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Keywords: Bayesian model x
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Bayesian Statistical Inference
Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray
in Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data
Physics, Particle Physics / Astrophysics / Cosmology
This chapter introduces the most important aspects of Bayesian statistical inference and techniques for performing such calculations in practice. It first reviews the basic steps in Bayesian ... More
This chapter introduces the most important aspects of Bayesian statistical inference and techniques for performing such calculations in practice. It first reviews the basic steps in Bayesian inference in early sections of the chapter, and then illustrates them with several examples in sections that follow. Numerical techniques for solving complex problems are next discussed, and the final section provides a summary of pros and cons for classical and Bayesian method. It argues that most users of Bayesian estimation methods are likely to use a mix of Bayesian and frequentist tools. The reverse is also true—frequentist data analysts, even if they stay formally within the frequentist framework, are often influenced by "Bayesian thinking," referring to "priors" and "posteriors." The most advisable position is to know both paradigms well, in order to make informed judgments about which tools to apply in which situations.Less
Željko IveziAndrew J. ConnollyJacob T. VanderPlasAlexander GrayŽeljko IveziAndrew J. ConnollyJacob T. VanderPlasAlexander Gray
This chapter introduces the most important aspects of Bayesian statistical inference and techniques for performing such calculations in practice. It first reviews the basic steps in Bayesian inference in early sections of the chapter, and then illustrates them with several examples in sections that follow. Numerical techniques for solving complex problems are next discussed, and the final section provides a summary of pros and cons for classical and Bayesian method. It argues that most users of Bayesian estimation methods are likely to use a mix of Bayesian and frequentist tools. The reverse is also true—frequentist data analysts, even if they stay formally within the frequentist framework, are often influenced by "Bayesian thinking," referring to "priors" and "posteriors." The most advisable position is to know both paradigms well, in order to make informed judgments about which tools to apply in which situations.
Keywords: Bayesian statistical inference, Bayesian techniques, Bayesian priors, Bayesian parameter uncertainty quantification, Bayesian model selection, nonuniform prior
Developing predictive models
E. J. Milner-Gulland and Marcus Rowcliffe
in Conservation and Sustainable Use: A Handbook of Techniques
Biology, Biodiversity / Conservation Biology
The effective management of natural resources use requires a mechanistic understanding of the system, not just correlations between variables of the kind discussed in Chapter 4. Understanding may ... More
The effective management of natural resources use requires a mechanistic understanding of the system, not just correlations between variables of the kind discussed in Chapter 4. Understanding may simply be in the form of a conceptual model, but is much more powerful when formalized as a mathematical model. This chapter introduces methods for building a model of the system that can be used to predict future sustainability with or without management interventions. The emphasis is on the simulation of biological and bioeconomic dynamics, for which step-by-step worked examples are given. These examples start with conceptual models, then show how to formalize these as mathematical equations, build these into computer code; test model sensitivity, validity, and alternative structures; and finally, explore future scenarios. Methods for modelling stochasticity and human behaviour are also introduced, as well as the use of Bayesian methods for understanding dynamic systems and exploring management interventions.Less
E. J. Milner-GullandMarcus Rowcliffe
The effective management of natural resources use requires a mechanistic understanding of the system, not just correlations between variables of the kind discussed in Chapter 4. Understanding may simply be in the form of a conceptual model, but is much more powerful when formalized as a mathematical model. This chapter introduces methods for building a model of the system that can be used to predict future sustainability with or without management interventions. The emphasis is on the simulation of biological and bioeconomic dynamics, for which step-by-step worked examples are given. These examples start with conceptual models, then show how to formalize these as mathematical equations, build these into computer code; test model sensitivity, validity, and alternative structures; and finally, explore future scenarios. Methods for modelling stochasticity and human behaviour are also introduced, as well as the use of Bayesian methods for understanding dynamic systems and exploring management interventions.
Keywords: mathematical models, conceptual models, simulation, management intervention, sensitivity analysis, model validation, scenario exploration, stochasticity, Bayesian models
Hierarchical Bayesian Models
N. Thompson Hobbs and Mevin B. Hooten
in Bayesian Models: A Statistical Primer for Ecologists
This chapter seeks to explain hierarchical models and how they differ from simple Bayesian models and to illustrate building hierarchical models using mathematically correct expressions. It begins ... More
This chapter seeks to explain hierarchical models and how they differ from simple Bayesian models and to illustrate building hierarchical models using mathematically correct expressions. It begins with the definition of hierarchical models. Next, the chapter introduces four general classes of hierarchical models that have broad application in ecology. These classes can be used individually or in combination to attack virtually any research problem. Examples are used to show how to draw Bayesian networks that portray stochastic relationships between observed and unobserved quantities. The chapter furthermore shows how to use network drawings as a guide for writing posterior and joint distributions.Less
N. Thompson HobbsMevin B. Hooten
This chapter seeks to explain hierarchical models and how they differ from simple Bayesian models and to illustrate building hierarchical models using mathematically correct expressions. It begins with the definition of hierarchical models. Next, the chapter introduces four general classes of hierarchical models that have broad application in ecology. These classes can be used individually or in combination to attack virtually any research problem. Examples are used to show how to draw Bayesian networks that portray stochastic relationships between observed and unobserved quantities. The chapter furthermore shows how to use network drawings as a guide for writing posterior and joint distributions.
Keywords: hierarchical models, hierarchical Bayesian models, Bayesian networks, stochastic relationships, network drawings, posterior distribution, joint distribution
Thinking about Evidence1
DAVID LAGNADO
in Evidence, Inference and Enquiry
10.5871/bacad/9780197264843.003.0007
Sociology, Methodology and Statistics
This chapter argues that people reason about legal evidence using small-scale qualitative networks. These cognitive networks are typically qualitative and incomplete, and based on people's causal ... More
This chapter argues that people reason about legal evidence using small-scale qualitative networks. These cognitive networks are typically qualitative and incomplete, and based on people's causal beliefs about the specifics of the case as well as the workings of the physical and social world in general. A key feature of these networks is their ability to represent qualitative relations between hypotheses and evidence, allowing reasoners to capture the concepts of dependency and relevance critical in legal contexts. In support of this claim, the chapter introduces some novel empirical and formal work on alibi evidence, showing that people's reasoning conforms to the dictates of a qualitative Bayesian model. However, people's inferences do not always conform to Bayesian prescripts. Empirical studies are also discussed in which people over-extend the discredit of one item of evidence to other unrelated items. This bias is explained in terms of the propensity to group positive and negative evidence separately and the use of coherence-based inference mechanisms. It is argued that these cognitive processes are a natural response to deal with the complexity of legal evidence.Less
This chapter argues that people reason about legal evidence using small-scale qualitative networks. These cognitive networks are typically qualitative and incomplete, and based on people's causal beliefs about the specifics of the case as well as the workings of the physical and social world in general. A key feature of these networks is their ability to represent qualitative relations between hypotheses and evidence, allowing reasoners to capture the concepts of dependency and relevance critical in legal contexts. In support of this claim, the chapter introduces some novel empirical and formal work on alibi evidence, showing that people's reasoning conforms to the dictates of a qualitative Bayesian model. However, people's inferences do not always conform to Bayesian prescripts. Empirical studies are also discussed in which people over-extend the discredit of one item of evidence to other unrelated items. This bias is explained in terms of the propensity to group positive and negative evidence separately and the use of coherence-based inference mechanisms. It is argued that these cognitive processes are a natural response to deal with the complexity of legal evidence.
Keywords: reasoning, legal evidence, qualitative networks, cognitive networks, alibi evidence, Bayesian model
Simple Bayesian Models
This chapter lays out the basic principles of Bayesian inference, building on the concepts of probability developed in Chapter 3. It seeks to use the rules of probability to show how Bayes' theorem ... More
This chapter lays out the basic principles of Bayesian inference, building on the concepts of probability developed in Chapter 3. It seeks to use the rules of probability to show how Bayes' theorem works, by making use of the conditional rule of probability and the law of total probability. The chapter begins with the central, underpinning tenet of the Bayesian view: the world can be divided into quantities that are observed and quantities that are unobserved. Unobserved quantities include parameters in models, latent states predicted by models, missing data, effect sizes, future states, and data before they are observed. We wish to learn about these quantities using observations. The Bayesian framework for achieving that understanding is applied in exactly the same way regardless of the specifics of the research problem at hand or the nature of the unobserved quantities.Less
This chapter lays out the basic principles of Bayesian inference, building on the concepts of probability developed in Chapter 3. It seeks to use the rules of probability to show how Bayes' theorem works, by making use of the conditional rule of probability and the law of total probability. The chapter begins with the central, underpinning tenet of the Bayesian view: the world can be divided into quantities that are observed and quantities that are unobserved. Unobserved quantities include parameters in models, latent states predicted by models, missing data, effect sizes, future states, and data before they are observed. We wish to learn about these quantities using observations. The Bayesian framework for achieving that understanding is applied in exactly the same way regardless of the specifics of the research problem at hand or the nature of the unobserved quantities.
Keywords: Bayesian inference, probability, Bayes' theorem, probability, observed quantities, unobserved quantities, observations, simple Bayesian models, likelihood
Bayesian Models: A Statistical Primer for Ecologists
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This book provides a comprehensive ... More
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This book provides a comprehensive and accessible introduction to the latest Bayesian methods. It emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach, and is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. The book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This book enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Less
Bayesian Models : A Statistical Primer for Ecologists
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This book provides a comprehensive and accessible introduction to the latest Bayesian methods. It emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach, and is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. The book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This book enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.
Keywords: Bayesian modeling, Bayesian models, computations, non-statisticians, mathematical statistics, probability, Markov chain Monte Carlo, ecologist
Writing Bayesian Models
This chapter offers a general set of steps for writing models to assist the researcher in formulating their own approach to the Bayesian model. The crucial skill of specifying models is often ... More
This chapter offers a general set of steps for writing models to assist the researcher in formulating their own approach to the Bayesian model. The crucial skill of specifying models is often neglected in statistical texts in general and texts on Bayesian modeling in particular. The central importance of model specification also motivates this chapter. The overarching challenge in building models is to specify the components of the posterior distribution and the joint distribution and to factor the joint distribution into sensible parts. This chapter first lays out a framework for doing just that, albeit in somewhat abstract terms, before moving on to a more concrete example—the effects of grazing by livestock and wild ungulates on structure and function of a sagebrush steppe ecosystem.Less
