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978-1-0716-1417-4

Gareth James, University of Southern California, Los Angeles, CA, USA; Daniela Witten, University of Washington, Seattle, WA, USA; Trevor Hastie, Stanford University, Stanford, CA, USA; Robert Tibshirani, Stanford University, Stanford, CA, USA

,978-1-4614-7137-0,978-1-4614-7139-4,978-1-4614-7138-7,978-1-0716-1305-4

Preface.- 1 Introduction.- 2 Statistical Learning.- 3 Linear Regression.- 4 Classification.- 5 Resampling Methods.- 6 Linear Model Selection and Regularization.- 7 Moving Beyond Linearity.- 8 Tree-Based Methods.- 9 Support Vector Machines.- 10 Deep Learning.- 11 Survival Analysis and Censored Data.- 12 Unsupervised Learning.- 13 Multiple Testing.- Index.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

<p>Presents an essential statistical learning toolkit for practitioners in science, industry, and other fields</p><p>Demonstrates application of the statistical learning methods in R</p><p>Includes new chapters on deep learning, survival analysis, and multiple testing</p><p>Covers a range of topics, such as linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and deep learning</p><p>Features extensive color graphics for a dynamic learning experience</p><p>Includes supplementary material: sn.pub/extras</p>

Gareth James is a professor of data sciences and operations, and the E. Morgan Stanley Chair in Business Administration, at the University of Southern California. He has published an extensive body of methodological work in the domain of statistical learning with particular emphasis on high-dimensional and functional data. The conceptual framework for this book grew out of his MBA elective courses in this area.Daniela Witten is a professor of statistics and biostatistics, and the Dorothy Gilford Endowed Chair, at the University of Washington. Her research focuses largely on statistical machine learning techniques for the analysis of complex, messy, and large-scale data, with an emphasis on unsupervised learning.Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University, and are co-authors of the successful textbook Elements of Statistical Learning. Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap.

9781071614174

165009_2_En

Steven S. Skiena, Stony Brook University Department of Computer Science, Stony Brook, NY, USA

,978-1-84996-720-4,978-1-84882-197-2,978-1-84800-069-8,978-1-84800-070-4

TO UPDATEPractical Algorithm Design.- to Algorithm Design.- Algorithm Analysis.- Data Structures.- Sorting and Searching.- Graph Traversal.- Weighted Graph Algorithms.- Combinatorial Search and Heuristic Methods.- Dynamic Programming.- Intractable Problems and Approximation Algorithms.- How to Design Algorithms.- The Hitchhiker’s Guide to Algorithms.- A Catalog of Algorithmic Problems.- Data Structures.- Numerical Problems.- Combinatorial Problems.- Graph Problems: Polynomial-Time.- Graph Problems: Hard Problems.- Computational Geometry.- Set and String Problems.- Algorithmic Resources.

'My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. … every 1 – pager has a simple picture, making it easy to remember.' (Steve Yegge, Get that Job at Google)'Steven Skiena’s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. … Every programmer should read this book, and anyone working in the field should keep it close to hand. … This is the best investment … a programmer or aspiring programmer can make.' (Harold Thimbleby, Times Higher Education)'It is wonderful to open to a random spot and discover an interesting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... The color really adds a lot of energy to the new edition of the book!' (Cory Bart, University of Delaware)---This newly expanded and updated third edition of the best-selling classic continues to take the 'mystery' out of designing algorithms, and analyzing their efficiency. It serves as the primary textbook of choice for algorithm design courses and interview self-study, while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.




The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Practical Algorithm Design, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, the Hitchhiker's Guide to Algorithms, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography.


NEW to the third edition:

-- New and expanded coverage of randomized algorithms, hashing, divide and conquer, approximation algorithms, and quantum computing

-- Provides full online support for lecturers, including an improved website component with lecture slides and videos

-- Full color illustrations and code instantly clarify difficult concepts

-- Includes several new 'war stories' relating experiences from real-world applications

-- Over 100 new problems, including programming-challenge problems from LeetCode and Hackerrank.

-- Provides up-to-date links leading to the best implementations available in C, C++, and Java

Additional Learning Tools:

-- Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, and the right path to solve them

-- Exercises include 'job interview problems' from major software companies

-- Highlighted 'take home lessons' emphasize essential concepts

-- The 'no theorem-proof' style provides a uniquely accessible and intuitive approach to a challenging subject

-- Many algorithms are presented with actual code (written in C)

-- Provides comprehensive references to both survey articles and the primary literature



This substantially enhanced third edition of The Algorithm Design Manual is an essential learning tool for students and professionals needed a solid grounding in algorithms. Professor Skiena is also the author of the popular Springer texts, The Data Science

'My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. … every 1 – pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types.' (Steve Yegge, Get that Job at Google)'Steven Skiena’s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. … Every programmer should read this book, and anyone working in the field should keep it close to hand. … This is the best investment … a programmer or aspiring programmer can make.' (Harold Thimbleby, Times Higher Education)'It is wonderful to open to a random spot and discover an interesting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... The color really adds a lot of energy to the new edition of the book!' (Cory Bart, University of Delaware)'The is the most approachable book on algorithms I have.' (Megan Squire, Elon University)---This newly expanded and updated third edition of the best-selling classic continues to take the 'mystery' out of designing algorithms, and analyzing their efficiency. It serves as the primary textbook of choice for algorithm design courses and interview self-study, while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.
The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Practical Algorithm Design, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, the Hitchhiker's Guide to Algorithms, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography.
NEW to the third edition: -- New and expanded coverage of randomized algorithms, hashing, divide and conquer, approximation algorithms, and quantum computing -- Provides full online support for lecturers, including an improved website component with lecture slides and videos -- Full color illustrations and code instantly clarify difficult concepts -- Includes several new 'war stories' relating experiences from real-world applications -- Over 100 new problems, including programming-challenge problems from LeetCode and Hackerrank. -- Provides up-to-date links leading to the best implementations available in C, C++, and Java Additional Learning Tools: -- Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them -- Exercises include 'job interview problems' from major software companies -- Highlighted 'take home lessons' emphasize essential concepts -- The 'no theorem-proof' style provides a uniquely accessible and intuitive approach to a challenging subject -- Many algorithms are presented with actual code (written in C) -- Provides comprehensive references to both survey articles and the primary literature Written by a well-known algorithms researcher who received the

<p>Unique, handy reference package with a practical, hands-on appeal to a wide audience</p><p>This classic bestseller has been fully updated, and enhanced with new and expanded material on hashing and randomized algorithms, divide and conquer algorithms, and dealing with hard problems (including quantum algorithms)</p><p>Contains a highly unique catalog of the 75 most important algorithmic problems</p><p>Additional useful information such as lecture slides and updates available via author's website</p>

Dr. Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. He was awarded the IEEE Computer Science and Engineering Undergraduate Teaching Award “for outstanding contributions to undergraduate education ...and for influential textbooks and software.”

9783030542559

978-0-387-84857-0

Trevor Hastie, Stanford University Dept. of Statistics, Stanford, CA, USA; Robert Tibshirani, Stanford University Dept. of Statistics, Stanford, CA, USA; Jerome Friedman, Stanford University Dept. of Statistics, Stanford, CA, USA

,978-1-4899-0519-2,978-0-387-95284-0,978-1-4899-0518-5,978-0-387-21606-5

Overview of Supervised Learning.- Linear Methods for Regression.- Linear Methods for Classification.- Basis Expansions and Regularization.- Kernel Smoothing Methods.- Model Assessment and Selection.- Model Inference and Averaging.- Additive Models, Trees, and Related Methods.- Boosting and Additive Trees.- Neural Networks.- Support Vector Machines and Flexible Discriminants.- Prototype Methods and Nearest-Neighbors.- Unsupervised Learning.- Random Forests.- Ensemble Learning.- Undirected Graphical Models.- High-Dimensional Problems: p ? N.

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression and path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for 'wide'' data (p bigger than n), including multiple testing and false discovery rates.

<p>The many topics include neural networks, support vector machines, classification trees and boosting - the first comprehensive treatment of this topic in any book</p><p>Includes more than 200 pages of four-color graphics</p><p>Includes supplementary material: sn.pub/extras</p>

Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

9780387848570

10.1007/978-0-387-84858-7

Stephen Abbott, Middlebury College Department of Mathematics, Middlebury, VT, USA

,978-1-4419-2866-5,978-0-387-95060-0,978-1-4684-9503-4,978-0-387-21506-8,978-1-4939-7072-8

Preface.- 1 The Real Numbers.- 2 Sequences and Series.- 3 Basic Topology of R.- 4 Functional Limits and Continuity.- 5 The Derivative.- 6 Sequences and Series of Functions.- 7 The Riemann Integral.- 8 Additional Topics.- Bibliography.- Index.

This lively introductory text exposes the student to the rewards of a rigorous study of functions of a real variable. In each chapter, informal discussions of questions that give analysis its inherent fascination are followed by precise, but not overly formal, developments of the techniques needed to make sense of them. By focusing on the unifying themes of approximation and the resolution of paradoxes that arise in the transition from the finite to the infinite, the text turns what could be a daunting cascade of definitions and theorems into a coherent and engaging progression of ideas. Acutely aware of the need for rigor, the student is much better prepared to understand what constitutes a proper mathematical proof and how to write one.Fifteen years of classroom experience with the first edition of Understanding Analysis have solidified and refined the central narrative of the second edition. Roughly 150 new exercises join a selection of the best exercises from the first edition, and three more project-style sections have been added. Investigations of Euler’s computation of ζ(2), the Weierstrass Approximation Theorem, and the gamma function are now among the book’s cohort of seminal results serving as motivation and payoff for the beginning student to master the methods of analysis.Review of the first edition:“This is a dangerous book. Understanding Analysis is so well-written and the development of the theory so well-motivated that exposing students to it could well lead them to expect such excellence in all their textbooks. … Understanding Analysis is perfectly titled; if your students read it, that’s what’s going to happen. … This terrific book will become the text of choice for the single-variable introductory analysis course … ”— Steve Kennedy, MAA Reviews

This lively introductory text exposes the student to the rewards of a rigorous study of functions of a real variable. In each chapter, informal discussions of questions that give analysis its inherent fascination are followed by precise, but not overly formal, developments of the techniques needed to make sense of them. By focusing on the unifying themes of approximation and the resolution of paradoxes that arise in the transition from the finite to the infinite, the text turns what could be a daunting cascade of definitions and theorems into a coherent and engaging progression of ideas. Acutely aware of the need for rigor, the student is much better prepared to understand what constitutes a proper mathematical proof and how to write one.Fifteen years of classroom experience with the first edition of Understanding Analysis have solidified and refined the central narrative of the second edition. Roughly 150 new exercises join a selection of the best exercises from the first edition, and three more project-style sections have been added. Investigations of Euler’s computation of ζ(2), the Weierstrass Approximation ­ Theorem, and the gamma function are now among the book’s cohort of seminal results serving as motivation and payoff for the beginning student to master the methods of analysis.

<p>Provides a polished and tuned-up version of the same core text that has proved successful with students and instructors for 15 years</p><p>Includes around 150 new exercises, in addition to around 200 of the best exercises from the first edition, and an accompanying solutions manual for instructors</p><p>Presents three new self-guided projects exploring Euler’s sum, the factorial function and the Weierstrass Approximation Theorem</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Stephen D. Abbott is Professor of Mathematics at Middlebury College. He is a two-time winner of Middlebury’s Perkins Award for Excellence in Teaching (1998, 2010). His published work includes articles in the areas of operator theory and functional analysis, the algorithmic foundations of robotics, and the intersection of science, mathematics and the humanities.

9781493927111

10.1007/978-1-4939-2712-8

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications. This completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory. The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher. The book is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information. Christopher M. Bishop is Deputy Director of Microsoft Research Cambridge, and holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society of Edinburgh. His previous textbook 'Neural Networks for Pattern Recognition' has been widely adopted. Coming soon: *For students, worked solutions to a subset of exercises available on a public web site (for exercises marked 'www' in the text) *For instructors, worked solutions to remaining exercises from the Springer web site *Lecture slides to accompany each chapter *Data sets available for download

Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. Similarly, new models based on kernels have had significant impact on both algorithms and applications. This new textbook reacts these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

<p>First text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years.</p><p>Presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible</p><p>First text to use graphical models to describe probability distributions. There are no other books that apply graphical models to machine learning.</p><p>First four-color book on pattern recognition</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

​Chris Bishop is a Microsoft Distinguished Scientist and the Laboratory Director at Microsoft Research Cambridge. He is also Professor of Computer Science at the University of Edinburgh, and a Fellow of Darwin College, Cambridge. In 2004, he was elected Fellow of the Royal Academy of Engineering, and in 2007 he was elected Fellow of the Royal Society of Edinburgh. <div>
</div><div>Chris obtained a BA in Physics from Oxford, and a PhD in Theoretical Physics from the University of Edinburgh, with a thesis on quantum field theory. He then joined Culham Laboratory where he worked on the theory of magnetically confined plasmas as part of the European controlled fusion programme. </div><div>
</div>

9780387310732

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

10.1007/978-0-387-45528-0

1 Introduction.- 2 Image Formation.- 3 Image Processing.- 4 Model Fitting and Optimization.- 5 Deep Learning.- 6 Recognition.- 7 Feature Detection and Matching.- 8 Image Alignment and Stitching.- 9 Motion Estimation.- 10 Computational Photography.- 11 Structure from Motion and SLAM.- 12 Depth Estimation.- 13 3D Reconstruction.- 14 Image-Based Rendering.- 15 Conclusion.- Appendix A: Linear Algebra and Numerical Techniques.- Appendix B: Bayesian Modeling and Inference.- Appendix C: Supplementary Material.

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade
Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.About the Author ​Dr. Richard Szeliski has more than 40 years’ experience in computer vision research, most recently at Facebook and Microsoft Research, where he led the Computational Photography and Interactive Visual Media groups. He is currently an Affiliate Professor at the University of Washington where he co-developed (with Steve Seitz) the widely adopted computer vision curriculum on which this book is based.

Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.Topics and features:Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized coursesIncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented realityPresents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade
Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

<p>Presents state-of-the-art techniques, featuring new material on deep learning and deep neural networks</p><p>Structured to support active curricula and project-oriented courses</p><p>Provides, exercises and additional readings, as well as supplementary material</p>

Dr. Richard Szeliski has more than 40 years’ experience in computer vision research, most recently at Facebook and Microsoft Research, where he led the Computational Photography and Interactive Visual Media groups. He is currently an Affiliate Professor at the University of Washington where he co-developed (with Steve Seitz) the widely adopted computer vision curriculum on which this book is based. He was awarded the IEEE Computer Society PAMI Distinguished Researcher Award in 2017 and is an IEEE and ACM Fellow.

