This text takes readers in a clear and progressive format from simple to recent and advanced topics in pure and applied probability such as contraction and annealed properties of non-linear semi-groups, functional entropy inequalities, empirical process convergence, increasing propagations of chaos, central limit, and Berry Esseen type theorems as well as large deviation principles for strong topologies on path-distribution spaces. Topics also include a body of powerful branching and interacting particle methods.
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods. Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology. This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.
Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the beginning, it contains many illustrations, photos and pictures, along with several website links. Computational tools such as simulation and Monte Carlo methods are included as well as complete toolboxes for both traditional and new computational techniques.
This book presents some new concentration inequalities for Feynman-Kac particle processes. It analyzes different types of stochastic particle models, including particle profile occupation measures, genealogical tree based evolution models, particle free energies, as well as backward Markov chain particle models. It illustrates these results with a series of topics related to computational physics and biology, stochastic optimization, signal processing and Bayesian statistics, and many other probabilistic machine learning algorithms. Special emphasis is given to the stochastic modeling, and to the quantitative performance analysis of a series of advanced Monte Carlo methods; including particle filters, genetic type island models, Markov bridge models, and interacting particle Markov chain Monte Carlo methodologies.
In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods. Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology. This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.
Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the beginning, it contains many illustrations, photos and pictures, along with several website links. Computational tools such as simulation and Monte Carlo methods are included as well as complete toolboxes for both traditional and new computational techniques.
This text takes readers in a clear and progressive format from simple to recent and advanced topics in pure and applied probability such as contraction and annealed properties of non-linear semi-groups, functional entropy inequalities, empirical process convergence, increasing propagations of chaos, central limit, and Berry Esseen type theorems as well as large deviation principles for strong topologies on path-distribution spaces. Topics also include a body of powerful branching and interacting particle methods.
Between 1983 and 1987, mercenaries adopting the pseudonym GAL (Grupos Antiterroristas de Liberación, Antiterrorist Liberation Group) paid by the Spanish treasury and relying upon national intelligence support were at war with the Basque militant group ETA (Euskadi (e)Ta Askatasuna, Basque Country and Freedom). Over four years, their campaign of extrajudicial assassinations spanned the French-Spanish border. Nearly thirty people were killed in a campaign comprised of torture, kidnapping, bombing and the assassination of suspected ETA activists and Basque refugees. This establishment of unofficial counterterrorist squads by a Spanish Government was a blatant detour from legality. It was also a rare case in Europe where no less than fourteen high-ranking Spanish police officers and senior government officials, including the Minister of Interior himself, were eventually arrested and condemned for counter-terrorism wrongdoings and illiberal practices. Thirty years later, this campaign of intimidation, coercion and targeted killings continues to grip Spain. The GAL affair was not only a serious example of a major departure from accepted liberal democratic constitutional principles of law and order, but also a brutal campaign that postponed by decades the possibility of a political solution for the Basque conflict. Counter-terror by proxy uncovers why and how a democratic government in a liberal society turned to a ‘dirty war’ and went down the route of illegal and extrajudicial killing actions. It offers a fuller examination of the long-term implications of the use of unorthodox counter-terrorist strategies in a liberal democracy.
By browsing about 10 000 000 scientific articles of over 200 major journals mainly in a 'cover to cover approach' some 200 000 publications were selected. The extracted data is part of the following fundamental material research fields: crystal structures (S), phase diagrams (also called constitution) (C) and the comprehensive field of intrinsic physical properties (P). This work has been done systematically starting with the literature going back to 1900. The above mentioned research field codes (S, C, P) as well as the chemical systems investigated in each publication were included in the present work. The aim of the Inorganic Substances Bibliography is to provide researchers with a comprehensive compilation of all up to now published scientific publications on inorganic systems in only three handy volumes.
Los autores muestran por qué este principio se impone hoy día como el término central de la alternativa política para el siglo XXI: anuda la lucha anticapitalista y la ecología política mediante su reivindicación de los “comunes” contra las nuevas formas de apropiación privada y estatal. Además, articula las luchas prácticas con las investigaciones sobre el gobierno colectivo de los recursos naturales o de la información y designa formas democráticas nuevas que aspiran a tomar el relevo de la representación política y del monopolio de los partidos. Esta emergencia de lo común en la acción reclama un trabajo de clarificación en el pensamiento. El sentido actual de lo común se distingue de los numerosos usos que se ha dado a esta noción, ya sean filosóficos, jurídicos o teológicos: bien supremo de la ciudad, universalidad de esencia, propiedad inherente a ciertas cosas, incluso alguna vez el fin perseguido por la creación divina. Pero hay otro hilo que vincula lo común, no a la esencia de los hombres o a la naturaleza de las cosas, sino a la actividad de los hombres mismos: sólo una práctica de puesta en conjunto puede decidir qué es “común”, reservar ciertas cosas al uso común, producir determinadas reglas capaces de obligar a los hombres. En este sentido, lo común reclama una nueva institución de la sociedad por ella misma: una revolución.
