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Defending society against natural hazards is a high-stakes game of chance against nature. Recent hurricanes, earthquakes, and tsunamis show that society often does poorly. Sometimes nature surprises us, when an earthquake, hurricane, or flood is bigger or has greater effects than expected from detailed natural hazard assessments. In other cases,...

This book uses insights from the cognitive sciences to illuminate Kafka's poetics, exemplifying a paradigm for literary studies in which cognitive-scientific insights are brought to bear directly on literary texts. The volume shows that the concept of "cognitive realism" can be a critically productive framework for exploring how textual evocations...

In two volumes - available individually and as a set - the Textbook of Neural Repair and Rehabilitation provides comprehensive coverage of the science and practice of neurological rehabilitation. Volume 1 - Neural Repair and Plasticity - covers the basic sciences relevant to recovery of function following injury to the nervous system. Volume 2 -...

More than ever before, there is widespread interest in studying bumble bees and the critical role they play in our ecosystems. Bumble Bees of North America is the first comprehensive guide to North American bumble bees to be published in more than a century. Richly illustrated with color photographs, diagrams, range maps, and graphs of seasonal...

The study of geometric discrepancy, which provides a framework for quantifying the quality of a distribution of a finite set of points, has experienced significant growth in recent decades. This book provides a self-contained course in number theory, Fourier analysis and geometric discrepancy theory, and the relations between them, at the advanced...

Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In...