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Since the parameters in dynamical systems of biological interest are inherently positive and bounded, bounded noises are a natural way to model the realistic stochastic fluctuations of a biological system that are caused by its interaction with the external world. Bounded Noises in Physics, Biology, and Engineering is the first contributed volume devoted to the modeling of bounded noises in theoretical and applied statistical mechanics, quantitative biology, and mathematical physics. It gives an overview of the current state-of-the-art and is intended to stimulate further research.   The volume is organized in four parts. The first part presents the main kinds of bounded noises and their applications in theoretical physics. The theory of bounded stochastic processes is intimately linked to its applications to mathematical and statistical physics, and it would be difficult and unnatural to separate the theory from its physical applications. The second is devoted to framing bounded noises in the theory of random dynamical systems and random bifurcations, while the third is devoted to applications of bounded stochastic processes in biology, one of the major areas of potential applications of this subject. The final part concerns the application of bounded stochastic processes in mechanical and structural engineering, the area where the renewed interest for non-Gaussian bounded noises started. Pure mathematicians working on stochastic calculus will find here a rich source of problems that are challenging from the point of view of contemporary nonlinear analysis.   Bounded Noises in Physics, Biology, and Engineering is intended for scientists working on stochastic processes with an interest in both fundamental issues and applications. It will appeal to a broad range of applied mathematicians, mathematical biologists, physicists, engineers, and researchers in other fields interested in complexity theory. It is accessible to anyone with a working knowledge of stochastic modeling, from advanced undergraduates to senior researchers.

Operational research. Game theory --- Probability theory --- Mathematics --- Mathematical physics --- Biology --- Applied physical engineering --- Engineering sciences. Technology --- Planning (firm) --- Computer science --- analyse (wiskunde) --- waarschijnlijkheidstheorie --- theoretische fysica --- stochastische analyse --- biologie --- economie --- informatica --- mathematische modellen --- wiskunde --- ingenieurswetenschappen --- kansrekening --- Random noise theory. --- Stochastic processes.

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This volume summarizes the state-of-the-art in the fast growing research area of modeling the influence of information-driven human behavior on the spread and control of infectious diseases. In particular, it features the two main and inter-related “core” topics: behavioral changes in response to global threats, for example, pandemic influenza, and the pseudo-rational opposition to vaccines. The motivation comes from the fact that people are likely to change their behavior and their propensity to vaccinate themselves and their children based on information and rumors about the spread of a disease. As a consequence there is a feedback effect that may deeply affect the dynamics of epidemics and endemics. In order to make realistic predictions, modelers need to go beyond classical mathematical epidemiology to take these dynamic effects into account. With contributions from experts in this field, the book fills a void in the literature. It goes beyond classical texts, yet preserves the rationale of many of them by sticking to the underlying biology without compromising on scientific rigor. Epidemiologists, theoretical biologists, biophysicists, applied mathematicians, and PhD students will benefit from this book. However, it is also written for Public Health professionals interested in understanding models, and for advanced undergraduate students, since it only requires a working knowledge of mathematical epidemiology.

Airborne infection. --- Communicable diseases -- Epidemiology -- Mathematical models. --- Communicable diseases. --- Epidemiology -- Mathematical models. --- Communicable diseases --- Behavior --- Investigative Techniques --- Infection --- Bacterial Infections and Mycoses --- Behavior and Behavior Mechanisms --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Psychiatry and Psychology --- Diseases --- Health Behavior --- Models, Theoretical --- Communicable Diseases --- Public Health --- Biology --- Health & Biological Sciences --- Biology - General --- Epidemiology & Epidemics --- Epidemiology --- Mathematical models --- Health behavior. --- Human behavior. --- Transmission. --- Causes and theories of causation. --- Action, Human --- Behavior, Human --- Ethology --- Human action --- Human beings --- Aetiology --- Etiology --- Behavior, Health --- Health habits --- Communicable disease transmission --- Disease transmission --- Germs, Spread of --- Spread of communicable diseases --- Spread of germs --- Transmission of diseases --- Transmission --- Mathematics. --- Immunology. --- Chemometrics. --- Health promotion. --- Infectious diseases. --- Biomathematics. --- Physiological, Cellular and Medical Topics. --- Math. Applications in Chemistry. --- Health Promotion and Disease Prevention. --- Infectious Diseases. --- Mathematical and Computational Biology. --- Human biology --- Physical anthropology --- Psychology --- Social sciences --- Psychology, Comparative --- Pathology --- Habit --- Health attitudes --- Human behavior --- Medicine and psychology --- Causes and theories of causation --- Physiology --- Chemistry --- Medicine. --- Emerging infectious diseases. --- Emerging infections --- New infectious diseases --- Re-emerging infectious diseases --- Reemerging infectious diseases --- Clinical sciences --- Medical profession --- Life sciences --- Medical sciences --- Physicians --- Immunobiology --- Serology --- Animal physiology --- Animals --- Anatomy --- Health Workforce --- Health promotion programs --- Health promotion services --- Promotion of health --- Wellness programs --- Preventive health services --- Health education --- Chemistry, Analytic --- Analytical chemistry --- Mathematics --- Measurement --- Statistical methods

