Mathematics, Statistics, Computer Science and Physics Quarterly UpdateApril, May and June 2015

Mathematics

Introduction to Mathematical Logic, Sixth Edition Elliott Mendelson, Queens College, Flushing, New York, USA ISBN: 978-1-4822-3772-6 May 2015 | 235 x 156 | 516pp | Hb | £57.95 | illus: 28 b/w, Editor: Ross, Robert Text type: Textbook Market: Math

This best-selling, classic textbook continues to provide a complete one-semester introduction to mathematical logic. The sixth edition incorporates recent work on Gödel’s second incompleteness theorem as well as an appendix on consistency proofs for first-order arithmetic. It also offers historical perspectives and many new exercises of varying difficulty, which motivate and lead students to an in-depth, practical understanding of the material.

Key Features:

Gives a careful, thorough explanation of Gödel’s ideas on completeness and incompleteness

Provides numerous useful examples to motive students

Presents a consistency proof of first-order arithmetic

Includes updated exercise sets at the end of each section

Solutions manual available upon qualifying course adoption

Audience: Undergraduate students taking a mathematical logic course; general mathematics readers.

Related titles: A First Course in Fuzzy Logic, Third Edition -- 978-1-58488-526-9 Sets, Functions, and Logic -- 978-1-58488-449-1 Combinatory Logic -- 978-1-4398-0000-3

Mathematics

Measure Theory and Fine Properties of Functions, Revised Edition Lawrence Craig Evans, University of California, Berkeley, USA and Ronald F. Gariepy, University of Kentucky, Lexington, USA ISBN: 978-1-4822-4238-6 April 2015 | 235 x 156 | 309pp | Hb | £46.99 | illus: 15 b/w, Editor: Ross, Robert Text type: Textbook Market: Mathematics

This book provides a detailed examination of the central assertions of measure theory in n-dimensional Euclidean space. It emphasizes the roles of Hausdorff measure and the capacity in characterizing the fine properties of sets and functions. The book covers theorems and differentiation in R

n , Hausdorff measures, area and coarea formulas for Lipschitz mappings and

related change-of-variable formulas, and Sobolev functions and functions of bounded variation. This second edition includes countless improvements in notation, format, and clarity of exposition. Also new are several sections describing the π-λ theorem, weak compactness criteria in L

1, and Young measure methods for weak convergence. In addition, the bibliography has

been updated.

Key Features:

Features careful examination and clearly written presentation of the central assertions of measure theory in n-dimensional Euclidean space

Presents complete proofs of key results often omitted in other books

Incorporates succinct, but complete proofs

Includes new examples, graphics, and exercises throughout

Provides extensive new references to applications

Updates the index and references

Audience: Upper undergraduate and graduate students taking a course on measure theory, analysis, or integration; professional mathematicians.

Related titles: Applied Functional Analysis, Second Edition -- 978-1-4200-9195-3 Real Analysis and Foundations, Second Edition -- 978-1-58488-483-5 Sets, Functions, and Logic -- 978-1-58488-449-1

Mathematics

Advanced Linear Algebra, Second Edition Bruce Cooperstein, University of California, Santa Cruz, USA ISBN: 978-1-4822-4884-5 April 2015 | 229 x 152 | 610pp | Hb | £57.99 | illus: 9 b/w, Editor: Ross, Robert Text type: Textbook Market: Mathematics

Introducing vector spaces over fields as well as the fundamental concepts of linear combinations, span of vectors, linear independence, basis, and dimension, this book discusses the algebra of polynomials with coefficients in a field, concentrating on results that are consequences of the division algorithm. It develops the structure theory of a linear operator on a finite dimensional vector space and explores inner product spaces from the GramSchmidt process to the spectral theorems for normal and self- adjoined operators.