9783030343712

190326_2_En

978-3-030-05386-4

Christian de Virgilio, Harbor-UCLA Medical Center, Torrance, CA, USA; Areg Grigorian, University of California, Ivine, Orange, CA, USA

Fever and Hypotension in the Intensive Care Unit.- Nausea, Vomiting, and Left Groin Mass.- Abdominal Pain, Nausea, and Vomiting.- Right Leg Pain, Swelling, and Erythema for Two Days.- Abnormal Screening Mammogram.- New Palpable Mass in Right Breast.- Recently Changed Skin Lesion.- Chest Pain, Diaphoresis, and Nausea.- Chest and Back Pain,- Hemoptysis, Cough and Weight Loss.- Incidentally Discovered Adrenal Mass on CT Scan.- Fatigue, Constipation, and Depressed Mood.- Intermittent Episodes of Sweating, Palpitations, and Hypertension.- Neck Mass That Moves With Swallowing.- Progressively Hoarse Voice.- Lump on Neck Increasing in Size.- Aural Fullness, Hearing Loss, and Tinnitus.- Postprandial Right Upper Quadrant Pain.- Right Upper Quadrant Pain, Fever, Nausea, and Vomiting.- Severe Epigastric Pain With Nausea and Vomiting.- New Onset of Painless Jaundice.- Bright Red Blood per Rectum.- Right Lower Quadrant Abdominal Pain.- Pencil-Thin Stools and Intermittent Constipation.- Chronic Constipation Presenting With Severe Abdominal Pain.- Left Lower Quadrant Pain and Fever.- Fatigue and Bloody Diarrhea.- Neck Pain and Extremity Weakness Following Trauma.- Loss of Consciousness Following Head Trauma.- Multiple Extremity Injuries After Motorcycle Accident.- Immediate Swelling After Trauma to the Knee.- Adolescent Male With Right Groin Pain and Limp.- Chronic Right Hand Pain.- Full-Term Male Infant With Respiratory Distress.- Infant With Bilious Emesis.- Infant With Nonbilious Emesis.- Infant Born With Abdominal Wall Defect.- Excessive Drooling in a Newborn.- Postoperative Bleeding.- Postoperative Decreased Urine Output.- Shortness of Breath Five Days After Surgery.- Abdominal Pain Following Motor Vehicle Collision.- Penetrating Abdominal Trauma.- Pedestrian Struck By Motor Vehicle.- Gunshot Wound to the Left Neck.- Stab Wound to the Chest.- Burns to the Face, Trunk, and Extremities.- Severe Right Leg Pain After Tibia Fracture.- Bloody Emesis.- Severe Epigastric Abdominal Pain.- Weight Loss and Early Satiety.- Chest Pain After Vomiting.- Scrotal Pain.- Scrotal Mass.- Blood in Urine.- Transient Loss of Vision in the Right Eye.- Right Calf Pain With Walking.- Sudden Onset of Severe Left-Sided Abdominal Pain.- Cold, Painful Right Lower Extremity.

Surgery: A Case Based Clinical Review has proven to be the premiere resource to help prepare medical students for the surgical shelf exam and clinical wards. The second edition was conceived after listening to the feedback we received from students. We have added several new chapters and updated the others. This book continues to provide the reader with a comprehensive understanding of surgical diseases in one easy-to-use reference that combines multiple teaching formats. The book begins using a case based approach. The cases presented cover the diseases most commonly encountered on a surgical rotation. The cases are followed by a series of short questions and answers, designed to provide further understanding of the important aspects of the history, physical examination, differential diagnosis, diagnostic work-up and management, and questions that may arise on surgical rounds and on the shelf exam. The book is written in an easy-to-understand manner to help reinforce important surgical exam concepts.The second edition of Surgery: A Case Based Clinical Review will be of great utility for medical students when they rotate on surgery, as well as interns, physician assistant students, nursing students, and nurse practitioner students.

<div>Surgery: A Case Based Clinical Review has proven to be the premiere resource to help prepare medical students for the surgical shelf exam and clinical wards. The second edition was conceived after listening to the feedback we received from students. We have added several new chapters and updated the others. This book continues to provide the reader with a comprehensive understanding of surgical diseases in one easy-to-use reference that combines multiple teaching formats. The book begins using a case based approach. The cases presented cover the diseases most commonly encountered on a surgical rotation. The cases are followed by a series of short questions and answers, designed to provide further understanding of the important aspects of the history, physical examination, differential diagnosis, diagnostic work-up and management, and questions that may arise on surgical rounds and on the shelf exam. The book is written in an easy-to-understand manner to help reinforce important surgical exam concepts.</div><div>
</div><div>The second edition of Surgery: A Case Based Clinical Review will be of great utility for medical students when they rotate on surgery, as well as interns, physician assistant students, nursing students, and nurse practitioner students.</div>

<p>Premiere surgical shelf exam resource in an easy-to-understand format</p><p>Focus on high-yield content</p><p>Key figures and tables visually reinforce important elements of the disease process</p><p>Combines several teaching approaches including case based, short questions and answers, management algorithms, and multiple-choice questions presented in the NBME format</p><p>Written by experts with significant roles in the surgical education of medical students</p>

9783030053864

313183_2_En

<div>Part I: The Protagonist’s Journey as Narrative Imperative.- Chapter One: The Protagonist’s Journey – Due to their central role, engaging the Protagonist is the most important aspect of the story-crafting process.- Chapter Two: Character Arc – In movies, there exists a recurring variety of character arcs including the most popular: positive transformation.- Chapter Three: Disunity – The Protagonist needs to change as reflected in their initial state of disunity.- Chapter Four: Deconstruction – Entering the New World, a series of challenges and trials deconstructs the Protagonist’s old ways of being.- Chapter Five: Reconstruction – Freed from their old ways of being, the Protagonist is reconstructed by embracing heretofore untapped inner potential.-Chapter Six: Unity – The Protagonist brings together all they have learned in the story’s final struggle and in doing so achieves unity.- Chapter Seven: The Protagonist’s Place Within the Screenplay Universe – The Protagonist’s journey interweaves between the External World and the Internal World.- Part II: The Protagonist’s Journey as Family of Characters.- Chapter Eight: Primary Character Archetypes – Five narrative dynamics common to movies represented by these archetypes: Protagonist, Nemesis, Attractor, Mentor, Trickster.- Chapter Nine: Nemesis – By providing opposition to the Protagonist, the Nemesis generates sustained conflict which creates the central drama of the story.- Chapter Ten: Attractor – During their journey, the Protagonist intersects with Attractor characters who connect with the Protagonist’s emotional development.- Chapter Eleven: Mentor – The Protagonist meets another type of ally, the Mentor who provides wisdom and contributes to the Protagonist’s intellectual growth.- Chapter Twelve: Trickster – A shapeshifter tests the will of the Protagonist by switching from ally to enemy, enemy to ally, and generating complications.- Chapter Thirteen: Subplots – Each Protagonist relationship with key characters is a mini-story with its own arc, theme, and contribution to the overall narrative.- Chapter Fourteen: Character Map – There is a structure to the Protagonist’s relationships with the story’s major characters.- Part III: The Protagonist’s Journey as Screenplay.- Chapter Fifteen: Breaking the Story I – Begin the story-crafting process by engaging the story’s central character with a Protagonist Character Treatment.- Chapter Sixteen: Breaking the Story II – Use a series of brainstorming exercises to explore the story universe and develop its characters.- Chapter Seventeen: Breaking the Story III – A first pass at wrangling the plot by working with Four Primary Plotline Points.- Chapter Eighteen: Breaking the Story IV – Track the Protagonist’s transformation arc through Four Themeline Movements.- Chapter Nineteen: Breaking the Story V – Expand the framework of the plot by identifying Ten Major Plotline Points.- Chapter Twenty: Breaking the Story VI – Construct the final story structure, both Plotline and Themeline into a Narrative Throughline.- Chapter Twenty-One: Writing the First Draft – Break down the writing process into sets of scenes from one Plotline Point to another all the way through the Denouement. </div>

Character drives plot. Based on this principle, this book walks aspiring writers through the fascinating world of character-driven screenwriting. When a writer engages their characters, they start a process which naturally leads to the story’s structure and everything else that makes for a well-written narrative. Exploring the protagonist’s journey and their “unity arc,” Myers explains how a family of characters surrounds the protagonist and influences their transformation process. This easy-to-follow guide features activities that will help writers of any level develop their stories from concept to scene-by-scene outline. Based upon a popular workshop Myers has led with over a thousand writers at all levels of experience, this book is a must-have for screenwriting students, both undergraduate and graduate, and those looking at advanced story development.

<div>Character drives plot. Based on this principle, this book walks aspiring writers through the fascinating world of character-driven screenwriting. When a writer engages their characters, they start a process which naturally leads to the story’s structure and everything else that makes for a well-written narrative. Exploring the protagonist’s journey and their “unity arc,” Myers explains how a family of characters surrounds the protagonist and influences their transformation process. This easy-to-follow guide features activities that will help writers of any level develop their stories from concept to scene-by-scene outline. Based upon a popular workshop Myers has led with over a thousand writers at all levels of experience, this book is a must-have for screenwriting students, both undergraduate and graduate, and those looking at advanced story development.
</div>

<p>Provides a new set of terminology to help students construct the interior and exterior arcs of character</p><p>Includes a diverse range of case studies, from Hollywood classics to contemporary feature films and television</p><p>Marks the first book-length study to take a Jungian approach to screenwriting</p>

<div>Scott Myers has written thirty projects for nearly every major Hollywood studio and broadcast network. He hosts GoIntoTheStory.com, which Writers’ Digest named “Best of the Best Scriptwriting Website.” An assistant professor at DePaul University, USA, Scott is a graduate of the University of Virginia and Yale University Divinity School, USA.
</div>

9783030796815

478294_1_En

10.1007/978-3-030-79682-2

978-0-387-40272-7

Larry Wasserman, Carnegie Mellon University Dept. Statistics, Pittsburgh, PA, USA

Probability.- Random Variables.- Expectation.- Inequalities.- Convergence of Random Variables.- Models, Statistical Inference and Learning.- Estimating the CDF and Statistical Functionals.- The Bootstrap.- Parametric Inference.- Hypothesis Testing and p-values.- Bayesian Inference.- Statistical Decision Theory.- Linear and Logistic Regression.- Multivariate Models.- Inference about Independence.- Causal Inference.- Directed Graphs and Conditional Independence.- Undirected Graphs.- Loglinear Models.- Nonparametric Curve Estimation.- Smoothing Using Orthogonal Functions.- Classification.- Probability Redux: Stochastic Processes.- Simulation Methods.

This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning.

This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate level.

Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.

Taken literally, the title 'All of Statistics' is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. <div>
</div><div>The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data. </div>

<p>Provides a concise introduction to a larger number of topics than are usually included in a graduate-level mathematical statistics class</p>

Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.

9780387402727

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

978-3-030-88345-4

Olivier L. De Weck, Massachusetts Institute of Technology, Cambridge, MA, USA

Chapter 1. What is Technology?.- Chapter 2. Technological Milestones of Humanity.- Chapter 3. Technology and Nature.- Chapter 4. Quantifying Technological Progress.- Chapter 5. Patents and Intellectual Property.- Chapter 6. Case 1: The Automobile.- Chapter 7. Diffusion and Disruption of Technology.- Chapter 8. Technology Roadmaps.- Chapter 9. Case 2: The Aircraft.- Chapter 10. Technology Strategy and Competition.- Chapter 11. Systems Modeling and Technology Sensitivity.- Chapter 12. Technology Infusion Analysis.- Chapter 13. Case 3: The Deep Space Network.- Chapter 14. Technology Scouting.- Chapter 15. Knowledge Management and Technology Transfer.- Chapter 16. R&D Portfolio Management.- Chapter 17. Technology Valuation and Finance.- Chapter 18. Case 4: DNA Sequencing.- Chapter 19. Impact of Technology on Industrial Ecosystems.- Chapter 20. Military and Intelligence Technologies.- Chapter 21. Aging and Technology.- Chapter 22. The Singularity: Fiction or Reality?

This textbook explains Technology Roadmapping, in both its development and practice, and illustrates the underlying theory of, and empirical evidence for, technologic evolution over time afforded by this strategy. The book contains a rich set of examples and practical exercises from a wide array of domains in applied science and engineering such as transportation, energy, communications, and medicine. Professor de Weck gives a complete review of the principles, methods, and tools of technology management for organizations and technologically-enabled systems, including technology scouting, roadmapping, strategic planning, R&D project execution, intellectual property management, knowledge management, partnering and acquisition, technology transfer, innovation management, and financial technology valuation. Special topics also covered include Moore’s law, S-curves, the singularity and fundamental limits to technology. Ideal for university courses in engineering, management, and business programs, as well as self-study or online learning for professionals in a range of industries, readers of this book will learn how to develop and deploy comprehensive technology roadmaps and R&D portfolios on diverse topics of their choice.<div>Introduces a unique framework, Advanced Technology Roadmap Architecture (ATRA), for developing quantitative technology roadmaps and competitive R&D portfolios through a lucid and rigorous step-by-step approach;Elucidates the ATRA framework through analysis which was validated on an actual $1 billion R&D portfolio at Airbus, leveraging a pedagogy significantly beyond typical university textbooks and problem sets;Reinforces concepts with in-depth case studies, practical exercises, examples, and thought experiments interwoven throughout the text;Maximizes reader competence on how to explicitly link strategy, finance, and technology.<div>
</div><div>The book follows and supports the MIT Professional Education Courses “Management of Technology: Roadmapping & Development,” https://professional.mit.edu/course-catalog/management-technology-roadmapping-development and “Management of Technology: Strategy & Portfolio Analysis” https://professional.mit.edu/course-catalog/management-technology-strategy-portfolio-analysis</div></div><div><div></div>








</div>

This textbook explains Technology Roadmapping, in both its development and practice, and illustrates the underlying theory of, and empirical evidence for, technologic evolution over time afforded by this strategy. The book contains a rich set of examples and practical exercises from a wide array of domains in applied science and engineering such as transportation, energy, communications, and medicine. Professor de Weck gives a complete review of the principles, methods, and tools of technology management for organizations and technologically-enabled systems, including technology scouting, roadmapping, strategic planning, R&D project execution, intellectual property management, knowledge management, partnering and acquisition, technology transfer, innovation management, and financial technology valuation. Special topics also covered include Moore’s law, S-curves, the singularity and fundamental limits to technology. Ideal for university courses in engineering, management, and business programs, as well as self-study or online learning for professionals in a range of industries, readers of this book will learn how to develop and deploy comprehensive technology roadmaps and R&D portfolios on diverse topics of their choice.<div>Introduces a unique framework, Advanced Technology Roadmap Architecture (ATRA), for developing quantitative technology roadmaps and competitive R&D portfolios through a lucid and rigorous step-by-step approach;Elucidates the ATRA framework through analysis which was validated on an actual $1 billion R&D portfolio at Airbus, leveraging a pedagogy significantly beyond typical university textbooks and problem sets;Reinforces concepts with in-depth case studies, practical exercises, examples, and thought experiments interwoven throughout the text;Maximizes reader competence on how to explicitly link strategy, finance, and technology.<div>
</div><div>The book follows and supports the MIT Professional Education Courses “Management of Technology: Roadmapping & Development,” https://professional.mit.edu/course-catalog/management-technology-roadmapping-development and “Management of Technology: Strategy & Portfolio Analysis” https://professional.mit.edu/course-catalog/management-technology-strategy-portfolio-analysis</div></div>

<p>Introduces a framework, ATRA, for quantitative technology roadmaps and R&D portfolios with a lucid step-by-step approach</p><p>Elucidates the ATRA framework through analysis which was validated on an actual $1 billion R&D portfolio at Airbus</p><p>Reinforces concepts with in-depth case studies, practical exercises, examples, and thought experiments</p>

Dr. Olivier L. de Weck is the Apollo Program Professor of Astronautics and Engineering Systems at the Massachusetts Institute of Technology in Cambridge, MA.

9783030883454

495472_1_En

Introduction.- Programming Techniques.- Efficiency.- Sorting and Searching.- Data Structures.- Dynamic Programming.- Graph Algorithms.- Algorithm Design Topics.- Range Queries.- Tree Algorithms.- Mathematics.- Advanced Graph Algorithms.- Geometry.- String Algorithms.- Additional Topics.- Appendix A: Mathematical Background.

Building on what already is the most comprehensive introduction to competitive programming, this enhanced new textbook features new material on advanced topics, such as calculating Fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. Critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills.Topics and features:Introduces dynamic programming and other fundamental algorithm design techniques, and investigates a wide selection of graph algorithmsCompatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structuresSurveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programmingReviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data setsDiscusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard libraryCovers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queriesDescribes a selection of more advanced topics, including square-root algorithms and dynamic programming optimizationFully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. Knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. With its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike.Dr. Antti Laaksonen has worked as a teacher and researcher at the University of Helsinki and Aalto University, Finland.

