Interactions of Degree and Quantification is a collection of chapters edited by Peter Hallman that deal with superlative, equative and differential constructions cross-linguistically, interactions of the comparative with both individual quantifiers and event structure, the use of the individual quantifier ‘some’ as a numeral, and the question of whether the very notion of ‘degree’ is reducible to a relation between individuals. These issues all represent semantic parallels and interactions between individual quantifiers (every, some, etc.) and degree quantifiers (more, most, numerals, etc.) in the expression of quantity and measurement. The contributions presented here advance the analytical depth and cross-linguistic breadth of the state of the art in semantics and its interface with syntax in human language.

This Handbook provides a compendium of research methods that are essential for studying interaction and communication across the behavioral sciences. Focusing on coding of verbal and nonverbal behavior and interaction, the Handbook is organized into five parts. Part I provides an introduction and historic overview of the field. Part II presents areas in which interaction analysis is used, such as relationship research, group research, and nonverbal research. Part III focuses on development, validation, and concrete application of interaction coding schemes. Part IV presents relevant data analysis methods and statistics. Part V contains systematic descriptions of established and novel coding schemes, which allows quick comparison across instruments. Researchers can apply this methodology to their own interaction data and learn how to evaluate and select coding schemes and conduct interaction analysis. This is an essential reference for all who study communication in teams and groups.

The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.

Over time the field of artificial intelligence has developed an "agent perspective" expanding its focus from thought to action, from search spaces to physical environments, and from problem-solving to long-term activity. Originally published as a special double volume of the journal Artificial Intelligence, this book brings together fundamental work by the top researchers in artificial intelligence, neural networks, computer science, robotics, and cognitive science on the themes of interaction and agency. It identifies recurring themes and outlines a methodology of the concept of "agency." The seventeen contributions cover the construction of principled characterizations of interactions between agents and their environments, as well as the use of these characterizations to guide analysis of existing agents and the synthesis of artificial agents.Artificial Intelligence series.Special Issues of Artificial Intelligence

Research progress in soil–root growth interactions has been slow due to the relative inaccessibility of roots in their natural environment and because root research cuts across the boundaries of soil science, ecology, crop science, and plant physiology, among others. Enhancing Understanding and Quantification of Soil–Root Growth Interactions takes on this challenge to solve society's growing problems in the conservation of quality water and soil resources. Researchers must come together and leverage our understanding of the rhizosphere to maximize efficient, sustainable use of limited water and soil nutrient resources. This is a serious calling—from addressing the critical needs in nations who cannot afford costly fertilizers, to the global challenge of enhancing soil carbon storage to reduce climate change effects of elevated carbon dioxide. This book brings together scientists from different disciplines, worldwide, together to encourage synthesis of transdisciplinary knowledge and further research and developments in the area of root–soil interactions.

Polarity (positive, negative) is one of the most fundamental concepts in the system of language and there are many expressions that are sensitive to polarity. For example, any in English and wh-mo in Japanese appear in negative contexts, but not in positive contexts. While previous studies have shown that polarity-sensitive expressions are a general phenomenon in languages, it has also become clear that there are variations in polarity-sensitive expressions. This volume explores the variations in polarity-sensitive expressions through comparisons between Japanese and other languages, such as English, German, Spanish, and Old Japanese, and examines the environments and contexts in which polarity-sensitive expressions occur, as well as the types of (cross-linguistic) variation allowed. The value of the present volume lies in its inclusion of research papers inquiring into various types of polarity-sensitive expressions, such as negative-, positive-, and discourse-sensitive polarity items as well as their variations. The research indicates new directions for the study of polarity-sensitive expressions in the fields of syntax, semantics, pragmatics, historical linguistics, corpus linguistics and psycholinguistics.

This book reports on the latest advances in complex and nonlinear cardiovascular physiology aimed at obtaining reliable, effective markers for the assessment of heartbeat, respiratory, and blood pressure dynamics. The chapters describe in detail methods that have been previously defined in theoretical physics such as entropy, multifractal spectra, and Lyapunov exponents, contextualized within physiological dynamics of cardiovascular control, including autonomic nervous system activity. Additionally, the book discusses several application scenarios of these methods. The text critically reviews the current state-of-the-art research in the field that has led to the description of dedicated experimental protocols and ad-hoc models of complex physiology. This text is ideal for biomedical engineers, physiologists, and neuroscientists. This book also: Expertly reviews cutting-edge research, such as recent advances in measuring complexity, nonlinearity, and information-theoretic concepts applied to coupled dynamical systems Comprehensively describes applications of analytic technique to clinical scenarios such as heart failure, depression and mental disorders, atrial fibrillation, acute brain lesions, and more Broadens readers' understanding of cardiovascular signals, heart rate complexity, heart rate variability, and nonlinear analysis

This book brings together chapters on the semantics and pragmatics of measurement, scales, and numerical expressions. The chapters highlight recent developments in measurement theory, the meaning of numerical expressions and the relation between measurement scales and entailment scales. The authors provide explorations in formal and experimental semantics and pragmatics, as well as at the interfaces of this field with others including philosophy of language and sociolinguistics. This book will be of interest to students and scholars in these areas, as well as psychology, psycholinguistics and artificial intelligence.

Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty

Affective Computing is a growing multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and many other disciplines. It explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems that intricately involve affect at their core. The Oxford Handbook of Affective Computing will help both new and experienced researchers identify trends, concepts, methodologies, and applications in this burgeouning field. The volume features 41 chapters divided into five main sections: history and theory, detection, generation, methodologies, and applications. Section One begins with a look at the makings of AC and a historical review of the science of emotion. Chapters discuss the theoretical underpinnings of AC from an interdisciplinary perspective involving the affective, cognitive, social, media, and brain sciences. Section Two focuses on affect detection or affect recognition, which is one of the most commonly investigated areas in AC. Section Three examines aspects of affect generation including the synthesis of emotion and its expression via facial features, speech, postures and gestures. Cultural issues in affect generation are also discussed. Section Four features chapters on methodological issues in AC research, including data collection techniques, multimodal affect databases, emotion representation formats, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues in AC. Finally, Section Five highlights existing and future applications of AC in domains such as formal and informal learning, games, robotics, virtual reality, autism research, healthcare, cyberpsychology, music, deception, reflective writing, and cyberpsychology. With chapters authored by world leaders in each area, The Oxford Handbook of Affective Computing is suitable for use as a textbook in undergraduate or graduate courses in AC, and will serve as a valuable resource for students, researchers, and practitioners across the globe.