see an ancient form of Lamu during these days.
Lake Turkana Festival (11-16 June)
Celebrated in the month of May, the Lake Turkana Festival is celebrated for encouraging and strengthening the bond and unity of different communities of the people. Nearly all the main tribal groups, living in northwest Kenya like Borana, Burji, Elmolo, Garee, Dassanech, Gabbra, Somali, Konso, Samburu, Rendille, Turkana, Sakuye and Wata, come forward to celebrate this festival so that they can get a chance to overcome all the stereotypes among them and can come under mutual understanding with themselves. As these communities of people have a bitter history on their side, as they fought frequently with each other for their rights in the past, this festival was organized for enriching their understanding and unity. The festival is celebrated every year in a small town named Loiyangalani, located on the south eastern coastal region of Lake Turkana. The place is well known for its Desert Museum that you can see nowhere else except here. Peaceful coexistence between different cultures are promoted through this festival. Nearly ten local ethnic communities live on the coast of Lake Turkana and the Lake Turkana Festival displays the performances of the ten communities,which can be considered unique and attractive by the outsiders. These people have their own way of living, living in unique huts and with a different variety of foods that can be tasted and enjoyed by the people who attend the festival.
The life and customs of the ten communities of Lake Turkana, their tradition and culture, arts and crafts, and music and dance leaves you with a positive experience that gives the fascinating and positive perception of life along the region of Lake Turkana. Each year the celebration takes place on a full moon day, which increases the beauty of the festival. Wandering on the streets of Loiyangalani gives you a memorable experience as the streets are decorated with festival mood, lights and cheers of different tribal clans. The festival goes for three days and on the final day of the festival the celebration ends with some political speeches, traditional dances, dramas or stage shows, fashion shows in their original traditional costumes and discos. Being a tourist, it will be more enthusiastic to wander along the streets and among the crowd of local tribes and watching the participants, visiting their traditional house and tasting their native food. Traveling to Lake Turkana with proper tourist guidance at the end of April and in May will let you experience the wonderful event.
Maulidi Festival (9-10 November)
Maulidi is one of the historical festivals of Kenya that is organized every year. As most of the Kenyan population belongs to the Muslim religion, Maulidi Festival has become one of the permanent features of the Islamic activities. The festival is celebrated in Lamu that gathers numbers of Muslims from several parts of the African continent, including from East Africa, and also the Islamic people from many parts of the world. This festival is celebrated on the birth of Prophet Mohammed, which is considered as the most important day of Muslims. Maulidi Festival is celebrated on the third month of every year as per the Muslim Calendar. According to the normal calendar used by world, the festival takes place during the month of June. The festival is being sponsored by the National Museum of Kenya from 1990 and also many local and international sponsors. The festival is organized with many cultural competitions like swimming, donkey races, which are the unique sports of the people of Kenya, tug of war, and henna painting competitions. The streets are filled with Swahili music and traditional dances as Lamu is well known for its rich culture and history. This is the main reason for which the Muslims of East Africa choose Lamu as the center for this event. Thousands of Muslims from all over the world recite qasidas prayers together that bring goosebumps to the listeners, and the festival gives you one unforgettable experience.
As the towns of Lamu are set in stone, traveling to Lamu for the Maulidi festival gives an outside the world feeling with its old history, culture and tradition since the town exists from the early 7th century. The Riyadha mosque founded in 1866 in Lamu is the location for their prayers. The peaceful and relaxing environment of Lamu with its beaches and natural richness makes the festival mood fresher and relaxed. Goma dance is most popular in the festival, in which people with their traditional dress and with a walking stick dance accordingly to the sound of the drum. The chanting and prayers can be heard throughout the night around the mosque accompanied with dance and songs. In spite of being a religious festival, it is also a historical festival so that the visitors are also allowed to participate with the natives. Visiting the island of Lamu during the Maulidi festival will impress the tourists and make them fall in love with the place and circumstances including the warmth and hospitality of the Lamu people.
Visit the German website Backpackertrail to find out more about this beautiful country, and to find out what activities Kenya has to offer.