Key Features:

Discusses the structure theory of an operator, various topics on inner product spaces, and the trace and determinant functions of a linear operator

Covers bilinear forms with a full treatment of symplectic spaces and orthogonal spaces

Explains the construction of tensor, symmetric, and exterior algebras

Includes a new section seven on linear groups (the group of invertible operators on a finite dimensional vector space)

Offers a new chapter on sesquilinear forms and their isometries

Audience Textbook for advanced or second level linear algebra course for undergraduates or graduate mathematics majors

Related titles: Handbook of Linear Algebra, Second Edition -- 978-1-4665-0728-9 A Combinatorial Approach to Matrix Theory and Its Applications -- 978-1-4200-8223-4 Finite-Dimensional Linear Algebra -- 978-1-4398-1563-2

Statistics

Handbook of Design and Analysis of Experiments Angela Dean, Ohio State University, USA, Max Morris, Iowa State University, USA, John Stufken, Arizona State University, USA and Derek Bingham, Simon Fraser University, Canada ISBN: 978-1-4665-0433-2 June 2015 | 254 x 178 | 984pp | Hb | £76.99 | illus: 144 b/w, 130 tables Editor: Calver, Rob Text type: Professional Market: Statistics

This handbook presents a comprehensive, carefully edited collection of chapters that explore the state of the art in the theory and applications of designed experiments and their analyses. Divided into seven parts, the book covers the history and general principles, designs for linear models, fractional factorial designs, optimal designs, computer experiments, issues that span various fields, and designs for the latest applications. Balancing coverage of methodology and applications, it is accessible to graduate students and new researchers needing an overview of the area. Key Features:

Provides a complete overview of the theory and modern applications

Covers key topics, such as linear models, fractional factorial designs, and optimal designs

Includes contributions from leading statisticians and researchers

Contributors from USA, Canada, UK, South Africa, India, Italy and Germany. Audience: Graduate students and researchers in statistics, industrial engineering, manufacturing, pharmaceutical industry, and life sciences. Related titles: Design and Analysis of Experiments with R -- 978-1-4398-6813-3 Theory of Factorial Design: Single- and Multi-Stratum Experiments -- 978-1-4665-0557-5 Design of Experiments: An Introduction Based on Linear Models -- 978-1-58488-923-6 Analysis of Messy Data Volume 1 -- 978-1-58488-334-0 Competitor:

Handbook of Statistics 13: Design and Analysis of Experiments, Rao & Ghosh, 1996, Elsevier

Statistics

Statistics for Finance Erik Lindström, Lund University, Sweden, Henrik Madsen, Technical University of Denmark, Lyngby and Jan Nygaard Nielsen ISBN: 978-1-4822-2899-1 May 2015 | 235 x 156 | 384pp | Hb | £57.99 | illus: 63 b/w, 11 tables Editor: Calver, Rob Text type: Textbook Market: Statistics

This text develops students’ professional skills in statistics with applications in finance. It bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The authors explain how various statistical and mathematical tools are used to price financial derivatives, identify interest rate models, and much more. The book includes examples, case studies, cross references, and end-of-chapter problems. Key Features:

Provides material for courses in financial econometrics and financial mathematics

Describes the modern theory of financial derivatives from an empirical point of view, focusing on identification and estimation theory

Presents the main ideas of proofs, avoiding tedious technical details

Connects the concepts through examples, case studies, and cross references throughout the book

Includes end-of-chapter problems that assess students’ understanding of both simple and complex mathematical concepts

Based on courses taught at TU Denmark and Lund, and already used throughout Scandinavia.

Solutions manual and figure slides available upon qualifying course adoption

Audience: Senior undergraduate and graduate students in statistics and mathematics; researchers in statistics, mathematics, economics, and finance. Related titles: A Course on Statistics for Finance -- 978-1-4398-9254-1 Statistical Methods for Financial Engineering -- 978-1-4398-5694-9 Stochastic Financial Models -- 978-1-4200-9345-2 Competitor:

Statistics and Data Analysis for Financial Engineering. Springer.Ruppert, 2010

Statistics

Modeling to Inform Infectious Disease Control Niels G. Becker, Australian National University, Canberra, Australia ISBN: 978-1-4987-3106-5 May 2015 | 235 x 156 | 208pp | Hb | £57.99 | illus: 43 b/w, 33 tables, Editor: Calver, Rob Text type: Professional Market: Statistics

Statistical modeling is increasingly used to inform infectious disease control, but the complex nature of the methods can make them difficult for public health professionals to apply. This book provides an accessible and practical introduction to the modeling of infectious diseases, enabling these professionals to use the techniques for effective infectious disease management. The mathematical details are kept to a minimum, with some provided in appendices, so that the methods can be understood by applied researchers. The book includes plenty of real examples to illustrate the application of the methods along with exercises to enable use as a course text. Key Features:

Provides an accessible and practical introduction to the modeling of infectious diseases

Focuses on practical application, keeping the mathematical details restricted to appendices

Contains many real examples to illustrate the methods

Offers practical guidance that can be used for effective infectious disease management

Includes exercises to enable use as a course text

Author is well known internationally; based in Australia, originally from Scandinavia. Audience:

Graduate students and researchers from biostatistics and epidemiology and Practitioners working for government agencies.

Related titles: Analysis of Infectious Disease Data -- 978-0-412-30990-8 Bayesian Disease Mapping -- 978-1-4665-0481-3 Biosurveillance -- 978-1-4398-0046-1 Competitor:

An Introduction to Infectious Disease Modelling. Oxford, Vynnycky & White, 2010

Statistics

Introductory Statistics for the Health Sciences Lise DeShea, University of Oklahoma, Oklahoma City, USA and Larry E. Toothaker, University of Oklahoma, Oklahoma City, USA ISBN: 978-1-4665-6533-3 April 2015 | 235 x 156 | 603pp | Hb | £63.99 | illus: 151 colours, 39 tables Editor: Grubbs, David Text type: Textbook Market: Statistics

This textbook provides students entering a health sciences program with a strong, practical foundation in statistics. Real research examples and data sets from many areas in the health sciences illustrate descriptive and inferential statistics, interval estimation, graphing, probability, and other topics. In color throughout, the book can be used in a first-semester course in a health sciences program or in a service course for undergraduate students. Electronic flashcards for smartphones and data sets are available via a supplementary website.

Key Features:

Presents lively examples drawing on data from real research studies, such as exercise during pregnancy and tai chi for patients with a chronic condition, in an understandable way for math-phobic learners

Emphasizes conceptual understanding, with formulas introduced only when necessary to support concepts

Requires no prior knowledge of statistics and builds from a foundational chapter about research and variables

Offers many student-friendly features, including a conversational writing style, frequent Check Your Understanding questions and answers, chapter exercises enlivened by understandable research scenarios, and e-flashcards for iOS and Android devices

Demonstrates transparency in research by offering all data sets, figures, and graphing code via an online data repository described on a supplementary website

Solutions manual and figure slides available upon qualifying course adoption

Audience: Students taking an introductory statistics course in preparation for or as part of a health sciences program (such as nursing or allied health).

Related titles: Practical Statistics for Medical Research -- 978-0-412-27630-9 Medical Biostatistics, Second Edition -- 978-1-58488-887-1 Introduction to Statistical Data Analysis for the Life Sciences -- 978-1-4398-2555-6

Competitor:

Biostatistics for the Health Sciences, Blair/Taylor, 2007, Prentice Hall, 552 pp

Statistics

Introductory Adaptive Trial Designs A Practical Guide with R Mark Chang, AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA ISBN: 978-1-4987-1746-5 June 2015 | 235 x 156 | 232pp | Hb | £49.99| illus: 19 b/w, 55 tables Editor: Grubbs, David Text type: Professional Market: Statistics

Instead of providing black box-like general commercial software packages, this tutorial-style book develops the R functions and algorithms necessary to customize adaptive designs to meet their needs. Designed as a practical, tutorial style resource, the book provides a 30 minute R tutorial and includes simulations for all examples.

Key Features:

By learning through doing, the reader doesn’t need to buy any software package, but instead can download the

popular freeware R and do adaptive design immediately.

Very practically focused

For those who do not have any experience with R, there is a 30 minute tutorial in Appendix A.

