This book integrates discoveries from recent years to show the diversity of molecular mechanisms that contribute to memory consolidation, reconsolidation, extinction, and forgetting. It provides a special focus on the processes that govern functional and structural plasticity of dendritic spines. In nine chapters, new and important ideas related to learning and memory processes will be presented. Themes discussed include the role of AMPA receptors in memory, two signalling cascades involved in local spine remodelling and memory, the role of extracellular matrix proteins in memory, the regulation of gene expression and protein translation, and mechanisms of retrieval-induced memory modulation and forgetting. We believe that the study of these topics represents a great step toward understanding the complexity of the brain and the processes it governs.

This book provides an overview of the main approaches used to analyze the dynamics of cellular automata. Cellular automata are an indispensable tool in mathematical modeling. In contrast to classical modeling approaches like partial differential equations, cellular automata are relatively easy to simulate but difficult to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction to cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of various topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kurka classification)? These classifications suggest that cellular automata be clustered, similar to the classification of partial differential equations into hyperbolic, parabolic and elliptic equations. This part of the book culminates in the question of whether the properties of cellular automata are decidable. Surjectivity and injectivity are examined, and the seminal Garden of Eden theorems are discussed. In turn, the third part focuses on the analysis of cellular automata that inherit distinct properties, often based on mathematical modeling of biological, physical or chemical systems. Linearity is a concept that allows us to define self-similar limit sets. Models for particle motion show how to bridge the gap between cellular automata and partial differential equations (HPP model and ultradiscrete limit). Pattern formation is related to linear cellular automata, to the Bar-Yam model for the Turing pattern, and Greenberg-Hastings automata for excitable media. In addition, models for sand piles, the dynamics of infectious d

Memory Mechanisms is an edited review volume that summarizes state-of-the-art knowledge on memory mechanisms at the molecular, cellular and circuit level. Each review is written by leading experts in the field, presenting not only current knowledge, but also discussing the concepts, providing critical reflections and suggesting an outlook for future studies. The memory mechanisms are also discussed in the context of diseases. Studies of memory deficits in disease models are introduced as well as approaches to restore memory deficits. Finally, the impact of contemporary memory research for psychiatry is illustrated.

This book integrates discoveries from recent years to show the diversity of molecular mechanisms that contribute to memory consolidation, reconsolidation, extinction, and forgetting. It provides a special focus on the processes that govern functional and structural plasticity of dendritic spines. In nine chapters, new and important ideas related to learning and memory processes will be presented. Themes discussed include the role of AMPA receptors in memory, two signalling cascades involved in local spine remodelling and memory, the role of extracellular matrix proteins in memory, the regulation of gene expression and protein translation, and mechanisms of retrieval-induced memory modulation and forgetting. We believe that the study of these topics represents a great step toward understanding the complexity of the brain and the processes it governs.

This book analyzes the impact of quiescent phases on biological models. Quiescence arises, for example, when moving individuals stop moving, hunting predators take a rest, infected individuals are isolated, or cells enter the quiescent compartment of the cell cycle. In the first chapter of Topics in Mathematical Biology general principles about coupled and quiescent systems are derived, including results on shrinking periodic orbits and stabilization of oscillations via quiescence. In subsequent chapters classical biological models are presented in detail and challenged by the introduction of quiescence. These models include delay equations, demographic models, age structured models, Lotka-Volterra systems, replicator systems, genetic models, game theory, Nash equilibria, evolutionary stable strategies, ecological models, epidemiological models, random walks and reaction-diffusion models. In each case we find new and interesting results such as stability of fixed points and/or periodic orbits, excitability of steady states, epidemic outbreaks, survival of the fittest, and speeds of invading fronts. The textbook is intended for graduate students and researchers in mathematical biology who have a solid background in linear algebra, differential equations and dynamical systems. Readers can find gems of unexpected beauty within these pages, and those who knew K.P. (as he was often called) well will likely feel his presence and hear him speaking to them as they read.

The volume contains a selection of manuscripts of lectures presented at the International Symposi- um on Operations Research (SOR 96). The Symposium took place at the Technical University of Braunschweig, September 3-6, 1996. SOR 96 was organized under the auspices of the two German societies of Operations Research, Deutsche Gesellschaft fur Operations Research (DGOR) and Gesellschaft fur Mathematik, Okonomie and Operations Research (GMOOR) in cooperation with the Working Group Discrete Optimization of the IFIP (WG7.4). Since 1995, DGOR and GMOORjointly prepare the Symposium as a common annual conference. In particular, the annual general meetings of the DGOR, the GMOOR and the WG7.4 took place during the conference. The Symposi~m had 527 participants from 32 countries around the world, including 92 partici- pants from Eastern Europe. The Symposium obviously attracts an international audience of workers fully covering the broad spectrum of Operations Research and related areas in economics, mathema- tics and computer science. The importance of a highly interdisciplinary field as Operations Research is increasing owing to the growth in applications in related disciplines. Technological advances in computer science and algorithmic mathematics are crucial for attacking the great challenges waiting in the areas of applications of Operations Research effectively. As a participant of SOR 96 one could well observe the current pace of achievements. Many of these results are in these proceedings. The program consisted of two plenary, 17 semiplenary, and 335 contributed lectures in 18 sections.

Nach der Eroberung der vormals turkisch besetzten Gebiete in den sog. Turkenkriegen (1683-1699 und 1716-1718) war die Geschichte Ungarns im 18. Jahrhundert durch Aufbruch und neue Siedlungsstrukturen gepragt. Neu angesiedelte Kolonisten aus Deutschland gestalteten die Veranderungen entscheidend mit. Zehn renommierte Autoren untersuchen die Prozesse der Ansiedlung und der Eingliederung der Kolonisten und beleuchten auf der Mikro- wie auf der Makroebene deren Akteure. Ins Blickfeld rucken Staat und Administration, kirchliche und weltliche Grundherren sowie immer wieder die Kolonisten und deren Bedeutung fur Wirtschaft und Gesellschaft des Konigreichs. Beitrage von Gabor Barna, Zoltan Csepregi, Zoltan Gozsy, Marta Fata, Zoltan Kaposi, Karl-Peter Krauss, Gyorgy Kurucz, Ernst Dieter Petritsch, Gerhard Seewann, Norbert Spannenberger, Katharina Wild"

Containing also: Kultur im Verfassungsstaat. Grund und Grenzen der Wissenschaftsfreiheit. Die Universitat im Zeichen von OEkonomisierung und Internationalisierung. Sprache als Kultur- und Rechtsgut

This book provides an overview of the main approaches used to analyze the dynamics of cellular automata. Cellular automata are an indispensable tool in mathematical modeling. In contrast to classical modeling approaches like partial differential equations, cellular automata are relatively easy to simulate but difficult to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction to cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of various topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kurka classification)? These classifications suggest that cellular automata be clustered, similar to the classification of partial differential equations into hyperbolic, parabolic and elliptic equations. This part of the book culminates in the question of whether the properties of cellular automata are decidable. Surjectivity and injectivity are examined, and the seminal Garden of Eden theorems are discussed. In turn, the third part focuses on the analysis of cellular automata that inherit distinct properties, often based on mathematical modeling of biological, physical or chemical systems. Linearity is a concept that allows us to define self-similar limit sets. Models for particle motion show how to bridge the gap between cellular automata and partial differential equations (HPP model and ultradiscrete limit). Pattern formation is related to linear cellular automata, to the Bar-Yam model for the Turing pattern, and Greenberg-Hastings automata for excitable media. In addition, models for sand piles, the dynamics of infectious d