This chapter offers a general set of steps for writing models to assist the researcher in formulating their own approach to the Bayesian model. The crucial skill of specifying models is often neglected in statistical texts in general and texts on Bayesian modeling in particular. The central importance of model specification also motivates this chapter. The overarching challenge in building models is to specify the components of the posterior distribution and the joint distribution and to factor the joint distribution into sensible parts. This chapter first lays out a framework for doing just that, albeit in somewhat abstract terms, before moving on to a more concrete example—the effects of grazing by livestock and wild ungulates on structure and function of a sagebrush steppe ecosystem.
Keywords: Bayesian models, specifying models, model specification, building models, basic framework, grazing, Bayesian modeling, sagebrush steppe ecosystem
Humans' Multisensory Perception, from Integration to Segregation, Follows Bayesian Inference
Ladan Shams and Ulrik Beierholm
in Sensory Cue Integration
Psychology, Cognitive Neuroscience, Cognitive Psychology
This chapter first discusses experimental findings showing that multisensory perception encompasses a spectrum of phenomena ranging from full integration (or fusion), to partial integration, to ... More
This chapter first discusses experimental findings showing that multisensory perception encompasses a spectrum of phenomena ranging from full integration (or fusion), to partial integration, to complete segregation. Next, it describes two Bayesian causal-inference models that can account for the entire range of combinations of two or more sensory cues. It shows that one of these models, which is a hierarchical Bayesian model, is a special form of the other one (which is a nonhierarchical model). It then compares the predictions of these models with human data in multiple experiments and shows that Bayesian causal-inference models can account for the human data remarkably well. Finally, a study is presented that investigates the stability of priors in the face of drastic change in sensory conditions.Less
Ladan ShamsUlrik Beierholm
This chapter first discusses experimental findings showing that multisensory perception encompasses a spectrum of phenomena ranging from full integration (or fusion), to partial integration, to complete segregation. Next, it describes two Bayesian causal-inference models that can account for the entire range of combinations of two or more sensory cues. It shows that one of these models, which is a hierarchical Bayesian model, is a special form of the other one (which is a nonhierarchical model). It then compares the predictions of these models with human data in multiple experiments and shows that Bayesian causal-inference models can account for the human data remarkably well. Finally, a study is presented that investigates the stability of priors in the face of drastic change in sensory conditions.
Keywords: multisensory perception, cue integration, Bayesian causal-inference models, sensory cues
Spatial variation in risk
Dirk U. Pfeiffer, Timothy P. Robinson, Mark Stevenson, Kim B. Stevens, David J. Rogers, and Archie C. A. Clements
in Spatial Analysis in Epidemiology
Biology, Disease Ecology / Epidemiology
This chapter discusses spatial variation in risk. Epidemiological disease investigations should include an assessment of the spatial variation of disease risk, as this may provide important clues ... More
This chapter discusses spatial variation in risk. Epidemiological disease investigations should include an assessment of the spatial variation of disease risk, as this may provide important clues leading to causal explanations. The objective is to produce a map representation of the important spatial effects present in the data while simultaneously removing any distracting noise or extreme values. The resulting smoothed map should have increased precision without introducing significant bias. The method used to analyse the data depends on how they have been recorded. Smoothing based on kernel functions, smoothing based and on Bayesian models, and spatial interpolation are discussed.Less
Dirk U. PfeifferTimothy P. RobinsonMark StevensonKim B. StevensDavid J. RogersArchie C. A. Clements
This chapter discusses spatial variation in risk. Epidemiological disease investigations should include an assessment of the spatial variation of disease risk, as this may provide important clues leading to causal explanations. The objective is to produce a map representation of the important spatial effects present in the data while simultaneously removing any distracting noise or extreme values. The resulting smoothed map should have increased precision without introducing significant bias. The method used to analyse the data depends on how they have been recorded. Smoothing based on kernel functions, smoothing based and on Bayesian models, and spatial interpolation are discussed.
Keywords: spatial variations, spatial epidemiological analysis, map representation, spatial effects, smoothing, kernel functions, Bayesian models, spatial interpolation
Characterizing Uncertainty of Future Climate Change Projections using Hierarchical Bayesian Models *
Claudia Tebaldi, Bruno Sansó, and Richard L. Smith
in Bayesian Statistics 9
Mathematics, Probability / Statistics
The use of projections from ensembles of climate models to characterize fu ture climate change at regional scales has become the most widely adopted framework, as opposed to what was standard ... More
The use of projections from ensembles of climate models to characterize fu ture climate change at regional scales has become the most widely adopted framework, as opposed to what was standard practice until just a few years ago when a single model's projections constituted the basis for arguing about future changes and their impacts. It is believed that comparing and synthe sizing simulations of multiple models is key to quantifying a best estimate of the future changes and its uncertainty. In the last few years there has been an explosion of literature in climate change science where mostly heuristic meth ods of synthesizing the output of multiple models have been proposed, and the statistical literature is showing more involvement by our community as well, of late. In this paper we give a brief overview of the mainstreams of research in this area and then focus on our recent work, through which we have proposed the framework of hierarchical Bayesian models to combine information from model simulations and observations, in order to derive posterior probabilities of temperature and precipitation change at regional scales.Less
Claudia TebaldiBruno SansóRichard L. Smith
The use of projections from ensembles of climate models to characterize fu ture climate change at regional scales has become the most widely adopted framework, as opposed to what was standard practice until just a few years ago when a single model's projections constituted the basis for arguing about future changes and their impacts. It is believed that comparing and synthe sizing simulations of multiple models is key to quantifying a best estimate of the future changes and its uncertainty. In the last few years there has been an explosion of literature in climate change science where mostly heuristic meth ods of synthesizing the output of multiple models have been proposed, and the statistical literature is showing more involvement by our community as well, of late. In this paper we give a brief overview of the mainstreams of research in this area and then focus on our recent work, through which we have proposed the framework of hierarchical Bayesian models to combine information from model simulations and observations, in order to derive posterior probabilities of temperature and precipitation change at regional scales.
Keywords: Climate change, Climate models, Ensembles, Bayesian hierarchical models, Forecast validation
This chapter sketches an approach to inference applicable to an enormous range of research problems—one that can be understood from first principles and that can be unambiguously communicated to ... More
This chapter sketches an approach to inference applicable to an enormous range of research problems—one that can be understood from first principles and that can be unambiguously communicated to other scientists, managers, and policy makers. In doing research, it is important that one is able to ask important questions and provide compelling answers to them. Doing so depends on establishing a line of inference that extends from current thinking, theory, and questions to new insight qualified by uncertainty. This chapter introduces a highly general, flexible approach to establishing this line of inference. It offers a somewhat abstract overview of this framework followed by a concrete example to properly illustrate this framework.Less
This chapter sketches an approach to inference applicable to an enormous range of research problems—one that can be understood from first principles and that can be unambiguously communicated to other scientists, managers, and policy makers. In doing research, it is important that one is able to ask important questions and provide compelling answers to them. Doing so depends on establishing a line of inference that extends from current thinking, theory, and questions to new insight qualified by uncertainty. This chapter introduces a highly general, flexible approach to establishing this line of inference. It offers a somewhat abstract overview of this framework followed by a concrete example to properly illustrate this framework.
Keywords: research problems, inference, ecology, Bayesian model, hierarchical models, ecological systems
Optimal Random Exploration for Trade‐related Nonindigenous Species Risk
Michael Springborn, Christopher Costello, and Peyton Ferrier
in Bioinvasions and Globalization: Ecology, Economics, Management, and Policy
Biology, Ecology, Biodiversity / Conservation Biology
This chapter identifies variables from the port inspection setting that influence the gains to exploration via random inspections. It begins by describing a Bayesian learning model of trade-related ... More
This chapter identifies variables from the port inspection setting that influence the gains to exploration via random inspections. It begins by describing a Bayesian learning model of trade-related non-indigenous species (NIS) risk in Section 10.2, which captures uncertainty over the true probability that trade from a given source is infested, and provides a framework for updating these beliefs as observations accrue. The formal inspection allocation decision problem is expressed in Section 10.3, where the computational demands of the central task are made clear. The analysis in Section 10.4 begins with the simplest possible nontrivial version of the problem. Elements of real-world complexity are subsequently added to build intuition for the ultimate task of exploring random inspection policy in an empirically-based setting. The workhorse method applies Monte Carlo simulation under various policies to characterize performance in terms of interceptions and to identify optimal choices for design and intensity of exploration.Less
Michael SpringbornChristopher CostelloPeyton Ferrier
This chapter identifies variables from the port inspection setting that influence the gains to exploration via random inspections. It begins by describing a Bayesian learning model of trade-related non-indigenous species (NIS) risk in Section 10.2, which captures uncertainty over the true probability that trade from a given source is infested, and provides a framework for updating these beliefs as observations accrue. The formal inspection allocation decision problem is expressed in Section 10.3, where the computational demands of the central task are made clear. The analysis in Section 10.4 begins with the simplest possible nontrivial version of the problem. Elements of real-world complexity are subsequently added to build intuition for the ultimate task of exploring random inspection policy in an empirically-based setting. The workhorse method applies Monte Carlo simulation under various policies to characterize performance in terms of interceptions and to identify optimal choices for design and intensity of exploration.
Keywords: non-indigenous species, invasive species, biological invasions, inspection allocation, Bayesian learning model, random inspections, port inspection
Surviving fully Bayesian nonparametric regression models
Timothy E. Hanson and Alejandro Jara
in Bayesian Theory and Applications
This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability ... More
This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing commonly used semiparametric survival models. It then discusses the Bayesian nonparametric priors used in the generalizations of the accelerated failure time (AFT) model. Next, the two generalizations of the accelerated failure time model are introduced and compared by means of real-life data analyses. The models correspond to generalizations of AFT models based on dependent extensions of the Dirichlet process (DP) and Polya tree (PT) priors. Advantages of the induced survival regression models include ease of interpretability and computational tractability.Less
Timothy E. HansonAlejandro Jara
