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This book proves some important new theorems in the theory of canonical inner models for large cardinal hypotheses, a topic of central importance in modern set theory. In particular, the author 'completes' the theory of Fine Structure and Iteration Trees (FSIT) by proving a comparison theorem for mouse pairs parallel to the FSIT comparison theorem for pure extender mice, and then using the underlying comparison process to develop a fine structure theory for strategy mice. Great effort has been taken to make the book accessible to non-experts so that it may also serve as an introduction to the higher reaches of inner model theory. It contains a good deal of background material, some of it unpublished folklore, and includes many references to the literature to guide further reading. An introductory essay serves to place the new results in their broader context. This is a landmark work in inner model theory that should be in every set theorist's library.
This book proves some important new theorems in the theory of canonical inner models for large cardinal hypotheses, a topic of central importance in modern set theory. In particular, the author 'completes' the theory of Fine Structure and Iteration Trees (FSIT) by proving a comparison theorem for mouse pairs parallel to the FSIT comparison theorem for pure extender mice, and then using the underlying comparison process to develop a fine structure theory for strategy mice. Great effort has been taken to make the book accessible to non-experts so that it may also serve as an introduction to the higher reaches of inner model theory. It contains a good deal of background material, some of it unpublished folklore, and includes many references to the literature to guide further reading. An introductory essay serves to place the new results in their broader context. This is a landmark work in inner model theory that should be in every set theorist's library.
This is an expository account of work on strong forms of the Axiom of Determinacy (AD) by a group of set theorists in Southern California, in particular by W. Hugh Woodin. The first half of the book reviews necessary background material, including the Moschovakis Coding Lemma, the existence of strong partition cardinals, and the analysis of pointclasses in models of determinacy. The second half of the book introduces Woodin's axiom system $mathrm{AD}^{+}$ and presents his initial analysis of these axioms. These results include the consistency of $mathrm{AD}^{+}$ from the consistency of AD, and its local character and initial motivation. Proofs are given of fundamental results by Woodin, Martin, and Becker on the relationships among AD, $mathrm{AD}^{+}$, the Axiom of Real Determinacy, and the Suslin property. Many of these results are proved in print here for the first time. The book briefly discusses later work and fundamental questions which remain open. The study of models of $mathrm{AD}^{+}$ is an active area of contemporary research in set theory. The presentation is aimed at readers with a background in basic set theory, including forcing and ultrapowers. Some familiarity with classical results on regularity properties for sets of reals under AD is also expected.
The author develops the theory of Hod mice below ADR+ "Θ is regular". He uses this theory to show that HOD of the minimal model of ADR+ "Θ is regular" satisfies GCH. Moreover, he shows that the Mouse Set Conjecture is true in the minimal model of ADR+ "Θ is regular".
Originally published in 1978, the papers in this book derive from a 1976 meeting sponsored by the Social Science Research Council to discuss the nature and principles of category formation. It is organized in three sections: real-world categories, the cognitive processes underlying categorization, and the nature of representation. Part I examines different structural aspects of real-world categories: folk biological taxonomies, within and between category structures for material objects, and some categories in a language that codes the world in a visual–gestural mode. All three chapters in Part I assume category processors who are able to perform at least three cognitive functions: They can judge similarity between stimuli; they can perceive and process the attributes of a stimulus; and they can learn. Part II presents analyses of these three cognitive functions. All discussion of psychological structures and processes lead eventually to the issue of representation, and Part III examines representational assumptions underlying the earlier discussions. Today it can be read and enjoyed in its historical context.

Taylor & Francis Group

Published: 2010-12-31

Total Pages: 1732


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This volume contains about 40 papers covering many of the latest developments in the fast-growing field of bioinformatics. The contributions span a wide range of topics, including computational genomics and genetics, protein function and computational proteomics, the transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications. Abstracts from the keynote addresses and invited talks are also included.The papers not only cover theoretical aspects of bioinformatics but also delve into the application of new methods, with input from computation, engineering and biology disciplines. This multidisciplinary approach to bioinformatics gives these proceedings a unique viewpoint of the field./a
This volume contains about 40 papers covering many of the latest developments in the fast-growing field of bioinformatics. The contributions span a wide range of topics, including computational genomics and genetics, protein function and computational proteomics, the transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications. Abstracts from the keynote addresses and invited talks are also included. The papers not only cover theoretical aspects of bioinformatics but also delve into the application of new methods, with input from computation, engineering and biology disciplines. This multidisciplinary approach to bioinformatics gives these proceedings a unique viewpoint of the field. Sample Chapter(s). Chapter 1: Whole-Genome Analysis of Dorsal Gradient Thresholds in the Drosophila Embryo (102 KB). Contents: Learning Predictive Models of Gene Regulation (C Leslie); Algorithms for Selecting Breakpoint Locations to Optimize Diversity in Protein Engineering by Site-Directed Protein Recombination (W Zheng et al.); Cancer Molecular Pattern Discovery by Subspace Consensus Kernel Classification (X Han); Transcriptional Profiling of Definitive Endoderm Derived from Human Embryonic Stem Cells (H Liu et al.); A Markov Model Based Analysis of Stochastic Biochemical Systems (P Ghosh et al.); Clustering of Main Orthologs for Multiple Genomes (Z Fu & T Jiang); Extraction, Quantification and Visualization of Protein Pockets (X Zhang & C Bajaj); Consensus Contact Prediction by Linear Programming (X Gao et al.); An Active Visual Search Interface for Medline (W Xuan et al.); Exact and Heuristic Algorithms for Weighted Cluster Editing (S Rahmann et al.); Reconcilation with Non-binary Species Trees (B Vernot et al.); and other papers. Readership: Research and application community in bioinformatics, systems biology, medicine, pharmacology and biotechnology. Graduate researchers in bioinformatics and computational biology.