List of other major festivals
January – New Year's Day
March – Nairobi Film Festival
April – Good Friday on April 19 Easter Monday on April 22
May – Labor Day
June – Madaraka Day on June 1, Eid al Fitr on June 5, Lake Turkana Festival, Maulidi Festival
August – Idd-ul-Azha on August 12, Maralal Camel Derby
October – Mashujaa Day on October 21, Moi day on October 10, Diwali on October 27
November – Lamu Cultural Festival
December – Independence Day (Jamhuri) on December 12, Christmas Day on December 25th, Boxing day on December 26, Rusinga Festival, Pawa Festival
Get Personalised Gifts Online at Best Price
Your Guide to the Different Types of Water Softeners
11 Places to Eat Free on Your Birthday
Most Enduring Fashion Emblems of 2020
Top Brothels In Melbourne
Different types of online advertisements
Have the Most Memorable Wedding: Get Married on a Yacht
Woman Luck Within An On The Internet Casino Gambler
What types of affiliate programs are offered
The Different Categories of Online Gambling and Their Advantages
Best Smart Watches On The Market
7 Modern Mediterranean Decorating Ideas for Your Home
What Are the Different Types of Addictions?
How Much Does It Typically Cost to Hire Movers?
3 Ways To Improve Your Confidence
access attention boost compare converts eventually everybody's exclusively expenses feeling good Gout occurs odds physician things understand vulnerable
© Copyright 2021 livesoma.com | All Rights Reserved |
Kancheepuram Silk Sarees Internet Shopping
The Story behind the evolution of Rummy Has Just Gone Viral!
3 Big Ideas for Decluttering Your Home
How to Conserve Water in Your Home
Tips for Arranging Holiday Flowers
Finding Pennsylvania Craps Games? Parx Casino Can Help You
How to choose a personal injury lawyer?
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 8,215
|
{"url":"https:\/\/sikademy.com\/answer\/computer-science\/discrete-mathematics\/question-by-using-the-rules-of-logical-equivalences-show-49oj\/","text":"is below this banner.\n\nCan't find a solution anywhere?\n\nNEED A FAST ANSWER TO ANY QUESTION OR ASSIGNMENT?\n\nYou will get a detailed answer to your question or assignment in the shortest time possible.\n\n## Here's the Solution to this Question\n\na)\u00a0$\\left( {p \\to \\left( {q \\to r} \\right)} \\right) \\to \\left( {\\left( {p \\wedge q} \\right) \\to r} \\right) = \\overline {\\left( {p \\to \\left( {q \\to r} \\right)} \\right)} \\vee \\left( {\\left( {p \\wedge q} \\right) \\to r} \\right) = \\overline {\\left( {\\overline p \\vee \\left( {q \\to r} \\right)} \\right)} \\vee \\left( {\\overline {\\left( {p \\wedge q} \\right)} \\vee r} \\right) = \\overline {\\left( {\\overline p \\vee \\left( {\\overline q \\vee r} \\right)} \\right)} \\vee \\left( {\\overline {\\left( {p \\wedge q} \\right)} \\vee r} \\right) = \\overline {\\left( {\\overline p \\vee \\overline q \\vee r} \\right)} \\vee \\left( {\\overline p \\vee \\overline q \\vee r} \\right) = p \\wedge q \\wedge \\overline r \\vee \\overline p \\vee \\overline q \\vee r = \\left( {p \\vee \\overline p \\vee \\overline q \\vee r} \\right) \\wedge \\left( {q \\vee \\overline p \\vee \\overline q \\vee r} \\right) \\wedge \\left( {\\overline r \\vee \\overline p \\vee \\overline q \\vee r} \\right) = \\left( {T \\vee \\overline q \\vee r} \\right) \\wedge \\left( {T \\vee \\overline p \\vee r} \\right) \\wedge \\left( {T \\vee \\overline p \\vee \\overline q } \\right) = T \\wedge T \\wedge T = T$\n\nQ. E. D.