Helps newcomers quickly get a feel of adaptive designs and grasp the foundations of adaptive design methods

without having to commit a huge amount of time and effort Audience:

Statisticians and students in the pharmaceutical sciences

Related titles: Adaptive Design Methods in Clinical Trials, Second Edition -- 978-1-4398-3987-4 Adaptive Design Theory and Implementation Using SAS and R, Second Edition -- 978-1-4822-5659-8 Bayesian Adaptive Methods for Clinical Trials -- 978-1-4398-2548-8 Competitor:

Clinical Trial Design: Bayesian and Frequentist Adaptive Methods, Yin, , Wiley 2012, 364pp

Statistics

Parallel Computing for Data Science With Examples in R, C++ and CUDA Norman Matloff, University of California, Davis, USA ISBN: 978-1-4665-8701-4 June 2015 | 235 x 156 | 328pp | Hb | £38.99 | illus: 7 b/w, 4 tables Editor: Kimmel, John Text type: Professional Market: Statistics

With a focus on multicore machines and clusters as well as GPU computing, this book covers parallel R in the broad context of the general principles of parallel computing. It gives concrete technical details on the various packages and methods of parallel computation in R, along with numerous examples of code. The book also explains general parallel programming issues, including loop scheduling, communications delays, and the implications of hardware structures on communications delays.

Key Features: Add international features to this list is any

Presents the material on parallel R in the broad context of the general principles of parallel computing

Focuses on multicore machines and clusters as well as GPU computing

Explains how parallel programming is executed

Includes techniques for debugging

Audience: Researchers and graduate students using R to analyze large data sets. Related titles: Statistical Computing with R -- 978-1-58488-545-0 Introduction to Scientific Programming and Simulation Using R -- 978-1-4200-6872-6 Statistical Computing in C++ and R -- 978-1-4200-6650-0 Competitor:

Parallel R, McCallum, O’Reilly, 2011, 126 pp

Statistics

Data Science in R A Case Studies Approach to Computational Reasoning and Problem Solving Deborah Nolan, University of California, Berkeley, USA and Duncan Temple Lang, University of California, Davis, USA ISBN: 978-1-4822-3481-7 April 2015 | 254 x 178 | 539pp | Pb | £49.99 | illus: 79 b/w, Editor: Kimmel, John Text type: Professional Market: Statistics

This book explains the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book’s collection of projects, exercises, and sample solutions encompass practical topics pertaining to data processing and analysis. The book can be used for self-study or as supplementary reading in a statistical computing course, allowing students to gain valuable data science skills.

Key Features:

Explores how computing is done for a broad range of data science problems

Includes authentic real-world data analysis projects that tie concepts into a data science workflow and illustrate the everyday activities of data scientists across a spectrum of fields

Shows how to read and transform raw data, manipulate and visualize the resulting data, and use statistical techniques to solve a problem or understand relationships between variables

Describes the use of simulation to understand stochastic processes and model interesting situations

Covers various data technologies, including databases, visualization with KML, and scraping data from Web pages with HTTP requests and text processing

Audience: Graduate students and practitioners in statistical computing and applied statistics.

Related titles: R Programming for Bioinformatics -- 978-1-4200-6367-7 Data Mining with R -- 978-1-4398-1018-7

Competitor:

Doing Data Science: Straight Talk from the Frontline, O’Reilly, O’Neil, 2913pp

Statistics

Statistical Learning with Sparsity The Lasso and Generalizations Trevor Hastie, Stanford University, California, USA, Robert Tibshirani, Stanford University, California, and Martin Wainwright, Department of Statistics, University of California, Berkeley ISBN: 978-1-4987-1216-3 June 2015 | 235 x 156 | 349pp | Hb | £57.99| illus: 99 colours, 11 colour tables Editor: Kimmel, John Text type: Reference Market: Statistics

Written by leading experts, this book discusses new methods for dealing with high-dimensional data. It summarizes the actively developing field of statistical learning with sparsity. Covering matrix decomposition, graphical models, compressed sensing, and more, it will be of interest to people analyzing data in many scientific disciplines.

Key Features:

Gives a comprehensive view and theoretical insights on general penalization procedures

Demonstrates, using real datasets, which displays to draw to reveal the information in data

Describes all graphic types use in the book with lists of the analyses in which they are applied

Audience:

Researchers and graduate students in many disciplines interested in statistical learning and machine learning.