This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability distributions. It begins by reviewing commonly used semiparametric survival models. It then discusses the Bayesian nonparametric priors used in the generalizations of the accelerated failure time (AFT) model. Next, the two generalizations of the accelerated failure time model are introduced and compared by means of real-life data analyses. The models correspond to generalizations of AFT models based on dependent extensions of the Dirichlet process (DP) and Polya tree (PT) priors. Advantages of the induced survival regression models include ease of interpretability and computational tractability.
Keywords: Bayesian nonparametric models, accelerated failure time model, semiparametric survival models, Dirichlet process, Polya tree, induced survival regression models
Investigating the genetic association between diabetes and malaria: an application of Bayesian ecological regression models with errors in covariates
L. Bernardinelli, C. Pascutto, C. Montomoli, and W. Gilks
in Spatial Epidemiology: Methods and Applications
Public Health and Epidemiology, Public Health, Epidemiology
This chapter describes a Bayesian hierarchical model and applies it to a new dataset on insulin-dependent diabetes mellitus (IDDM) prevalence among 18-year-old males born in Sardinia between 1936 and ... More
This chapter describes a Bayesian hierarchical model and applies it to a new dataset on insulin-dependent diabetes mellitus (IDDM) prevalence among 18-year-old males born in Sardinia between 1936 and 1973, using malaria prevalence in 1938–40 as the ecological covariate. It shows how to deal with the potential bias associated with using such a proxy by extending the Bayesian model to allow for covariate measurement error. It provides a method for choosing the hyperprior distributions for the spatial variation parameters of the model, and discusses the sensitivity of the results to different choices.Less
L. BernardinelliC. PascuttoC. MontomoliW. Gilks
This chapter describes a Bayesian hierarchical model and applies it to a new dataset on insulin-dependent diabetes mellitus (IDDM) prevalence among 18-year-old males born in Sardinia between 1936 and 1973, using malaria prevalence in 1938–40 as the ecological covariate. It shows how to deal with the potential bias associated with using such a proxy by extending the Bayesian model to allow for covariate measurement error. It provides a method for choosing the hyperprior distributions for the spatial variation parameters of the model, and discusses the sensitivity of the results to different choices.
Keywords: Bayesian model, hierarchical model, diabetes mellitus, malaria, bias, spatial epidemiology
Bayesian methods for mapping disease risk
D. Clayton and L. Bernardinelli
in Geographical and Environmental Epidemiology: Methods for Small Area Studies
The construction of disease maps has been a central problem of descriptive epidemiology throughout its history. There are two main classes of disease maps: maps of standardized rates, and maps of ... More
The construction of disease maps has been a central problem of descriptive epidemiology throughout its history. There are two main classes of disease maps: maps of standardized rates, and maps of statistical significance of the difference between risk in each area and the overall risk averaged over the entire map. This chapter focuses on the mapping problem with particular attention to smoothing maps of rates computed for small areas. The use of spatial correlation structure along with Bayesian concepts suggests ways of smoothing these maps.Less
D. ClaytonL. Bernardinelli
The construction of disease maps has been a central problem of descriptive epidemiology throughout its history. There are two main classes of disease maps: maps of standardized rates, and maps of statistical significance of the difference between risk in each area and the overall risk averaged over the entire map. This chapter focuses on the mapping problem with particular attention to smoothing maps of rates computed for small areas. The use of spatial correlation structure along with Bayesian concepts suggests ways of smoothing these maps.
Keywords: Bayesian models, mapping, smoothing, small-area studies
Bayesianism
Brian D. Haig
in The Philosophy of Quantitative Methods: Understanding Statistics
Psychology, Social Psychology
Chapter 4 focuses on Bayesian confirmation theory, a formal theory of reasoning based on probability theory. It deals with important, and related, general ideas, such as rationality, confirmation, ... More
Chapter 4 focuses on Bayesian confirmation theory, a formal theory of reasoning based on probability theory. It deals with important, and related, general ideas, such as rationality, confirmation, and inductive inference, including statistical inference. The chapter also provides a selective discussion of Bayesian statistics. The chapter traces some of the broad contours of Bayesian confirmation theory and then presents an evaluation of a philosophy of Bayesian statistical practice. Psychology's attitudes to Bayesianism are briefly discussed. Considered is the question of whether Bayesianism provides an illuminating account of the approach to theory evaluation known as inference to the best explanation. The chapter offers some broad recommendations for research practice.Less
Chapter 4 focuses on Bayesian confirmation theory, a formal theory of reasoning based on probability theory. It deals with important, and related, general ideas, such as rationality, confirmation, and inductive inference, including statistical inference. The chapter also provides a selective discussion of Bayesian statistics. The chapter traces some of the broad contours of Bayesian confirmation theory and then presents an evaluation of a philosophy of Bayesian statistical practice. Psychology's attitudes to Bayesianism are briefly discussed. Considered is the question of whether Bayesianism provides an illuminating account of the approach to theory evaluation known as inference to the best explanation. The chapter offers some broad recommendations for research practice.
Keywords: Bayesianism, Bayesian confirmation theory, Bayes's theorem, Bayesianism and scientific method, philosophy of Bayesian statistical modeling
Simplicity and Model Selection
Jan Sprenger and Stephan Hartmann
in Bayesian Philosophy of Science
Philosophy, Philosophy of Science
Is simplicity a virtue of a good scientific theory, and are simpler theories more likely to be true or predictively successful? If so, how much should simplicity count vis-à-vis predictive accuracy? ... More
Is simplicity a virtue of a good scientific theory, and are simpler theories more likely to be true or predictively successful? If so, how much should simplicity count vis-à-vis predictive accuracy? We address this question using Bayesian inference, focusing on the context of statistical model selection and an interpretation of simplicity via the degree of freedoms of a model. We rebut claims to prove the epistemic value of simplicity by means of showing its particular role in Bayesian model selection strategies (e.g., the BIC or the MML). Instead, we show that Bayesian inference in the context of model selection is usually done in a philosophically eclectic, instrumental fashion that is more tuned to practical applications than to philosophical foundations. Thus, these techniques cannot justify a particular "appropriate weight of simplicity in model selection".Less
Jan SprengerStephan Hartmann
Is simplicity a virtue of a good scientific theory, and are simpler theories more likely to be true or predictively successful? If so, how much should simplicity count vis-à-vis predictive accuracy? We address this question using Bayesian inference, focusing on the context of statistical model selection and an interpretation of simplicity via the degree of freedoms of a model. We rebut claims to prove the epistemic value of simplicity by means of showing its particular role in Bayesian model selection strategies (e.g., the BIC or the MML). Instead, we show that Bayesian inference in the context of model selection is usually done in a philosophically eclectic, instrumental fashion that is more tuned to practical applications than to philosophical foundations. Thus, these techniques cannot justify a particular "appropriate weight of simplicity in model selection".
Keywords: Statistical model selection, Bayesian model selection, Bayesian Information Criterion (BIC), simplicity, instrumental Bayesianism, statistical models
Domestic Coalition Shifts in War Termination
in Paths to Peace: Domestic Coalition Shifts, War Termination and the Korean War
Stanford University Press
10.11126/stanford/9780804762694.003.0002
Political Science, Conflict Politics and Policy
This chapter outlines the existing literature about war termination. It demonstrates that there is a causal connection between the difficulty of ending wars and the fact that they are started and ... More
This chapter outlines the existing literature about war termination. It demonstrates that there is a causal connection between the difficulty of ending wars and the fact that they are started and ended by politicians. Realpolitik, domestic politics, and bargaining models can be used to illustrate categories about war termination. Bayesian models of war termination theorized more explicitly about lags in the updating process that can result in protracted stalemates. These models showed that a lag in updating can delay war termination, they do not elaborate on how states get beyond this lag. Ending war needed settling with the enemy as well as at home. It is noted that policy stability can result governing coalitions being ineffective for altering the status quo, even when such changes are necessary or desirable. Furthermore, a coalition shift can overpower the obstacles to peace and thus allows a war to end.Less
This chapter outlines the existing literature about war termination. It demonstrates that there is a causal connection between the difficulty of ending wars and the fact that they are started and ended by politicians. Realpolitik, domestic politics, and bargaining models can be used to illustrate categories about war termination. Bayesian models of war termination theorized more explicitly about lags in the updating process that can result in protracted stalemates. These models showed that a lag in updating can delay war termination, they do not elaborate on how states get beyond this lag. Ending war needed settling with the enemy as well as at home. It is noted that policy stability can result governing coalitions being ineffective for altering the status quo, even when such changes are necessary or desirable. Furthermore, a coalition shift can overpower the obstacles to peace and thus allows a war to end.
Keywords: war termination, realpolitik, domestic politics, bargaining models, Bayesian models, lags, governing coalitions, coalition shift
Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches
Bruce Walsh and Michael Lynch
in Evolution and Selection of Quantitative Traits
Biology, Evolutionary Biology / Genetics, Biochemistry / Molecular Biology
When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and ... More
When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and their Bayesian extensions. In this setting, REML can be used to estimate genetic variances and BLUP can be used to estimate the mean breeding value in any given generation. The latter allows for genetic trends to be separated from environmental trends without the need for a control population. Under the infinitesimal model setting (wherein selection-induced allele-frequency changes are small during the course of the experiment), the use of the relationship matrix in a BLUP analysis accounts for drift, nonrandom mating, and linkage disequilibrium.Less
Bruce WalshMichael Lynch
When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and their Bayesian extensions. In this setting, REML can be used to estimate genetic variances and BLUP can be used to estimate the mean breeding value in any given generation. The latter allows for genetic trends to be separated from environmental trends without the need for a control population. Under the infinitesimal model setting (wherein selection-induced allele-frequency changes are small during the course of the experiment), the use of the relationship matrix in a BLUP analysis accounts for drift, nonrandom mating, and linkage disequilibrium.
Keywords: animal model, Bayesian mixed-models, BLUP, BLUP selection, Gibbs sampler, Henderson's mixed-model equations, infinitesimal model, Markov chain Monte Carlo, Metropolis-Hastings algorithm, MCMC, mixed models, numerator relationship matrix, prediction error variances, relationship matrix, REML
Bayesian Hierarchical Modeling of Public Health Surveillance Data: A Case Study of Air Pollution and Mortality
Scott L. Zeger, Francesca Dominici, Aidan Mcdermott, and Jonathan M. Samet
in Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance
This chapter illustrates the use of log-linear regression and hierarchical models to estimate the association of daily mortality with acute exposure to particulate air pollution. It focuses on ... More
This chapter illustrates the use of log-linear regression and hierarchical models to estimate the association of daily mortality with acute exposure to particulate air pollution. It focuses on multistage models of daily mortality data in the eighty-eight largest cities in the United States to illustrate the main ideas. These models have been used to quantify the risks of shorter-term exposure to particulate pollution and to address key causal questions.Less
Scott L. ZegerFrancesca DominiciAidan McdermottJonathan M. Samet
This chapter illustrates the use of log-linear regression and hierarchical models to estimate the association of daily mortality with acute exposure to particulate air pollution. It focuses on multistage models of daily mortality data in the eighty-eight largest cities in the United States to illustrate the main ideas. These models have been used to quantify the risks of shorter-term exposure to particulate pollution and to address key causal questions.
Keywords: air pollution, mortality, public health monitoring, public health surveillance, Bayesian hierarchical models