Building on what already is the most comprehensive introduction to competitive programming, this enhanced new textbook features new material on advanced topics, such as calculating Fourier transforms, finding minimum cost flows in graphs, and using automata in string problems. Critically, the text accessibly describes and shows how competitive programming is a proven method of implementing and testing algorithms, as well as developing computational thinking and improving both programming and debugging skills.Topics and features: introduces dynamic programming and other fundamental algorithm design techniques, and investigates a wide selection of graph algorithms; compatible with the IOI Syllabus, yet also covering more advanced topics, such as maximum flows, Nim theory, and suffix structures; surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming; reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets; discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library; covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries; describes a selection of more advanced topics, including square-root algorithms and dynamic programming optimization.Fully updated, expanded and easy to follow, this core textbook/guide is an ideal reference for all students needing to learn algorithms and to practice for programming contests. Knowledge of programming basics is assumed, but previous background in algorithm design or programming contests is not necessary. With its breadth of topics, examples and references, the book is eminently suitable for both beginners and more experienced readers alike.

<p>Provides a comprehensive introduction to algorithmic problem solving in the context of programming contests</p><p>Describes numerous “folklore” algorithm design tricks used by experienced competitive programmers</p><p>Presents an accessible style designed to aid the reader in developing an intuitive understanding of why algorithms work and how to design them</p><p>Expanded second edition, featuring new material on code optimization, the discrete Fourier transform, minimum-cost flows, automata theory, and heuristic search algorithms</p>

Dr. Antti Laaksonen has worked as a teacher and researcher at the University of Helsinki and Aalto University, Finland. He has served as one of the organizers of the Finnish Olympiad in Informatics since 2008, and as the Scientific Chair of the Baltic Olympiad in Informatics in 2016. He has also coached and led the Finnish team at several international programming contests, including the International Olympiad in Informatics 2009–2016, and has established experience in teaching programming and algorithms.​

9783030393564

454700_2_En

978-3-662-56508-7

Marlon Dumas, University of Tartu, Tartu, Estonia; Marcello La Rosa, The University of Melbourne, Melbourne, , Australia; Jan Mendling, Vienna University of Economics and Business, Vienna, Austria; Hajo A. Reijers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

,978-3-642-33142-8,978-3-642-33144-2,978-3-642-43473-0,978-3-642-33143-5

1 Introduction to Business Process Management.- 2 Process Identification.- 3 Essential Process Modeling.- 4 Advanced Process Modeling.- 5 Process Discovery.- 6 Qualitative Process Analysis.- 7 Quantitative Process Analysis.- 8 Process Redesign.- 9 Process-Aware Information Systems.- 10 Process Implementation with Executable Models.- 11 Process Monitoring.- 12 BPM as an Enterprise Capability.

<div>This textbook covers the entire Business Process Management (BPM) lifecycle, from process identification to process monitoring, covering along the way process modelling, analysis, redesign and automation. Concepts, methods and tools from business management, computer science and industrial engineering are blended into one comprehensive and inter-disciplinary approach. The presentation is illustrated using the BPMN industry standard defined by the Object Management Group and widely endorsed by practitioners and vendors worldwide.</div><div>
</div><div>In addition to explaining the relevant conceptual background, the book provides dozens of examples, more than 230 exercises – many with solutions – and numerous suggestions for further reading. This second edition includes extended and completely revised chapters on process identification, process discovery, qualitative process analysis, process redesign, process automation and process monitoring. A new chapter on BPM as an enterprise capability has been added, which expands the scope of the book to encompass topics such as the strategic alignment and governance of BPM initiatives.</div><div>
</div><div>The textbook is the result of many years of combined teaching experience of the authors, both at the undergraduate and graduate levels as well as in the context of professional training. Students and professionals from both business management and computer science will benefit from the step-by-step style of the textbook and its focus on fundamental concepts and proven methods. Lecturers will appreciate the class-tested format and the additional teaching material available on the accompanying website.</div>

<div>This textbook covers the entire Business Process Management (BPM) lifecycle, from process identification to process monitoring, covering along the way process modelling, analysis, redesign and automation. Concepts, methods and tools from business management, computer science and industrial engineering are blended into one comprehensive and inter-disciplinary approach. The presentation is illustrated using the BPMN industry standard defined by the Object Management Group and widely endorsed by practitioners and vendors worldwide.</div><div>
</div><div>In addition to explaining the relevant conceptual background, the book provides dozens of examples, more than 230 exercises – many with solutions – and numerous suggestions for further reading. This second edition includes extended and completely revised chapters on process identification, process discovery, qualitative process analysis, process redesign, process automation and process monitoring. A new chapter on BPM as an enterprise capability has been added, which expands the scope of the book to encompass topics such as the strategic alignment and governance of BPM initiatives.</div><div>
</div><div>The textbook is the result of many years of combined teaching experience of the authors, both at the undergraduate and graduate levels as well as in the context of professional training. Students and professionals from both business management and computer science will benefit from the step-by-step style of the textbook and its focus on fundamental concepts and proven methods. Lecturers will appreciate the class-tested format and the additional teaching material available on the accompanying website.</div>

<p>Covers the whole BPM lifecycle, including process identification, discovery, analysis, redesign, automation and monitoring</p><p>Class-tested textbook complemented with additional teaching material on the accompanying website</p><p>Covers both relevant conceptual background, industrial standards and actionable skills</p>

<div>Marlon Dumas is a professor of Information Systems at University of Tartu, Estonia and Adjunct Professor at Queensland University of Technology (QUT), Australia. He is co-editor of a textbook on Process-Aware Information Systems (Wiley, 2005) and has taught BPM both in academia and as a professional trainer for over a decade in a dozen countries. He is also an active BPM researcher with a focus on process modeling, analysis and monitoring. He is one of the main architects of two open-source BPM projects – Apromore and Nirdizati.</div><div>
</div><div>Marcello La Rosa is a professor of Information Systems at The University of Melbourne, Australia. Prior to that, he held an appointment at QUT, Australia. Marcello leads the Apromore open-source project, for the development of an advanced process analytics platform, and contributes to the predictive process monitoring platform Nirdizati. His research interests focus on process mining, analysis and consolidation. Marcello has taught BPM to students and practitioners in Australia and overseas for over ten years. His MOOCs, co-developed with the other authors of this book, have been attended by over 25,000 students worldwide.</div><div>
</div><div>Jan Mendling is a full professor with the Institute for Information Business at the WU Vienna, Austria. Prior to that, he held appointments at Humboldt University of Berlin, Germany, and at QUT, Australia. Currently, he is also a visiting professor at the University of Ljubljana and the University of Liechtenstein. His main research interests are in business process management and process mining. Jan has taught BPM to students and practitioners at different institutions in Europe and Australia. He is co-founder of the Berliner BPM-Offensive, a practitioners’ forum for BPM, and a board member of the Austrian Process Management Society (Gesellschaft für Prozessmanagement).</div><div>
</div><div>Hajo A. Reijers is a full professor of Business Informatics at Vrije Universiteit Amsterdam, the Netherlands. He also holds a position as part-time, full professor at Eindhoven University of Technology. Previously, he worked as a management consultant in the BPM field. Hajo has taught BPM to students at all academic levels and provides training to practitioners at the TIAS Business School. He is one of the founders of the Business Process Management Forum, a Dutch platform for the exchange of knowledge between industry and academia.</div>

9783662565087

308018_2_En

10.1007/978-3-662-56509-4

Lawrence M. Friedman; Curt D. Furberg; David L. DeMets; David M. Reboussin; Christopher B. Granger

Lawrence M. Friedman, North Bethesda, MD, USA; Curt D. Furberg, Wake Forest School of Medicine, Winston-Salem, NC, USA; David L. DeMets, University of Wisconsin, Madison, WI, USA; David M. Reboussin, Wake Forest School of Medicine, Winston-Salem, NC, USA; Christopher B. Granger, Duke University, Durham, NC, USA

Introduction to Clinical Trials.- Ethical Issues.- What is the Question?.- Study Population.- Basic Study Design.- The Randomization Process.- Blinding.- Sample Size.- Baseline Assessment.- Recruitment of Study Participants.- Data Collection and Quality Control.- Assessment and Reporting of Harm.- Assessment of Health Related Quality of Life.- Participant Adherence.- Survival Analysis.- Monitoring Committee Structure & Function.- Statistical Methods Used in Interim Monitoring.- Issues in Data Analysis.- Closeout.- Reporting and Interpreting of Results.- Multicenter Trials.- Regulatory Issues.

This is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials. The three authors of the first four editions have been joined by two others who add great expertise. Most chapters have been revised considerably from the fourth edition. A chapter on regulatory issues has been included and the chapter on data monitoring has been split into two and expanded. Many contemporary clinical trial examples have been added. There is much new material on adverse events, adherence, issues in analysis, electronic data, data sharing, and international trials. This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials to illustrate the fundamentals. The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan, and reporting the trial results according to the pre-specified objectives.Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful. This book has been successfully used for teaching courses in clinical trial methodology.

This is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials. The three authors of the first four editions have been joined by two others who add great expertise. A chapter on regulatory issues has been included and the chapter on data monitoring has been split into two and expanded. Many contemporary clinical trial examples have been added. There is much new material on adverse events, adherence, issues in analysis, electronic data, data sharing and international trials.This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials to illustrate the fundamentals.The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan and reporting the trial results according to the pre-specified objectives.Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful.

<p>New chapter covers current regulatory issues and data monitoring is now covered in two chapters</p><p>An essential, up-to-date reference for researchers and students involved with clinical trials</p><p>Includes numerous examples of published clinical trials from a variety of medical disciplines</p><p>Technical details are kept to a minimum through the use of graphs and tables</p><p>The authors are active researchers leading clinical trials in a broad range of subjects</p>

Lawrence M. Friedman received his M.D. from the University of Pittsburgh. After training in internal medicine, he went to the National Heart, Lung and Blood Institute of the National Institutes of Health. During his many years there, Dr. Friedman was involved in numerous clinical trials and epidemiology studies, having major roles in their design, management and monitoring. While at the NIH and subsequently, he served as a consultant on clinical trials to various NIH institutes and to other governmental and nongovernmental organizations. Dr. Friedman has been a member of many data monitoring and other safety committees. Curt D. Furberg is Professor Emeritus of the Division of Public Health Sciences of the Wake Forest University School of Medicine. He received his M.D. and Ph.D. at the University of Umea, Sweden, and is a former chief, Clinical Trials Branch and Associate Director, Clinical Applications and Prevention Program, National Heart, Lung, and Blood Institute. Dr. Furberg established the Department of Public Health Sciences and served as its chair from 1986 to 1999. He has played major scientific and administrative roles in numerous multicenter clinical trials and has served in a consultative or advisory capacity on others. Dr. Furberg’s research activities include the areas of clinical trials methodology and cardiovascular epidemiology. David L. DeMets, PhD is currently the Max Halperin Professor of Biostatistics and former Chair of the Department of Biostatistics and Medical Informatics at the University of Wisconsin – Madison He has co-authored numerous papers on statistical methods and four texts on clinical trials, two specifically on data monitoring. He has served on many NIH and industry-sponsored data monitoring committees for clinical trials in diverse disciplines. He served on the Board of Directors of the American Statistical Association, as well as having been President of the Society for Clinical Trials and President of the Eastern North American Region (ENAR) of the Biometric Society. In addition he was Elected Fellow of the International Statistics Institute, the American Statistical Association, the Association for the Advancement of Science, the Society for Clinical Trials and the American Medical Informatics Association. In 2013, he was elected as a member of the Institute of Medicine. Christopher B. Granger is Professor of Medicine at Duke University, where he is an active clinical cardiologist and a clinical trialist at the Duke Clinical Research Institute. He received his M.D. at University of Connecticut and his residency training at the University of Colorado. He has had Steering Committee, academic leadership, and operational responsibilities for many clinical trials in cardiology. He has been on numerous Data Monitoring Committees. He serves on the National Heart, Lung, and Blood Institute Board of External Experts. He works with the Clinical Trials Transformation Initiative, a partnership between the U.S. Food and Drug Administration and Duke aiming to increase the quality and efficiency of clinical trials. He is a founding member of the Sensible Guidelines for the Conduct of Clinical Trials group, a collaboration between McMaster, Oxford, and Duke Universities. David M. Reboussin is a Professor in the Department of Biostatistical Science at the Wake Forest University School of Medicine, where he has worked since 1992. He has a master’s degree in Statistics from the University of Chicago and received his doctorate in Statistics from the University of Wisconsin at Madison. He is currently Principle Investigator for the Systolic Blood Pressure Intervention Trial Coordinating Center and has been a co-investigator in the coordinating centers for several NIH and industry funded clinical trials including Action to Control Cardiovas

9783319185385

978-3-030-43879-1

Robert W. Erickson, University of Colorado Boulder, Boulder, CO, USA; Dragan Maksimović, University of Colorado Boulder, Boulder, CO, USA

© Springer Science+Business Media Dordrecht 1997; © Kluwer Academic Publishers 2001

,978-0-7923-7270-7,978-1-4757-0558-4,978-1-4757-0559-1,978-0-306-48048-5

Principles of Steady State Converter Analysis.- Steady-State Equivalent Circuit Modeling, Losses, and Efficiency.- Switch Realization.- The Discontinuous Conduction Mode.- Converter Circuits.- Converter Dynamics and Control.- AC Equivalent Circuit Modeling.- Converter Transfer Functions.- Controller Design.- Input Filter Design. - AC and DC Equivalent Circuit Modeling of the Discontinuous Conduction Mode.- Current Programmed Control.- Magnetics.- Basic Magnetics Theory.- Inductor Design.- Transformer Design.- Modern Rectifiers and Power System Harmonics.- Power and Harmonics in Nonsinusoidal Systems.- Line-Commutated Rectifiers.- Pulse-Width Modulated Rectifiers.- Resonant Converters.- Resonant Conversion.- Soft Switching.

Fundamentals of Power Electronics, Third Edition, is an up-to-date and authoritative text and reference book on power electronics. This new edition retains the original objective and philosophy of focusing on the fundamental principles, models, and technical requirements needed for designing practical power electronic systems while adding a wealth of new material. Improved features of this new edition include: new material on switching loss mechanisms and their modeling; wide bandgap semiconductor devices; a more rigorous treatment of averaging; explanation of the Nyquist stability criterion; incorporation of the Tan and Middlebrook model for current programmed control; a new chapter on digital control of switching converters; major new chapters on advanced techniques of design-oriented analysis including feedback and extra-element theorems; average current control; new material on input filter design; new treatment of averaged switch modeling, simulation, and indirect power; and sampling effects in DCM, CPM, and digital control.

Fundamentals of Power Electronics, Third Edition, is intended for use in introductory power electronics courses and related fields for both senior undergraduates and first-year graduate students interested in converter circuits and electronics, control systems, and magnetic and power systems. It will also be an invaluable reference for professionals working in power electronics, power conversion, and analog and digital electronics.Includes an increased number of end of chapter problems;Updated and reorganized, including three completely new chapters;Includes key principles and a rigorous treatment of topics.

Fundamentals of Power Electronics, Third Edition, is an up-to-date and authoritative text and reference book on power electronics. This new edition retains the original objective and philosophy of focusing on the fundamental principles, models, and technical requirements needed for designing practical power electronic systems while adding a wealth of new material. Improved features of this new edition include: new material on switching loss mechanisms and their modeling; wide bandgap semiconductor devices; a more rigorous treatment of averaging; explanation of the Nyquist stability criterion; incorporation of the Tan and Middlebrook model for current programmed control; a new chapter on digital control of switching converters; major new chapters on advanced techniques of design-oriented analysis including feedback and extra-element theorems; average current control; new material on input filter design; new treatment of averaged switch modeling, simulation, and indirect power; and sampling effects in DCM, CPM, and digital control.

Fundamentals of Power Electronics, Third Edition, is intended for use in introductory power electronics courses and related fields for both senior undergraduates and first-year graduate students interested in converter circuits and electronics, control systems, and magnetic and power systems. It will also be an invaluable reference for professionals working in power electronics, power conversion, and analog and digital electronics.