\n\nb) 1)\u00a0$\\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\wedge \\neg r} \\right) \\vee \\left( {p \\wedge r} \\right)} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\vee p} \\right) \\wedge \\left( {q \\vee r} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) \\wedge \\left( {\\neg r \\vee r} \\right)} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\vee p} \\right) \\wedge \\left( {q \\vee r} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) \\wedge T} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\vee p} \\right) \\wedge \\left( {q \\vee r} \\right) \\wedge \\left( {\\neg r \\vee p} \\right)} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {q \\vee \\left( {p \\wedge r} \\right)} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) = \\left( {\\left( {p \\wedge q \\wedge q} \\right) \\vee \\left( {p \\wedge q \\wedge p \\wedge r} \\right)} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) = \\left( {\\left( {p \\wedge q} \\right) \\vee \\left( {p \\wedge q \\wedge r} \\right)} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {T \\vee r} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) = \\left( {p \\wedge q} \\right) \\wedge T \\wedge \\left( {\\neg r \\vee p} \\right) = \\left( {p \\wedge q} \\right) \\wedge \\left( {\\neg r \\vee p} \\right) = p \\wedge q \\wedge \\neg r \\vee p \\wedge q \\wedge p = p \\wedge q \\wedge \\neg r \\vee p \\wedge q = p \\wedge q \\wedge \\left( {\\neg r \\vee T} \\right) = p \\wedge q \\wedge T = p \\wedge q$\n\n2)\u00a0$\\neg \\left( {p \\to \\neg q} \\right) = \\neg \\left( {\\neg p \\vee \\neg q} \\right) = \\neg \\neg p \\wedge \\neg \\neg q = p \\wedge q$\n\nSo,\u00a0$\\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\wedge \\neg r} \\right) \\vee \\left( {p \\wedge r} \\right)} \\right) = p \\wedge q$\u00a0and\u00a0$\\neg \\left( {p \\to \\neg q} \\right) = p \\wedge q$\n\nThen\n\n$\\left( {p \\wedge q} \\right) \\wedge \\left( {\\left( {q \\wedge \\neg r} \\right) \\vee \\left( {p \\wedge r} \\right)} \\right) = \\neg \\left( {p \\to \\neg q} \\right)$\n\nQ. E. D.\n\nc)\u00a0$\\left( {\\left( {p \\vee q} \\right) \\wedge \\left( {p \\to r} \\right) \\wedge \\left( {q \\to r} \\right)} \\right) \\to r = \\overline {\\left( {\\left( {p \\vee q} \\right) \\wedge \\left( {p \\to r} \\right) \\wedge \\left( {q \\to r} \\right)} \\right)} \\vee r = \\overline {\\left( {p \\vee q} \\right)} \\vee \\overline {\\left( {p \\to r} \\right)} \\vee \\overline {\\left( {q \\to r} \\right)} \\vee r = \\overline {\\left( {p \\vee q} \\right)} \\vee \\overline {\\left( {\\overline p \\vee r} \\right)} \\vee \\overline {\\left( {\\overline q \\vee r} \\right)} \\vee r = \\left( {\\overline p \\wedge \\overline q } \\right) \\vee \\left( {p \\wedge \\overline r } \\right) \\vee \\left( {q \\wedge \\overline r } \\right) \\vee r = \\left( {\\overline p \\wedge \\overline q } \\right) \\vee \\overline r \\wedge \\left( {p \\vee q} \\right) \\vee r = \\overline {\\left( {p \\vee q} \\right)} \\vee \\overline r \\wedge \\left( {p \\vee q} \\right) \\vee r = \\left( {\\overline {\\left( {p \\vee q} \\right)} \\vee \\overline r } \\right) \\wedge \\left( {\\overline {\\left( {p \\vee q} \\right)} \\vee \\left( {p \\vee q} \\right)} \\right) \\vee r = \\left( {\\overline {\\left( {p \\vee q} \\right)} \\vee \\overline r } \\right) \\wedge T \\vee r = \\left( {\\overline {\\left( {p \\vee q} \\right)} \\vee \\overline