text:
Q: Format long not working when adding to structure I am trying to add a number in Unix time to a structure (e.g.      1.500648654999999e+09), but even when I put format long it is being saved in an abbreviated way (1.5006e+09).
 format long
    TimeToAdd = BL05_tsq_StartTimes(1) - (4*3600);
    format long
    LFPinfo(i).startTime = LFPinfo(i).startTime+TimeToAdd;

A: The summary of format states

Set Command Window output display format

It changes the output display format in the Command Window to the format specified by style. The computation and value stored in the memory wouldn't be affected by the format command.
To display the formatted string in the command window, you need to use fprintf, and specify the precision you prefer. For example:
fprintf('%.10f\n',LFPinfo(i).startTime)

redpajama_set_name: RedPajamaStackExchange


text:
Sing, Scream and Shout: Kojies win second-straight, GSP, Sophomores back on top
Posted on February 22, 2009 | News | Comments Off on Sing, Scream and Shout: Kojies win second-straight, GSP, Sophomores back on top
First it was the elated screams of a sea of skunk, then the roars of an army of Peter Pans and finally the screeching cheers from the sophomore class that filled Moody Coliseum on Saturday night, when the winners of the 53rd annual Sing Song: Believe were announced on the Moody stage.
Ko Jo Kai won its second-straight Sing Song, and Gamma Sigma Phi returned to its winning ways Saturday night when the Sing Song co-chairs announced the winners of the traditional ACU singing competition. The sophomore class, which won for the first time since 2002, won the mixed voices division with their show, "Flight of the Sophomores."
The women of Ko Jo Kai erupted in ecstasy after hearing the result that they had won the women's division. The win marked the club's 13th total victory and second in a row.
"I'm so excited that we won a second time in a row; we're starting a streak." said Kojie Aubrey Bonneau, senior graphic design major from Dallas.
The Kojies won first place in the audience favorite, entertainment and overall categories. They placed third in the vocals category.
"I was extremely happy with [the results]. I thought they were really realistic; they matched each category, especially with the vocals," said Kojie Lora Courtney, senior interior design major from Auburn, Calif. "We got third there, but everyone tried really hard to make an overall great show."
Sigma Theta Chi won the vocals category, but placed second in the other three categories.
"We gave all that we had, and we felt awesome about it," said Siggie Sarah Brooks, senior marketing major from Bartlett, Tenn. "As the curtain was going down, we were like, 'this is what Sing Song is all about.' But [the Kojies] had a great show."
Alpha Kai Omega placed third in all categories, except for vocals, where it placed second.
"It's not exactly what we expected, but it turned out really well," said KaiO Marisa Munoz, senior elementary education major from Snyder. "We are so proud of ourselves. We don't have any regrets."
In the men's category GSP's show, "Second Star to the Right and Straight on to Moody," claimed its first win since 2007. GSP has won 12 shows overall.
"I'm proud of these guys; they are the best crew, and we won because of the individuals that made up this team," Reeves said.
Reeves said he was glad this year's competition was more competitive and thought both Frater Sodalis and Galaxy had strong shows and the vocal competition was a toss up.
"Both the Moonies and Frats sang amazing," he said.
Although Reeves was the person at the front of the stage directing the army of Peter Pans in GSP's show, he said it was a combination of hard work from him, his co-director Tyler Lewis, junior finance major from Spring and the men of GSP that earned them the win. Reeves plans to graduate in May and said it felt great to finish his last Sing Song on top.
"It's a good way to go out," Reeves said.
Although Galaxy did not repeat its 2008 win, director of the club's show, Wade Huggins, said he was proud of the men who learned his choreography and sang the lyrics he wrote in the show, "Gondoliers: You Know, The Guys in Venice With The Boat and Pole and Hats."
"It was definitely disappointing, but [we] worked long and hard for this show, and there were a great many hours and sleepless nights put into it," Huggins said.
Galaxy won first in the appearance category, and Huggins said the Moonies would begin working hard to produce a show that will be a contender in 2009.
"We're on the search for a director for next year, and you can believe we're going to have a quality show," Huggins said.
In the mixed-voiced division, the sophomore's show beat out three classes and a group that was combined of members from the International Students' Association, Essence of Ebony and Hispanos Unidos. The freshman class placed second overall, and the senior class finished third.
Deanne Galloway, senior speech pathology major from Tehachapi, Cali., attributed the seniors' third place finish to the number of postmen and postwomen who did not participate in the show because of other commitments to their social clubs. Victory was not in the cards for the seniors, but nothing could keep their spirits down.
"We just wanted to have fun, and we did," Galloway said. "We won entertainment, so I thank that explains everything."
Sophomore directors Jessica Williams, English major from Atlanta, and Lucas Wright, electronic media major from Abilene, could not have been more surprised by their win in the overall category.
"I was shocked," Wright said. "I was just shocked."
Williams had confidence in her group, hoping for the best but preparing for the worst.
"Our group is great, we just didn't know what to expect," Williams said. "It was elation."
Rene Glena, sophomore communication disorder major from Athens, has traveled to Abilene for Sing Song since age 11. She knew the senior class' legacy of winning Sing Song, but said the real satisfaction came from triumphing over a different class.
"I think it was beating the freshmen that was most exciting," Glena said. "They were our big rivals."
The roar of the crowd boomed and overflowed Moody Coliseum on Saturday night signaling the imminent conclusion of Sing Song; ecstatic participants were out receiving congratulatory hugs and praise from loved ones and friends.
A mixture of feelings of relief, accomplishment, joy and uncertainty overcame one of the Sing Song co-chairs Preston Woolfolk, junior political science and international studies major from San Antonio.
"It went better than expected," Woolfolk said. "The quality of the show was phenomenal. I would say the overall talent and excitement the acts demonstrated were amazing; their effort really showed tonight."
With a mass of feelings generating inside Moody, Tom Craig, director of Student Productions, explained what made Sing Song spectacular.
"The hours that the students invest in the creation process is what makes Sing Song special," Craig said. "The time it takes to rehearse and put it all together creates student relationships that last a lifetime."
The 54th annual Sing Song's theme will be Name Fame.
Posted by Staff on Feb 22nd, 2009 and filed under News. You can follow any responses to this entry through the RSS 2.0. Both comments and pings are currently closed.	- This post has been viewed 30283 times.
» GATA, Galaxy and sophomores take home the trophy - 02/21/2016
» Sing Song director selection begins - 10/17/2015
» 2016 Sing Song co-chairs selected - 04/23/2015
» JMC Network Newscast – February 13, 2015 - 02/17/2015
» Crowdfunding is the smartest invention - 02/15/2015

redpajama_set_name: RedPajamaCommonCrawl


text:
Longitarsus celticus is a species of beetle in the subfamily Galerucinae that can be found in Austria, Czech Republic, France, Germany, Italy, Spain, Switzerland, Ukraine, and Yugoslavia.