<p>Includes an increased number of end of chapter problems</p><p>Updated and reorganized, including three completely new chapters</p><p>Includes key principles and a rigorous treatment of topics</p>

Robert W. Erickson received the B.S. (1978), M.S. (1980), and Ph.D. (1982) degrees in Electrical Engineering, from the California Institute of Technology, Pasadena, California. Since 1982, he has been a member of the faculty of Electrical, Computer, and Energy Engineering at the University of Colorado, Boulder, where he served as department Chair in 2002-2006, 2014-15, and 2018-2020. He co-directs the Colorado Power Electronics Center. Professor Erickson is a Fellow of the IEEE, a Fellow of the CU/NREL Renewable and Sustainable Energy Institute, and holds the endowed Palmer Leadership Chair. He is the author of approximately one hundred journal and conference papers in the area of power electronics. In 1996, he received the IEEE Power Electronics Society Transactions Prize Paper Award, for the paper 'Nonlinear Carrier Control for High-Power-Factor Boost Rectifier.' He received the CU-Boulder Inventor of the Year Award in 2015, and the Holland Teaching Excellence Award in 2010. His current research interests include modeling and control of power conversion systems, modular/multilevel converter systems, and power electronics for electric vehicles and renewable energy sources (wind and solar). Dr. Maksimović is a Charles V. Schelke Endowed Professor in the Department of Electrical, Computer and Energy Engineering. He co-founded the Colorado Power Electronics Center (CoPEC), and has since served as the CoPEC Co-Director. CoPEC research program in smart power electronics and digital control for high-frequency switched-mode power converters has attracted significant support from numerous industrial sponsors and agencies (NSF, DARPA, ARPA-E, DOE, ONR, DOEd). Prof. Maksimovic is a Fellow of the IEEE. He has published over 300 papers in journals and at professional conferences, and holds over 30 US patents. His current research interests include power electronics for renewable energy sources and energy efficiency, high frequency power conversion using wide bandgap semiconductors, digital control of switched-mode power converters, as well as analog, digital and mixed-signal integrated circuits for power management applications.

9783030438791

103385_3_En

10.1007/978-3-030-43881-4

978-1-4419-9981-8

,978-0-387-95448-6,978-0-387-95495-0,978-1-4757-5601-2,978-0-387-21752-9

Preface.- 1 Smooth Manifolds.- 2 Smooth Maps.- 3 Tangent Vectors.- 4 Submersions, Immersions, and Embeddings.- 5 Submanifolds.- 6 Sard's Theorem.- 7 Lie Groups.- 8 Vector Fields.- 9 Integral Curves and Flows.- 10 Vector Bundles.- 11 The Cotangent Bundle.- 12 Tensors.- 13 Riemannian Metrics.- 14 Differential Forms.- 15 Orientations.- 16 Integration on Manifolds.- 17 De Rham Cohomology.- 18 The de Rham Theorem.- 19 Distributions and Foliations.- 20 The Exponential Map.- 21 Quotient Manifolds.-  22 Symplectic Manifolds.- Appendix A: Review of Topology.- Appendix B: Review of Linear Algebra.- Appendix C: Review of Calculus.- Appendix D: Review of Differential Equations.- References.- Notation Index.- Subject Index.

This book is an introductory graduate-level textbook on the theory of smooth manifolds. Its goal is to familiarize students with the tools they will need in order to use manifolds in mathematical or scientific research—smooth structures, tangent vectors and covectors, vector bundles, immersed and embedded submanifolds, tensors, differential forms, de Rham cohomology, vector fields, flows, foliations, Lie derivatives, Lie groups, Lie algebras, and more. The approach is as concrete as possible, with pictures and intuitive discussions of how one should think geometrically about the abstract concepts, while making full use of the powerful tools that modern mathematics has to offer.This second edition has been extensively revised and clarified, and the topics have been substantially rearranged. The book now introduces the two most important analytic tools, the rank theorem and the fundamental theorem on flows, much earlier so that they can be used throughout the book. A few new topics have been added, notably Sard’s theorem and transversality, a proof that infinitesimal Lie group actions generate global group actions, a more thorough study of first-order partial differential equations, a brief treatment of degree theory for smooth maps between compact manifolds, and an introduction to contact structures.Prerequisites include a solid acquaintance with general topology, the fundamental group, and covering spaces, as well as basic undergraduate linear algebra and real analysis.

This book is an introductory graduate-level textbook on the theory of smooth manifolds. Its goal is to familiarize students with the tools they will need in order to use manifolds in mathematical or scientific research--- smooth structures, tangent vectors and covectors, vector bundles, immersed and embedded submanifolds, tensors, differential forms, de Rham cohomology, vector fields, flows, foliations, Lie derivatives, Lie groups, Lie algebras, and more. The approach is as concrete as possible, with pictures and intuitive discussions of how one should think geometrically about the abstract concepts, while making full use of the powerful tools that modern mathematics has to offer.This second edition has been extensively revised and clarified, and the topics have been substantially rearranged. The book now introduces the two most important analytic tools, the rank theorem and the fundamental theorem on flows, much earlier so that they can be used throughout the book. A few new topics have been added, notably Sard’s theorem and transversality, a proof that infinitesimal Lie group actions generate global group actions, a more thorough study of first-order partial differential equations, a brief treatment of degree theory for smooth maps between compact manifolds, and an introduction to contact structures.Prerequisites include a solid acquaintance with general topology, the fundamental group, and covering spaces, as well as basic undergraduate linear algebra and real analysis.

<p>New edition extensively revised and clarified, and topics have been substantially rearranged</p><p>Introduces the two most important analytic tools, the rank theorem and the fundamental theorem on flows, much earlier in the text</p><p>Added topics include Sard’s theorem and transversality, a proof that infinitesimal Lie group actions generate global group actions, a more thorough study of first-order partial differential equations, a brief treatment of degree theory for smooth maps between compact manifolds, and an introduction to contact structures</p><p>Includes supplementary material: sn.pub/extras</p><p>Includes supplementary material: sn.pub/extras</p>

John M. Lee is Professor of Mathematics at the University of Washington in Seattle, where he regularly teaches graduate courses on the topology and geometry of manifolds. He was the recipient of the American Mathematical Society's Centennial Research Fellowship and he is the author of four previous Springer books: the first edition (2003) of Introduction to Smooth Manifolds, the first edition (2000) and second edition (2010) of Introduction to Topological Manifolds, and Riemannian Manifolds: An Introduction to Curvature (1997).

9781441999818

10.1007/978-1-4419-9982-5

978-0-387-96787-5

Serge Lang, Yale University Dept. Mathematics, New Haven, CT, USA

1 Numbers.- 2 Linear Equations.- 3 Real Numbers.- 4 Quadratic Equations Interlude On Logic and Mathematical Expressions.- Interlude On Logic and Mathematical Expressions.- 5 Distance and Angles.- 6 Isometries.- 7 Area and Applications.- 8 Coordinates and Geometry.- 9 Operations on Points.- 10 Segments, Rays, and Lines.- 11 Trigonometry.- 12 Some Analytic Geometry.- 13 Functions.- 14 Mappings.- 15 Complex Numbers.- 16 Induction and Summations.- 17 Determinants.

This is a text in basic mathematics with multiple uses for either high school or college level courses. Readers will get a firm foundation in basic principles of mathematics which are necessary to know in order to go ahead in calculus, linear algebra or other topics. The subject matter is clearly covered and the author develops concepts so the reader can see how one subject matter can relate and grow into another.

9780387967875

10.1007/978-1-4612-1027-6

978-0-387-40101-0

1 General Probability Theory.- 2 Information and Conditioning.- 3 Brownian Motion.- 4 Stochastic Calculus.- 5 Risk-Neutral Pricing.- 6 Connections with Partial Differential Equations.- 7 Exotic Options.- 8 American Derivative Securities.- 9 Change of Numéraire.- 10 Term-Structure Models.- 11 Introduction to Jump Processes.- A Advanced Topics in Probability Theory.- A.1 Countable Additivity.- A.3 Random Variable with Neither Density nor Probability Mass Function.- B Existence of Conditional Expectations.- C Completion of the Proof of the Second Fundamental Theorem of Asset Pricing.- References.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes. This book is being published in two volumes. This second volume develops stochastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time. Masters level students and researchers in mathematical finance and financial engineering will find this book useful. Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes. This book is being published in two volumes. This second volume develops stochastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time. Master's level students and researchers in mathematical finance and financial engineering will find this book useful.

<p>Developed for the professional Master's program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S.</p><p>Tested in the classroom and revised over a period of several years</p><p>Includes supplementary material: sn.pub/extras</p>

Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

9780387401010

10.1007/978-1-4757-4296-1

978-3-662-57264-1

Martin Aigner, Freie Universität Berlin, Berlin, Germany; Günter M. Ziegler, Freie Universität Berlin, Berlin, Germany

,978-3-662-44204-3,978-3-662-44206-7,978-3-662-44205-0,978-3-662-49592-6

Number Theory: 1. Six proofs of the infinity of primes.- 2. Bertrand’s postulate.- 3. Binomial coefficients are (almost) never powers.- 4. Representing numbers as sums of two squares.- 5. The law of quadratic reciprocity.- 6. Every finite division ring is a field.- 7. The spectral theorem and Hadamard’s determinant problem.- 8. Some irrational numbers.- 9. Three times π2/6.- Geometry: 10. Hilbert’s third problem: decomposing polyhedral.- 11. Lines in the plane and decompositions of graphs.- 12. The slope problem.- 13. Three applications of Euler’s formula.- 14. Cauchy’s rigidity theorem.- 15. The Borromean rings don’t exist.- 16. Touching simplices.- 17. Every large point set has an obtuse angle.- 18. Borsuk’s conjecture.- Analysis: 19. Sets, functions, and the continuum hypothesis.- 20. In praise of inequalities.- 21. The fundamental theorem of algebra.- 22. One square and an odd number of triangles.- 23. A theorem of Pólya on polynomials.- 24. Van der Waerden's permanent conjecture.- 25. On a lemma of Littlewood and Offord.- 26. Cotangent and the Herglotz trick.- 27. Buffon’s needle problem.- Combinatorics: 28. Pigeon-hole and double counting.- 29. Tiling rectangles.- 30. Three famous theorems on finite sets.- 31. Shuffling cards.- 32. Lattice paths and determinants.- 33. Cayley’s formula for the number of trees.- 34. Identities versus bijections.- 35. The finite Kakeya problem.- 36. Completing Latin squares.- Graph Theory: 37. Permanents and the power of entropy.- 38. The Dinitz problem.- 39. Five-coloring plane graphs.- 40. How to guard a museum.- 41. Turán’s graph theorem.- 42. Communicating without errors.- 43. The chromatic number of Kneser graphs.- 44. Of friends and politicians.- 45. Probability makes counting (sometimes) easy.- About the Illustrations.- Index.

This revised and enlarged sixth edition of Proofs from THE BOOK features an entirely new chapter on Van der Waerden’s permanent conjecture, as well as additional, highly original and delightful proofs in other chapters.

From the citation on the occasion of the 2018 'Steele Prize for Mathematical Exposition'

“… It is almost impossible to write a mathematics book that can be read and enjoyed by people of all levels and backgrounds, yet Aigner and Ziegler accomplish this feat of exposition with virtuoso style. […] This book does an invaluable service to mathematics, by illustrating for non-mathematicians what it is that mathematicians mean when they speak about beauty.”

From the Reviews

'... Inside PFTB (Proofs from The Book) is indeed a glimpse of mathematical heaven, where clever insights and beautiful ideas combine in astonishing and glorious ways. There is vast wealth within its pages, one gem after another. ... Aigner and Ziegler... write: '... all we offer is the examples that we have selected, hoping that our readers will share our enthusiasm about brilliant ideas, clever insights and wonderful observations.' I do. ... '

Notices of the AMS, August 1999

'... This book is a pleasure to hold and to look at: ample margins, nice photos, instructive pictures and beautiful drawings ... It is a pleasure to read as well: the style is clear and entertaining, the level is close to elementary, the necessary background is given separately and the proofs are brilliant. ...'

LMS Newsletter, January 1999

'Martin Aigner and Günter Ziegler succeeded admirably in putting together a broad collection of theorems and their proofs that would undoubtedly be in the Book of Erdös. The theorems are so fundamental, their proofs so elegant and the remaining open questions so intriguing that every mathematician, regardless of speciality, can benefit from reading this book. ... '

SIGACT News, December 2011

This revised and enlarged sixth edition of Proofs from THE BOOK features an entirely new chapter on Van der Waerden’s permanent conjecture, as well as additional, highly original and delightful proofs in other chapters.From the citation on the occasion of the 2018 'Steele Prize for Mathematical Exposition' “… It is almost impossible to write a mathematics book that can be read and enjoyed by people of all levels and backgrounds, yet Aigner and Ziegler accomplish this feat of exposition with virtuoso style. […] This book does an invaluable service to mathematics, by illustrating for non-mathematicians what it is that mathematicians mean when they speak about beauty.”From the Reviews'... Inside PFTB (Proofs from The Book) is indeed a glimpse of mathematical heaven, where clever insights and beautiful ideas combine in astonishing and glorious ways. There is vast wealth within its pages, one gem after another. ... Aigner and Ziegler... write: '... all we offer is the examples that we have selected, hoping that our readers will share our enthusiasm about brilliant ideas, clever insights and wonderful observations.' I do. ... 'Notices of the AMS, August 1999'... This book is a pleasure to hold and to look at: ample margins, nice photos, instructive pictures and beautiful drawings ... It is a pleasure to read as well: the style is clear and entertaining, the level is close to elementary, the necessary background is given separately and the proofs are brilliant. ...'LMS Newsletter, January 1999'Martin Aigner and Günter Ziegler succeeded admirably in putting together a broad collection of theorems and their proofs that would undoubtedly be in the Book of Erdös. The theorems are so fundamental, their proofs so elegant and the remaining open questions so intriguing that every mathematician, regardless of speciality, can benefit from reading this book. ... ' SIGACT News, December 2011

<p>Revised and enlarged sixth edition</p><p>New chapter on Van der Waerden’s permanent conjecture</p><p>New sections on the asymptotics for the number of Latin squares</p><p>New proof for the Basel problem</p><p>Geometric explanation for the involution proof for Fermat's two squares theorem</p><p>Presents some recent jewels and surprises</p>

Martin Aigner received his Ph.D. from the University of Vienna and has been professor of mathematics at the Freie Universität Berlin since 1974. He has published in various fields of combinatorics and graph theory and is the author of several monographs on discrete mathematics, among them the Springer books Combinatorial Theory and A Course on Enumeration. Martin Aigner is a recipient of the 1996 Lester R. Ford Award for mathematical exposition of the Mathematical Association of America MAA.Günter M. Ziegler received his Ph.D. from M.I.T. and has been professor of mathematics in Berlin – first at TU Berlin, now at Freie Universität – since 1995. He has published in discrete mathematics, geometry, topology, and optimization, including the Lectures on Polytopes with Springer, as well as „Do I Count? Stories from Mathematics“. Günter M. Ziegler is a recipient of the 2006 Chauvenet Prize of the MAA for his expository writing and the 2008 Communicator award of the German Science Foundation.Martin Aigner and Günter M. Ziegler have started their work on Proofs from THE BOOK in 1995 together with Paul Erdös. The first edition of this book appeared in 1998 – it has since been translated into 13 languages: Brazilian, Chinese, German, Farsi, French, Hungarian, Italian, Japanese, Korean, Polish, Russian, Spanish, and Turkish.

9783662572641

978-0-387-90244-9

Robin Hartshorne, Department of Mathematics University of California at Berkeley, Berkeley, CA, USA

I Varieties.- II Schemes.- III Cohomology.- IV Curves.- V Surfaces.- Appendix A Intersection Theory.- 1 Intersection Theory.- 2 Properties of the Chow Ring.- 3 Chern Classes.- 4 The Riemann-Roch Theorem.- 5 Complements and Generalizations.- Appendix B Transcendental Methods.- 1 The Associated Complex Analytic Space.- 2 Comparison of the Algebraic and Analytic Categories.- 3 When is a Compact Complex Manifold Algebraic?.- 4 Kähler Manifolds.- 5 The Exponential Sequence.- Appendix C The Weil Conjectures.- 1 The Zeta Function and the Weil Conjectures.- 2 History of Work on the Weil Conjectures.- 3 The /-adic Cohomology.- 4 Cohomological Interpretation of the Weil Conjectures.- Results from Algebra.- Glossary of Notations.

