Handbook of Labor Economics is presented in 3 volume set. Preliminary. Perspectives on the past and prospects for the future: An American perspective. Perspectives on the past and prospects for the future: A European perspective (R. Layard, S. Nickell). New empirical methods in labor economics (J. Angrist, A. Krueger). Institutions and laws in the labor market (F. Blau, L. Kahn). New developments in econometric studies of labor markets (R. Moffitt). New evidence from matched employer-employee micro European data (J. Abowd, F. Kramarz). Game theoretic models in labor economics (M. Meyer). Inequality in the labor market (L. Katz). Intergenerational mobility in the labor market (G. Solon). Economics of migration (G. Borjas). Economics of the minimum wage (C. Brown). New developments in the economics of schooling (D.E. Card). Economic analysis of training programs (R.J. LaLonde). Macroeconomics and the labor market (R.H Topel). Microeconomic perspectives on the macroeconomic labor market (G. Bertola). New developments in the theory of discrimination (G. Loury). New developments in the economics of gender and race in the labor market (J. Altonji, R. Blank). Internal labor markets and the economics of personnel (R. Gibbons, M. Waldman). The relationship between firm size and wages (W. Oi). New developments in the economic analysis of retirement (O. Mitchell, R. Lumsdaine). Health issues and the labor market (J. Currie, B.C. Madrian). New developments in the study of labor supply (R. Blundell). A new survey of labor supply findings (T. MaCurdy). Pay, performance and executive compensation (K.J. Murphy). Labor markets in the transitional Eastern European Economies (J. Svejnar). Labor markets in developing countries (J. Behrman). Crime and the labor market (R. Freeman). Economic analysis of programs to support the injured and disabled (J. Bound, R. Burkhauser). New developments in the study of contracts in the labor market (J.M. Malcomson). New developments in the public sector labor market (J. Borland, R. Gregory). Layoffs, downsizing and the length of jobs (H. Farber). Job creation and job destruction at the firm level (S. Davis, J. Haltiwanger). Labor market impacts of international trade (G. Johnson, F. Stafford). Causes and consequences of long-term unemployment in European labor markets (S. Machin, A. Manning). New developments in models of search in the labor market (D.T. Mortensen, C.A. Pissarides).

«The aim of this volume is to provide an introduction and selective overview of the rapidly emerging field of computational economics. Computational economics provides an important set of tools that an increasing number of economists will need to acquire in order to understand and do state-of-the-art research in virtually all areas of economics. Articles in the volume range from very applied, policy oriented applications of computational methods, to highly theoretical and mathematically complex analyses of algorithms and numerical methods. The book emphasizes the unique contributions of computational methods in economics, and focuses on problems for which well developed solutions are not already available from the literature in operations research, numerical methods, and computer science. As well as covering relatively mature areas in the field, a number of chapters are included which cover more speculative «frontier topics», in particular recently discovered computational innovations and research results.»

Fundamentals of Cognitive Neuroscience, winner of a 2013 Most Promising New Textbook Award from the Text and Academic Authors Association, offers a comprehensive and easy-to-follow guide to cognitive neuroscience. Chapters in this introductory text cover all aspects of the field?the neural framework, sight, sound, consciousness, learning/memory, problem solving, speech, executive control, emotions, socialization and development?in a student-friendly format with extensive pedagogy and ancillaries to aid both the student and professor. Throughout the text, case studies and everyday examples are used to help students understand the more challenging aspects of the material. Written by two leading experts in the field, the text takes a unique thematic approach, guiding students along a clear path to understand the latest findings whether or not they have a background in neuroscience.

Computer Networks: A Systems Approach, Fifth Edition, discusses the key principles of computer networking. It focuses on the underlying concepts and technologies that make the Internet work. Topics covered include network design and architecture; the ways users can connect to a network; the concepts of switching, routing, and internetworking; end-to-end protocols; congestion control and resource allocation; end-to-end data; network security; and network applications such as e-mail and the Web, IP telephony and video streaming, and peer-to-peer file sharing. Each chapter includes a problem statement, which introduces issues to be examined; shaded sidebars that elaborate on a topic or introduce a related advanced topic; What’s Next? discussions that deal with emerging issues in research, the commercial world, or society; and exercises. This book is written for graduate or upper-division undergraduate classes in computer networking. It will also be useful for industry professionals retraining for network-related assignments, as well as network practitioners seeking to understand the workings of network protocols and the big picture of networking.

There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. Included are step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs. This book is intended for first-year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Knowledge of algebra and basic calculus is a prerequisite.

Brain Mapping: A Comprehensive Reference offers foundational information for students and researchers across neuroscience. With over 300 articles and a media rich environment, this resource provides exhaustive coverage of the methods and systems involved in brain mapping, fully links the data to disease (presenting side by side maps of healthy and diseased brains for direct comparisons), and offers data sets and fully annotated color images. Each entry is built on a layered approach of the content – basic information for those new to the area and more detailed material for experienced readers. Edited and authored by the leading experts in the field, this work offers the most reputable, easily searchable content with cross referencing across articles, a one-stop reference for students, researchers and teaching faculty.