References

C
Beetles described in 1975
Beetles of Europe

redpajama_set_name: RedPajamaWikipedia


If your umbrella collection consists of a bunch of those buy-and-toss numbers you get from a street peddler whenever you happen to be caught in a downpour – the kind of umbrellas you don't miss when they're forgotten on the subway – why not invest a little thought into picking one that goes beyond basic New York black and won't collapse like a cheap lawn chair at the first gust of wind? You may not want to pony up $295 for the much-coveted Burberry plaid, but for a fraction of that price you can find an umbrella that keeps you dry while making a splash.
Liberty's khaki-black-and-red-plaid model (pictured, $40 at Venture) is a classy, functional umbrella in the perfect print that will stay chic for seasons to come. Other fun bumbershoots from the same line come with goldfish prints on vinyl (pictured) and in faux python ($36.95 each at Laytner's Linens & Home).
For more takes on the classic-with-a-twist, check out Echo's black model with tiny, festive polka dots (pictured, $48 at Tribeca Luggage & Leather) and the line's other subtle, clean designs, which often feature understated florals and dark iridescent solids.
We also love the Museum of Modern Art Design Store's Clouds umbrella (pictured, $45), with its simple black exterior and a turquoise interior covered with white, fluffy clouds – so the weather will be perfect wherever you walk. Very Magritte. And if it's kitsch you're after, Bed Bath & Beyond's Inspirations line should do the trick, with prints derived from famous works of art, like a pink-and-blue print of Warhol's Marilyn and Monet's Waterlilies (pictured) done in muted tones ($20 each).
Bob Mackie is having a sample sale this week with offerings from his Mackie line, a lower-priced collection of swank cocktail suits, all available at wholesale prices or below. 498 Seventh Ave., near 36th St. (212-736-0305); A.E., M.C., V.; Mon.-Fri. 10-5; 3/5-3/9.
Eileen Fisher's semi-annual consolidation sale offers reduced prices on women's separates from her fall collection, with all items under $70. 395 W. Broadway (212-431-4567); A.E., M.C., V.; Thurs. 11-7, Fri.-Sat. 11-8, Sun. noon-6; 3/8-3/11.
Tourneau's liquidation sale means 20 to 70 percent off original prices for its famous watches and jewelry from brand names like Raymond Weil and Movado. 635 Madison Ave., at 59th St. (212-758-6688); A.E., M.C., V.; Mon. and Thurs. 10-6:30, Tues., Wed., Fri., and Sat. 10-6.
The Quilted Corner is marking down its large selection of country-style quilts for its winter clearance sale, with all quilts reduced by up to 60 percent. 120 Fourth Ave. (212-505-6568); Mon.-Fri. 11-7, Sat. 10-6; through 3/31.


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O Cabeleira é um romance regionalista do século XIX, do autor cearense Franklin Távora. Foi lançado em 1876.
Conta a história de José Gomes (o Cabeleira) e seu pai Joaquim Gomes, ambos precursores do cangaço do nordeste brasileiro, e suas desventuras por Pernambuco.

É considerado uma das maiores obras do autor, além de uma das obras pioneiras no romance regionalista nordestino.

Adaptações
A obra foi filmada em 1963, com elenco formado por Hélio Souto, Milton Ribeiro e Marlene França.

As locações se deram na cidade de Mococa, em São Paulo, e Arceburgo, em Minas Gerais.

Em 2008, o livro de Franklin Távora foi adaptado para os quadrinhos pelos roteiristas Hiroshi Maeda e Leandro Assis e pelo desenhista Allan Alex.

Em 2009 foi publicado o livro Cabeleira e outros cordéis de cangaço, escrito pelo conterrâneo do Cabeleira, o cordelista Rafael de Oliveira, pela editora Coqueiro, do Recife.

Ligações externas

Livros de 1876
Romances do Brasil
Livros adaptados para o cinema
Cangaço na ficção


A Bibliography on the Economics of Quality and Grades.
An Economic Appraisal of the EEC Fruit and Vegetable Grading System.
A Bibliography on the Economics of Quality and Grades."
Will you succeed as a consultant?
Can civil servants be consultants?
Will I survive as a consultant?
Ethical consultants do not . . .
Academic Fraud Statistics for you to check with Source documents on Bengal Famine Academics contest Amartya SenBrief case against Amartya Sen How Sen's theory causes famines How Sen's theory causes famines Current state of controversy "Are boom famines possible?" "Can speculation cause famines?." "Rejoinder: an untenable hypothesis on the causes of famine"Famines: the Bowbrick-Sen dispute and some related issues,""Reply: famine and Mr Bowbrick"The causes of famine: a reply", "A refutation of Sen's theory of famine", Food Policy.
(Mahalanobis et al.)Mahalanobis.Report of the Famine Inquiry Commission, How Sen's Theory causes famines and in the Word document How Sen's Theory Can Cause Famines.
Entitlement, Shortage, and the 1943 Bengal Famine: Another Look, Journal of Peasant Studies, vol. 31, no. 1, Octobor 2003, 45-72.
I sued my internet provider - and won!
Bowbrick, P., Will the Council of Economic Advisers destroy Scotland?
Bowbrick, P., "How faked research damages the economy."
Bowbrick, P., Did ignoring whistleblowers kill 90 people?
Bowbrick, P., Commissions - or bribes?
Bowbrick, P., "Refereeing: perhaps there isn't a conspiracy after all"
Who says a sentence has to have a verb?


Pick either license (American English) or licence (Commonwealth English), not both - select the one which matches the content of the article the template is used in.
Parameter latest release date is unnecessary.
A screenshot from version 2.0. In the picture, "Lan," the player, fires Guided Missiles at another tank, while "dummy1_(tm)" chats, all while it rains. Taken from the low-quality release of the game. They are playing a map called "Battle City" by Brad2901.
| caption = A screenshot from version 2.0. In the picture, "Lan," the player, fires Guided Missiles at another tank, while "dummy1_(tm)" chats, all while it rains. Taken from the low-quality release of the game. They are playing a map called "Battle City" by Brad2901.
| developer = Yoyodyne Industries Inc.
Huling pagbabago: 05:21, 25 Disyembre 2013.


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Uncharted Creator Amy Hennig to be Honored With GDC Lifetime Achievement Award
By Chris Coker December 12, 2018
Amy Hennig, writer and creative director on the Uncharted and Legacy of Kain series, is set to receive a lifetime achievement award at the 19th Annual Game Developers Choice Awards.
The awards ceremony kicks off on Wednesday, March 20, 2019, at 6:30pm PST, at the San Francisco Moscone Center. Hennig's influence in games over the past 30 years has propelled the medium to brave new creative spaces, as she oversaw the production of award-winning games that focused heavily on plot, story, and character development.
"Amy Hennig is a powerful figure in the game world; her work exemplifies what good game narrative can be, with pathos, humor, suspense, and energy. She is truly one of the most influential developers in the games industry," said Katie Stern, general manager of the Game Developers Conference. "These past accomplishments are just milestones in a career that we'll be following for years to come, but for one night at the GDCAs, we'll reflect on the hard work and artistry that makes game developers like Amy the heart of the industry."
Hennig joins a prestigious list of former Lifetime Achievement Award recipients, including the likes of Double Fine's Tim Schafer, Epic Games's Tim Sweeney, Nintendo's Shigeru Miyamoto, Warren Spector, John Carmack, Hironobu Sakaguchi, Hideo Kojima, Sid Meier, Ken Kutaragi, Dr. Ray Muzyka and Dr. Greg Zeschuk, Peter Molyneux, and more.
In a July 2018 interview with Geoff Keighley and VentureBeat, Hennig admits that her career in games began somewhat fortuitously while working on a master's in film theory and production at the University of California at Berkeley. While doing pretty much anything she could to make money and pay for school, a high school friend asked her if she would be willing to help with the art and animation for an Atari game he was working on. With more an eye on the money than anything else, Hennig took the job, completing the game a year later.
While the game ended up being canceled, Hennig notes that the experience was a watershed moment for her, coming at a time when she encountered a certain resistance to her ambitions as a female filmmaker. Games, on the other hand, were a blue ocean of unwritten rules and promise.
"In film school, we were learning about the Lumiere brothers and Edward Porter and Sergei Eisenstein, people who had to figure out what film was. But then we were just following their lead. In games, we got to be those people. We got to figure out how we were going to make this stuff, what the mechanics and the language of these games would be. That's what inspired me."
Speaking to her role as a creative director on multiple projects dating back all the way to Legacy of Kain: Soul Reaver, Hennig revealed that, while most people think a creative director rules with an iron fist, the job is much more about giving others creative latitude.
"You have to have enough humility to say — in your head, not out loud — 'That's not what I would have done, what I was picturing, but is it better than my idea?' If so, awesome. Is it just as good, even though it's not what I was picturing? Then that's fantastic because they have a sense of ownership and passion. If it's not as good, you have to have enough ego to say, 'Here's the reason I asked for it that way. Here's a correction,' And have the presence of mind – because we're all human beings with flaws – to not react the wrong way in the moment."
Hennig left Naughty Dog in 2014 before joining the now-defunct Visceral Games that same year. Following Visceral's closure, she founded an independent game studio and consultancy firm and is working on an as-yet-unannounced title. Earlier this year, she revealed that not releasing a new title since 2011's Uncharted 3: Drake's Deception is "killing" her.
For news, updates, and info on the games industry, follow OnlySP on Facebook, Twitter, and YouTube.
amy hennig
Legacy of Kain
NieR:Automata Game Of the YoRHa Confirmed for 2019
Shadow of the Tomb Raider DLC Behind-the-Scenes Video Released