Robin Hartshorne studied algebraic geometry with Oscar Zariski and David Mumford at Harvard, and with J.-P. Serre and A. Grothendieck in Paris. After receiving his Ph.D. from Princeton in 1963, Hartshorne became a Junior Fellow at Harvard, then taught there for several years. In 1972 he moved to California where he is now Professor at the University of California at Berkeley. He is the author of 'Residues and Duality' (1966), 'Foundations of Projective Geometry (1968), 'Ample Subvarieties of Algebraic Varieties' (1970), and numerous research titles. His current research interest is the geometry of projective varieties and vector bundles. He has been a visiting professor at the College de France and at Kyoto University, where he gave lectures in French and in Japanese, respectively. Professor Hartshorne is married to Edie Churchill, educator and psychotherapist, and has two sons. He has travelled widely, speaks several foreign languages, and is an experienced mountain climber. He is also an accomplished amateur musician: he has played the flute for many years, and during his last visit to Kyoto he began studying the shakuhachi.

9780387902449

10.1007/978-1-4757-3849-0

978-0-387-95385-4

Serge Lang, Yale University Dept. Mathematics, New Haven, CT, USA

One The Basic Objects of Algebra.- I Groups.- II Rings.- III Modules.- IV Polynomials.- Two Algebraic Equations.- V Algebraic Extensions.- VI Galois Theory.- VII Extensions of Rings.- VIII Transcendental Extensions.- IX Algebraic Spaces.- X Noetherian Rings and Modules.- XI Real Fields.- XII Absolute Values.- Three Linear Algebra and Representations.- XIII Matrices and Linear Maps.- XIV Representation of One Endomorphism.- XV Structure of Bilinear Forms.- XVI The Tensor Product.- XVII Semisimplicity.- XVIII Representations of Finite Groups.- XIX The Alternating Product.- Four Homological Algebra.- XX General Homology Theory.- XXI Finite Free Resolutions.- Appendix 2 Some Set Theory.

This book is intended as a basic text for a one-year course in Algebra at the graduate level, or as a useful reference for mathematicians and professionals who use higher-level algebra. It successfully addresses the basic concepts of algebra. For the revised third edition, the author has added exercises and made numerous corrections to the text.

Comments on Serge Lang's Algebra:
Lang's Algebra changed the way graduate algebra is taught, retaining classical topics but introducing language and ways of thinking from category theory and homological algebra. It has affected all subsequent graduate-level algebra books.
April 1999 Notices of the AMS, announcing that the author was awarded the Leroy P. Steele Prize for Mathematical Exposition for his many mathematics books.

The author has an impressive knack for presenting the important and interesting ideas of algebra in just the 'right' way, and he never gets bogged down in the dry formalism which pervades some parts of algebra.
MathSciNet's review of the first edition

From April 1999 Notices of the AMS, announcing that the author was awarded the Leroy P. Steele Prize for Mathematical Exposition for his many mathematics books: 'Lang's Algebra changed the way graduate algebra is taught, retaining classical topics but introducing language and ways of thinking from category theory and homological algebra. It has affected all subsequent graduate-level algebra books.'
From MathSciNet's review of the first edition:
'The author has an impressive knack for presenting the important and interesting ideas of algebra in just the 'right' way, and he never gets bogged down in the dry formalism which pervades some parts of algebra.'
This book is intended as a basic text for a one-year course in Algebra at the graduate level, or as a useful reference for mathematicians and professionals who use higher-level algebra. This book successfully addresses all of the basic concepts of algebra. For the new edition, the author has added exercises and made numerous corrections to the text.

<p>This book is considered a classic, which "changed the way algebra was taught" (Notices of the AMS)</p>

9780387953854

10.1007/978-1-4613-0041-0

Diana Weedman Molavi, Sinai Hospital of Baltimore Pathology, Baltimore, MD, USA

,978-0-387-52080-3,978-0-387-74485-8,978-1-4899-8922-2,978-0-387-74486-5

Using the Microscope.- Descriptive Terms in Anatomic Patholgy.- Infection and Inflammation.- Interpreting the Complex Epithelium.- Ditzels.- Esophagus.- Stomach and Duodenum.- Colon and Appendix.- Liver.- Pancreas.- Prostate.- Bladder.- Kidney.- Testis.- Ovary.- Cervix and Vagina.- Uterus.- Placenta.- Breast.- Bone Marrow.- Lymph Node and Spleen.- Lungs and Pleura.- Thymus and Mediastinum.- Thyroid.- Salivary Gland.- Neuroendocrine Neoplasms.- Brain and Meninges.- Skin.- Soft Tissues.- Bone.- A Primer on Immunostains.- So You Want to Get a Job?.

<div>Within the field of pathology, there is a wide gap in pedagogy between medical school and residency. As a result, the pathology intern often comes into residency unprepared for the practical demands of the field, and without the foundation to digest professional-level textbooks. Completely illustrated in color, this book is uniquely directed at the junior pathology resident, and goes first through some very basic introductory material, then progresses through each organ system. Within each chapter, there is a brief review of salient normal histology, a discussion of typical specimen types, a strategic approach to the specimen, and a discussion of how the multitude of different diagnoses relate to each other. The book’s goal is to lay the foundation of practical pathology, and provide a scaffold on which to build more detailed knowledge. The second edition retains the informal voice and brevity of the first edition, but with new and expanded chapters, new illustrations, and updated material.</div>

Within the field of pathology, there is a wide gap in pedagogy between medical school and residency. As a result, the pathology intern often comes into residency unprepared for the practical demands of the field, and without the foundation to digest professional-level textbooks. Completely illustrated in color, this book is uniquely directed at the junior pathology resident, and goes first through some very basic introductory material, then progresses through each organ system. Within each chapter, there is a brief review of salient normal histology, a discussion of typical specimen types, a strategic approach to the specimen, and a discussion of how the multitude of different diagnoses relate to each other. The book’s goal is to lay the foundation of practical pathology, and provide a scaffold on which to build more detailed knowledge. The second edition retains the informal voice and brevity of the first edition, but with new and expanded chapters, new illustrations, and updated material.

<p>Uniquely directed at junior residents in pathology</p><p>Written with no prior pathology knowledge assumed</p><p>Each organ-system-based chapter can be reviewed in 20-30 minutes</p><p>Conversational and informal style</p><p>Completely illustrated in color with annotated figures</p><p>Ample white space is provided for notes and additions</p><p>Includes supplementary material: sn.pub/extras</p>

<div>Diana Weedman Molavi MD PhD, </div><div>Staff Pathologist at Sinai Hospital of Baltimore, </div><div>Baltimore, MD</div><div>
</div>

9783319592107

149114_2_En

978-3-030-40343-0

Charu C. Aggarwal, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

Preface.- 1 Linear Algebra and Optimization: An Introduction.- 2 Linear Transformations and Linear Systems.- 3 Eigenvectors and Diagonalizable Matrices.- 4 Optimization Basics: A Machine Learning View.- 5 Advanced Optimization Solutions.- 6 Constrained Optimization and Duality.- 7 Singular Value Decomposition.- 8 Matrix Factorization.- 9 The Linear Algebra of Similarity.- 10 The Linear Algebra of Graphs.- 11 Optimization in Computational Graphs.- Index.

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows: 1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts.
2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The “parent problem” of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks.
A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors. This textbook targets graduate level students and professors in computer science, mathematics and data science. Advanced undergraduate students can also use this textbook. The chapters for this textbook are organized as follows:1. Linear algebra and its applications: The chapters focus on the basics of linear algebra together with their common applications to singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. Numerous machine learning applications have been used as examples, such as spectral clustering, kernel-based classification, and outlier detection. The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra. The focus is clearly on the most relevant aspects of linear algebra for machine learning and to teach readers how to apply these concepts.
2. Optimization and its applications: Much of machine learning is posed as an optimization problem in which we try to maximize the accuracy of regression and classification models. The “parent problem” of optimization-centric machine learning is least-squares regression. Interestingly, this problem arises in both linear algebra and optimization, and is one of the key connecting problems of the two fields. Least-squares regression is also the starting point for support vector machines, logistic regression, and recommender systems. Furthermore, the methods for dimensionality reduction and matrix factorization also require the development of optimization methods. A general view of optimization in computational graphs is discussed together with its applications to back propagation in neural networks.
A frequent challenge faced by beginners in machine learning is the extensive background required in linear algebra and optimization. One problem is that the existing linear algebra and optimization courses are not specific to machine learning; therefore, one would typically have to complete more course material than is necessary to pick up machine learning. Furthermore, certain types of ideas and tricks from optimization and linear algebra recur more frequently in machine learning than other application-centric settings. Therefore, there is significant value in developing a view of linear algebra and optimization that is better suited to the specific perspective of machine learning.


<div></div>

<p>First textbook to provide an integrated treatment of linear algebra and optimization with a special focus on machine learning issues</p><p>Includes many examples to simplify exposition and facilitate in learning semantically</p><p>Complemented by examples and exercises throughout the book. A solution manual for the exercises at the end of each chapter is available to teaching instructors</p><p>Includes supplementary material: sn.pub/extras</p>

Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his undergraduate degree in Computer Science from the Indian Institute of Technology at Kanpur in 1993 and his Ph.D. in Operations Research from the Massachusetts Institute of Technology in 1996. He has published more than 400 papers in refereed conferences and journals and has applied for or been granted more than 80 patents. He is author or editor of 19 books, including textbooks on data mining, neural networks, machine learning (for text), recommender systems, and outlier analysis. Because of the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He has received several internal and external awards, including the EDBT Test-of-Time Award (2014), the IEEE ICDM Research Contributions Award (2015), and the ACM SIGKDD Innovation Award (2019). He has served as editor-in-chief of the ACM SIGKDD Explorations, and is currently serving as an editor-in-chief of the ACM Transactions on Knowledge Discovery from Data. He is a fellow of the SIAM, ACM, and the IEEE, for “contributions to knowledge discovery and data mining algorithms.”

9783030403430

476746_1_En

10.1007/978-3-030-40344-7

Catherine S.W. Albin, Emory University School of Medicine, Atlanta, GA, USA; Sahar F. Zafar, Harvard University, Boston, MA, USA

Part One: A Comprehensive “How-To” Guide.- Pre-Rounding On and Presenting Floor Patients. Pre-Rounding and Presenting NeuroICU Patients.- The Coma Exam.- Tips for Common Cranial Nerve Exam Findings.- Stroke and Vascular Anatomy.- Basics of Computed Tomography (CT).- Basics of MRI Ordering and Assessment.- Understanding Transcranial Dopplers (TCDs).- Tips and Tricks for EEG Interpretation.- Part Two: Vascular Neurology.- Acute Ischemic Stroke – First Encounter Assessment and Management.- Perfusion Imaging.- Ischemic Stroke: Admission Checklist.- Stroke Workup Beyond the Basics.- Ischemic Stroke – Dissection.- Ischemic Stroke - Symptomatic Carotid Stenosis (“Hot Carotid”).- Ischemic Stroke – Post Stroke Management of Anticoagulation.- Selected Anti-Platelets and Anticoagulation in Stroke Prevention.- Acute Management Strategies – TPA and Mechanical Thrombectomy Trials.- Venous Sinus Thrombosis.- Posterior Reversible Vasoconstriction Syndrome (PRES) and Reversible Cerebral Vasoconstriction Syndrome (RCVS).- Part Three: Non-Vascular Inpatient Neurology.- Altered Mental Status.- Framework for Workup of Unknown Brain “Lesion”.- Approach to First-Time Seizure.- Pharmacology Tips for Commonly Used AEDs Tips.- Approach to Infectious Encephalitis and Meningitis.- Aseptic Meningitis.- Inflammatory and Autoimmune Encephalitis.- Differential Diagnosis and Ordering Guide: Neuroanatomical Syndromes.- Autoimmune Encephalitis Testing.- Approach to New Onset Weakness.- Workup of New Demyelinating Lesions.- Approach to the “Dizzy” Patient.- Part Four: NeuroICU.- Intracranial Pressure: Theory and Management Strategies.- Management of External Ventricular Catheters.- Malignant Middle Cerebral Artery Infarction Intracerebral Hemorrhage – Management.- Intracranial Hemorrhage – LandmarkTrials.- Reversal of Selected Anti-Thrombotics.- An In-Depth Review of Reversing Direct Factor XA-Inhibitor-Related Hemorrhages.- Intracranial Hemorrhage - Management of Anticoagulation.- Subarachnoid Hemorrhage – Differential.- Aneurysmal SAH – Admission and Early Management.- Subarachnoid Hemorrhage – Scoring Systems.- Aneurysmal SAH – Daily Management Principles.- Subarachnoid Hemorrhage – Notable Trials.- Traumatic Brain Injury.-Trials in TBI.- Induced Hypothermia after Cardiac Arrest.- Status Epilepticus.- Continuous EEG Monitoring, Electrographic Seizures and The Ictal-Interictal Continuum.- Neuromuscular Crises: ICU Management of Guillan Barr & Myasthenia Gravis.- Evaluation of C-Spine Trauma.- ICU Management of Spinal Cord Injuries.- Management of Post-Operative Craniotomy Patients.- Post-Operative Management of Cerebrovascular Patients.- Preparation for Brain Death Testing.- Nutrition in the NeuroICU.- Hypernatremia in the NeuroICU.- Hyponatremia in the NeuroICU.- Pressors and Inotropes Commonly Used in the NeuroICU Seizure Prophylaxis in the NeuroICU.- Venous Thromboembolism Prophylaxis in the NeuroICU.- Part Five: Important References.- Brainstem Anatomy NeuroICU Intravenous Fluid Compositions.- Anti-Epileptic Drug Chart, For Use in Adults.- Drug-Drug Interactions Common in Neuro Patients.- Myasthenia Gravis: Medications to Avoid.- Parkinson’s Disease: Medications to Avoid.

This practical guide for trainees and advanced practice providers covers the essential management of hospitalized patients with acute neurologic conditions. Divided into five sections, this text serves as an incredibly easy-to-use, visually accessible, how-to manual that covers exactly what every responding clinician needs to know to care for the patient in front of them.

The first section provides tangible guidance about how to pre-round, structure a presentation, examine neurologically ill patients, and interpret the core diagnostics obtained in many neurology patients: CT, MRI and EEG. The next three sections cover common complaints encountered in the hospital: spanning from non-vascular admissions, vascular & stroke neurology topics, and core neurocritical care principals and chief complaints. Throughout are checklists, scoring systems, pro-tips, images, helpful reminders, as well as concise summary of the pertinent literature.

This is an ideal guide for medical students, neurology & neurosurgery trainees and advanced practice providers, as well as experienced professionals who want to brush up on the latest updates.

This practical guide for trainees and advanced practice providers covers the essential management of hospitalized patients with acute neurologic conditions. Divided into five sections, this text serves as an incredibly easy-to-use, visually accessible, how-to manual that covers exactly what every responding clinician needs to know to care for the patient in front of them.The first section provides tangible guidance about how to pre-round, structure a presentation, examine neurologically ill patients, and interpret the core diagnostics obtained in many neurology patients: CT, MRI and EEG. The next three sections cover common complaints encountered in the hospital: spanning from non-vascular admissions, vascular & stroke neurology topics, and core neurocritical care principals and chief complaints. Throughout are checklists, scoring systems, pro-tips, images, helpful reminders, as well as concise summary of the pertinent literature. This is an ideal guide for medical students, neurology & neurosurgery trainees and advanced practice providers, as well as experienced professionals who want to brush up on the latest updates.

