This second edition explores how money 'works' in the modern economy and synthesises the key principles of Modern Money Theory, exploring macro accounting, currency regimes and exchange rates in both the USA and developing nations.
A selective review of modern decision science and implications for decision-support systems. The study suggests ways to synthesize lessons from research on heuristics and biases with those from "naturalistic research." It also discusses modern tools, such as increasingly realistic simulations, multiresolution modeling, and exploratory analysis, which can assist decisionmakers in choosing strategies that are flexible, adaptive, and robust.
Managing People in Sport Organizations provides a comprehensive overview of the theory and practice of managing people within a strategic framework. This revised and updated second edition examines a range of strategic human resource management approaches that can be used by sport organizations to respond to contemporary challenges and to develop a sustainable performance culture. Drawing on well-established conceptual frameworks and current empirical research, the book systematically covers every key area of HRM theory and practice, including: recruitment training and development performance management and appraisal motivation and reward organizational culture employee relations diversity managing change This new edition also includes expanded coverage of social media, volunteers, and individuals within organizations, and is supported with a new companion website carrying additional resources for students and instructors, including PowerPoint slides, exam questions and useful web links. No other book offers such an up-to-date introduction to core concepts and key professional skills in HRM in sport, and therefore Managing People in Sport Organizations is essential reading for any sport management student or any HR professional working in sport.
Mathematical Visualization is a young new discipline. It offers efficient visualization tools to the classical subjects of mathematics, and applies mathematical techniques to problems in computer graphics and scientific visualization. Originally, it started in the interdisciplinary area of differential geometry, numerical mathematics, and computer graphics. In recent years, the methods developed have found important applications. The current volume is the quintessence of an international workshop in September 1997 in Berlin, focusing on recent developments in this emerging area. Experts present selected research work on new algorithms for visualization problems, describe the application and experiments in geometry, and develop new numerical or computer graphical techniques.
The primary objective of this NATO Advanced Study Institute (ASI) was to present an up-to-date overview of various current areas of interest in the field of photovoltaic and related photoactive materials. This is a wide-ranging subject area, of significant commercial and environmental interest, and involves major contributions from the disciplines of physics, chemistry, materials, electrical and instrumentation engineering, commercial realisation etc. Therefore, we sought to adopt an inter disciplinary approach, bringing together recognised experts in the various fields while retaining a level of treatment accessible to those active in specific individual areas of research and development. The lecture programme commenced with overviews of the present relevance and historical development of the subject area, plus an introduction to various underlying physical principles of importance to the materials and devices to be addressed in later lectures. Building upon this, the ASI then progressed to more detailed aspects of the subject area. We were also fortunately able to obtain a contribution from Thierry Langlois d'Estaintot of the European Commission Directorate, describing present and future EC support for activities in this field. In addition, poster sessions were held throughout the meeting, to allow participants to present and discuss their current activities. These were supported by what proved to be very effective feedback sessions (special thanks to Martin Stutzmann), prior to which groups of participants enthusiastically met (often in the bar) to identify and agree topics of common interest.
At some point in their careers, virtually every scientist and technician, as well as many medical professionals, regardless of their area of specialization have a need to utilize cell culture systems. Updating and significantly expanding upon the previous editions, Basic Cell Culture Protocols, Fourth Edition provides the novice cell culturist with sufficient information to perform the basic techniques, to ensure the health and identity of their cell lines, and to be able to isolate and culture specialized primary cell types. The intent of this extensive volume is to generate a valuable resource containing clear methodologies pertinent to current areas of investigation, rather than attempting to educate cell culturists on specific cell types or organ systems. Written in the highly successful Methods in Molecular BiologyTM, 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. Comprehensive and up-to-date, Basic Cell Culture Protocols, Fourth Edition compiles the essential techniques needed to approach this vital laboratory activity with full success.
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers