Introductory Mathematics for the Life Sciences offers a straightforward introduction to the mathematical principles needed for studies in the life sciences. Starting with the basics of numbers, fractions, ratios, and percentages, the author explains progressively more sophisticated concepts, from algebra, measurement, and scientific notation through the linear, power, exponential, and logarithmic functions to introductory statistics. Worked examples illustrate concepts, applications, and interpretations, and exercises at the end of each chapter help readers apply and practice the skills they develop. Answers to the exercises are posted at the end of the text.

The Ning-Meng reach of the Yellow River basin is located in the Inner Mongolia region at the Northern part of the Yellow River. Due to the special geographical conditions, the river flow direction is towards the North causing the Ning-Meng reach to freeze up every year in wintertime. Both during the freeze-up and break-up period, unfavourable conditions occur which may cause ice jamming and ice dam formation leading to dike breaching and overtopping of the embankment. Throughout history this has often led to considerable casualties and property loss. Enhanced economic development and human activities in the region have altered the characteristics of the ice regime in recent decades, leading to several ice disasters during freezing or breaking-up periods. The integrated water resources management plan developed by the Yellow River Conservancy Commission (YRCC) outlines the requirements for water regulation in the upper Yellow River during ice flood periods. YRCC is developing measures that not only safeguard against ice floods, but also assure the availability of adequate water resources. These provide the overall requirements for developing an ice regime forecasting system including lead-time prediction and required accuracy. In order to develop such a system, numerical modelling of ice floods is an essential component of current research at the YRCC, together with field observations and laboratory experiments. In order to properly model river ice processes it is necessary to adjust the hydrodynamic equations to account for thermodynamic effects. In this research, hydrological and meteorological data from 1950 to 2010 were used to analyse the characteristics of ice regimes in the past. Also, additional field observations were carried out for ice flood model calibration and validation. By combining meteorological forecasting models with statistical models, a medium to short range air temperature forecasting model for the Ning-Meng reach was established. These results were used to improve ice formation modelling and prolong lead-time prediction. The numerical ice flood model developed in this thesis for the Ning-Meng reach allows better forecasting of the ice regime and improved decision support for upstream reservoir regulation and taking appropriate measures for disaster risk reduction.

This textbook describes rules and procedures for the use of Differential Operators (DO) in Ordinary Differential Equations (ODE). The book provides a detailed theoretical and numerical description of ODE. It presents a large variety of ODE and the chosen groups are used to solve a host of physical problems. Solving these problems is of interest primarily to students of science, such as physics, engineering, biology and chemistry. Scientists are greatly assisted by using the DO obeying several simple algebraic rules. The book describes these rules and, to help the reader, the vocabulary and the definitions used throughout the text are provided. A thorough description of the relatively straightforward methodology for solving ODE is given. The book provides solutions to a large number of associated problems. ODE that are integrable, or those that have one of the two variables missing in any explicit form are also treated with solved problems. The physics and applicable mathematics are explained and many associated problems are analyzed and solved in detail. Numerical solutions are analyzed and the level of exactness obtained under various approximations is discussed in detail.

This edited volume collects six surveys that present state-of-the-art results on modeling, qualitative analysis, and simulation of active matter, focusing on specific applications in the natural sciences. Following the previously published Active Particles volumes, these chapters are written by leading experts in the field and reflect the diversity of subject matter in theory and applications within an interdisciplinary framework. Topics covered include: Variability and heterogeneity in natural swarms Multiscale aspects of the dynamics of human crowds Mathematical modeling of cell collective motion triggered by self-generated gradients Clustering dynamics on graphs Random Batch Methods for classical and quantum interacting particle systems The consensus-based global optimization algorithm and its recent variants Mathematicians and other members of the scientific community interested in active matter and its many applications will find this volume to be a timely, authoritative, and valuable resource.

This title was first published in 2003. India's tax revenues depend on manufacturing while agriculture and services generate employment. WTO's Uruguay and Doha rounds imply large tariff cuts. This affects the competitiveness of the Indian manufacturing sector and has implications for government deficits. Excessive dependence on indirect taxes and subsidies to regulate markets introduces distortions and is incompatible with free market principles. The book analyses welfare implications of fiscal and trade policies for India. To put the results in perspective, developments in trade theory, public finance and Computable General Equilibrium (CGE) modelling are covered. Theoretical results are juxtaposed with empirical findings from these models. Methodology to construct CGE models is also covered. The trade model covers tariff cuts under various assumptions besides incorporating "new trade theory". As tax reforms and tariff cuts are independent, past tax reforms like MODVAT (MODified VAT) and proposed reforms like VAT, elimination/reduction of subsidies are covered using a separate tax model.

