Plots Designs And Schemes

Plots, Designs, and Schemes is the first study that investigates the long history of American conspiracy theories from the perspective of literary and cultural studies. Since research in these fields has so far almost exclusively focused on the contemporary period, the book concentrates on the time before 1960. Four detailed case studies offer close readings of the Salem witchcraft crisis of 1692, fears of Catholic invasion during the 1830s to 1850s, antebellum conspiracy theories about slavery, and anxieties about Communist subversion during the 1950s. The study primarily engages with factual texts, such as sermons, pamphlets, political speeches, and confessional narratives, but it also analyzes how fears of conspiracy were dramatized and negotiated in fictional texts, such as Nathaniel Hawthorne's Young Goodman Brown (1835) or Hermann Melville's Benito Cereno (1855). The book offers three central insights: 1. The American predilection for conspiracy theorizing can be traced back to the co-presence and persistence of a specific epistemological paradigm that relates all effects to intentional human action, the ideology of republicanism, and the Puritan heritage. 2. Until far into the twentieth century, conspiracy theories were considered a perfectly legitimate form of knowledge. As such, they shaped how many Americans, elites as well as “common” people, understood and reacted to historical events. The Revolutionary War and the Civil War would not have occurred without widespread conspiracy theories. 3. Although most extant research claims the opposite, conspiracy theories have never been as marginal and unimportant as in the past decades. Their disqualification as stigmatized knowledge only occurred around 1960, and coincided with a shift from theories that detect conspiracies directed against the government to conspiracies by the government.

This study investigates the long history of American conspiracy theories. Whereas most extant research claims that conspiracy theories have never been more widespread and influential than in the present, the book demonstrates that the opposite is the case. Until far into the twentieth century, conspiracy theories were considered a perfectly legitimate form of knowledge. They shaped how many Americans understood and reacted to historical events.

Association schemes are of interest to both mathematicians and statisticians and this book was written with both audiences in mind. For statisticians, it shows how to construct designs for experiments in blocks, how to compare such designs, and how to analyse data from them. The reader is only assumed to know very basic abstract algebra. For pure mathematicians, it tells why association schemes are important and develops the theory to the level of advanced research. This book arose from a course successfully taught by the author and as such the material is thoroughly class-tested. There are a great number of examples and exercises that will increase the book's appeal to both graduate students and their instructors. It is ideal for those coming either from pure mathematics or statistics backgrounds who wish to develop their understanding of association schemes.

Theory Conspiracy provides a state-of-the-art collection that takes stage on the meeting and/or battlegrounds between conspiracy theory and theory-asconspiracy. By deliberately scrambling the syntax—conspiracy theory cum theory conspiracy—it seeks to open a set of reflections on the articulation between theory and conspiracy that addresses how conspiracy might rattle the sense of theory as such. In this sense, the volume also inevitably stumbles on the recent debates on postcritique. The suspicion that our ways of reading in the humanities have been far too suspicious, if not paranoid, has gained considerable attention in a humanities continuously questioned as superfluous at best and leftist and dangerous at worst. The chapters in this volume all approach this problematic from different angles. It features clear engaging writing by a set of contributors who have published extensively on questions of paranoia, conspiracy theory, and/or the state of theory today. This collection will appeal to readers interested in conspiracy theories, critical theory, and the future of humanities.

‘Subdivision’ is a way of representing smooth shapes in a computer. A curve or surface (both of which contain an in?nite number of points) is described in terms of two objects. One object is a sequence of vertices, which we visualise as a polygon, for curves, or a network of vertices, which we visualise by drawing the edges or faces of the network, for surfaces. The other object is a set of rules for making denser sequences or networks. When applied repeatedly, the denser and denser sequences are claimed to converge to a limit, which is the curve or surface that we want to represent. This book focusses on curves, because the theory for that is complete enough that a book claiming that our understanding is complete is exactly what is needed to stimulate research proving that claim wrong. Also because there are already a number of good books on subdivision surfaces. The way in which the limit curve relates to the polygon, and a lot of interesting properties of the limit curve, depend on the set of rules, and this book is about how one can deduce those properties from the set of rules, and how one can then use that understanding to construct rules which give the properties that one wants.

This issue of The Ministry of the Word contains a complete record of the twelve messages given by webcast from Anaheim, California, as the December 2020 semiannual training on the crystallization-studies of the books of Job, Proverbs, and Ecclesiastes. The key statements in the following section embody and summarize the crucial truths and main burdens in these twelve messages. The Reports and Announcements section contains an update concerning Europe, reports from regions across Europe, and the winter 2020 mass distribution update. Also included is information concerning upcoming conferences and trainings hosted by Living Stream Ministry and a website link for information related to similar events in Europe.

The demand for comparable, long-term, high quality data on forest ecosystems' status and changes is increasing at the international and global level. Yet, sources for such data are limited and in many case it is not possible to compare data from different monitoring initiatives across space and time because of methodological differences. Apart from technical manuals, there is no comprehensive multidisciplinary, scientific, peer-reviewed reference for forest monitoring methods that can serve and support the user community. This book provides in a single reference the state-of-the-art of monitoring methods as applied at the international level. The book present scientific concepts and methods that form the basis of the transnational, long-term forest monitoring in Europe and looks at other initiatives at the global level. Standardized methods that have been developed over two decades in international forest monitoring projects are presented. Emphasis is put on trans-nationally harmonized methods, related data quality issues, current achievements and on remaining open questions. A comprehensive overview of needs, requirements, organization and possible outcomes of an integrated monitoring program Tested and quality assured, internationally harmonized methodologies based on a complete revision of existing methods carried out in 2009-2011 Connection with monitoring results allows assessment of the potential of the monitoring method

ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs and mixed models, which are common in many practical applications. Features Accessible to readers with a basic background in probability and statistics Covers fundamental concepts of experimental design and cause-effect relationships Introduces classical ANOVA models, including contrasts and multiple testing Provides an example-based introduction to mixed models Features basic concepts of split-plot and incomplete block designs R code available for all steps Supplementary website with additional resources and updates are available here. This book is primarily aimed at students, researchers, and practitioners from all areas who wish to analyze corresponding data with R. Readers will learn a broad array of models hand-in-hand with R, including the applications of some of the most important add-on packages.