Related titles: R Graphics, Second Edition -- 978-1-4398-3176-2 Machine Learning -- 978-1-4200-6718-7 Machine Learning -- 978-1-4665-8328-3 Statistical Learning for High-Dimensional Data -- 978-1-4665-1084-5 Competitor:

An Introduction to Statistical Learning, 978-1461471370, James, 2013, Springer

Statistics

Graphical Data Analysis with R Antony Unwin, University of Augsburg ISBN: 978-1-4987-1523-2 May 2015 | 235 x 156 | 308pp | Hb | £44.99 | illus: 135 colours, 2 tables Editor: Kimmel, John Text type: Professional Market: Statistics

Graphical data analysis is a basic principle of sound graphical design useful for data cleaning, exploring data, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. This book offers a wide array of graphical displays for a data presentation that includes modern tools for data visualization and representation. The book demonstrates the method of drawing information from real datasets since seeing graphics in action will be more helpful to readers than discussing theoretical properties.

Key Features:

Displays method to draw information from real datasets

Explains every graphic in detail: why it was chosen, what story it tells, and how to draw it in R

Demonstrates how all data analyses are structured in the same way

Describes how graphic types are used in the book and lists of the analysis in which they are applied

Audience:

Explains why you draw graphics to display data and which graphics to draw using R.

Related titles: Graphics for Statistics and Data Analysis with R -- 978-1-58488-087-5 Interactive Graphics for Data Analysis -- 978-1-58488-594-8 Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition -- 978-1-4822-3736-8 Competitor:

R Graphics Cookbook, Chang, 2013, O’Reilly

Statistics

Reproducible Research with R and R Studio, Second Edition Christopher Gandrud, Hertie School of Governance, Berlin, Germany ISBN: 978-1-4987-1537-9 June 2015 | 235 x 156 | 326pp | Pb | £44.99 | illus: 31 b/w, 16 tables Editor: Kimmel, John Text type: Professional Market: Statistics

This book brings much of this information on reproducible research together in one accessibly written text. It presents a practical reproducible research workflow that researchers in any quantitative empirical discipline can use to gather data, analyze it, and dynamically present the results. In doing so, it gives practical instruction in how to utilize a number of recent technological advances as part of a reproducible research workflow.

Key Features:

Provides researchers with a reproducible research workflow for using R/RStudio to make the entire research process reproducible—from data gathering, to analysis, to presentation

Includes instructions not only for creating reproducible research in R, but also extensively discusses how to take advantage of recent developments in RStudio

Emphasizes the presentation of reproducible research with non-print formats such as HTML5 slideshows, blogs, and other web-based content

Covers a range of techniques to organize and remotely store files at all stages of the research process, which both streamlines the research process—especially by making revisions easier—and enhances reproducibility

Audience:

Book and journal authors who want to document their research; applies to many disciplines

Related titles: Implementing Reproducible Research -- 978-1-4665-6159-5 Competitor:

Bioinformatics Data Skills: Reproducible Robust Research with Open Source Tools, Buffalo, 2015.

Statistics

Dynamic Documents with R and knitr, Second Edition Yihui Xie, RStudio ISBN: 978-1-4987-1696-3 March 2017 | 235 x 156 | 288pp | Pb | £44.99| illus: 70 b/w, 4 tables Editor: Kimmel, John Text type: Professional Market: Statistics

The first edition of this book was written with the knitr package version 1.4 which was released more than a year ago. There have been quite a few changes during the development of this package as well as a few useful new features in the RStudio IDE. This new edition gives a detailed introduction on R Markdown support in the RStudio IDE and shows what one can do with the simple markdown language due to its integration with Pandoc. Key Features:

Makes report writing easier for both beginners and advanced users

Explains basic and advanced applications of knitr, a popular program created by the author that was designed for doing reproducible research

Offers the option of using R, Python, LaTeX, Markdown and other programs

Audience:

Book and journal authors who want to document their research; applies to many disciplines

Related titles: Implementing Reproducible Research -- 978-1-4665-6159-5 Reproducible Research with R and R Studio -- 978-1-4665-7284-3 Reproducible Research with R and R Studio, Second Edition -- 978-1-4987-1537-9 Competitor

Bioinformatics Data Skills: Reproducible Robust Research with Open Source Tools, Buffalo, 2015