text:
Festival Distribution
Contacts - Festival Passes - Venues - Hospitality - Film Database - Newsletter - Privacy
Complete programme
Piazza Maggiore and BarcArena
Download the programme (PDF)
TIckets Reservation, Access and Health
Download the catalogue (PDF)
Film lessons
Focus on restoration
IL CINEMA RITROVATO 2020
FESTIVAL CATALOGUE | pp. 384
Our catalogue is more than a guide to our films! It's an essential part of the festival, an encyclopedia of knowledge which arouse curiosity, put the films in their proper historical context and preserve the memory of the films seen. Please note that the information in the catalogue is also available online.
BUY ON CINESTORE
AUGUSTO GENINA. THE PRICE OF BEAUTY
Curated by Mariann Lewinsky and Andrea Meneghelli | 2 Dvd + Booklet
Presented for the first time or in the most recent restorations, four films showcasing Augusto Genina's genius and the extraordinary generation of actresses, between stardom and post-stardom, who lit up his silent films. Addio giovinezza! (1918): based on Camasio and Oxilia's successful comedy, miraculously rediscovered, a film pulsating with spontaneity and the radiant presence of Maria Jacobini. La maschera e il volto (1919): a satirical and caustic comedy about marital and sexual mores. Unprecedented audacity. Addio giovinezza! (1927): a remake, but it seems like a century has gone by. Genina and his muse Carmen Boni set their sights on international film and create a splendid modern romantic comedy. Prix de beauté (1930): Genina's crowning moment and farewell to silent film. Louise Brooks dazzles with all her aura of innocence and sensuality in a timeless European masterpiece. With essays by Mariann Lewinsky, Andrea Meneghelli, Paola Cristalli and Michele Canosa and six diva portraits by Vittorio Martinelli.
FELLINI 23 1⁄2. TUTTI I FILM
by Aldo Tassone | Book, pp. 880
Every title from Fellini's prodigious career is included in this systematic, in-depth study: twenty-three and a half films, from feature-lengths to shorts, from Luci del varietà (1950), the 'half ' co-directed with Alberto Lattuada, to La voce della luna (1990). Planned and researched by author Aldo Tassone over the course of a lifetime, this volume has now been published to celebrate the centenary of the director's birth. It gathers together more than four decades of studies, research and intimate conversations with the director and his collaborators. Fellini 23 1⁄2 is an invitation to immerse yourself in the individual works of one of the most original and revered directors of the second half of the 20th century. It explores the genesis of each film, evoking their narrative drama and figurative power, and reconstructing, through the selection of a powerful body of reviews, the reactions of Italian, French and American critics, in a comprehensive, dialectical comparison of voices. Attention is also given to some projects that never came to fruition, such as Il viaggio di G. Mastorna and Viaggio a Tulum.
Do you want to keep update on all the events?
The Fondazione Cineteca di bologna offers a large catalogue of Books, DVDs and Gadgets to arouse all cinema lovers curiosity.


fast potato chips cutting machine mango papaya stick making machine can use for potato; carrot and taro strip cutting. And it has smooth surface cutting, fast cutting speed and high output. Its output is more than 1000KG in one hour. Easy to operate, easy to wash and labor saving. The cutting size can be customized.
fast potato chips cutting machine mango papaya stick making machine is now a general-purpose model DL3000-100 single screw, is mainly used for the production of a variety of pasta, fried foods, rice noodles, pasta, pasta and other products, stable output, simple and convenient operation. 3000 is the length of the screw and 100 is the diameter of the screw.
fast potato chips cutting machine mango papaya stick making machine consists of feeding system, extrusion system, rotary cutting system, heating system, transmission system and control system. The use of advanced screw extrusion technology, the use of high temperature and high pressure material curing and expansion molding, one-time completion. The host adopts variable frequency speed regulation to ensure the stability of the production process. Product color, variety, appearance, natural and realistic, delicate texture, raw materials are widely used of .


EVANSTON, Ill. --- Sparks literally fly when a sperm and an egg hit it off. The fertilized mammalian egg releases from its surface billions of zinc atoms in "zinc sparks," one wave after another, a Northwestern University-led interdisciplinary research team has found.
Using cutting-edge technology they developed, the team is the first to capture images of these molecular fireworks and pinpoint the origin of the zinc sparks: tiny zinc-rich packages just below the egg's surface.
Woodruff is a Thomas J. Watkins Memorial Professor in Obstetrics and Gynecology and director of the Women's Health Research Institute at Northwestern University Feinberg School of Medicine.
The study is published today (Dec. 15) by the journal Nature Chemistry, provides the first quantitative physical measurements of zinc localization in single cells in a mammal.
The research team, including experts from the U.S. Department of Energy's Advanced Photon Source (APS), developed a suite of four physical methods to determine how much zinc there is in an egg and where it is located at the time of fertilization and in the two hours just after. Sensitive imaging methods allowed the researchers to see and count individual zinc atoms in egg cells and visualize zinc spark waves in three dimensions.
O'Halloran is a Charles E. and Emma H. Morrison Professor in Chemistry in the Weinberg College of Arts and Sciences and director of Northwestern's Chemistry of Life Processes Institute.
The studies reported in Nature Chemistry are the culmination of six years of work and build on prior discoveries made by the Woodruff and O'Halloran labs using data from work performed at Northwestern and the APS. In previous studies in mouse eggs, this research team discovered the egg's tremendous zinc requirement for reaching maturity. In addition, the researchers determined that an egg loses 10 billion of its 60 billion zinc atoms upon fertilization in a series of four or five waves called "zinc sparks." Release of zinc sparks from the egg is essential for embryo formation in the two hours following fertilization.
One major hurdle O'Halloran and Woodruff faced was the lack of sensitive methods for measuring zinc in single cells. To address this problem, they formed a collaborative team with other researchers in Northwestern's Chemistry of Life Processes Institute to develop the tools they needed.
The National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant U54HD076188) and the W.M. Keck Foundation supported the research.
In addition to O'Halloran, Woodruff, Dravid and Vogt, other authors of the paper are lead author Emily L. Que, Reiner Bleher, Francesca E. Duncan, Betty Y. Kong, Seth A. Garwin and Amanda R. Bayer, of Northwestern; and Sophie C. Gleber and Si Chen, of Argonne National Laboratory.


text:
Offset recruits Hit-Boy for the first song since TakeOff's death
Offset has attached to Hit-Boy to release his first song since Departures died last November.
The lively club anthem, "2 Live", serves as a direct contrast to Quavo's somber solo track "Without You," which he released last week. Offset's bouncy track instead finds Hit-Boy rapping about his fun experience at the club, while Migos member spits about a late-night love interest who is "going crazy."
The new number comes after Hit teased the collaboration on social media earlier this week as he looks to keep his 2022 hot streak alive.
It also follows the manufacturer's recent announcement that he is working on one joint album with R&B legend Musiq Soulchild called Victims and villainswhich will be released later this year.
"2 Live" will likely appear on Offset's upcoming solo album, which he delayed out of respect for TakeOff, which was shot and killed outside a bowling alley in Houston, Texas November 1st. It follows Set's previously released singles "54321" and "CODE". Moneybag Yo.
The upcoming project will serve as the follow-up to his 2019 solo debut Father of 4which debuted at No. 4 on the Billboard 200.
During an interview with SENSE last August, Offset went into detail about what his still-untitled LP sounds like, which he previously confirmed on Twitter will clock in at 13 tracks.
"This is just the beginning," he explained. "It's just the gutter and the core, from the heart. I got a lot of different flows on it. I rap, even though I see a lot of the artists today, they like auto-tune. A lot. I feel like I'm not on at all that wave.
"When I came in, we came out of the trenches, so that's what people want to hear because that's what people go through every day. Doesn't anyone drive a Wraith."
He added:[In] Black culture right now, and the world in general, the poor outweigh the rich by a thousand percent. So you have to talk about crap that goes on in real life. Just the real content of what people see every day. Get back to it."
Offset Still Struggling To Process TakeOff's Death: 'Shit Not Easy'
Regarding TakeOff's passing, Offset gave an emotional speech at the rapper's funeralwhich took place at the State Farm Arena in Atlanta, Georgia, and praised his late Migos collaborator for his contributions to rap music.
"Changed music culture forever, you did it Take," Offset said while holding back tears. "You changed that flow. That flow came from Take, the originator. The originator of that flow. He changed the music."
He continued: "Lord give us the strength, give us the strength, the family and everyone, give us the strength. I don't want to question God, but I just don't understand".
Hit-Boy, meanwhile, was recently crowned HipHopDXs Best producer in 2022 thanks to a standout year where he dropped joint projects with Dreezy and Pacman Da Gunman while contributing to Beyonce's Renaissance, The game Drillmatic and Ab-Soul's Herbertamong other albums.
His crowning achievement, however, was The King's Disease IIIhis fourth collaboration with U.S in three years and arguably the finest episode of their Grammy-winning series.
Musician Testifies About Ticketmaster 'Monopoly,' Goes Viral
Queer Jams of the Week: New music from Sam Smith, Pvris, Adam Lambert & More
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text:
The Mayo Clinic Diet is designed to help you lose up to 6 to 10 pounds (2.7 to 4.5 kilograms) during the initial two-week phase. After that, you transition into the second phase, where you continue to lose 1 to 2 pounds (0.5 to 1 kilogram) a week until you reach your goal weight. By continuing the lifelong habits that you've learned, you can then maintain your goal weight for the rest of your life.
Some Christians integrate yoga and other aspects of Eastern spirituality with prayer and meditation. This has been attributed to a desire to experience God in a more complete way.[281] In 2013, Monsignor Raffaello Martinelli, servicing Congregation for the Doctrine of the Faith, having worked for over 23 years with Cardinal Joseph Ratzinger (Pope Benedict XVI),[282] said that for his Meditation, a Christian can learn from other religious traditions (zen, yoga, controlled respiration, Mantra), quoting Aspects of Christian meditation: "Just as "the Catholic Church rejects nothing of what is true and holy in these religions," neither should these ways be rejected out of hand simply because they are not Christian. On the contrary, one can take from them what is useful so long as the Christian conception of prayer, its logic and requirements are never obscured. It is within the context of all of this that these bits and pieces should be taken up and expressed anew."[283] Previously, the Roman Catholic Church, and some other Christian organizations have expressed concerns and disapproval with respect to some eastern and New Age practices that include yoga and meditation.[284][285][286]
On January 16, 1904, the first large-scale bodybuilding competition in America took place at Madison Square Garden in New York City. The competition was promoted by Bernarr Macfadden, the father of physical culture and publisher of original bodybuilding magazines such as Health & Strength. The winner was Al Treloar, who was declared "The Most Perfectly Developed Man in the World".[5] Treloar won a $1,000 cash prize, a substantial sum at that time. Two weeks later, Thomas Edison made a film of Treloar's posing routine. Edison had also made two films of Sandow a few years before. Those were the first three motion pictures featuring a bodybuilder. In the early 20th century, Macfadden and Charles Atlas continued to promote bodybuilding across the world. Alois P. Swoboda was an early pioneer in America.
This terse definition hinges on the meaning of three Sanskrit terms. I. K. Taimni translates it as "Yoga is the inhibition (nirodhaḥ) of the modifications (vṛtti) of the mind (citta)".[142]Swami Vivekananda translates the sutra as "Yoga is restraining the mind-stuff (Citta) from taking various forms (Vrittis)."[143] Edwin Bryant explains that, to Patanjali, "Yoga essentially consists of meditative practices culminating in attaining a state of consciousness free from all modes of active or discursive thought, and of eventually attaining a state where consciousness is unaware of any object external to itself, that is, is only aware of its own nature as consciousness unmixed with any other object."[144][145][146]
Samuel states that Tantrism is a contested concept.[183] Tantra yoga may be described, according to Samuel, as practices in 9th to 10th century Buddhist and Hindu (Saiva, Shakti) texts, which included yogic practices with elaborate deity visualizations using geometrical arrays and drawings (mandala), fierce male and particularly female deities, transgressive life stage related rituals, extensive use of chakras and mantras, and sexual techniques, all aimed to help one's health, long life and liberation.[183][266]
The origins of yoga have been speculated to date back to pre-Vedic Indian traditions; it is mentioned in the Rigveda,[note 1] but most likely developed around the sixth and fifth centuries BCE, in ancient India's ascetic and śramaṇa movements.[8][note 2] The chronology of earliest texts describing yoga-practices is unclear, varyingly credited to Upanishads.[9] The Yoga Sutras of Patanjali date from the first half of the 1st millennium CE,[10][11] but only gained prominence in the West in the 20th century.[12] Hatha yoga texts emerged sometimes between the 9th and 11th century with origins in tantra.[13][14]