<p>Offers a practical guide to neurocritical care for trainees in neurology</p><p>Acts as a practical beside tool</p><p>Written by expert authors</p>

Sahar F. Zafar, MD, MBBS<div><div>Department of Neurology<div>Massachusetts General Hospital</div><div>Harvard Medical School</div><div>Boston, MA</div><div>
</div><div>Catherine SW Albin, MD </div><div>Department of Neurology</div><div>Division of Neurocritical Care</div><div>Emory University School of Medicine </div><div>Atlanta, GA</div></div></div>

9783030757311

485093_1_En

978-981-19-0062-4

Masatoshi Makuuchi; Norihiro Kokudo; Irinel Popescu; Jacques Belghiti; Ho-Seong Han; Kyoichi Takaori; Dan G. Duda

Masatoshi Makuuchi, The University of Tokyo, Tokyo, Japan; Norihiro Kokudo, The University of Tokyo, Tokyo, Japan; Irinel Popescu, Fundeni Clinical Institute, Bucharest, Romania; Jacques Belghiti, Emeritus Professor University Paris Cité, Paris, France; Ho-Seong Han, Seoul National University College of Medicine Seoul National University Bundang Hospital, Seoul, Korea (Republic of); Kyoichi Takaori, Nagahama City Hospital Network, Shiga, Japan; Dan G. Duda, Massachusetts General Hospital, Harvard Medical School, Boston, USA

The IASGO Textbook of Multi-Disciplinary Management of Hepato-Pancreato-Biliary Diseases

1. Surgical anatomy of the liver.- 2.Surgical anatomy of the pancreas.- 3. Surgical anatomy of the biliary tract.- 4. Liver function and posthepatectomy liver failure.- 5. Surgical approach to Pancreas, Liver, Biliary Physiologic Impairment.- 6. Biliary tract functions and impairment.- 7. Preinvasive intraductal biliary neoplasm: Biliary intraepithelial biliary neoplasm and intraductal papillary neoplasm of bile duct.- 8. Pathology of biliary tract cancers.- 9. Multifocal hepatocellular carcinoma: Genomic and transcriptional heterogeneity.- 10. Intraductal neoplasms of the pancreas.- 11. Mucinous cystic neoplasms (MCNs). -12. Pathology of Pancreatic Cancer.- 13. CT in Hepato-Bilio-Pancreatic Surgical Pathology.- 14. Magnetic Resonance Elastography (MRE) to assess hepatic fibrosis.- 15. FDG-PET for management on Hepato-pancreato-biliary disease.- 16. Endoscopic ultrasound for hepato-pancreato-biliary diseases.- 17. Intraoperative imaging techniques in liver surgery.- 18. Scientific rationale for combination therapies in HPB malignancies Use of radiotherapy alone and in combination with other therapies for hepatocellular carcinoma: Rationale and future directions.- 19. Recent update in chemotherapy of Cholangiocarcinoma.- 20. Chemotherapy in pancreatic ductal adenocarcinoma.- 21. Immune-checkpoint inhibitors in hepatocellular carcinoma.- 22. Molecularly targeted therapy in cholangiocarcinoma.- 23. Systemic therapies in pancreatic cancers.- 24. Endoscopic Biliary Drainage and Associated Procedures Required for Patients with Malignant Biliary Strictures.- 25. Endoscopic management of peripancreatic fluid collection.- 26. Endoscopic ultrasound and fine needle tissue acquisition for pancreatic tumors.- 27. Concept and purpose of ERAS.- 28. Multidisciplinary Enhanced Recovery After Surgery (ERAS) pathway for hepatobiliary and pancreatic surgery.- 29. ERAS for pancreatic surgery.- 30.Ultrasound-guided anatomic resection of the liver.- 31. Parenchyma-sparing hepatic resection for multiple metastatic tumors.- 32. Open and laparoscopic liver hanging maneuver.- 33. The Glissonean pedicle approach: The Takasaki Technique.- 34. Laparoscopic Major Hepatectomy and Parenchymal-Sparing Anatomical Hepatectomy.- 35. Laparoscopic anatomical resection of the liver: Segmentectomy and Sub-segmentectomy.- 36. Modified ALPPS procedure.- 37. Artery-first approach in pancreaticoduodenectomy.- 38. Organ and parenchyma sparing pancreatic surgery.- 39. Isolated pancreatoduodenectomy with portal vein resection using the Nakao mesenteric approach.- 40. Pancreaticoduodenectomy with hepatic artery resection.- 41. Pancreaticoduodenectomy with splenic artery resection for tumors of the pancreatic head and/or body invading the splenic artery.- 42. Pancreaticoduodenectomy with superior mesenteric resection and reconstruction for locally advanced tumors.- 43. Robotic Pancreaticoduodenectomy.- 44. Duodenum-Preserving Pancreatic Head Resection.- 45. Artery-first approaches to distal pancreatectomy.- 46. Spleen-preserving distal pancreatectomy.- 47. Distal pancreatectomy with en bloc celiac axis resection (DP-CAR).- 48. Modified Distal Pancreatectomy with Celiac Axis En-bloc Resection (modified DP-CAR).- 49. Robotic distal pancreatectomy.- 50. Pancreaticoduodenectomy with superior mesenteric resection and reconstruction for locally advanced tumors.- 51. Pancreatic resection for solid pseudopapillary neoplasms.- 52. Pancreatic resection for neuroendocrine neoplasms of the pancreas.- 53. International Consensus Guidelines for the management of intraductal papillary mucinous neoplasms.- 54. Remnant pancreatic cancer after surgical re

This textbook includes 70 chapters contributed by an exceptional group of experts in all areas of hepato-pancreato-biliary diseases, bringing a multi-disciplinary approach to treatments. The book is designed to cover all aspects of the liver and pancreatic anatomy and pathology, as well as therapy. The topics are comprehensively reviewed, and as well as summarizing the previous works, the authors provide discussions of practice-changing techniques and approaches to therapy of HBP cancers. Treating the diseases in hepato-pancreato-biliary regions is particularly difficult due to the complex anatomy, aggressive biological behavior, and poor prognosis. Therefore, ample illustrations are included to tackle these challenges.The IASGO Textbook of Multi-Disciplinary Management of Hepato-Pancreato-Biliary Diseases aims to update the academic and non-academic medical professionals, such as surgeons, radiation oncologists, medical oncologists, gastroenterologists, interventional radiologists, radiologists, basic scientists. In collaboration with the International Association of Surgeons, Gastroenterologists and Oncologists (IASGO), delivers a valuable and well-organized textbook for medical professionals.

This textbook includes 70 chapters contributed by an exceptional group of experts in all areas of hepato-pancreato-biliary diseases, bringing a multi-disciplinary approach to treatments. The book is designed to cover all aspects of the liver and pancreatic anatomy and pathology, as well as therapy. The topics are comprehensively reviewed, and as well as summarizing the previous works, the authors provide discussions of practice-changing techniques and approaches to therapy of HBP cancers. Treating the diseases in hepato-pancreato-biliary regions is particularly difficult due to the complex anatomy, aggressive biological behavior, and poor prognosis. Therefore, ample illustrations are included to tackle these challenges.The IASGO Textbook of Multi-Disciplinary Management of Hepato-Pancreato-Biliary Diseases aims to update the academic and non-academic medical professionals, such as surgeons, radiation oncologists, medical oncologists, gastroenterologists, interventional radiologists, radiologists, basic scientists. In collaboration with the International Association of Surgeons, Gastroenterologists and Oncologists (IASGO), delivers a valuable and well-organized textbook for medical professionals.<div><div><div></div><div><div><div></div><div></div></div></div></div></div>

<p>Cover all aspect of liver and pancreatic anatomy and pathology, as well as therapy</p><p>Provides multidisciplinary approaches to difficult to treat disease</p><p>International participation from all continents within the framework of IASGO</p>

<div>This Textbook is published in collaboration with the International Association of Surgeons, Gastroenterologists and Oncologists (IASGO).</div><div>
</div><div>​Dr. Masatoshi Makuuchi served as Professor and Chairman for both Hepatobiliary Pancreatic Surgery Division and Artificial Organ and Transplantation Surgery Division, University of Tokyo, Japan, and is the President of the IASGO. He has pioneered multiple techniques in liver surgery.</div><div>
</div><div>Dr. Norihiro Kokudo served as Professor and Chairman for both Hepatobiliary Pancreatic Surgery Division and Artificial Organ and Transplantation Surgery Division at The University of Tokyo Hospital, Japan. He is now the President of the National Center for Global Health and Medicine and IASGO VicePresident, and a leader in the field of liver cancer treatment.</div><div>
</div><div>Dr. Irinel Popescu led the Department of Surgery and Liver Transplantation at the Fundeni Clinical Institute in Romania. He was elected as a corresponding member of the Romanian Academy. He introduced liver transplantation in Romania and performed more than 1,000 liver transplantations. He serves as the VicePresident of IASGO.</div><div>
</div><div>Dr. Jacques Belghiti was the Head of the HepatoBilioPancreatic Surgery and Liver Transplantation department in Beaujon Hospital, University of Paris. In 2014 he was nominated by the President of France to the board of the High Authority for Health. Professor Belghiti’s has produced important studies in the surgical techniques of liver resection and hepato‐pancreato‐biliary surgical oncology. He serves as the VicePresident of IASGO.</div><div>
</div><div>Dr. Ho-Seong Han is a Professor at the Seoul National University Hospital and Chairman of Department of Surgery at the Seoul National University Bundang Hospital, Korea. He is a pioneer in minimally invasive surgery in the field of hepato‐pancreato‐biliary surgery and has performed more than 1,000 laparoscopic liver surgeries. He serves as teh Treasurer of the IASGO.</div><div>
</div><div>Dr. Kyoicihi Takaori was the Director of the Pancreatic Cancer Unit, Kyoto University Hospital Cancer Center, Japan. He has made important contributions to pancreatic cancer surgery techniques, robotic surgery, multimodality management of pancreatic cancer, and screening for pancreatic cancer. He serves as Secretary General of IASGO.</div><div>
</div><div>Dr. Dan G. Duda is the Director of Translational Research in Gastrointestinal Radiation Oncology at Massachusetts General Hospital and Harvard Medical School, Boston, USA. He is an expert in combinatorial strategies for liver and pancreatic malignancies, and is Secretary General of IASGO.</div>

9789811900624

517115_1_En

,978-3-319-19202-4,978-3-319-19200-0,978-3-319-19201-7,978-3-319-36756-9

Part I Foundations: Introduction.- Special Relativity.- Part II Symmetry Tools: Lie Group Theory.- The Framework.- Part III The Equations of Nature: Measuring Nature.- Free Theory.- Interaction Theory.- Part IV Applications: Quantum Mechanics.- Quantum Field Theory.- Classical Mechanics.- Electrodynamics.- Gravity.- Closing Words.- Part V Appendices: Vector Calculus.- Calculus.- Linear Algebra.- Additional Mathematical Notions.

This is a textbook that derives the fundamental theories of physics from symmetry.<br/> It starts by introducing, in a completely self-contained way, all mathematical tools needed to use symmetry ideas in physics. Thereafter, these tools are put into action and by using symmetry constraints, the fundamental equations of Quantum Mechanics, Quantum Field Theory, Electromagnetism, and Classical Mechanics are derived.<br/> <br/> As a result, the reader is able to understand the basic assumptions behind, and the connections between the modern theories of physics. The book concludes with first applications of the previously derived equations.<br/> <br/> Thanks to the input of readers from around the world, this second edition has been purged of typographical errors and also contains several revised sections with improved explanations. 

This is a textbook that derives the fundamental theories of physics from symmetry.<br/> It starts by introducing, in a completely self-contained way, all mathematical tools needed to use symmetry ideas in physics. Thereafter, these tools are put into action and by using symmetry constraints, the fundamental equations of Quantum Mechanics, Quantum Field Theory, Electromagnetism, and Classical Mechanics are derived.<br/> <br/> As a result, the reader is able to understand the basic assumptions behind, and the connections between the modern theories of physics. The book concludes with first applications of the previously derived equations.<br/> <br/> Thanks to the input of readers from around the world, this second edition has been purged of typographical errors and also contains several revised sections with improved explanations. 

<p>A highly praised new approach to teaching basic physics based on symmetry principles</p><p>Self-contained and pedagogical presentation</p><p>Reveals the inner consistency and elegance of theoretical physics in a way no textbook has done before</p><p>This second corrected edition contains many revised sections with improved explanations</p>

9783319666303

333060_2_En

978-0-387-40100-3

1 The Binomial No-Arbitrage Pricing Model.- 1.1 One-Period Binomial Model.- 1.2 Multiperiod Binomial Model.- 1.3 Computational Considerations.- 1.4 Summary.- 1.5 Notes.- 1.6 Exercises.- 2 Probability Theory on Coin Toss Space.- 2.1 Finite Probability Spaces.- 2.2 Random Variables, Distributions, and Expectations.- 2.3 Conditional Expectations.- 2.4 Martingales.- 2.5 Markov Processes.- 2.6 Summary.- 2.7 Notes.- 2.8 Exercises.- 3 State Prices.- 3.1 Change of Measure.- 3.2 Radon-Nikodým Derivative Process.- 3.3 Capital Asset Pricing Model.- 3.4 Summary.- 3.5 Notes.- 3.6 Exercises.- 4 American Derivative Securities.- 4.1 Introduction.- 4.2 Non-Path-Dependent American Derivatives.- 4.3 Stopping Times.- 4.4 General American Derivatives.- 4.5 American Call Options.- 4.6 Summary.- 4.7 Notes.- 4.8 Exercises.- 5 Random Walk.- 5.1 Introduction.- 5.2 First Passage Times.- 5.3 Reflection Principle.- 5.4 Perpetual American Put: An Example.- 5.5 Summary.- 5.6 Notes.- 5.7 Exercises.- 6 Interest-Rate-Dependent Assets.- 6.1 Introduction.- 6.2 Binomial Model for Interest Rates.- 6.3 Fixed-Income Derivatives.- 6.4 Forward Measures.- 6.5 Futures.- 6.6 Summary.- 6.7 Notes.- 6.8 Exercises.- Proof of Fundamental Properties of Conditional Expectations.- References.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stchastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.
This book is being published in two volumes. The first volume presents the binomial asset-pricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuous-time theory in the second volume.
Chapter summaries and detailed illustrations are included. Classroom tested exercises conclude every chapter. Some of these extend the theory and others are drawn from practical problems in quantitative finance.
Advanced undergraduates and Masters level students in mathematical finance and financial engineering will find this book useful.
Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.
This book is being published in two volumes. The first volume presents the binomial asset-pricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuous-time theory in the second volume.
Chapter summaries and detailed illustrations are included. Classroom tested exercises conclude every chapter. Some of these extend the theory and others are drawn from practical problems in quantitative finance.
Advanced undergraduates and Masters level students in mathematical finance and financial engineering will find this book useful.
Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

<p>Developed for the professional Master's program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S.</p><p>Has been tested in the classroom and revised over a period of several years</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

9780387401003

10.1007/978-0-387-22527-2

978-1-4614-6270-5

Distribution rights for India: Researchco Book Centre, New Delhi, India

,978-1-4419-2811-5,978-0-387-90459-7,978-1-4757-3972-5,978-1-4757-3971-8,978-1-4939-7069-8

Preface.- 1 Introduction.- 2 Sequences.- 3 Continuity.- 4 Sequences and Series of Functions.- 5 Differentiation.- 6 Integration.- 7 Capstone.- Appendix on Set Notation.- Selected Hints and Answers.- References.- Index.