Computer Science

Game AI Pro 2 Collected Wisdom of Game AI Professionals Edited by Steven Rabin, Bothell, Washington, USA ISBN: 978-1-4822-5479-2 May 2015 | 235 x 191 | 575pp | Hb | £49.99 | illus: 177 b/w, 20 tables, Editor: Adams, Rick Text type: Professional Market: Computer Game Development

Game AI Pro

2 presents cutting-edge tips, tricks, and techniques for artificial intelligence (AI) in games, drawn from developers

of shipped commercial games as well as some of the best-known academics in the field. It contains knowledge, advice, hard-earned wisdom, and insights gathered from across the community of developers and researchers who have devoted themselves to game AI. The book provides a toolbox of proven techniques that can be applied to many common and not-so-common situations. Key Features:

Edited volume in popular area of gaming with well-known cadre of international contributors.

Audience: Computer Game Developers and Designers. Computer Graphics Professionals. Related titles: Unreal Game Development -- 978-1-56881-459-9 Maya Python for Games and Film -- 978-0-12-378578-7 GPU Pro 4 -- 978-1-4665-6743-6 Competitor: AI Programming Wisdom (Vols 1-4)" Rabin, Charles River Media, 2008, 640pp

Computer Science

Numerical Algorithms Methods for Computer Vision, Machine Learning, and Graphics Justin Solomon, Stanford University, California, USA ISBN: 978-1-4822-5188-3 April 2015 | 254 x 178 | 392pp | Pack - Book and Ebook | £49.99 | illus: 132 b/w, 14 tables Editor: Cohen, Randi Text type: Textbook Market: Computer Science

Most existing textbooks on this subject were written either for mathematics or engineering students and do not address the unique situation of computer science students, who have some background in discrete mathematics but less familiarity with continuous methods of proof and algorithms. This book is written specifically for those students, filled throughout with practical examples using the algorithms being taught. The book also teaches theory in the context of application in parallel by delving into real-world problems in computer graphics and computer vision. Key Features:

Focuses on CS applications of numerical methods rather than describing them in the abstract

Provides applications to learning, graphics, and other fields in CS worked out in detail

Derivation of each algorithm from scratch with limited math background necessary

Contains a unified treatment of broad numerical topics with grounding in practical problems

Includes pointers to more detailed resources, applications, and related recent research

Audience: Advanced undergraduate/graduate computer science students, computer graphics professionals Related titles: Practical Linear Algebra -- 978-1-56881-234-2 Practical Linear Algebra -- 978-1-4665-7956-9 3D Math Primer for Graphics and Game Development, 2nd Edition -- 978-1-56881-723-1 Discrete Mathematics with Ducks -- 978-1-4665-0499-8 Competitor: Numerical Algorithms with C, Engeln-Müllges, 2014, Springer, 597 pp

Endorsements: "This book covers an impressive array of topics, many of which are paired with a real-world application. Its conversational style and relatively few theorem-proofs make it well suited for computer science students as well as professionals looking for a refresher." —Dianne Hansford, FarinHansford.com

Computer Science

Intermediate C Programming Yung-Hsiang Lu, Purdue University, West Lafayette, IN ISBN: 978-1-4987-1163-0 June 2015 | 254 x 178 | 544pp | Pb | £49.99 | illus: 123 b/w, 4 tables Editor: Cohen, Randi Text type: Textbook Market: Computer Science & Engineering

This text provides a classroom-tested introduction to C programming for intermediate students who have taken at least one programming course. Suitable for a one-semester course in computer science, computer engineering, or electrical engineering, the book covers many concepts essential for understanding how programs work inside computers. It focuses on developing software and debugging. The author shows students common programming mistakes and compares them with correct programs. Key Features:

Introduces C programming to intermediate students and programmers

Explains how to fix frequent programming mistakes

Includes programming examples tested in Linux

Covers recursion in depth

Provides exercises throughout

Useful for C programming courses worldwide

Audience: Undergraduate students in computer science and engineering taking a C programming course (after CS1). Related titles: Programming in C++ for Engineering and Science -- 978-1-4398-2534-1 C -- 978-1-4822-1450-5 Linux with Operating System Concepts -- 978-1-4822-3589-0 Competitor: System Programming with C and Unix, Hoover, 2009, Pearson, 400 pp

Endorsements: "This well-written book provides the necessary tools and practical skills to turn students into seasoned programmers. It not only

teaches students how to write good programs, but, more uniquely, also teaches them how to avoid writing bad programs.”

