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Artists --- Mexico --- Regions & Countries - Americas --- History & Archaeology --- Biography. --- Jackson, Everett Gee, --- Social life and customs.

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After a tumultuous career as a revolutionary in Ireland and an ultra-conservative Catholic in the United States, Thomas D'Arcy McGee moved to Canada in 1857, where he became a force for moderation and the leading Irish Canadian politician in the country. Determined that Canada should avoid the ethno-religious strife that afflicted Ireland, he articulated an inclusive, broad-minded nationalism based on generosity of spirit, a willingness to compromise, and a reasonable balance between order and liberty. To realize his vision, McGee became a strong supporter of the "new northern nationality." A spellbinding orator who emerged as the youngest and most intellectually gifted of the Fathers of Confederation, he fought what he saw as the atavistic and intolerant elements of Canadian life - the Orange Order, with its strident anti-Catholicism; the opponents of separate schools, whom he viewed as enemies of minority rights; and above all the Fenian Brotherhood, with its dreams of revolutionizing Ireland and annexing Canada to the United States. Convinced that compromise with Fenianism was impossible, he set out to destroy the movement through a strategy of confrontation and polarization - channeling his earlier extreme tendencies in the service of moderation and attempting to reduce the influence of Fenianism within his own community. In the process, he alienated many of his former supporters, who came to regard him as a traitor who sacrificed the cause of Irish nationalism on the altar of personal ambition. On 7 April 1868, McGee was assassinated on the doorstep of his Ottawa boarding house. As someone who took an uncompromising stand against militants within his own ethno-religious community, and who attempted to balance core values with minority rights, McGee has become increasingly relevant in today's complex multicultural society.

Politicians --- McGee, Thomas D'Arcy, --- MacGee, Thomas d'Arcy --- M'Gee, Thomas d'Arcy --- D'Arcy McGee --- M'Gee, Thomas Darcy --- McGee, Thomas d'Arcy --- Darcy McGee, Thomas --- Canada --- Politics and government --- History

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"Discourse and Digital Practices shows how tools from discourse analysis can be used to help us understand new communication practices associated with digital media, from video gaming and social networking to apps and photo sharing. Fourteen eminent scholars including James Paul Gee and Camilla Vasquez address the challenges of working with digital texts and interactions, and illustrate how different approaches to discourse analysis can be adapted in the face of these new digital practices. This cutting-edge book will be of interest to advanced students studying courses on digital literacies or language and digital practices"-- "Discourse and Digital Practices shows how tools from discourse analysis can be used to help us understand new communication practices associated with digital media, from video gaming and social networking to apps and photo sharing. This cutting-edge book:draws together fourteen eminent scholars in the field including James Paul Gee, David Barton, Ilana Snyder, Phil Benson, Victoria Carrington, Guy Merchant, Camilla Vasquez, Neil Selwyn and Rodney Jonesaddresses the central question: "How does discourse analysis enable us to understand digital practices?"demonstrates how digital practices and the associated new technologies challenge discourse analysts to adapt traditional analytic tools and formulate new theories and methodologiesanalyses a different type of digital media in each chapterexamines digital practices from a wide variety of approaches including textual analysis, conversation analysis, interactional sociolinguistics, multimodal discourse analysis, object ethnography, geosemiotics, and critical discourse analysis. Discourse and Digital Practices will be of interest to advanced students studying courses on digital literacies or language and digital practices"--

Discourse analysis --- Technological innovations --- Digital --- Social media --- Data processing --- Discoursanalyse --- Technologische innovaties --- Discoursanalyse en de digitale wereld --- Sociale netwerken --- Technological innovations. --- Digital. --- Social media. --- Data processing. --- gegevensverwerking --- taalgebruik --- Discoursanalyse. --- Technologische innovaties. --- Discoursanalyse en de digitale wereld. --- gegevensverwerking. --- taalgebruik. --- Gegevensverwerking. --- Taalgebruik. --- Digital media. --- Discourse analysis - Data processing --- Alice Chik --- Camilla Vasquez --- Christoph Hafner --- conversation analysis --- David Barton --- digital literacies --- discourse and digital literacies --- discourse and digital practices --- discourse and new media --- Guy Merchant --- Ilana Snyder --- interactional sociolinguistics --- James Paul Gee --- James Paul Gee digital literacies --- language and digital literacies --- language and new media --- language and social media --- multimodal discourse analysis --- Neil Selwyn --- object ethnography --- Phil Benson --- Rodney Jones --- semiotics --- textual analysis --- Victoria Carrington

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Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too restrictive for many problems. Therefore, the main goal of this book is to give a systematic presentation of the original generalized estimating equations (GEE) and some of its further developments. Subsequently, the emphasis is put on the unification of various GEE approaches. This is done by the use of two different estimation techniques, the pseudo maximum likelihood (PML) method and the generalized method of moments (GMM). The author details the statistical foundation of the GEE approach using more general estimation techniques. The book could therefore be used as basis for a course to graduate students in statistics, biostatistics, or econometrics, and will be useful to practitioners in the same fields.

Generalized estimating equations. --- Models, Statistical. --- Public welfare. --- Statistics as Topic -- methods. --- Generalized estimating equations --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Estimation theory. --- Estimating techniques --- Estimating equations, Generalized --- Equations, Generalized estimating --- GEE (Statistics) --- Statistics. --- Statistical Theory and Methods. --- Least squares --- Mathematical statistics --- Stochastic processes --- Correlation (Statistics) --- Linear models (Statistics) --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics

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In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.

multiple cancer types --- integrative analysis --- omics data --- prognosis modeling --- classification --- gene set enrichment analysis --- boosting --- kernel method --- Bayes factor --- Bayesian mixed-effect model --- CpG sites --- DNA methylation --- Ordinal responses --- GEE --- lipid–environment interaction --- longitudinal lipidomics study --- penalized variable selection --- convolutional neural networks --- deep learning --- feed-forward neural networks --- machine learning --- gene regulatory network --- nonparanormal graphical model --- network substructure --- false discovery rate control --- gaussian finite mixture model --- clustering analysis --- uncertainty --- expectation-maximization algorithm --- classification boundary --- gene expression --- RNA-seq --- n/a --- lipid-environment interaction