Sport Education: International Perspectives presents a series of studies of the innovative pedagogical model that has taken the physical education world by storm. Since the emergence of the Sport Education model in the mid-1990s it has been adopted and adapted in physical education programs around the world and a new research literature has followed in its wake. This book offers a review of international Sport Education schemes and projects, and documents what it takes to run a successful Sport Education program. Exploring Sport Education across all levels of education, from the elementary school to the university, the book provides answers to key question such as: * What models have been developed to teach Sport Education? * What do successful SE programs look like? * What do teachers think about SE and how to make it work? * What are the implications for professional development across the range of human movement studies? With contributions from leading international scholars and practitioners from the US, Europe and Asia, this book offers a more thoughtful and critical set of perspectives on Sport Education than any other. It is essential reading for any student, pre-service teacher, classroom teacher or university instructor working in SE, PE, youth sport, sports coaching or related disciplines.

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of 1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.

New essays by outstanding European and American medievalists on major aspects of the most enduring medieval epic. The legend of Tristan and Isolde -- the archetypal narrative about the turbulent effects of all-consuming, passionate love -- achieved its most complete and profound rendering in the German poet Gottfried von Strassburg's verse romance Tristan (ca. 1200-1210). Along with his great literary rival Wolfram von Eschenbach and his versatile predecessor Hartmann von Aue, Gottfried is considered one of three greatest poets produced by medieval Germany, andover the centuries his Tristan has lost none of its ability to attract with the beauty of its poetry and to challenge -- if not provoke -- with its sympathetic depiction of adulterous love. The essays, written by a dozen leading Gottfried specialists in Europe and North America, provide definitive treatments of significant aspects of this most important and challenging high medieval version of the Tristan legend. They examine aspects of Gottfried'sunparalleled narrative artistry; the important connections between Gottfried's Tristan and the socio-cultural situation in which it was composed; and the reception of Gottfried's challenging romance both by later poets inthe Middle Ages and by nineteenth- and twentieth-century authors, composers, and artists -- particularly Richard Wagner. The volume also contains new interpretations of significant figures, episodes, and elements (Riwalin and Blanscheflur, Isolde of the White Hands, the Love Potion, the performance of love, the female figures) in Gottfried's revolutionary romance, which provocatively elevates a sexual, human love to a summum bonum. Will Hasty is Professor of German at the University of Florida. He is the editor of Companion to Wolfram's "Parzival," (Camden House, 1999). Click here to view the introduction (PDF file 83KB)

Originally published in 1980, this title came about after many late night discussions between the authors during a 3-week workshop on Mathematical Approaches to Person Perception in 1974. In subsequent meetings a mutual interest emerged in the development of cognitive information processing metaphors for human thought and their application to problems of social perception, memory and judgment. Within the context of modern research on social cognition, the most distinctive aspects of the authors' work was its empirical focus on how people cognitively represent people in memory, and its theoretical emphasis on models of cognitive organization and process. They concluded that an adequate theory of social memory was the necessary foundation for solutions to many questions concerning social perception and judgment that had dominated the 1974 workshop. This volume summarizes work conducted between 1974 and 1979 on social memory by these authors. In addition to six chapters summarizing individual research programs, the volume includes a general introduction and a concluding theoretical integration.

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.

This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for wide'' data (p bigger than n), including multiple testing and false discovery rates.

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Originally published in 1980, this title came about after many late night discussions between the authors during a 3-week workshop on Mathematical Approaches to Person Perception in 1974. In subsequent meetings a mutual interest emerged in the development of cognitive information processing metaphors for human thought and their application to problems of social perception, memory and judgment. Within the context of modern research on social cognition, the most distinctive aspects of the authors' work was its empirical focus on how people cognitively represent people in memory, and its theoretical emphasis on models of cognitive organization and process. They concluded that an adequate theory of social memory was the necessary foundation for solutions to many questions concerning social perception and judgment that had dominated the 1974 workshop. This volume summarizes work conducted between 1974 and 1979 on social memory by these authors. In addition to six chapters summarizing individual research programs, the volume includes a general introduction and a concluding theoretical integration.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