Researchers in the natural sciences are faced with problems that require a novel approach to improve the quality of forecasts of processes that are sensitive to environmental conditions. Nonlinearity of a system may significantly complicate the predictability of future states: a small variation of parameters can dramatically change the dynamics, while sensitive dependence of the initial state may severely limit the predictability horizon. Uncertainties also play a role. This volume addresses such problems by using tools from chaos theory and systems theory, adapted for the analysis of problems in the environmental sciences. Sensitive dependence on the initial state (chaos) and the parameters are analyzed using methods such as Lyapunov exponents and Monte Carlo simulation. Uncertainty in the structure and the values of parameters of a model is studied in relation to processes that depend on the environmental conditions. These methods also apply to biology and economics. This text aims to be suitable for research workers at universities and (semi-) governmental institutes for the environment, agriculture, ecology, meteorology and water management, and theoretical economists.

Reliability is an essential concept in mathematics, computing, research, and all disciplines of engineering, and reliability as a characteristic is, in fact, a probability. Therefore, in this book, the author uses the statistical approach to reliability modelling along with the MINITAB software package to provide a comprehensive treatment of modelling, from the basics through advanced modelling techniques. The book begins by presenting a thorough grounding in the elements of modelling the lifetime of a single, non-repairable unit. Assuming no prior knowledge of the subject, the author includes a guide to all the fundamentals of probability theory, defines the various measures associated with reliability, then describes and discusses the more common lifetime models: the exponential, Weibull, normal, lognormal and gamma distributions. She concludes the groundwork by looking at ways of choosing and fitting the most appropriate model to a given data set, paying particular attention to two critical points: the effect of censored data and estimating lifetimes in the tail of the distribution. The focus then shifts to topics somewhat more difficult: the difference in the analysis of lifetimes for repairable versus non-repairable systems and whether repair truly "renews" the system methods for dealing with system with reliability characteristic specified for more than one component or subsystem the effect of different types of maintenance strategies the analysis of life test data The final chapter provides snapshot introductions to a range of advanced models and presents two case studies that illustrate various ideas from throughout the book.

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale network optimization problems.

This book includes selected contributions on applied mathematics, numerical analysis, numerical simulation and scientific computing related to fluid mechanics problems, presented at the FEF-"Finite Element for Flows" conference, held in Rome in spring 2017. Written by leading international experts and covering state-of-the-art topics in numerical simulation for flows, it provides fascinating insights into and perspectives on current and future methodological and numerical developments in computational science. As such, the book is a valuable resource for researchers, as well as Masters and Ph.D students.

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in Matlab(r). Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given.

This title was first published in 2002: Why do endogenous cycles persist in Spain? Manuel Roman demonstrates a highly novel approach to the study of finance and the persistence of endogenous growth cycles, providing a balanced account of the Post Keynesian, Classical and Neo-classical political economy approaches. Finding key propositions from a representative set of heterodox cycles' models, he rigorously tests their chief claims, grounding his research in empirical data. The endogenous forces behind persistent fluctuations in the Spanish economy are also identified and explored in this theoretically rich text, the first of its kind to examine the Spanish economy in such great detail.

Updated to textbook form by popular demand, this second edition discusses diverse mathematical models used in economics, ecology, and the environmental sciences with emphasis on control and optimization. It is intended for graduate and upper-undergraduate course use, however, applied mathematicians, industry practitioners, and a vast number of interdisciplinary academics will find the presentation highly useful. Core topics of this text are: * Economic growth and technological development * Population dynamics and human impact on the environment * Resource extraction and scarcity * Air and water contamination * Rational management of the economy and environment * Climate change and global dynamics The step-by-step approach taken is problem-based and easy to follow. The authors aptly demonstrate that the same models may be used to describe different economic and environmental processes and that similar investigation techniques are applicable to analyze various models. Instructors will appreciate the substantial flexibility that this text allows while designing their own syllabus. Chapters are essentially self-contained and may be covered in full, in part, and in any order. Appropriate one- and two-semester courses include, but are not limited to, Applied Mathematical Modeling, Mathematical Methods in Economics and Environment, Models of Biological Systems, Applied Optimization Models, and Environmental Models. Prerequisites for the courses are Calculus and, preferably, Differential Equations.

This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can be used as a reference for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for professionals such as petroleum engineers, mining engineers, chemists, mechanical engineers, biologists, biology and medical engineering, applied mathematicians, and others who perform mathematical modeling.

