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Mathematical Modelling of Biosystems
This volume is an interdisciplinary book, which introduces, in a very readable way, state of the art research in the fundamental topics of mathematical modelling of Biosystems. These topics include: the study of Biological Growth and its mechanisms, the coupling of pattern to form via theorems of Differential Geometry, the human immunodeficiency virus dynamics, the inverse folding problem and the possibility of analysing true protein backbone flexibility, the Biclustering techniques for the organization of microarray data, the analytical approach to the modelling of biomolecular structure via Steiner trees, the action of biocides on resistance mechanisms of mutated and phenotypic bacteria strains, a description of the fundamental processes for the distribution and abundances of species towards a unified theory of Ecology, and a special introduction to Protein Physics aiming to explain the all-or-none first order phase transitions from native to denatured states.
Mathematical Modelling for Sustainable Development
Mathematics needs Sustainable Development. When science was gradually reinvented in European medieval societies, it was legitimised as contributing to the disclosure of God’s divine creation. The conflicts that emerged became well known as a result of the clash between Galileo and the Church. Science found a new legitimacy through recognition that it was a powerful force against superstition. In the Enlightenment the argument was pushed forward by attributing Progress to the advancement of science: science could produce a better world by promoting rationality. In our modern society, science has become intimately linked to technology. Science for its own sake unfortunately rarely has positive outcomes in terms of research grant applications. Meanwhile, science and technology, and the progress they are supposed to produce, meet with wide scale scepticism. We all know of the current global problems: climate change, resource depletion, a thinning ozone layer, space debris, declining biodiversity, malnutrition, dying ecosystems, global inequity, and the risk of unprecedented nuclear wars
Mathematical Modeling of Complex Biological Systems : A Kinetic Theory Approach
This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems—comprised of large populations of interacting cells—whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. The authors propose a new biological model for the analysis of competition between cells of an aggressive host and cells of a corresponding immune system.Because the microscopic description of a biological system is far more complex than that of a physical system of inert matter, a higher level of analysis is needed to deal with such complexity. Mathematical models using kinetic theory may represent a way to deal with such complexity, allowing for an understanding of phenomena of nonequilibrium statistical mechanics not described by the traditional macroscopic approach. The proposed models are related to the generalized Boltzmann equation and describe the population dynamics of several interacting elements (kinetic population models).The particular models proposed by the authors are based on a framework related to a system of integro-differential equations, defining the evolution of the distribution function over the microscopic state of each element in a given system. Macroscopic information on the behavior of the system is obtained from suitable moments of the distribution function over the microscopic states of the elements involved. The book follows a classical research approach applied to modeling real systems, linking the observation of biological phenomena, collection of experimental data, modeling, and computational simulations to validate the proposed models. Qualitative analysis techniques are used to identify the prediction ability of specific models.
Mathematical Modeling of Biological Systems ; Vol. II : Epidemiology, Evolution and Ecology,Immunology, Neural Systems and the Brain, and Innovative Mathematical Methods
This two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout both works are mathematical and computational approaches to examine central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.
Mathematical Modeling of Biological Systems ; Vol. I : Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis
This two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout both works are mathematical and computational approaches to examine central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.
Mathematical Modeling for the Life Sciences
Proposing a wide range of mathematical models that are currently used in life sciences may be regarded as a challenge, and that is precisely the challenge that this book takes up. Of course this panoramic study does not claim to offer a detailed and exhaustive view of the many interactions between mathematical models and life sciences. This textbook provides a general overview of realistic mathematical models in life sciences, considering both deterministic and stochastic models and covering dynamical systems, game theory, stochastic processes and statistical methods. Each mathematical model is explained and illustrated individually with an appropriate biological example. Finally three appendices on ordinary differential equations, evolution equations, and probability are added to make it possible to read this book independently of other literature.
Mathematical Methods in Time Series Analysis and Digital Image Processing
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed.
Mathematical Methods in Robust Control of Linear Stochastic Systems
Linear stochastic systems are successfully used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. This monograph presents a useful methodology for the control of such stochastic systems with a focus on robust stabilization in the mean square, linear quadratic control, the disturbance attenuation problem, and robust stabilization with respect to dynamic and parametric uncertainty.
Mathematical Methods in Engineering
This book contains some of the contributions that have been carefully selected and peer-reviewed, which were presented at the International Symposium MME06 Mathematical Methods in Engineering, held in Cankaya University, Ankara, April 2006. The Symposium provided a setting for discussing recent developments in Fractional Mathematics, Neutrices and Generalized Functions, Boundary Value Problems, Applications of Wavelets, Dynamical Systems and Control Theory.
Mathematical Methods for Robust and Nonlinear Control : EPSRC Summer School
The underlying theory on which much modern robust and nonlinear control is based can often be dif?cult for the student to grasp. In particular, the mathematical - pects can be problematic for students from a standard engineering background. The EPSRC sponsored Summer School which was held in Leicester in September 2006 attempted to “?ll the gap” in students’ appreciation the theory relevant to several important areas of control. This book is a collection of lecture notes which were p- sented at that workshop and consists of, broadly, two parts. The ?rst nine chapters are devoted to the theory behind several areas of robust and nonlinear control and are aimed at introducing fundamental concepts to the reader. The last six chapters contain detailed case studies which aim to demonstrate the use and effectiveness of these modern techniques in real engineering applications. It is hoped that this book will provide a useful introduction to many of the more common robust and nonlinear control techniques and serve as a valuable reference for the more adept practitioner.