r } \\right) \\vee r = \\overline {\\left( {p \\vee q} \\right)} \\vee \\overline r \\vee r = \\overline {\\left( {p \\vee q} \\right)} \\vee T = T$\n\nQ. E. D.","date":"2023-02-01 12:42:18","metadata":"{\"extraction_info\": {\"found_math\": true, \"script_math_tex\": 0, \"script_math_asciimath\": 0, \"math_annotations\": 7, \"math_alttext\": 0, \"mathml\": 0, \"mathjax_tag\": 0, \"mathjax_inline_tex\": 0, \"mathjax_display_tex\": 0, \"mathjax_asciimath\": 0, \"img_math\": 0, \"codecogs_latex\": 0, \"wp_latex\": 0, \"mimetex.cgi\": 0, \"\/images\/math\/codecogs\": 0, \"mathtex.cgi\": 0, \"katex\": 0, \"math-container\": 0, \"wp-katex-eq\": 0, \"align\": 0, \"equation\": 0, \"x-ck12\": 0, \"texerror\": 0, \"math_score\": 0.33242765069007874, \"perplexity\": 870.7171127037265}, \"config\": {\"markdown_headings\": true, \"markdown_code\": true, \"boilerplate_config\": {\"ratio_threshold\": 0.18, \"absolute_threshold\": 20, \"end_threshold\": 15, \"enable\": true}, \"remove_buttons\": true, \"remove_image_figures\": true, \"remove_link_clusters\": true, \"table_config\": {\"min_rows\": 2, \"min_cols\": 3, \"format\": \"plain\"}, \"remove_chinese\": true, \"remove_edit_buttons\": true, \"extract_latex\": true}, \"warc_path\": \"s3:\/\/commoncrawl\/crawl-data\/CC-MAIN-2023-06\/segments\/1674764499934.48\/warc\/CC-MAIN-20230201112816-20230201142816-00451.warc.gz\"}"}
| null | null |
Эйнар Кваран (; , Вадланес — , Рейкьявик) — исландский писатель, драматург и поэт конца XIX — первой половины XX века.
Имя
После рождения он получил имя Эйнар и отчество (патроним) Хьорлейфссон. В 1913 году альтинг, по инициативе комитета по именам, членом которого был Эйнар Хьорлейфссон, принял закон (впоследствии отменённый), разрешающий исландцам брать имена и фамилии древнего происхождения. Пользуясь возможностью в 1916 году Эйнар взял себе фамилию Кваран, использовав эпоним из древней исландской саги о людях из Лососьей долины. Таким образом, полное имя Эйнара — Эйнар Хьйорлейфссон Кваран (), и он в своё время являлся одним из немногих исландцев имеющим и патроним, и фамилию. Устоявшимся в Исландии является употребление только имени и фамилии писателя — Эйнар Кваран (), иногда в сочетании с сокращением отчества — Эйнар Х. Кваран ().
Биография
Эйнар Кваран родился 6 декабря 1859 года в небольшой деревне Вадланес на востоке Исландии недалеко от Эйильсстадира в семье преподобного Хьйёрлейфюра Эйнарссона и домохозяйки Гвюдлёйг Эйоульфсдоуттир. Детство Эйнара прошло в различных селениях на севере возле Скага-фьорда. В 1877 году Эйнар поступил, а в 1881 году окончил колледж в Рейкьявике, известный как Латинская школа.
В 1882 году поступил на экономический факультет Копенгагенского университета, где вместе с тремя другими студентами-исландцами издавал исландский литературный журнал Verðandi, который отстаивал идеи реализма и разрыва с прошлым восхищением сагами.
В 1885 году Эйнар эмигрировал в Канаду, где он жил в центре исландской культуры — в Новой Исландии в Виннипеге и помог основать два исландскоязычных еженедельных изданий — «Heimskringla» и «Lögberg».
По возвращении в Исландию в 1895 году Эйнар стал журналистом и редактором в Рейкьявике и Акюрейри; участвовал в борьбе за исландскую независимость и писал об образовании и театре. Он был соредактором «Ísafold», тогда ведущей газеты Исландии, и редактором «Fjallkonan». С 1892 по 1895 год и в 1908—1909 годах редактировал «Skírnir» — журнал Исландского литературного общества.