Praise for the First Edition ". . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner." —Mathematical Geosciences The state of the art in geostatistics Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive, up-to-date reference on the topic, now featuring the latest developments in the field. The authors explain both the theory and applications of geostatistics through a unified treatment that emphasizes methodology. Key topics that are the foundation of geostatistics are explored in-depth, including stationary and nonstationary models; linear and nonlinear methods; change of support; multivariate approaches; and conditional simulations. The Second Edition highlights the growing number of applications of geostatistical methods and discusses three key areas of growth in the field: New results and methods, including kriging very large datasets; kriging with outliers; nonse??parable space-time covariances; multipoint simulations; pluri-gaussian simulations; gradual deformation; and extreme value geostatistics Newly formed connections between geostatistics and other approaches such as radial basis functions, Gaussian Markov random fields, and data assimilation New perspectives on topics such as collocated cokriging, kriging with an external drift, discrete Gaussian change-of-support models, and simulation algorithms Geostatistics, Second Edition is an excellent book for courses on the topic at the graduate level. It also serves as an invaluable reference for earth scientists, mining and petroleum engineers, geophysicists, and environmental statisticians who collect and analyze data in their everyday work.
This book represents a rather complicated history of encounters, changes in research interest and some very interesting results. Initially it is the very fruitful interaction of Ecology and Geology. The point of view of ecologists is extremely refreshing for hard science people. Interaction and inter-relationships are the focus of Ecology whereas the traditional sciences, such as Geology, have tried to isolate the natural phenomena so that thye could be studied in a more rigorous manner. The traditional sciences were of course natural science – based since the world to be observed was at the door step of everyone, mountains, weather patterns, plants and so forth. Chemistry and Physics were de ned after Mathematics in order to establish more precise and viable principles of the behavior of the materials that formed the world around mankind. It became quite clear that the observation of the natural world was too complicated to consider all of the possible variables which could affect an observed process or situation. The systems were simpli ed and taken into the laboratory in order to better master the phenomena observed. Physics c- cerned itself with non-reacting materials, subjected to essentially mechanical forces.
This book covers the classical theory of Markov chains on general state-spaces as well as many recent developments. The theoretical results are illustrated by simple examples, many of which are taken from Markov Chain Monte Carlo methods. The book is self-contained, while all the results are carefully and concisely proven. Bibliographical notes are added at the end of each chapter to provide an overview of the literature. Part I lays the foundations of the theory of Markov chain on general states-space. Part II covers the basic theory of irreducible Markov chains on general states-space, relying heavily on regeneration techniques. These two parts can serve as a text on general state-space applied Markov chain theory. Although the choice of topics is quite different from what is usually covered, where most of the emphasis is put on countable state space, a graduate student should be able to read almost all these developments without any mathematical background deeper than that needed to study countable state space (very little measure theory is required). Part III covers advanced topics on the theory of irreducible Markov chains. The emphasis is on geometric and subgeometric convergence rates and also on computable bounds. Some results appeared for a first time in a book and others are original. Part IV are selected topics on Markov chains, covering mostly hot recent developments.
This monograph sheds new light on pulmonary sensory receptors. Diving into the pulmonary microenvironment, the book focuses on the role of pulmonary neuroepithelial bodies (NEBs) as potential receptors and effectors, able to store and release neurotransmitters. It explores NEBs as potential stem cell niche and highlights the multidisciplinary approach taken to identify and study NEBs, including functional morphological investigation, live cell imaging, genetic models, and laser microdissection combined with gene expression analysis. Complexly organized NEBs are an integral part of the intrapulmonary airway epithelium of all air-breathing vertebrates. For decades a quest has been going on to unravel the functional significance of these intriguing structures that appear to be modified in the course of many pulmonary diseases. The NEB microenvironment (ME) is composed of organoid clusters of pulmonary neuroendocrine cells (PNECs) that are able to store and release neurotransmitters and are closely contacted by extensive nerve terminals, emphasizing a potential receptor/effector role and probable signalling to the central nervous system. PNECs are largely shielded from the airway lumen by a special type of Clara cells, the Clara-like cells, with potential stem cell characteristics. So far, functional studies of the pulmonary NEB ME revealed that PNECs can be activated by various mechanical and chemical stimuli, resulting in a calcium-mediated release of neurotransmitters. In the past decades, a number of publications have exposed NEBs as potential hypoxia sensors. Recent experimental evidence unveiled that the NEB ME is a quiescent stem cell niche in healthy postnatal lungs, and silencing may involve bone morphogenetic protein signalling mediated by vagal afferents. Only an integrated approach that takes all current information into account will be able to explain the full role of the pulmonary NEB ME in health and disease. This highly informative and carefully presented book, provides insights for researchers, PhD students with an interest in (bio)medical and veterinary science, especially in the field of the autonomic innervation of the lung, chemo-and mechanoreceptors
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