For over three decades, this best-selling classic has been used by thousands of students in the United States and abroad as a must-have textbook for a transitional course from calculus to analysis. It has proven to be very useful for mathematics majors who have no previous experience with rigorous proofs. Its friendly style unlocks the mystery of writing proofs, while carefully examining the theoretical basis for calculus. Proofs are given in full, and the large number of well-chosen examples and exercises range from routine to challenging.The second edition preserves the book’s clear and concise style, illuminating discussions, and simple, well-motivated proofs. New topics include material on the irrationality of pi, the Baire category theorem, Newton's method and the secant method, and continuous nowhere-differentiable functions.Review from the first edition:'This book is intended for the student who has a good, but naïve, understanding of elementary calculus and now wishes to gain a thorough understanding of a few basic concepts in analysis.... The author has tried to write in an informal but precise style, stressing motivation and methods of proof, and ... has succeeded admirably.'—MATHEMATICAL REVIEWS

For over three decades, this best-selling classic has been used by thousands of students in the United States and abroad as a must-have textbook for a transitional course from calculus to analysis. It has proven to be very useful for mathematics majors who have no previous experience with rigorous proofs. Its friendly style unlocks the mystery of writing proofs, while carefully examining the theoretical basis for calculus. Proofs are given in full, and the large number of well-chosen examples and exercises range from routine to challenging.The second edition preserves the book’s clear and concise style, illuminating discussions, and simple, well-motivated proofs. New topics include material on the irrationality of pi, the Baire category theorem, Newton's method and the secant method, and continuous nowhere-differentiable functions.

<p>Revised and updated second edition with new material</p><p>Text for a transition course between calculus and more advanced analysis courses</p><p>Contains new material on topics such as irrationality of pi, the Baire category theorem, Newton's method and the secant method, and continuous nowhere-differentiable functions</p><p>Includes new examples and improved proofs</p><p>Includes supplementary material: sn.pub/extras</p>

Kenneth A. Ross is currently an emeritus professor of mathematics at the University of Oregon.Jorge M. López is currently professor of mathematics at the University of Puerto Rico.

9781461462705

10.1007/978-1-4614-6271-2

Diana Noland, Noland Nutrition, Burbank, CA, USA; Jeanne A. Drisko, University of Kansas Health System, Kansas City, KS, USA; Leigh Wagner, University of Kansas Medical Center, Kansas City, KS, USA

Part I: Principles.- Section 1: Global Healthcare Challenge of the 21st Century and the Future of Chronic Disease.- The History and Evolution of Medicine.- Influences of the Nutrition Transition on chronic Disease.- Nutritional and Metabolic Wellness.- Nutritional Ecology and Human Health.- The Radial: Integrative and Functional MNT.- The Power of Listening and the Patient's Voice: 'Please Hear Me'. Section 2: Metabolic Characteristics and Mechanism of Chronic Disease.- Metabolic Correction Therapy: A Biochemical-Physiological Mechanisitc Explanation of Functional Medicine.- The Nutrition Assessment of Metabolic and Nutritional Balance.- IFMNT NIBLETS Nutrition Assessment Differential.- Nutritional Role of Fatty Acids.- Lipidomics: Clinical Application.- Structure: From Organelle and Cell Membrane to Tissue.- Protective Mechanisms and Susceptibility to Xenobiotic and Load.- Detoxification and Biotransformation.- Drug-Nutrient Interactions.- The Enterohepatic Circulation.- A Nutritional Genomics Approach to Epigenetic Influences on Chronic Disease.- Nutritional Influences on Methylation.- The Immune System: Our Body's Homeland Security Against Disease.- Allergy, Intolerance, and Sensitivity.- Infection: A Stealth Underlying Pathology of Chronic Disease.- Body Composition.- The Therapeutic Ketogenic Diet: Harnessing Glucose, Insulin, and Ketone Metabolism.- The GUT Immune System.- Centrality of the GI Tract to Overall Health and Functional Medicine Strategies for GERD, IBS, IBD.- The Microbiome and Brain Health.- The Role of Nutrition in Integrative Oncology.- The Microenvironment of Chronic Disease.- Chronic Pain.- Nutrition and Behavorial Health/Mental Health/Neurological Health.- Neurodevelopmental Disorders in Children.- Nutritional Influences on Hormonal Health.- Nutritional Influences on Reproduction: A Functional Approach.- Lifestyle Patterns of Chronic Disease.- Circadian Rhythm: Light-Dark Cycles.- Nutrition with Movement for Better Energy and Health. Mental, Emotional, and Spiritual Imbalances.- Part II: Practice.- The IFMNT Practitioner.- The Patient Story and Relationship-Centered Care.- The Nutrition-Focused Physical Exam.- Modifiable Lifestyle Factors: Exercise, Sleep, Stress, Relationships.- Developing Interventions to Address Priorities: Food, Dietary Supplements, Lifestyle, and Referrals.- Therapeutic Diets.- Dietary Supplements: Understanding the Complexity of Use and Applications to Health.- Clinical Approaches to Monitoring and Evaluations of the Chronic Disease Client.- Ayurvedic Approach in Chronic Disease Management.- Section 2: Cases & Grand Rounds.- Cardiometabolic Syndrome.- Revolutionary New Concepts in the Prevention and Treatment of Cardiovascular Disease.- Immune System Under Fire: The Rise of Food Immune Reaction and Autoimmunity.- Amyotrophic Lateral Sclerosis (ALS): The Application of Integrative & Functional Medical Nutrition Therapy (IFMNT).- Gastroenterology.- Respiratory.- The Skin, Selected Dermatologic Conditions and Medical Nutrition Therapy.- Movement Issues with Chronic Ill or Chronic Pain Patients.- Section 3: Practitioner Practice Resources.- Systems Biology Resources.- Initial Nutrition Assessment Checklist.- Nutritional Diagnosis Resources.- Specialized Diets.- Motivational Interviewing.- Authorization for the Release of Information.- Patient Handouts.

This textbook is a practical guide to the application of the philosophy and principles of Integrative and Functional Medical Nutrition Therapy (IFMNT) in the practice of medicine, and the key role nutrition plays in restoring and maintaining wellness. The textbook provides an overview of recent reviews and studies of physiological and biochemical contributions to IFMNT and address nutritional influences in human heath overall, including poor nutrition, genomics, environmental toxicant exposures, fractured human interactions, limited physical movement, stress, sleep deprivation, and other lifestyle factors. Ultimately, this textbook serves to help practitioners, healthcare systems, and policy makers better understand this different and novel approach to complex chronic disorders. It provides the reader with real world examples of applications of the underlying principles and practices of integrative/functional nutrition therapies and presents the most up-to-date intervention strategies and clinical tools to help the reader keep abreast of developments in this emerging specialty field. Many chapters include comprehensive coverage of the topic and clinical applications with supplementary learning features such as case studies, take-home messages, patient and practitioner handouts, algorithms, and suggested readings.Integrative and Functional Medical Nutrition Therapy: Principles and Practices will serve as an invaluable guide for healthcare professionals in their clinical application of nutrition, lifestyle assessment, and intervention for each unique, individual patient.

This textbook is a practical guide to the application of the philosophy and principles of Integrative and Functional Medical Nutrition Therapy (IFMNT) in the practice of medicine, and the key role nutrition plays in restoring and maintaining wellness. The textbook provides an overview of recent reviews and studies of physiological and biochemical contributions to IFMNT and address nutritional influences in human heath overall, including poor nutrition, genomics, environmental toxicant exposures, fractured human interactions, limited physical movement, stress, sleep deprivation, and other lifestyle factors. Ultimately, this textbook serves to help practitioners, healthcare systems, and policy makers better understand this different and novel approach to complex chronic disorders. It provides the reader with real world examples of applications of the underlying principles and practices of integrative/functional nutrition therapies and presents the most up-to-date intervention strategies and clinical tools to help the reader keep abreast of developments in this emerging specialty field. Many chapters include comprehensive coverage of the topic and clinical applications with supplementary learning features such as case studies, take-home messages, patient and practitioner handouts, algorithms, and suggested readings.Integrative and Functional Medical Nutrition Therapy: Principles and Practices will serve as an invaluable guide for healthcare professionals in their clinical application of nutrition, lifestyle assessment, and intervention for each unique, individual patient.

<p>Includes assessment and intervention algorithms for IFMNT</p><p>Contains up-to-date information and strategies for medical and health professionals</p><p>Includes a systems biology approach that considers physiological and biochemical mechanisms and their nutritional and lifestyle influences</p><p>Presents current and future trends in this emerging field</p><p>Includes clear learning objectives, key points, and section summaries geared toward courses in medical, nursing, nutrition and allied health education</p><p>Provides case studies, checklists, patient and practitioner handouts, suggested readings, figures, illustrations, and video links</p>

9783030307295

393615_1_En

Why probability and statistics?.- Outcomes, events, and probability.- Conditional probability and independence.- Discrete random variables.- Continuous random variables.- Simulation.- Expectation and variance.- Computations with random variables.- Joint distributions and independence.- Covariance and correlation.- More computations with more random variables.- The Poisson process.- The law of large numbers.- The central limit theorem.- Exploratory data analysis: graphical summaries.- Exploratory data analysis: numerical summaries.- Basic statistical models.- The bootstrap.- Unbiased estimators.- Efficiency and mean squared error.- Maximum likelihood.- The method of least squares.- Confidence intervals for the mean.- More on confidence intervals.- Testing hypotheses: essentials.- Testing hypotheses: elaboration.- The t-test.- Comparing two samples.

Probability and Statistics are studied by most science students, usually as a second- or third-year course. Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. The strength of this book is that it readdresses these shortcomings; by using examples, often from real-life and using real data, the authors can show how the fundamentals of probabilistic and statistical theories arise intuitively. It provides a tried and tested, self-contained course, that can also be used for self-study.

A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. A website at www.springeronline.com/1-85233-896-2 gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite for the book is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to useful modern methods such as the bootstrap.

This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects.

Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. The strength of this book is that it readdresses these shortcomings; by using examples, often from real life and using real data, the authors show how the fundamentals of probabilistic and statistical theories arise intuitively. A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to students. In addition there are over 350 exercises, half of which have answers, of which half have full solutions. A website gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to modern methods such as the bootstrap.

<p>Developed from tried and tested course material, this book provides a self-contained course that is also suitable for self-study</p><p>Uses real examples and real data sets that will be familiar to students</p><p>Features quick exercises to give direct feedback to the student, and over 350 exercises</p><p>Includes an introduction to the bootstrap, a modern method that is often missing in other books</p><p>Includes full solutions to half the exercises given in the book; solutions to the rest are provided on an accompanying website</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Michel Dekking, Cor Kraaikamp, Rik Lopuhaä and Ludolf Meester are professors in the Department of Applied Mathematics at TU Delft, The Netherlands. The material in this book has been successfully taught there for several years, and at the University of Leiden, The Netherlands, and Wesleyan University, USA, since 2003.

9781852338961

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

978-0-387-98403-2

,978-0-387-90036-0,978-0-387-90035-3,978-1-4612-9840-3,978-1-4612-9839-7

I. Categories, Functors, and Natural Transformations.- II. Constructions on Categories.- III. Universals and Limits.- IV. Adjoints.- V Limits.- VI. Monads and Algebras.- VII. Monoids.- VIII. Abelian Categories.- IX. Special Limits.- X. Kan Extensions.- XI. Symmetry and Braiding in Monoidal Categories.- XII. Structures in Categories.- Appendix. Foundations.- Table of Standard Categories: Objects and Arrows.- Table of Terminology.

Categories for the Working Mathematician provides an array of general ideas useful in a wide variety of fields. Starting from the foundations, this book illuminates the concepts of category, functor, natural transformation, and duality. The book then turns to adjoint functors, which provide a description of universal constructions, an analysis of the representations of functors by sets of morphisms, and a means of manipulating direct and inverse limits. These categorical concepts are extensively illustrated in the remaining chapters, which include many applications of the basic existence theorem for adjoint functors. The categories of algebraic systems are constructed from certain adjoint-like data and characterized by Beck's theorem. After considering a variety of applications, the book continues with the construction and exploitation of Kan extensions. This second edition includes a number of revisions and additions, including two new chapters on topics of active interest. One is on symmetric monoidal categories and braided monoidal categories and the coherence theorems for them. The second describes 2-categories and the higher dimensional categories which have recently come into prominence. The bibliography has also been expanded to cover some of the many other recent advances concerning categories.

9780387984032

10.1007/978-1-4757-4721-8

978-3-030-41067-4

Matthew F. Dixon, Illinois Institute of Technology, Chicago, IL, USA; Igor Halperin, New York University, Brooklyn, NY, USA; Paul Bilokon, Imperial College London, London, UK

Chapter 1. Introduction.- Chapter 2. Probabilistic Modeling.- Chapter 3. Bayesian Regression & Gaussian Processes.- Chapter 4. Feed Forward Neural Networks.- Chapter 5. Interpretability.- Chapter 6. Sequence Modeling.- Chapter 7. Probabilistic Sequence Modeling.- Chapter 8. Advanced Neural Networks.- Chapter 9. Introduction to Reinforcement learning.- Chapter 10. Applications of Reinforcement Learning.- Chapter 11. Inverse Reinforcement Learning and Imitation Learning.- Chapter 12. Frontiers of Machine Learning and Finance.

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance.

Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance.

Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.

<p>Introduces fundamental concepts in machine learning for canonical modeling and decision frameworks in finance</p><p>Presents a unified treatment of machine learning, financial econometrics and discrete time stochastic control problems in finance</p><p>Chapters include examples, exercises and Python codes to reinforce theoretical concepts and demonstrate the application of machine learning to algorithmic trading, investment management, wealth management and risk management</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Paul Bilokon, Ph.D., is CEO and Founder of Thalesians Ltd. Paul has made contributions to mathematical logic, domain theory, and stochastic filtering theory, and, with Abbas Edalat, has published a prestigious LICS paper. He is a member of the British Computer Society, the Institution of Engineering and the European Complex Systems Society.

Matthew Dixon, FRM, Ph.D., is an Assistant Professor of Applied Math at the Illinois Institute of Technology and an Affiliate of the Stuart School of Business. He has published over 20 peer reviewed publications on machine learning and quant finance and has been cited in Bloomberg Markets and the Financial Times as an AI in fintech expert. He is Deputy Editor of the Journal of Machine Learning in Finance, Associate Editor of the AIMS Journal on Dynamics and Games, and is a member of the Advisory Board of the CFA Quantitative Investing Group.

Igor Halperin, Ph.D., is a Research Professor in Financial Engineering at NYU, and an AI Research associate at Fidelity Investments. Igor has published more than 50 scientific articles in machine learning, quantitative finance and theoretic physics. Prior to joining the financial industry, he held postdoctoral positions in theoretical physics at the Technion and the University of British Columbia.

9783030410674

476939_1_En

What is Data Science?.- Mathematical Preliminaries.- Data Munging.- Scores and Rankings.- Statistical Analysis.- Visualizing Data.- Mathematical Models.- Linear Algebra.- Linear and Logistic Regression.- Distance and Network Methods.- Machine Learning.- Big Data: Achieving Scale.

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world
Includes “Homework Problems,” providing a wide range of exercises and projects for self-study
Provides a complete set of lecture slides and online video lectures at www.data-manual.com
Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter
Recommends exciting “Kaggle Challenges” from the online platform Kaggle
Highlights “False Starts,” revealing the subtle reasons why certain approaches fail
Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

<p>Provides an introduction to data science, focusing on the fundamental skills and principles needed to build systems for collecting, analyzing, and interpreting data</p><p>Lays the groundwork of what really matters in analyzing data; ‘doing the simple things right’</p><p>Aids the reader in developing mathematical intuition, illustrating the key concepts with a minimum of formal mathematics</p><p>Highlights the core values of statistical reasoning using the approaches which come most naturally to computer scientists</p><p>Includes supplementary material: sn.pub/extras</p>

Dr. Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. He was awarded the IEEE Computer Science and Engineering Undergraduate Teaching Award “for outstanding contributions to undergraduate education ...and for influential textbooks and software.” Dr. Skiena is the author of six books, including the popular Springer titles The Algorithm Design Manual and Programming Challenges: The Programming Contest Training Manual.

9783319554433

437269_1_En

10.1007/978-3-319-55444-0

Sheldon Axler, San Francisco State University, San Francisco, CA, USA

About the Author.- Preface for Students.- Preface for Instructors.- Acknowledgments.- 1. Riemann Integration.- 2. Measures.- 3. Integration.- 4. Differentiation.- 5. Product Measures.- 6. Banach Spaces.- 7. L^p Spaces.- 8. Hilbert Spaces.- 9. Real and Complex Measures.- 10. Linear Maps on Hilbert Spaces.- 11. Fourier Analysis.- 12. Probability Measures.- Photo Credits.- Bibliography.- Notation Index.- Index.- Colophon: Notes on Typesetting.