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With chapters on free boundaries, constitutive equations, stochastic dynamics, nonlinear diffusion–consumption, structured populations, and applications of optimal control theory, this volume presents the most significant recent results in the field of mathematical oncology. It highlights the work of world-class research teams, and explores how different researchers approach the same problem in various ways. Tumors are complex entities that present numerous challenges to the mathematical modeler. First and foremost, they grow. Thus their spatial mean field description involves a free boundary problem. Second, their interiors should be modeled as nontrivial porous media using constitutive equations. Third, at the end of anti-cancer therapy, a small number of malignant cells remain, making the post-treatment dynamics inherently stochastic. Fourth, the growth parameters of macroscopic tumors are non-constant, as are the parameters of anti-tumor therapies. Changes in these parameters may induce phenomena that are mathematically equivalent to phase transitions. Fifth, tumor vascular growth is random and self-similar. Finally, the drugs used in chemotherapy diffuse and are taken up by the cells in nonlinear ways. Mathematical Oncology 2013 will appeal to graduate students and researchers in biomathematics, computational and theoretical biology, biophysics, and bioengineering.

Mathematics --- General biophysics --- Human biochemistry --- Oncology. Neoplasms --- tumoren --- medische biochemie --- biofysica --- biochemie --- oncologie --- wiskunde

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The aim of this book is not only to illustrate the state of the art of tumor systems biomedicine, but also and mainly to explicitly capture the fact that a increasing number of biomedical scientists is now directly working on mathematical modeling, and a larger number are collaborating with bio-mathematical scientists. Moreover, a number of biomathematicians started working in biomedical institutions. The book is characterized by a coherent view of tumor modeling, based on the concept that mathematical modeling is (with medicine and molecular biology) one of the three pillars of molecular medicine. Indeed this volume is characterized by a well-structured presence of a large number of biomedical scientists directly working in Mathematical or Systems Biomedicine, and of a number biomathematicians working in hospitals. This give to this book an unprecedented tone, providing an original interdisciplinary insight into the biomedical applications. Finally, all biomedical contributors were asked to briefly summarize in one section of their contributes their point of view on her/his own interactions with quantitative scientists working in Systems Biomedicine.

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The book "Problems in Mathematical Biophysics - a volume in memory of Alberto Gandolfi" aims at reviewing the current state of the art of the mathematical approach to various areas of theoretical biophysics. Leading authors in the field have been invited to contribute, having a strong appreciation of Alberto Gandolfi as a scientist and as a man and sharing his same passion for biology and medicine, as well as his style of investigation. Encompassing both theoretical and practical aspects of Mathematical Biophysics, the topics covered in this book span a spectrum of different problems, in biology, and medicine, including population dynamics, tumor growth and control, immunology, epidemiology, ecology, and others. As a result, the book offers a comprehensive and current overview of compelling subjects and challenges within the realm of mathematical biophysics. In their contributions, the authors have effectively conveyed not only their research findings but also their peculiar perspective and approach to problem-solving, dealing with oncology, epidemiology, neuro-sciences, and biochemistry. The chapters pertain to a wide array of mathematical areas such as continuous Markov chains, partial differential equations, kinetic theory, applied statistical mechanics, noise-induced transitions, and many others.

Mathematics. --- Applications of Mathematics.