Проработав 19 лет в журналистике в Канаде и Исландии, Эйнар в 1906 году решил полностью посвятить себя литературной работе и правительство Исландии предоставило ему стипендию, чтобы он мог полностью посвятить себя писательской деятельности. Начиная с 1906 года он опубликовал пять романов, две пьесы и какое-то время руководил театральной труппой Рейкьявика.
Эйнар был дважды женат. Его первая жена, Матильда Петерсен, была датчанкой; она умерла в Канаде, и их двое детей умерли в младенчестве. В 1888 году он женился на Гислине Гисладоуттир; у них было пятеро детей, один из которых — старший сын Сигюрдюр, умер от туберкулеза, когда ему было 15 лет.
Творчество
Эйнар очень рано заинтересовался книгами. По рассказам его родных, он начал сочинять стихи и рассказы ещё в раннем возрасте. Когда ему было двенадцать лет, он сжег целое собрание написанных им рассказов. Его интерес к литературе возрастает в годы учёбы в латинской гимназии в Рейкьявике, где он пишет стихи, пьесы и рассказы. Его лучшие работы этих лет, без сомнения, — это его два рассказа «Orgelið» () и «Hvorn eiðinn á ég að rjúfa?» (). Рассказы были напечатаны и получили неоднозначные отзывы, в частности их сочли несколько революционными, а автора посчитали аморальным.
Эйнар написал множество рассказов, романов, пьес и сборник стихов. Он был приверженцем чистоты и красоты языка, писал очень хорошо и стилистически красиво. Его революционной для исландской литературы работой стал рассказ «Vonir» (), который он написал в 1890 году, находясь в Канаде и повествующий об эмигрантском опыте.
Эйнар также был выдающимся спиритуалистом, автором первой положительной оценки спиритизма на исландском языке, а также соучредителем и президентом экспериментального общества, в результате которого было создано Исландское общество психических исследований (), в котором он был первый президент. Он сыграл важную роль в расследовании и популяризации многих исландских медиумов, особенно Индриди Индридасона и Хафстейна Бьёрднссона. В поздних литературных произведениях Эйнара значительное место занимал спиритизм, особенно в романе «Sögur Rannveigar» (), написанном в 1919—1922 годах, и христианский гуманизм. По мнению Стейнгримюра Торстейнссона, своим творчеством Эйнар оказал влияние на исландскую культуру и мировоззрение, в частности, сделав исландцев менее ортодоксальными и менее суровыми в воспитании своих детей.
В 1920-х годах ходили слухи, что Эйнара считают лауреатом Нобелевской премии по литературе.
Исландский историк литературы и литературный критик Сигюрдюр Нордаль пренебрежительно отозвался об Эйнаре как о чрезмерно сосредоточенном на всепрощении и, следовательно, терпимом к тем вещам, против которых писателю как-раз и следует следует скорее протестовать, чем прощать. По мнению Сигюрдюра Эйнару следовало бы писать в духе исландского национализма и современных ему интерпретаций Ницше, считая кровную месть лучшей этической моделью. В 1930-х годах лауреат Нобелевской премии Халльдор Лакснесс еще более резко критиковал Эйнара за его увлечение спиритизмом.
Примечания
Писатели Исландии
Поэты Исландии
|
{
"redpajama_set_name": "RedPajamaWikipedia"
}
| 5,288
|
Q: PostgreSQL substitute case sensitive variables in a command Hi I have some variables in a plpgsql script. It's all case sensitive.
schema := 'myschema';
table_name := 'MyTable'
column_name := 'MyColumn'
I need to put those variables in a simple statement:
select max(column_name) from schema.table_name.
I feel like I am battling the case sensitivity with PostgreSQL. I basically need to recreate this:
select max("MyColumn") from myschema."MyTable";
For the life of me I can't get this work and am clearly too dumb for PostgreSQL. Trying with EXECUTE(), EXECUTE() w/ FORMAT(), quote_indent() etc etc. Any thoughts?
A: Got it with this gem
execute format('select max(%I) from %s.%I', column_name, schema_name, table_name);
Depressing that that took hours of my life...
|
{
"redpajama_set_name": "RedPajamaStackExchange"
}
| 765
|
The world constantly throws up new challenges about what it means to be Christian and to live a distinctively Christian lifestyle.