Sam has a PhD in management group decision processes in health-related decision settings, and a BSc in Psychology with Criminology – both from the University of South Wales. Her interest in health services research began during her PhD studies when she researched the judgement processes of NICE Guidance Development Groups (GDGs). She joined the Health Economics & Policy Research Unit at the University of South Wales in September 2007, and provided health economics research support, working on various healthcare projects and clinical trials, including: PAAD, ELIJAH, TCADS, PREFERS and many others.
She recently moved to Swansea Centre for Health Economics (SCHE) at Swansea University in January 2015, taking on a combined role as Research and Operations Assistant. Her main responsibilities now focus on: assisting in the management of SCHE procedures and policies, assessing unit costs for healthcare interventions, measuring health-related quality of life for economic evaluation (cost utility analysis), and supporting health-related organisations with prioritisation decisions using Programme Budgeting and Marginal Analysis (PBMA). Sam is currently assisting on research projects including: HAPPIKNEES, CREAM, POETIC and GASP.
Sam also teaches in a number of Health Economics subjects and is currently supervising two PhDs.
Perry, J., Allen, D., Pimm, C., Meek, A., Lowe, K., Groves, S., Cohen, D. & Felce, D. (2013). Adults with intellectual disabilities and challenging behaviour: the costs and outcomes of in- and out-of-area placements. Journal of Intellectual Disability Research 57(2), 139-152.
Allen, D., Cohen, D., Hood, K., Robling, M., Atwell, C., Lane, C., Lowes, L., Channon, S., Gillespie, D., Groves, S., Harvey, J. & Gregory, J. (2012). Continuity of care in the transition from child to adult diabetes services: a realistic evaluation study. Journal of Health Services Research & Policy 17(3), 140-148.
Roberts, S., Williams, J., Cohen, D., Akbari, A., Groves, S. & Button, L. (2011). Feasibility of using routinely collected inpatient data to monitor quality and inform choice: a case study using the UK inflammatory bowel disease audit. Frontline Gastroenterology 2(3), 153-159.


text:
Manilkara spectabilis is an uncommon species of tree in the sapodilla family.

In 1997, the IUCN were mistakenly under the impression that a specimen in the US, collected in 1899 from a site near Limón in the Atlantic coastal forests of Costa Rica was the only specimen that had ever been collected for of the species, and therefore assumed it might be an endemic to this location. Based on this supposition, the species was provisionally declared 'critically endangered'. It had in fact been collected in Nicaragua in 1951 already, and after being declared 'critically endangered' it was soon found elsewhere in eastern coastal Costa Rica by local researchers.

References

spectabilis
Plants described in 1912
Critically endangered plants
Trees of Costa Rica
Taxonomy articles created by Polbot


text:
import os
import json

from bjm_jsondiff import benjamin_jsondiff

from grip import export

def _all_resources_and_assets(path):
    pattern = "'\(main/res\)\|\(assets\)'"
    return _find_sth_by_pattern(path, "*.*", pattern)

def _all_dynamic_libraries(path):
    pattern = '\.so$'
    return _find_sth_by_pattern(path, "*.so", pattern)

def _all_jar_files(path):
    pattern = '\.jar$'
    return _find_sth_by_pattern(path, "*.jar", pattern)

def _find_sth_by_pattern(path, suffix, pattern):
    cmd = "find %s -name '*.*' | grep -e %s" % (path, pattern)
    filename_list = os.popen(cmd).read().split('\n')
    ret = {}
    ret['data'] = {}
    total_size = 0
    for filename in filename_list:
        if filename == '':
            continue
        key = filename.split(path)[1].lstrip('/')
        ret['data'][key] = {}
        size = os.path.getsize(filename)
        ret['data'][key]['size'] = size
        total_size += size

    ret['total_size'] = total_size

    return ret

def _large_size_dectect(resources, empathy):
    ret = []
    for filename, entry in resources['data'].iteritems():
        size = entry['size']
        if size > empathy * 1024:
            ret.append({"size": size, "file": filename})

    return ret

def similar_jar_packages(path):
    """
    Detect whether this project use similar jar files.
    For now, only similar json libraries detecting rule supported.
    """
    # TODO refactor. extract to a configuration file.
    json_pattern_list = ['gson', 'json-simple', 'fastjson']
    ret = {}
    ret['json']= {}
    ret['json']['list'] = []
    total_json_files_size = 0
    jarfiles = _all_jar_files(path)
    for filename, entry in jarfiles['data'].iteritems():
        size = entry['size']
        for pattern in json_pattern_list:
            if filename.find(pattern) != -1:
                ret['json']['list'].append({"size": size, "file": filename})
                total_json_files_size += size
                break

    ret['json']['total_size'] = total_json_files_size

    return ret

def diff_resource_change(base, now):
    """
    Calcuate resource changes of two different version project.

    @param base: base resource list
    @type base: an instance of C{dict}, each key-value pair looks like this:
        '<filepath>': {'size'}: <filesize>

    @param now: base resource list
    @type now: an instance of C{dict}, each key-value pair looks like this:
        '<filepath>': {'size'}: <filesize>

    @return an instance of changes
    """

    raw_res_differences = benjamin_jsondiff(base['data'], now['data'])

    ret = {}
    ret['increase'] = {}
    ret['increase']['count'] = 0
    ret['increase']['size'] = 0
    ret['increase']['list'] = []
    ret['decrease'] = {}
    ret['decrease']['count'] = 0
    ret['decrease']['size'] = 0
    ret['decrease']['list'] = []
    ret['add'] = {}
    ret['add']['count'] = 0
    ret['add']['size'] = 0
    ret['add']['list'] = []
    ret['remove'] = {}
    ret['remove']['count'] = 0
    ret['remove']['size'] = 0
    ret['remove']['list'] = []
    ret['add']['list'] = []
    ret['total'] = {}
    ret['total']['size_diff'] = 0
    ret['total']['size_diff_adjust'] = 0
    ret['total']['size_diff_rate'] = 0.0
    ret['trendcy'] = 'plain'

    for diff in raw_res_differences:
        if 'add' in diff:
            ret['add']['count'] += 1
            ret['add']['size'] += diff['value']['size']
            ret['add']['list'].append({'file': diff['add'], "size": diff['value']['size']})
            ret['total']['size_diff'] += diff['value']['size']
        elif 'remove' in diff:
            ret['remove']['count'] += 1
            ret['remove']['size'] += diff['prev']['size']
            ret['remove']['list'].append({'file': diff['remove'], "size": diff['prev']['size']})
            ret['total']['size_diff'] -= diff['prev']['size']
        elif 'replace' in diff:
            if diff['prev'] < diff['value']:
                size = diff['value'] - diff['prev']
                ret['increase']['size'] += size
                ret['increase']['count'] += 1
                ret['increase']['list'].append({'file': diff['replace'][0:-5], "size": size})
            elif diff['prev'] > diff['value']:
                size = diff['prev'] - diff['value']
                ret['decrease']['size'] += size
                ret['decrease']['count'] += 1
                ret['decrease']['list'].append({'file': diff['replace'][0:-5], "size": size})
            ret['total']['size_diff'] += (diff['value'] - diff['prev'])

    total_size_diff_rate = float(now['total_size'] - base['total_size']) * \
            100.0 / float(base['total_size'])

    ret['total']['size_diff_rate'] = total_size_diff_rate

    ret['total']['size_diff_adjust'] = now['total_size'] - base['total_size']

    if ret['total']['size_diff'] > 0:
        ret['trendcy'] = 'increase'
    elif ret['total']['size_diff'] < 0:
        ret['trendcy'] = 'decrease'
    return ret

def dulplicated_resource_remover(res, assets):
    # TODO
    """

    """
    ret = {}

    return ret

def large_size_resources(path, empathy):
    """
    Find all the resources which size are larger than L{empathy}(KB).