Mathematical Implications of Einstein-Weyl Causality
The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics.
Mathematical Control Theory : An Introduction
Mathematical Control Theory: An Introduction presents, in a mathematically precise manner, a unified introduction to deterministic control theory. With the exception of a few more advanced concepts required for the final part of the book, the presentation requires only a knowledge of basic facts from linear algebra, differential equations, and calculus. In addition to classical concepts and ideas, the author covers the stabilization of nonlinear systems using topological methods, realization theory for nonlinear systems, impulsive control and positive systems, the control of rigid bodies, the stabilization of infinite dimensional systems, and the solution of minimum energy problems.
Mathematical Aspects of Classical and Celestial Mechanics
In this book we describe the basic principles, problems, and methods of clssical mechanics. Our main attention is devoted to the mathematical side of the subject. Although the physical background of the models considered here and the applied aspects of the phenomena studied in this book are explored to a considerably lesser extent, we have tried to set forth first and foremost the “working” apparatus of classical mechanics. This apparatus is contained mainly in Chapters 1, 3, 5, 6, and 8. Chapter 1 is devoted to the basic mathematical models of classical - chanics that are usually used for describing the motion of real mechanical systems. Special attention is given to the study of motion with constraints and to the problems of realization of constraints in dynamics. In Chapter 3 we discuss symmetry groups of mechanical systems and the corresponding conservation laws. We also expound various aspects of ord- reduction theory for systems with symmetries, which is often used in appli- tions. Chapter 4 is devoted to variational principles and methods of classical mechanics. They allow one, in particular, to obtain non-trivial results on the existence of periodic trajectories. Special attention is given to the case where the region of possible motion has a non-empty boundary. Applications of the variational methods to the theory of stability of motion are indicated.
Mathematical and Computational Models for Congestion Charging
This book presents rigorous treatments of issues related to congestion pricing. The chapters describe recent advances in areas such as mathematical and computational models for predicting traffic congestion, determining when, where, and how much to levy tolls, and analyzing the impact of tolls on transporation systems. The analyses and methodologies developed in this book provide Mechanisms that aid in determining and comparing congestion pricing schemes; Methodologies for evaluating the efficiency of existing and proposed congestion pricing schemes; A means to predict the impact of pricing on urban transporation systems; and Information essential to the financial and political success of congestion pricing programs.
Math Everywhere : Deterministic and Stochastic Modelling in Biomedicine, Economics and Industry
These proceedings are reporting on the conference ''Math Everywhere", a successful event celebrating a leading scientist, promoting ideas he pursued and sharing the open atmosphere he is known for. The areas of the contributions are the following , Deterministic and Stochastic Systems. Mathematical Problems in Biology, Medicine and Ecology, Mathematical Problems in Industry and Economics.
Materials Issues for Generation IV Systems ; Status, Open Questions and Challenges
Global warming, shortage of low-cost oil resources and the increasing demand for energy are currently controlling the world's economic expansion while often opposing desires for sustainable and peaceful development. In this context, atomic energy satisfactorily fulfills the criteria of low carbon gas production and high overall yield. However, in the absence of industrial fast-breeders the use of nuclear fuel is not optimal, and the production of high activity waste materials is at a maximum. These are the principal reasons for the development of a new, fourth generation of nuclear reactors, minimizing the undesirable side-effects of current nuclear energy production technology while increasing yields by increasing operation temperatures and opening the way for the industrial production of hydrogen through the decomposition of water.
Matematica generale con il calcolatore
By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.
Martens and Fishers (Martes) in human-altered environments : An international perspective
Examines the conditions where humans and martens are compatible and incompatible, and promotes land use practices that allow Martes to be representatively distributed and viable. All Martes have been documented to use forested habitats and 6 species (excluding the stone marten) are generally considered to require complex mid- to late-successional forests throughout much of their geographic ranges. All species in the genus require complex horizontal and vertical structure to provide escape cover protection from predators, habitat for their prey, access to food resources, and protection from the elements. Martens and the fisher have high metabolic rates, have large spatial requirements, have high surface area to volume ratios for animals that often inhabit high latitudes, and often require among the largest home range areas per unit body weight of any group of mammals. Resulting from these unique life history characteristics, this genus is particularly sensitive to human influences on their habitats, including habitat loss, stand-scale simplification of forest structure via some forms of logging, and landscape-scale effects of habitat fragmentation. Given their strong associations with structural complexity in forests, martens and the fisher are often considered as useful barometers of forest health and have been used as ecological indicators, flagship, and umbrella species in different parts of the world. Thus, efforts to successfully conserve and manage martens and fishers are associated with the ecological fates of other forest dependent species and can greatly influence ecosystem integrity within forests that are increasingly shared among wildlife and humans.We have made great strides in our fundamental understanding of how animals with these unique life history traits perceive and utilize habitats, respond to habitat change, and how their populations function and perform under different forms of human management and mismanagement.
Mars, A Cosmic Stepping Stone : Uncovering Humanity’s Cosmic Context
The questions of our origin and cosmic abundance of life are among the compelling facing humanity. For all of the difficulties facing us however, the planet Mars may act as a cosmic stepping stone in uncovering the answers. This book examines these issues in one of the comprehensive treatments about Mars and our legacy of engagement with it.
Markov Decision Processes with Their Applications
Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters.