The priest, broadcaster, writer and ethicist Samuel Wells considers some of the biggest contemporary political, social and moral challenges and grapples with them in the light of Christian hope and wisdom.
Under three headings - Engaging the World, Being Human, and Facing Mortality - he probes a wide range of issues including the rise of religious extremism, migration, ecology, social media, sexual identities, inequality, obesity, life stages from childhood to old age, dementia, facing death and much more.
This striking and profoundly wise book sets out to shape a theological imagination and fluency that is grounded in the reality of being human in a suffering world and yet open to transformation by the life and wisdom of God.
How Then Shall We Live? by Samuel Wells was published by Canterbury Press in June 2016 and is our 23940th best seller. The ISBN for How Then Shall We Live? is 9781848258624.
Reviews of How Then Shall We Live?
Be the first to review How Then Shall We Live?!
Got a question? No problem! Just click here to ask us about How Then Shall We Live?.
Details for How Then Shall We Live?
|
{
"redpajama_set_name": "RedPajamaC4"
}
| 9,127
|
WEP calls for the London Mayor to join forces over domestic violence
Newsdesk 23rd August 2016 23rd August 2016 Politics
Read time:1 minute, 53 seconds
Sophie Walker invites London Mayor Sadiq Khan to work with her on tackling rising rates of domestic violence in the capital.
A release of new statistics from the Metropolitan Police show a rise of 8% in reported incidents of domestic violence in London.
The Women's Equality Party leader, Sophie Walker, responded to the news: "During my campaign to be London's first female Mayor earlier this year, I set out clear plans to tackle the horrifying prevalence of domestic violence in our city.
"It is simply terrible these figures are rising and, what's more, that less than a third of the incidents investigated by the Met Police resulted in further action.
"We have plans to tackle domestic violence both at the point at which it is reported and before this through preventative teaching in schools, rehabilitation of offenders, and specialist support for every survivor. I invite Sadiq Khan, who has styled himself as London's first 'feminist Mayor', to take on these plans and to show himself to be a man of action as well as words."
Walker explained that rising rates of violence against women and girls often occur at times of crisis, putting the figures in the context of current political, economic and international uncertainties and claimed that the party could bring support to City Hall.
"Understanding rising domestic violence rates is one thing, but the central issue for us is combatting them. I was the only London Mayoral candidate to set out a clear set of policies that prioritised this issue. The Women's Equality Party is dedicated to ending violence against women in all its forms."
WEP's policies for London include better police enforcement of Domestic Violence Protection Notices/Orders (DVPO), so that perpetrators and not victims are removed from their homes, and ring-fenced stable and sustainable funding for specialist support services, that are for and led by women, including BAME women and disabled women.
WEP would also work with local authority services to establish a solid pan-London system to help women fleeing domestic and sexual abuse find refuge and secure accommodation, as well as ring-fence a proportion of London's housing investment to build refuges those trapped in dangerous situations because they can't afford to escape.
Tagged : politicsSadiq KhanSophie WalkerWomen's Equality Party
FeaturesHealthNewsPolitics
Truss pledges comprehensive conversion therapy ban in Spring 2022.
By OutNewsGlobal 29th October 2021 29th October 2021
"Red Wall" Conservative is the Tories' first out, female bisexual MP.
By Newsdesk 11th October 2021 11th October 2021
Carrie Johnson's speech to LGBT Tories: text in full.
By Newsdesk 6th October 2021 6th October 2021
UK Government appoints new LGBT business champion.
By Newsdesk 10th September 2021 10th September 2021
FeaturesPolitics
"LGBT rights are human rights". Meet the UK's new Special LGBT Envoy.
By Rob Harkavy 21st May 2021 21st May 2021
Construction News launches 2016 LGBT survey
Judge blocks Obama transgender school bathroom policy
|
{
"redpajama_set_name": "RedPajamaCommonCrawl"
}
| 9,902
|
End of preview. Expand
in Data Studio
README.md exists but content is empty.
- Downloads last month
- -