    @param path: path of resources
    @type path: C{str}

    @param empathy: empathy, measured in KB
    @type empathy: C{int}

    @return all hit resources
    """

    """
    # Deprecated
    cmd = "du -sk `find %s -name '*.*' | grep -e '\(/res\)\|\(assets\)' | grep -v xml`  | sort -r -n | awk '{if ($1 >= %d) {print;}}'" % (path, empathy)
    output = os.popen(cmd)
    raw =  output.read()
    lines = raw.split('\n')
    ret = []
    for line in lines:
        if line == '':
            continue
        entries = line.split('\t')
        size = entries[0]
        filename = entries[1].split(path)[1].lstrip('/')
        ret.append({"size": size, "file": filename})
    """

    resources = _all_resources_and_assets(path)

    return _large_size_dectect(resources, empathy)

def large_size_dynamic_libraries(path, empathy):
    """
    Find all the resources which size are larger than L{empathy}(KB).

    @param path: path of resources
    @type path: C{str}

    @param empathy: empathy, measured in KB
    @type empathy: C{int}

    @return all hit resources
    """
    resources = _all_dynamic_libraries(path)

    return _large_size_dectect(resources, empathy)

def load_from_project(path):
    ret = {}
    ret['assets_and_resources'] = _all_resources_and_assets(path)
    print 'assets'
    ret['jar'] = _all_jar_files(path)
    print 'jar packages'
    ret['dynamic_so_libs'] = _all_dynamic_libraries(path)
    print 'dynamic libraries'

    return ret

def load_from_cache(path):
    ret = None
    with open(path) as f:
        ret = json.load(f)
    return ret

def save(**kwargs):
    """
    save assets, resources, java packages, dynamic libraries properties.
    """
    out_filename = kwargs['out_filename']
    out_path = kwargs['out_path']
    assets_and_resources = kwargs['assets_and_resources']
    jars = kwargs['jar']
    dynamic_so_libs = kwargs['so']

    filename = out_path + '/' + out_filename
    json_result = {}
    json_reuslt['assets_and_resources'] = assets_and_resources
    json_result['jar'] = jars
    json_result['dynamic_so_libs'] = dynamic_so_libs
    content = json.dumps(json_result)

    with open(filename, 'w') as f:
        f.write(content)

def report(**kwargs):
    """
    """
    resources_diff = kwargs['resources_diff']
    measure = 1024 if 'measure' not in kwargs else kwargs['measure']
    report_filename = 'report' if 'report_filename' not in kwargs else kwargs['report_filename']
    # FIXME
    title = u'android资源分析结果' if 'title' not in kwargs else kwargs['title']
    path = '.' if 'path' not in kwargs else kwargs['path']

    report_md_tpl = ""
    # FIXME
    with open("report_tpl.md") as f:
        report_md_tpl = f.read()

    var = []

    tmp = resources_diff['add']['count']
    var.append(tmp)
    tmp = resources_diff['add']['size']
    var.append(tmp)

    tmp = resources_diff['remove']['count']
    var.append(tmp)
    tmp = resources_diff['remove']['size']
    var.append(tmp)

    tmp = resources_diff['increase']['count']
    var.append(tmp)
    tmp = resources_diff['increase']['size']

    var.append(tmp)
    tmp = resources_diff['decrease']['count']
    var.append(tmp)
    tmp = resources_diff['decrease']['size']
    var.append(tmp)

    # FIXME
    tmp = '增加' if resources_diff['total']['size_diff'] > 0 else '减少'
    var.append(tmp)

    tmp = resources_diff['total']['size_diff']
    var.append(tmp)

    tmp = resources_diff['total']['size_diff_rate']
    var.append(tmp)

    # large resources
    large_resources = kwargs['large_resources']
    tpl = '''

        %s
        %s

    '''
    tmp = ''
    for res in large_resources:
        tmp += tpl % (res['file'], res['size'] / measure)
    var.append(tmp)

    # large dynamic libraries
    large_so_libs = kwargs['large_so_libs']
    tpl = '''

        %s
        %s

    '''
    tmp = ''
    for so in large_so_libs:
        tmp += tpl % (so['file'], so['size'] / measure)
    var.append(tmp)

    # similar jar packages
    similar_jars = kwargs['similar_jars']
    tpl = '''

        %s
        %s

    '''
    tmp = ''
    for jar in similar_jars['json']['list']:
        tmp += tpl % (jar['file'], jar['size'] / measure)
    var.append(tmp)

    report_md = report_md_tpl % tuple(var)

    report_md_path = path + '/' + report_filename + ".md"
    with open(report_md_path, 'w') as f:
        f.write(report_md)

    report_html_path = path + '/' + report_filename + '.html'

    export(path=report_md_path, out_filename = report_html_path, title = title)

redpajama_set_name: RedPajamaGithub


The Residences at Webster Square present a unique opportunity for high-rise condominium living in the heart of Lincoln Park. Featuring one- to four-bedroom residences, the 12-story building offers homeowners the luxury, convenience and service of a full-amenity building. Penthouse and combination units are also available. Webster Square is situated in one of Lincoln Park's most sought-after locations, offering homeowners unparalleled access to local shops, restaurants, recreation, and cultural attractions including the Lincoln Park Zoo and Steppenwolf Theater.


Genres: School Drama / Comedy?
Summary: A girl, who cares about nothing except her grades, ends up delivering class notes to a male classmate who become attached to her as his only friend.
Personal comments: It seems we have quite some in-your-face brutal humor styled comedies. I couldn't stop laughing throughout the first episode. Though it's mostly comedy, it is mixed with quite some dark scenes with some rather melancholy moments. It reminds me very much of Lovely Complex, except this is has a lot more of a take-no-prisoner brutality feel to it. In terms of character, it actually feels like gender reversed duo from Hyouka. This, in my opinion is definitely a keeper.


is fully accessible, delivers customer service excellence and provides added value.
UKAS will be impartial, agile and proactive in underpinning the national quality infrastructure, enabling the UK economy to thrive.
Is to continue to strengthen our operations teams, developing the capacity and capability to exceed the expectations of our customers and stakeholders and deliver accreditation services to the highest quality and technical standards.
We are continually optimising new technology to improve our open, collaborative customer and stakeholder relations, and to develop UKAS into an even more flexible organisation, with the capability and capacity to meet the increasing demand for accreditation.
The growth and diversification of UKAS has been built on core values that have underpinned our activities for many years.
These values are: Professionalism, Responsibility, Innovation, Delivery and Excellence which form the acronym: PRIDE.
These values set us apart from other organisations, requiring that we think and act differently, resulting in a clearly defined UKAS brand that is highly respected in the marketplace. They are imprinted in our DNA, making us who we are today and setting the foundation for the UKAS of the future.
UKAS core values are not about what we do, but the guiding principles behind how we interact with our customers. If these values resonate with you, then do visit our Careers section to find out about current opportunities.


The High Peaks Wilderness Complex and the Vanderwhacker Mountain Wild Forest Unit Management Plan (UMP) Amendments are final and implementation of the management actions has begun, New York State Department of Environmental Conservation (DEC) Commissioner Basil Seggos announced today.
Commissioner Seggos said, "Defining DEC's management of the Boreas Ponds and the more than 50,000 acres of land added to these two Adirondack Forest Preserve units will help protect these precious lands for future generations. We are excited to implement these management actions, which will facilitate access while ensuring these sensitive natural resources are protected. The final amendments to the Unit Management Plan announced today will improve accessibility while reinforcing DEC's commitment to preserving this unique resource and helping the town of North Hudson and the other communities in the Five Town Hub realize the economic potential of these lands. The amendments also define steps to manage these lands sustainability and address safety concerns while ensuring visitors can enjoy its breathtaking views and outstanding recreational opportunities."
DEC has begun implementing management actions described in the two UMP Amendments. Currently group size regulations for all of the High Peaks Wilderness, including the former Dix Mountain Wilderness lands, are in effect, limiting day use groups (hikers) to no more than 15 people and overnight use groups (campers) to no more than 8 people.
Construction of the Mt. Van Hoevenberg East Trail from the Olympics Sport Complex to the summit of the mountain is underway. DEC developed a sustainable route and design for the trail to provide an enjoyable experience for hikers, while protecting this resource. Adirondack Mountain Club Professional Trail Crews have been contracted to construct the trail. In addition, the project will include protections for vegetation and soils on the summit. To limit overuse, DEC is promoting hikes and activities in lesser used areas of the Adirondacks via the Adventure Adirondack social media channel.
The UMP Amendment also defines regulatory changes to the land throughout the unit and the lands added to the unit. Changes to the recreational infrastructure along State Route 73 to address safety and manage high use issues currently experienced in these areas are also described.
Both the High Peaks Wilderness UMP Amendment and the Vanderwhacker Wild Forest UMP Amendment are available on DEC's website to view or download.