We live in a world that is ever on the move, as is increasingly recognised within research on mobilities. Yet studies of mobility have failed to 'go to sea' with the same enthusiasm as mobilities ashore. When we consider mobility, we most often examine those movements that evidently form part of our everyday lives. We forget to look outwards to the sea. Yet ships have played - and continue to play - a significant role in shaping socio-cultural, political and economic life. This book turns our attention to the manifold mobilities that occur at sea through an exploration of the mobilities of ships themselves as well as the movements of objects, subjects and ideas that are mobilised by ships. The Mobilities of Ships brings together seven chapters that tack through unexplored waters and move between diverse case studies, including pirate ships, naval vessels and luxury yachts. In so doing, The Mobilities of Ships offers a rich insight into the world of shipping mobilities past and present. This book was published as a special issue of Mobilities.

Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.

We live in a world that is ever on the move, as is increasingly recognised within research on mobilities. Yet studies of mobility have failed to 'go to sea' with the same enthusiasm as mobilities ashore. When we consider mobility, we most often examine those movements that evidently form part of our everyday lives. We forget to look outwards to the sea. Yet ships have played - and continue to play - a significant role in shaping socio-cultural, political and economic life. This book turns our attention to the manifold mobilities that occur at sea through an exploration of the mobilities of ships themselves as well as the movements of objects, subjects and ideas that are mobilised by ships. The Mobilities of Ships brings together seven chapters that tack through unexplored waters and move between diverse case studies, including pirate ships, naval vessels and luxury yachts. In so doing, The Mobilities of Ships offers a rich insight into the world of shipping mobilities past and present. This book was published as a special issue of Mobilities.

A secret school hidden in the deep forests of Northern Ireland is protected by an ancient powerful magick. But an evil presence lurks in the forest. A portal to another dark realm was cracked and sinister energy is leaking through, killing everything that surrounds it. A group of eleven special children of Blackhill Manor face a race against time to develop their magickal powers, and stop the destruction from spreading. They will need the power of an ancient dagger called the Athame. The crystals that power it are missing and they must be found. Can twelve-year-old Luna Green lead the new Guardians of the Athame to find the missing crystals in time to protect the world from the Shadow Walkers and the darkness that will be unleashed?

This book takes the reader through the various aspects of a career in general practice from the time of applying to medical school until retirement. It will be a practical guide for anyone who is interested in the profession.

There have been a lot of changes to medical careers over the last few years that are now coming to completion, making this a thoroughly up to date guide for all those thinking of going into general practice.

This study aims to foreground key literary works in Persian and Australian culture that deal with the representation of exile and dislocation. Through cultural and literary analysis, Dislocation, Writing, and Identity in Australian and Persian Literature investigates the influence of dislocation on self-perception and the remaking of connections both through the act of writing and the attempt to transcend social conventions. Examining writing and identity in David Malouf's An Imaginary Life (1978), Iranian Diaspora Literature, and Shahrnush Parsipur's Women Without Men (1989/ Eng.1998), Hasti Abbasi provides a literary analysis of dislocation, with its social and psychological manifestations. Abbasi reveals how the exploration of exile/dislocation, as a narrative that needs to be investigated through imagination and meditation, provides a mechanism for creative writing practice.

This volume provides a thorough overview of the Wilms' Tumour Gene (WT1). The book begins with three review chapters that cover the involvement of WT1 in pediatric cancer, kidney disease, and tissue development and homeostasis. The next few chapters discuss cell marking and lineage tracing, epicardial cell methodology, colony forming assays for bone marrow stem cells, angiogenesis assays and zebrafish tools. The next group of chapters explores the latest tools in genomics, molecular biology, and biochemistry. They discuss dissecting transcription factor function in cell free systems, ChiP seq, proteomics, RNA interactome, and multiphoton imaging of lipids, measuring the binding constants of protein-nucleic acid interactions, and bioinformatics approaches for analyzing Next Generation Sequence data. The final chapter discusses protocols for clinical trials for immune therapy using anti-WT1 peptides. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Practical and thorough, The Wilms' Tumour (WT1) Gene: Methods and Protocols is a valuable resource for anyone who is interested in the diverse methodologies used in WT1 research.