High temperature, high oil pressure, oil and gas well completion testing have always been a technical challenge and basic theoretical research is one of the key factors needed to ensure a successful completion test. The completion test basic theory includes: a stress analysis of the completion string, completion string buckling behavior, and temperature and pressure distribution prediction. The completion string is the main bearing and power transmission component for oil and gas well operations and production, and it is required to take on a combination of loads, which result in completion string deformation. Because of these complex relationships, completion string stress analysis has become increasingly more complicated. This book discusses the characters of tubular strings in HTHP (High Temperature - High Pressure) oil and gas wells. These characters include the mechanical behavior of tubular strings and the temperature and pressure variation of tubular strings in different conditions. Mathematical models are established for different conditions and solution existence and uniqueness of some models is discussed, providing algorithms corresponding to the different models. Numerical experiments are presented to verify the validity of models and the feasibility of algorithms, and the impact of the parameters of models for oil and gas wells is also discussed. This book is written for production and testing engineers to provide them with the tools to deal more effectively with the numerical decisions they have to take and for researchers and technicians in petroleum and gas testing and production engineering. Finally, it is also intended to serve as a reference book for mathematicians, college teachers and students.

Stephen Trudgill presents an internationally authored research-level text, aimed at providing a synopsis of developments in solute modelling in catchment ecosystems over the last ten years. The volume includes particular advances in solute modelling, especially at the catchment scale, emphasising the influences of weathering, ecosystem processes and hydrological processes as well as the application of models and modelling principles. The intended audience for the book is research scientists in cognate fields and postgraduate research workers, although it is especially aimed at those interested in catchment systems. It will also enable specialists to grasp the essentials of topics outside their own field. The book will be of use in a management context as successful water quality management actions are often dependent upon the predictive success of models. It will also show how models can be used to assess the sensitivity of solute production to environmental change and human influence, such as land use change and variation in atmospheric inputs, focussing upon surface catchments rather than groundwater and soil solutes.

This book is a collection of state-of-the-art surveys on various topics in mathematical finance, with an emphasis on recent modelling and computational approaches. The volume is related to a a ~Special Semester on Stochastics with Emphasis on Financea (TM) that took place from September to December 2008 at the Johann Radon Institute for Computational and Applied Mathematics of the Austrian Academy of Sciences in Linz, Austria.

From artificial neural net / game theory / semantic applications, to modeling tools, smart manufacturing systems, and data science research - this book offers a broad overview of modern intelligent methods and applications of machine learning, evolutionary computation, Industry 4.0 technologies, and autonomous agents leading to the Internet of Things and potentially a new technological revolution. Though chiefly intended for IT professionals, it will also help a broad range of users of future emerging technologies adapt to the new smart / intelligent wave. In separate chapters, the book highlights fourteen successful examples of recent advances in the rapidly evolving area of intelligent systems. Covering major European projects paving the way to a serious smart / intelligent collaboration, the chapters explore e.g. cyber-security issues, 3D digitization, aerial robots, and SMEs that have introduced cyber-physical production systems. Taken together, they offer unique insights into contemporary artificial intelligence and its potential for innovation.

The use of mathematical modeling in engineering allows for a significant reduction of material costs associated with design, production, and operation of technical objects, but it is important for an engineer to use the available computational approaches in modeling correctly. Taking into account the level of modern computer technology, this new volume explains how an engineer should properly define the physical and mathematical problem statement, choose the computational approach, and solve the problem by proven reliable computational approach using computer and software applications during the solution of a particular problem. This work is the result of years of the authors' research and experience in the fields of power and rocket engineering where they put into practice the methods of mathematical modeling shown in this valuable volume. The examples in the book are based on two approaches. The first approach involves the use of the relatively simple mathematical system MathCad. The second one involves the solving of problems using Intel Visual Fortran compiler with IMSL Libraries. The use of other software packages (Maple, MathLab, Mathematica) or compilers ( , ++, Visual Basic) for code is equally acceptable in the solution of the problems given in the book. Intended for professors and instructors, scientific researchers, students, and industry professionals, the book will help readers to choose the most appropriate mathematical modeling method to solve engineering problems, and the authors also include methods that allow for the solving of nonmathematical problems as mathematical problems.

A comprehensive mathematical and computational modeling of CO2 Geosequestration and Compressed Air Energy Storage Energy and environment are two interrelated issues of great concern to modern civilization. As the world population will soon reach eight billion, the demand for energy will dramatically increase, intensifying the use of fossil fuels. Utilization of fossil fuels is by far the largest anthropogenic source of CO2 emission into the earth's atmosphere. This unavoidable reality necessitates efforts to mitigate CO2 from indefi nitely being emitted in the atmosphere. CO2 geo-sequestration is currently considered to be a vital technology for this purpose. Meanwhile, and as fossil fuels will sooner or later be depleted, utilization of renewable energy resources is inevitable. Nowadays, wind and solar energy, being clean and sustainable, are gaining momentum. However, their availability is intermittent. This intermittent nature of solar and wind energy necessitates storing the produced energy at off-peak times for later use. Compressed air energy storage in subterranean caverns, aquifers and coal seams is currently considered to be a plausible technology for this purpose. CO2 geo-sequestration and compressed air energy storage are thus vital technologies for current and future energy strategy development. These technologies can be made safe and cost-effective by utilizing computational tools capable of simulating the involved multiphysical phenomena and processes. Computational modeling of such systems is challenging and resource-consuming. Meeting such a challenge constitutes the focal point of this book. This book addresses comprehensive theoretical and computational modeling aspects of CO2 geosequestration and compressed air energy storage. The book consists of 16 chapters authored by prominent researchers in these two fi elds. The authors of the book endeavoured to present years of innovative work, making it available for a wide range of readers, including geoscientists, poromechanists, applied mathematicians, computational geoscientists, geologists and reservoir engineers.

