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Studying the complex physical systems of stellar jets necessitates the incorporation of nonlinear effects which occur on a wide variety of length and timescales. One of the primary methods used to study the physics of jets is numerical simulations that apply high performance computing techniques. Such techniques are also required for analysing the huge modern astrophysical datasets. This book examines those computing techniques. It is a collection of the lectures from the fifth and final school of the JETSET network, "Jets From Young Stars V: High Performance Computing in Astrophysics." It begins with an introduction to parallel programming techniques, with an emphasis on Message Passing Interface (MPI), before it goes on to review grid technology techniques and offer a practical introduction to Virtual Observatory. The second half of the book, then, is devoted to applications of high performance computing techniques, including 3D radiation transfer, to jet and star formation processes. Aimed at graduate students in astrophysics, this book presents state-of-the-art methods, thereby offering interesting new insights to researchers in the field.
This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
In Environment, Trade and Society in Southeast Asia: A Longue Durée Perspective, eleven historians bring their knowledge and insights to bear on the long Braudelian sweep of Southeast Asian history. In doing so they seek both to debunk simplistic assumptions about fragile traditions and transformational modernities, and to identify real repeating patterns in Southeast Asia's past: clientelistic political structures, periodic tectonic and climatic disasters, ethnic occupational specializations, long cycles of economic globalization and deglobalization. Their contributions range across many centuries: from the Austronesian expansion to the Aceh tsunami, and from the Sanskrit cosmopolis to the Asian financial crisis. The book is inspired by, and dedicated to, Peter Boomgaard, a scholar whose work has embodied the Braudelian spirit in Southeast Asian historiography. This title is available online in its entirety in Open Access.
This review of the most up-to-date observational and theoretical information concerning the chemical evolution of the Milky Way compares the abundances derived from field stars and clusters, giving information on the abundances and dynamics of gas.