This volume provides a thorough overview of the Wilms' Tumour Gene (WT1). The book begins with three review chapters that cover the involvement of WT1 in pediatric cancer, kidney disease, and tissue development and homeostasis. The next few chapters discuss cell marking and lineage tracing, epicardial cell methodology, colony forming assays for bone marrow stem cells, angiogenesis assays and zebrafish tools. The next group of chapters explores the latest tools in genomics, molecular biology, and biochemistry. They discuss dissecting transcription factor function in cell free systems, ChiP seq, proteomics, RNA interactome, and multiphoton imaging of lipids, measuring the binding constants of protein-nucleic acid interactions, and bioinformatics approaches for analyzing Next Generation Sequence data. The final chapter discusses protocols for clinical trials for immune therapy using anti-WT1 peptides. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Practical and thorough, The Wilms' Tumour (WT1) Gene: Methods and Protocols is a valuable resource for anyone who is interested in the diverse methodologies used in WT1 research.

As seen in Netflix's Chef's Table, acclaimed chef Lennox Hastie teaches you how to train your senses and instincts to respond to fire — and how different ingredients react to it — to perfect the art of cooking with flame.  A world expert in cooking with fire, Hastie is a masterful guide to how important the fire itself is. His narrative and step-by-step instructions explain the '6 stages of fire', the varying properties of types of wood and the optimum temperatures required to get the best out different ingredients. He also references the diverse methods used by different cultures over the centuries that have influenced the way we cook today. Interwoven through this instructional text, are over 90 recipes for seafood, vegetables, meat and desserts, where he puts theory into practice and shows you how to get the very best result for each dish. The recipes themselves are simple and intended to help you master different techniques and ingredients with delicious results. Far more than a barbecue cookbook, Finding Fire is an inspiring journey to mastering the art of cooking over a wood fire.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

When an old adversary threatens Rome, the city calls once more on her hero and defender: Coriolanus. But famine threatens the city, the citizens' hunger swells to an appetite for change, and on returning from the field Coriolanus must confront the march of realpolitik and the voice of an angry people. This is one of Shakespeare's last tragedies, best known for its political and military themes. Shakespeare's searing play of political manipulation and revenge is here abridged and this version was first produced at the Donmar Warehouse, London, directed by Josie Rourke and with Tom Hiddleston in the title role. The script has been edited and abridged by Rob Hastie and Josie Rourke.

As research emerges on the effectiveness of psychological therapies for bipolar disorder, this is the first manual guiding the treatment of those in adolescence and early adulthood, taking into account the developmental issues which can have significant impact on therapeutic outcomes. Core issues covered include engagement difficulties, how cognitive therapy should be adapted for adolescents, the impact of the disorder on the person's psychosocial development, managing comorbidity (particularly alcohol and substance use), medication adherence, the impact of family dynamics, and issues around control and independence in the therapeutic relationship. The manual is illustrated with case studies and text boxes describing tips and techniques for the therapist. Providing clear clinical guidance, backed by an extensive literature review and theoretical overview, this is essential reading for all mental health specialists implementing psychological interventions for young people with bipolar disorder.

Conference Overview and the Role of Chemistry in High-Temperature Materials Science and Technology LEO BREWER Department of ChemistIy, University of California, and Materials and Chemical Sciences Division, Lawrence Berkeley Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 I don't want to compete with the fascinating historic account that John Drowart gave us, but I would like to go through the history of high don't get the reaction that I get from temperature symposia. I hope I some of my classes when I say, "Remember when such-and-such hap pened during the War?" And I get this blank look, and one of the students will say, "I wasn't born until after the Korean War. " Neverthe less, during World War II, many people in the high-temperature field had their first initiation. But there was one handicap. Owing to security measures, they were not able to interact with one another. Following the War, it was recognized that the high-temperature field was going to expand to meet the demands for materials with unique properties. To meet the demands for new fabrication techniques, it was important to establish better communications among various people. High-tempera ture symposia were established at that time and have continued very frequently, and I'd like to point out why they are especially important for this field. One problem is that it is not easy to work at high temperatures.