This book presents a selection of advanced case studies that cover a substantial range of issues and real-world challenges and applications in space engineering. Vital mathematical modeling, optimization methodologies and numerical solution aspects of each application case study are presented in detail, with discussions of a range of advanced model development and solution techniques and tools. Space engineering challenges are discussed in the following contexts: *Advanced Space Vehicle Design *Computation of Optimal Low Thrust Transfers *Indirect Optimization of Spacecraft Trajectories *Resource-Constrained Scheduling, *Packing Problems in Space *Design of Complex Interplanetary Trajectories *Satellite Constellation Image Acquisition *Re-entry Test Vehicle Configuration Selection *Collision Risk Assessment on Perturbed Orbits *Optimal Robust Design of Hybrid Rocket Engines *Nonlinear Regression Analysis in Space Engineering *Regression-Based Sensitivity Analysis and Robust Design *Low-Thrust Multi-Revolution Orbit Transfers *Modeling and Optimization of Balance Layout Problems *Pilot-Induced Oscillations Alleviation *Modeling and Optimization of Hybrid Transfers to Near-Earth Objects *Probabilistic Safety Analysis of the Collision Between Space Debris and Satellite *Flatness-based Low-thrust Trajectory Optimization for Spacecraft Proximity Operations The contributing authors are expert researchers and practitioners in either the space engineering and/or in the applied optimization fields. Researchers and practitioners working in various applied aspects of space engineering will find this book practical and informative. Academics, graduate and post-graduate students in aerospace engineering, applied mathematics, operations research, optimization, and optimal control, will find this book useful.

This volume collects together research and survey papers written by invited speakers of the conference celebrating the 70th birthday of Laszlo Lovasz. The topics covered include classical subjects such as extremal graph theory, coding theory, design theory, applications of linear algebra and combinatorial optimization, as well as recent trends such as extensions of graph limits, online or statistical versions of classical combinatorial problems, and new methods of derandomization. Laszlo Lovasz is one of the pioneers in the interplay between discrete and continuous mathematics, and is a master at establishing unexpected connections, "building bridges" between seemingly distant fields. His invariably elegant and powerful ideas have produced new subfields in many areas, and his outstanding scientific work has defined and shaped many research directions in the last 50 years. The 14 contributions presented in this volume, all of which are connected to Laszlo Lovasz's areas of research, offer an excellent overview of the state of the art of combinatorics and related topics and will be of interest to experienced specialists as well as young researchers.

The main objective of the book is to highlight the modeling of magnetic particles with different shapes and magnetic properties, to provide graduate students and young researchers information on the theoretical aspects and actual techniques for the treatment of magnetic particles in particle-based simulations. In simulation, we focus on the Monte Carlo, molecular dynamics, Brownian dynamics, lattice Boltzmann and stochastic rotation dynamics (multi-particle collision dynamics) methods. The latter two simulation methods can simulate both the particle motion and the ambient flow field simultaneously. In general, specialized knowledge can only be obtained in an effective manner under the supervision of an expert. The present book is written to play such a role for readers who wish to develop the skill of modeling magnetic particles and develop a computer simulation program using their own ability. This book is therefore a self-learning book for graduate students and young researchers. Armed with this knowledge, readers are expected to be able to sufficiently enhance their skill for tackling any challenging problems they may encounter in future.

This proceedings volume convenes selected, peer-reviewed papers presented at the 3rd International Conference on Mathematics and its Applications in Science and Engineering - ICMASE 2022, which was held on July 4-7, 2022 by the Technical University of Civil Engineering of Bucharest, Romania. Works in this volume cover new developments in applications of mathematics in science and engineering, with emphasis on mathematical and computational modeling of real-world problems. Topics range from the use of differential equations to model mechanical structures to the employ of number theory in the development of information security and cryptography. Educational issues specific to the acquisition of mathematical competencies by engineering and science students at all university levels are also touched on. Researchers and university students are the natural audiences for this book, which can be equally appealing to practitioners seeking up-to-date techniques in mathematical applications to different contexts and disciplines.

This book summarizes a series of research work on integrated process planning and scheduling (IPPS) done by the authors, focusing on discussing the properties, novel solution methods and applications of process planning, scheduling and IPPS problems under different machining environments. It is a valuable reference resource for teachers, students and researchers working in the fields of engineering, management science and other related disciplines.