Quantifying and Managing Soil Functions in Earth's Critical Zone: Combining Experimentation and Mathematical Modelling, Volume 142, the latest in the Advances in Agronomy series continues its reputation as a leading reference and first-rate source for the latest research in agronomy. Each volume contains an eclectic group of reviews by leading scientists throughout the world. Five volumes are published yearly, ensuring that the authors' contributions are disseminated to the readership in a timely manner. As always, the subjects covered are varied and exemplary of the myriad of subject matter dealt with by this long-running serial.

In July 2009, many experts in the mathematical modeling of biological sciences gathered in Les Houches for a 4-week summer school on the mechanics and physics of biological systems. The goal of the school was to present to students and researchers an integrated view of new trends and challenges in physical and mathematical aspects of biomechanics. While the scope for such a topic is very wide, they focused on problems where solid and fluid mechanics play a central role. The school covered both the general mathematical theory of mechanical biology in the context of continuum mechanics but also the specific modeling of particular systems in the biology of the cell, plants, microbes, and in physiology.
These lecture notes are organized (as was the school) around five different main topics all connected by the common theme of continuum modeling for biological systems: Bio-fluidics, Bio-gels, Bio-mechanics, Bio-membranes, and Morphogenesis. These notes are not meant as a journal review of the topic but rather as a gentle tutorial introduction to the readers who want to understand the basic problematic in modeling biological systems from a mechanics perspective.

Modelling and Control in Biomedical Systems (including Biological Systems) was held in Reims, France, 20-22 August 2006. This Symposium was organised by the University of Reims Champagne Ardenne and the Societe de l Electricite, de l Electronique et des TIC (SEE).
The Symposium attracted practitioners in engineering, information technology, mathematics, medicine and biology, and other related disciplines, with authors from 24 countries. Besides the abstracts of the four plenary lectures, this volume contains the 92 papers that were presented by their authors at the Symposium
The papers included two invited keynote presentations given by internationally prominent and well-recognised research leaders: Claudio Cobelli, whose talk is titled "Dynamic modelling in diabetes: from whole body to genes"; and Irving J. Bigio, whose talk is titled "Elastic scattering spectroscopy for non-invasive detection of cancer." Two prestigious industrial speakers were also invited to give keynote presentations: Terry O'Brien from LIDCO, whose talk is titled "LIDCO: From the laboratory to protocolized goal directed therapy"; and Lorenzo Quinzio of Philips, whose talk is titled "Clinical decision support in monitoring and information systems."
* A valuable source of information on the state-of- the-art in Modelling and Control in Biomedical Systems
* Including abstracts of four plenary lectures, and 92 papers presented by their authors"

This book provides a comprehensive introduction to the mathematical theory of nonlinear problems described by singular elliptic equations. There are carefully analyzed logistic type equations with boundary blow-up solutions and generalized Lane-Emden-Fowler equations or Gierer-Meinhardt systems with singular nonlinearity in anisotropic media. These nonlinear problems appear as mathematical models in various branches of Physics, Mechanics, Genetics, Economics, Engineering, and they are also relevant in Quantum Physics and Differential Geometry.
One of the main purposes of this volume is to deduce decay rates for general classes of solutions in terms of estimates of particular problems. Much of the material included in this volume is devoted to the asymptotic analysis of solutions and to the qualitative study of related bifurcation problems. Numerical approximations illustrate many abstract results of this volume. A systematic description of the most relevant singular phenomena described in these lecture notes includes existence (or nonexistence) of solutions, unicity or multiplicity properties, bifurcation and asymptotic analysis, and optimal regularity.
The method of presentation should appeal to readers with different backgrounds in functional analysis and nonlinear partial differential equations. All chapters include detailed heuristic arguments providing thorough motivation of the study developed later on in the text, in relationship with concrete processes arising in applied sciences. The book includes an extensive bibliography and a rich index, thus allowing for quick orientation among the vast collection of literature on the mathematical theory of nonlinear singularphenomena

Mathematical modelling modules feature in most university undergraduate mathematics courses. As one of the fastest growing areas of the curriculum it represents the current trend in teaching the more complex areas of mathematics. This book introduces mathematical modelling to the new style of undergraduate - those with less prior knowledge, who require more emphasis on application of techniques in the following sections: What is mathematical modelling?; Seeing modelling at work through population growth; Seeing modelling at work through published papers; Modelling in mechanics.
Written in the lively interactive style of the Modular Mathematics Series, this text will encourage the reader to take part in the modelling process.

While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

As the operations of the world become more and more dependent on highly interconnected, massively complex, networked systems of computational devices, the need to develop a mathematical understanding of their properties and behaviours is increasingly pressing. Our approach, described in this monograph, is to combine the compositionality of formal specification -- using techniques from algebra, computation theory, logic, and probability theory -- with the control of level of abstraction afforded by the classical mathematical modelling method.

From climate change forecasts and pandemic maps to Lego sets and Ancestry algorithms, models encompass our world and our lives. In her thought-provoking new book, Annabel Wharton begins with a definition drawn from the quantitative sciences and the philosophy of science but holds that history and critical cultural theory are essential to a fuller understanding of modeling. Considering changes in the medical body model and the architectural model, from the Middle Ages to the twenty-first century, Wharton demonstrates the ways in which all models are historical and political. Examining how cadavers have been described, exhibited, and visually rendered, she highlights the historical dimension of the modified body and its depictions. Analyzing the varied reworkings of the Holy Sepulchre in Jerusalem-including by monumental commanderies of the Knights Templar, Alberti's Rucellai Tomb in Florence, Franciscans' olive wood replicas, and video game renderings-she foregrounds the political force of architectural representations. And considering black boxes-instruments whose inputs we control and whose outputs we interpret, but whose inner workings are beyond our comprehension-she surveys the threats posed by such opaque computational models, warning of the dangers that models pose when humans lose control of the means by which they are generated and understood. Engaging and wide-ranging, Models and World Making conjures new ways of seeing and critically evaluating how we make and remake the world in which we live.