—Siau Cheng Khoo, Ph.D., National University of Singapore

"This book is unique in that it covers the C programming language from a bottom-up perspective, which is rare in programming

books.” ---Niklas Elmqvist, Ph.D., Associate Professor and Program Director, Master of Science in Human–Computer

Interaction, University of Maryland

Physics

Ultrasound Imaging and Therapy Edited by Aaron Fenster, Robarts Research Institute, London, Ontario, Canada and James C. Lacefield, The University of Western Ontario, London, Canada ISBN: 978-1-4398-6628-3 May 2015 | 254 x 178 | 339pp | Hb | £95.00 | illus: 157 b/w, 25 colours, 10 tables, Editor: Han, Luna Text type: Reference Market: Biomedical Imaging

This book discusses the use of ultrasound imaging for diagnosis with image-guided interventions and ultrasound-based therapy. It covers the background on the technology of transducers and beam formers for use in 2D, 3D and 4D ultrasound as well as developments in tissue characterization, Doppler techniques, ultrasound contrast agents, and ultrasound-guided biopsy and therapy. The first part of the book deals with transducers, beam formers, and imaging systems. The second section discusses diagnostic applications and the last part looks at the use of ultrasound in image-guided interventions.

Key Features:

Provides a complete overview of the state of the art of current and developing techniques for ultrasound imaging and therapy

Covers both diagnostic and therapeutic applications

Discusses Doppler techniques, ultrasound contrast agents, and image-guided interventions

Summarizes technology developments in 2D, 3D, and 4D ultrasound

Ultrasound a hugely important modality in Europe, Asia, and Middle East

Audience: Researchers, physicians, trainees, technologists, technicians, and graduate students interested in diagnostic and therapeutic applications of ultrasound.

Related titles: The Physics of Medical Imaging -- 978-0-85274-349-2 Physics for Diagnostic Radiology, Third Edition -- 978-0-7503-0591-4 Biomedical Technology and Devices Handbook -- 978-0-8493-1140-6 Biomedical Technology and Devices, Second Edition -- 978-1-4398-5959-9

Physics

Essentials of In Vivo Biomedical Imaging Edited by Simon R. Cherry, University of California, Davis, USA, Ramsey D. Badawi, University of California, Davis, USA and Jinyi Qi, University of California, Davis, USA ISBN: 978-1-4398-9874-1 May 2015 | 254 x 203 | 288pp | Pack - Book and Ebook | £63.99 | illus: 147 colours, 8 colour tables, Editor: Han, Luna Text type: Textbook Market: Biomedical Engineering

This book helps scientists and physician–scientists choose and utilize the appropriate in vivo imaging technologies and methods for their research. Featuring contributions from leading experts in the field, this authoritative reference text explains what each in vivo imaging technology can measure, describes major in vivo imaging methods and approaches, and gives examples demonstrating the rich repertoire of modern biomedical imaging to address a wide range of morphological, functional, metabolic, and molecular parameters in a safe and noninvasive manner.

Key Features:

Lead author is a native of the UK and Editor in Chief of one of the top biomedical imaging journals in the world.

Helps scientists and physician–scientists choose and utilize the appropriate in vivo imaging technologies and methods for their research

Describes how each in vivo imaging technology works, what it can measure, and what applications it is best suited for

Discusses the strengths and limitations of major in vivo imaging methods and approaches

Related titles: 3D Imaging in Medicine, Second Edition -- 978-0-8493-3179-4 Electromagnetic Analysis and Design in Magnetic Resonance Imaging -- 978-0-8493-9693-9 Biosignal and Medical Image Processing, Second Edition -- 978-1-4200-6230-4