Physiologically Based Pharmacokinetic (PBPK) Modeling: Methods and Applications in Toxicology and Risk Assessment presents foundational principles, advanced techniques and applications of PBPK modeling. Contributions from experts in PBPK modeling cover topics such as pharmacokinetic principles, classical physiological models, the application of physiological models for dose-response and risk assessment, the use of in vitro information, and in silico methods. With end-of-chapter exercises that allow readers to practice and learn the skills associated with PBPK modeling, dose-response, and its applications to safety and risk assessments, this book is a foundational resource that provides practical coverage of PBPK modeling for graduate students, academics, researchers, and more.

Flexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced econometric and statistical analysis where datasets are characterized by complexity, multiplicity, and large sample sizes, necessitating the need for considerable flexibility in modeling techniques. It reviews three forms of flexibility: methods which provide flexibility in their error distribution; methods which model non-central parts of the distribution (such as quantile regression); and finally models that allow the mean function to be flexible (such as spline models). Each chapter discusses the key aspects of fitting a regression model. R programs accompany the methods. This book is particularly relevant to non-specialist practitioners with intermediate mathematical training seeking to apply Bayesian approaches in economics, biology, finance, engineering and medicine.

Power Systems Modelling and Fault Analysis: Theory and Practice, Second Edition, focuses on the important core areas and technical skills required for practicing electrical power engineers. Providing a comprehensive and practical treatment of the modeling of electrical power systems, the book offers students and professionals the theory and practice of fault analysis of power systems, covering detailed and advanced theories and modern industry practices. The book describes relevant advances in the industry, such as international standards developments and new generation technologies, such as wind turbine generators, fault current limiters, multi-phase fault analysis, the measurement of equipment parameters, probabilistic short-circuit analysis, and more.

The book addresses optimization in the petroleum industry from a practical, large-scale-application-oriented point of view. The models and techniques presented help to optimize the limited resources in the industry in order to maximize economic benefits, ensure operational safety, and reduce environmental impact. The book discusses several important real-life applications of optimization in the petroleum industry, ranging from the scheduling of personnel time to the blending of gasoline. It covers a wide spectrum of relevant activities, including drilling, producing, maintenance, and distribution. The text begins with an introductory overview of the petroleum industry and then of optimization models and techniques. The main body of the book details a variety of applications of optimization models and techniques within the petroleum industry. Applied  Optimization in the Petroleum Industry helps readers to find effective optimization-based solutions to their own practical problems in a large and important industrial sector, still the main source of the world’s energy and the source of raw materials for a wide variety of industrial and consumer products.

Time and Methods in Environmental Interfaces Modelling: Personal Insights considers the use of time in environmental interfaces modeling and introduce new methods, from the global scale (e.g. climate modeling) to the micro scale (e.g. cell and nanotubes modeling), which primarily arise from the personal research insights of the authors. As the field of environmental science requires the application of new fundamental approaches that can lead to a better understanding of environmental phenomena, this book helps necessitate new approaches in modeling, including category theory, that follow new achievements in physics, mathematics, biology, and chemistry.

Within the field of modeling complex objects in natural sciences, which considers systems that consist of a large number of interacting parts, a good tool for analyzing and fitting models is the theory of random evolutionary systems, considering their asymptotic properties and large deviations. In Random Evolutionary Systems we consider these systems in terms of the operators that appear in the schemes of their diffusion and the Poisson approximation. Such an approach allows us to obtain a number of limit theorems and asymptotic expansions of processes that model complex stochastic systems, both those that are autonomous and those dependent on an external random environment. In this case, various possibilities of scaling processes and their time parameters are used to obtain different limit results.

An Invitation to Applied Mathematics: Differential Equations, Modeling, and Computation introduces the reader to the methodology of modern applied mathematics in modeling, analysis, and scientific computing with emphasis on the use of ordinary and partial differential equations. Each topic is introduced with an attractive physical problem, where a mathematical model is constructed using physical and constitutive laws arising from the conservation of mass, conservation of momentum, or Maxwell's electrodynamics. Relevant mathematical analysis (which might employ vector calculus, Fourier series, nonlinear ODEs, bifurcation theory, perturbation theory, potential theory, control theory, or probability theory) or scientific computing (which might include Newton's method, the method of lines, finite differences, finite elements, finite volumes, boundary elements, projection methods, smoothed particle hydrodynamics, or Lagrangian methods) is developed in context and used to make physically significant predictions. The target audience is advanced undergraduates (who have at least a working knowledge of vector calculus and linear ordinary differential equations) or beginning graduate students. Readers will gain a solid and exciting introduction to modeling, mathematical analysis, and computation that provides the key ideas and skills needed to enter the wider world of modern applied mathematics.

Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians.

Mathematic Modelling: Improving the Implementation, Monitoring and Evaluation of Interventions, Part B, the latest volume in the Advances in Parasitology series contains comprehensive and up-to-date reviews in the field of mathematic modeling and its implementation within parasitology. The series includes medical studies of parasites of major influence, such as Plasmodium falciparum and trypanosomes, along with reviews of more traditional areas, such as zoology, taxonomy, and life history, all of which shape current thinking and applications.

Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432.