Endorsements: “Terrific book. It is essential reading for anyone using imaging as a research tool.” --Michael F. Insana, Willett Professor of Engineering, Department of Bioengineering, University of Illinois at Urbana-Champaign “an ideal overview of medical imaging systems for anyone looking for clarity in presentation of the systems and a simple elegance to understanding them.” --Brian W. Pogue, Professor of Engineering, Professor of Physics & Astronomy, and Professor of Surgery, Geisel School of Medicine, Dartmouth College “an excellent book… very comprehensive with ample color figures, which makes it easy to read. I strongly recommend it” --Weibo Cai, PhD, Departments of Radiology, Medical Physics, and Biomedical Engineering, University of Wisconsin- Madison

Physics

Physics Curiosities, Oddities, and Novelties John Kimball ISBN: 978-1-4665-7635-3 May 2015 | 235 x 156 | 371pp | Pb | £22.99 | illus: 204 b/w, 2 tables, Editor: Han, Luna Text type: Professional

In an easily accessible style, this book presents the most interesting physics concepts that have meaning in our daily lives. Filled with intriguing and unusual examples, the book explores a historical progression, from classical physics to quantum mechanics and relativity. This book also gives insight into physics through minimal scientific jargon. For example, readers learn the physics behind dimples on golf balls, 3D movies, refrigerators, and the battery in your car.

Key Features:

Provides a sensible and entertaining way to navigate through mind-boggling physics concepts

Offers an escape from the tedium frequently associated with physics

Avoids all but the most essential formulas

Includes real examples that reveal interesting, practical, and novel aspects

Uses minimal technical jargon

Related titles: The Physics Companion, 2nd Edition -- 978-1-4665-1779-0 Physics of Sailing -- 978-1-4200-7376-8 A Cultural History of Physics -- 978-1-56881-329-5

Audience: Students of all levels, from high school to graduate level. Curious lay readers who are interested in science. Endorsements: “As a teacher of physics, I like this book a lot. It lightens the subject nicely.” -- Philip B. Allen, Professor, Department of Physics and Astronomy, Stony Brook University "This book introduces important physical concepts in a casual and entertaining way... I recommend it to high school students curious about science and to anyone interested in qualitative physics." -- Oleg Lunin, University at Albany "all of the physical concepts are expressed in terms of common language.... good as a reference for students [and] as popular reading for those having curiosity about physics and mathematics...." -- Ching-Yao Fong, Distinguished Professor of Physics, University of California, Davis “…concise, clear, and insightful… a useful, interesting, and accessible resource for physics teachers and interested students of all levels.” -- David Bittel, Physics Teacher, Bristol Eastern High School

Physics

Motor Proteins and Molecular Motors Anatoly B. Kolomeisky ISBN: 978-1-4822-2475-7 May 2015 | 235 x 156 | 220pp | Hb | £57.99 | illus: 68 b/w, 3 tables Editor: McGowan, Francesca Text type: Professional Market: Physics

Highlighting the future utilization of nanomachines in the development of new nanoscale devices and materials, this book

explains how motor proteins function at the molecular level, how they interact with each other and with other molecules,

and what they do for living systems. It offers multiple examples and limits the use of heavy mathematics in favor of more

microscopic explanations, making it accessible to students and researchers from various fields in science and engineering

including biology, chemistry, physics, and materials science.

Includes a definitive account of key and fast-developing area

Provides an interdisciplinary approach geared to a diverse spectrum of readers

Presents fundamental physical principles and concepts necessary for understanding processes at the molecular level

Avoids heavy mathematical calculations in favor of simple physical-chemical explanations of underlying phenomena

Offers multiple examples to illustrate the richness and complexity of motor proteins dynamics

Author is internationally known, and will be on sabbatical in Oxford University in autumn 2015.

Audience:

Graduate students and researchers on molecular motors and motor proteins from a wide range of disciplines including

physics, chemistry and biology.

Related titles:

Quantitative Understanding of Biosystems -- 978-1-4200-8972-1

Introduction to Proteins -- 978-1-4398-1071-2

Chemical Physics -- 978-1-4398-2251-7

Introduction to Experimental Biophysics - A Laboratory Guide -- 978-1-4665-5765-9

Competitor:

Mechanisms of Motor Proteins and the Cytoskeleton, Howard (2001/2005), Sinauer, 384pp.

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Rob CalverDiscipline: StatisticsEmail: Rob.Calver@tandf.co.uk

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