This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results. Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics.Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration. Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach. Lebesgue integration links into results such as the Lebesgue Differentiation Theorem. The development of products of abstract measures leads to Lebesgue measure on Rn.Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem. An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures. Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform. The final chapter offers a taste of probability.Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics. A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysis that is freely available online.

This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results. Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics.Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration. Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach. Lebesgue integration links into results such as the Lebesgue Differentiation Theorem. The development of products of abstract measures leads to Lebesgue measure on Rn.Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem. An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures. Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform. The final chapter offers a taste of probability.Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics. A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysis that is freely available online.

<p>Electronic version is free to the world via Springer’s Open Access program</p><p>Provides student-friendly explanations with ample examples and exercises throughout</p><p>Includes chapters on Hilbert space operators, Fourier analysis, and probability measures</p><p>Prepares students for further graduate studies by promoting a deep understanding of key concepts</p><p>Includes supplementary material: sn.pub/extras</p>

Sheldon Axler is Professor of Mathematics at San Francisco State University. He has won teaching awards at MIT and Michigan State University. His career achievements include the Mathematical Association of America’s Lester R. Ford Award for expository writing, election as Fellow of the American Mathematical Society, over a decade as Dean of the College of Science & Engineering at San Francisco State University, member of the Council of the American Mathematical Society, member of the Board of Trustees of the Mathematical Sciences Research Institute, and Editor-in-Chief of the Mathematical Intelligencer. His previous publications include the widely used textbook Linear Algebra Done Right.

9783030331429

465399_1_En

Originally published with title "Riemannian Manifolds: An Introduction to Curvature"

,978-0-387-98322-6,978-0-387-98271-7,978-1-4684-9228-6,978-0-387-22726-9

Preface.- 1. What Is Curvature?.- 2. Riemannian Metrics.- 3. Model Riemannian Manifolds.- 4. Connections.- 5. The Levi-Cevita Connection.- 6. Geodesics and Distance.- 7. Curvature.- 8. Riemannian Submanifolds.- 9. The Gauss–Bonnet Theorem.- 10. Jacobi Fields.- 11. Comparison Theory.- 12. Curvature and Topology.- Appendix A: Review of Smooth Manifolds.- Appendix B: Review of Tensors.- Appendix C: Review of Lie Groups.- References.- Notation Index.- Subject Index.

This textbook is designed for a one or two semester graduate course on Riemannian geometry for students who are familiar with topological and differentiable manifolds. The second edition has been adapted, expanded, and aptly retitled from Lee’s earlier book, Riemannian Manifolds: An Introduction to Curvature. Numerous exercises and problem sets provide the student with opportunities to practice and develop skills; appendices contain a brief review of essential background material.While demonstrating the uses of most of the main technical tools needed for a careful study of Riemannian manifolds, this text focuses on ensuring that the student develops an intimate acquaintance with the geometric meaning of curvature. The reasonably broad coverage begins with a treatment of indispensable tools for working with Riemannian metrics such as connections and geodesics. Several topics have been added, including an expanded treatment of pseudo-Riemannian metrics, a more detailed treatment of homogeneous spaces and invariant metrics, a completely revamped treatment of comparison theory based on Riccati equations, and a handful of new local-to-global theorems, to name just a few highlights.Reviews of the first edition:Arguments and proofs are written down precisely and clearly. The expertise of the author is reflected in many valuable comments and remarks on the recent developments of the subjects. Serious readers would have the challenges of solving the exercises and problems. The book is probably one of the most easily accessible introductions to Riemannian geometry. (M.C. Leung, MathReview)The book’s aim is to develop tools and intuition for studying the central unifying theme in Riemannian geometry, which is the notion of curvature and its relation with topology. The main ideas of the subject, motivated as in the original papers, are introduced here in an intuitive and accessible way…The book is an excellent introduction designed for a one-semester graduate course, containing exercises and problems which encourage students to practice working with the new notions and develop skills for later use. By citing suitable references for detailed study, the reader is stimulated to inquire into further research. (C.-L. Bejan, zBMATH)

<div><div>​This textbook is designed for a one or two semester graduate course on Riemannian geometry for students who are familiar with topological and differentiable manifolds. The second edition has been adapted, expanded, and aptly retitled from Lee’s earlier book, Riemannian Manifolds: An Introduction to Curvature. Numerous exercises and problem sets provide the student with opportunities to practice and develop skills; appendices contain a brief review of essential background material.<div>
</div><div>While demonstrating the uses of most of the main technical tools needed for a careful study of Riemannian manifolds, this text focuses on ensuring that the student develops an intimate acquaintance with the geometric meaning of curvature. The reasonably broad coverage begins with a treatment of indispensable tools for working with Riemannian metrics such as connections and geodesics. Several topics have been added, including an expanded treatment of pseudo-Riemannian metrics, a more detailed treatment of homogeneous spaces and invariant metrics, a completely revamped treatment of comparison theory based on Riccati equations, and a handful of new local-to-global theorems, to name just a few highlights.</div><div>
</div><div>Reviews of the first edition:</div>
</div><div>Arguments and proofs are written down precisely and clearly. The expertise of the author is reflected in many valuable comments and remarks on the recent developments of the subjects. Serious readers would have the challenges of solving the exercises and problems. The book is probably one of the most easily accessible introductions to Riemannian geometry. (M.C. Leung, MathReview) </div><div>
</div><div>The book’s aim is to develop tools and intuition for studying the central unifying theme in Riemannian geometry, which is the notion of curvature and its relation with topology. The main ideas of the subject, motivated as in the original papers, are introduced here in an intuitive and accessible way…The book is an excellent introduction designed for a one-semester graduate course, containing exercises and problems which encourage students to practice working with the new notions and develop skills for later use. By citing suitable references for detailed study, the reader is stimulated to inquire into further research. (C.-L. Bejan, zBMATH)</div></div>

<p>Easy for instructors to adapt the topical coverage to suit their course</p><p>Develops an intimate acquaintance with the geometric meaning of curvature</p><p>Gives students strong skills via numerous exercises and problem sets</p>

​John 'Jack' M. Lee is a professor of mathematics at the University of Washington. Professor Lee is the author of three highly acclaimed Springer graduate textbooks : Introduction to Smooth Manifolds, (GTM 218) Introduction to Topological Manifolds (GTM 202), and Riemannian Manifolds (GTM 176). Lee's research interests include differential geometry, the Yamabe problem, existence of Einstein metrics, the constraint equations in general relativity, geometry and analysis on CR manifolds.

9783319917542

978-0-85729-081-6

Marek Capiński, AGH University of Science and Technology Faculty of Applied Mathematics, Kraków, Poland; Tomasz Zastawniak, University of York Department of Mathematics, Heslington, York, UK

A Simple Market Model.- Risk-Free Assets.- Portfolio Management.- Forward and Futures Contracts.- Options: General Properties.- Binomial Model.- General Discrete Time Models.- Continuous Time Model.- Interest Rates.

As with the first edition, Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style. Assuming only basic knowledge of probability and calculus, it presents three major areas of mathematical finance, namely option pricing based on the no-arbitrage principle in discrete and continuous time setting, Markowitz portfolio optimisation and the Capital Asset Pricing Model, and basic stochastic interest rate models in discrete setting.In this second edition, the material has been thoroughly revised and rearranged. New features include:• A case study to begin each chapter – a real-life situation motivating the development of theoretical tools;• A detailed discussion of the case study at the end of each chapter;• A new chapter on time-continuous models with intuitive outlines of the mathematical arguments and constructions;• Complete proofs of the two fundamental theorems of mathematical finance in discrete setting.From the reviews of the first edition:”This text is an excellent introduction to Mathematical Finance. Armed with a knowledge of basic calculus and probability a student can use this book to learn about derivatives, interest rates and their term structure and portfolio management.”(Zentralblatt MATH)”Given these basic tools, it is surprising how high a level of sophistication the authors achieve, covering such topics as arbitrage-free valuation, binomial trees, and risk-neutral valuation.” (www.riskbook.com)”The reviewer can only congratulate the authors with successful completion of a difficult task of writing a useful textbook on a traditionally hard topic.” (K. Borovkov, The Australian Mathematical Society Gazette, Vol. 31 (4), 2004)

Mathematics for Finance: An Introduction to Financial Engineering combines financial motivation with mathematical style. Assuming only basic knowledge of probability and calculus, it presents three major areas of mathematical finance, namely Option pricing based on the no-arbitrage principle in discrete and continuous time setting, Markowitz portfolio optimisation and Capital Asset Pricing Model, and basic stochastic interest rate models in discrete setting.

<p>A case study to begin each chapter – a real-life situation motivating the development of theoretical tools</p><p>A detailed discussion of the case study at the end of each chapter</p><p>A new chapter on time-continuous models with intuitive outlines of the mathematical arguments and constructions</p><p>Complete proofs of the two fundamental theorems of mathematical finance in discrete setting</p><p>Includes supplementary material: sn.pub/extras</p>

​Marek Capinski is Professor of Mathematics at AGH University of Science and Technology, Poland. <div>
</div><div>Tomasz Zastawniak is Professor of Mathematics at the University of York, UK.
</div>

9780857290816

10.1007/978-0-85729-082-3

978-3-030-72979-0

David Hui, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Alexander A. Leung, University of Calgary, Calgary, AB, USA; Christopher Ma, University of Calgary, Calgary, AB, USA

Pulmonary Medicine.- Cardiology.- Nephrology.- Critical Care.- Gastroenterology.- Hematology.- Oncology.- Infectious Diseases.- Rheumatology.- Neurology.- Endocrinology.- Dermatology.- Geriatrics.- Palliative Care.- Nutrition.- Toxicology and Addiction.- Obstetric Medicine.- General Internal Medicine.- Common Drug Classes.- Appendix I. Advanced Cardiac Life Support.- Appendix II. List of Common Abbreviations.- Index.

The fully updated fifth edition of this highly successful textbook provides an integrated symptom- and issue-based approach to internal medicine with easily accessible, high-yield clinical information. For each topic, carefully organized sections on different diagnoses, investigations, and treatments are designed to facilitate patient care and examination preparation. Numerous clinical pearls and comparison tables are provided to help enhance learning, and international units (US and metric) are used to facilitate application in everyday clinical practice.



In addition to the central tenets of internal medicine, the book covers many highly important, rarely discussed topics in medicine, including: palliative care, obstetrical medicine, transfusion reactions, needle stick injuries, interpretation of gram stain, depression and code status discussion. This fifth edition additionally includes new coverage of the coronavirus-19 and cancer survivorship while being fully updated throughout. Authors present this information in a streamlined fashion, preserving the book’s pocket-sized, quick reference format.



Approach to Internal Medicine continues to serve as an essential reference primarily for medical students, residents, and fellows -- with practicing physicians, nurses, and advanced practice providers also finding the text of value as a point of care reference.

The fully updated fifth edition of this highly successful textbook provides an integrated symptom- and issue-based approach to internal medicine with easily accessible, high-yield clinical information. For each topic, carefully organized sections on different diagnoses, investigations, and treatments are designed to facilitate patient care and examination preparation. Numerous clinical pearls and comparison tables are provided to help enhance learning, and international units (US and metric) are used to facilitate application in everyday clinical practice. In addition to the central tenets of internal medicine, the book covers many highly important, rarely discussed topics in medicine, including: palliative care, obstetrical medicine, transfusion reactions, needle stick injuries, interpretation of gram stain, depression and code status discussion. This fifth edition additionally includes new coverage of the coronavirus-19 and cancer survivorship while being fully updated throughout. Authors present this information in a streamlined fashion, preserving the book’s pocket-sized, quick reference format. Approach to Internal Medicine continues to serve as an essential reference primarily for medical students, residents, and fellows -- with practicing physicians, nurses, and advanced practice providers also finding the text of value as a point of care reference.

<p>Provides a rapid review of evidence-based internal medicine in a comprehensive, yet concise, format</p><p>Includes new coverage of the coronavirus-19 and cancer survivorship while being fully updated throughout</p><p>Includes numerous mnemonics and clinical pearls scattered throughout the book</p>

9783030729790

186923_5_En

10.1007/978-3-030-72980-6

,978-1-4419-2313-4,978-0-387-40122-5,978-1-4684-9515-7,978-0-387-21554-9

Part I: General Theory.-Matrix Lie Groups.- The Matrix Exponential.- Lie Algebras.- Basic Representation Theory.- The Baker–Campbell–Hausdorff Formula and its Consequences.- Part II: Semisimple Lie Algebras.- The Representations of sl(3;C).-Semisimple Lie Algebras.- Root Systems.- Representations of Semisimple Lie Algebras.- Further Properties of the Representations.- Part III: Compact lie Groups.- Compact Lie Groups and Maximal Tori.- The Compact Group Approach to Representation Theory.- Fundamental Groups of Compact Lie Groups.- Appendices.

This textbook treats Lie groups, Lie algebras and their representations in an elementary but fully rigorous fashion requiring minimal prerequisites. In particular, the theory of matrix Lie groups and their Lie algebras is developed using only linear algebra, and more motivation and intuition for proofs is provided than in most classic texts on the subject.In addition to its accessible treatment of the basic theory of Lie groups and Lie algebras, the book is also noteworthy for including:<br/><br/><br/>a treatment of the Baker–Campbell–Hausdorff formula and its use in place of the Frobenius theorem to establish deeper results about the relationship between Lie groups and Lie algebrasmotivation for the machinery of roots, weights and the Weyl group via a concrete and detailed exposition of the representation theory of sl(3;C)an unconventional definition of semisimplicity that allows for a rapid development of the structure theory of semisimple Lie algebrasa self-contained construction of the representations of compact groups, independent of Lie-algebraic argumentsThe second edition of Lie Groups, Lie Algebras, and Representations contains many substantial improvements and additions, among them: an entirely new part devoted to the structure and representation theory of compact Lie groups; a complete derivation of the main properties of root systems; the construction of finite-dimensional representations of semisimple Lie algebras has been elaborated; a treatment of universal enveloping algebras, including a proof of the Poincaré–Birkhoff–Witt theorem and the existence of Verma modules; complete proofs of the Weyl character formula, the Weyl dimension formula and the Kostant multiplicity formula.Review of the first edition:“This is an excellent book. It deserves to, and undoubtedly will, become the standard text for early graduate courses in Lie group theory ... an important addition to the textbook literature ... it is highly recommended.”— The Mathematical Gazette

This textbook treats Lie groups, Lie algebras and their representations in an elementary but fully rigorous fashion requiring minimal prerequisites. In particular, the theory of matrix Lie groups and their Lie algebras is developed using only linear algebra, and more motivation and intuition for proofs is provided than in most classic texts on the subject.In addition to its accessible treatment of the basic theory of Lie groups and Lie algebras, the book is also noteworthy for including:a treatment of the Baker–Campbell–Hausdorff formula and its use in place of the Frobenius theorem to establish deeper results about the relationship between Lie groups and Lie algebrasmotivation for the machinery of roots, weights and the Weyl group via a concrete and detailed exposition of the representation theory of sl(3;C)an unconventional definition of semisimplicity that allows for a rapid development of the structure theory of semisimple Lie algebrasa self-contained construction of the representations of compact groups, independent of Lie-algebraic argumentsThe second edition of Lie Groups, Lie Algebras, and Representations contains many substantial improvements and additions, among them: an entirely new part devoted to the structure and representation theory of compact Lie groups; a complete derivation of the main properties of root systems; the construction of finite-dimensional representations of semisimple Lie algebras has been elaborated; a treatment of universal enveloping algebras, including a proof of the Poincaré–Birkhoff–Witt theorem and the existence of Verma modules; complete proofs of the Weyl character formula, the Weyl dimension formula and the Kostant multiplicity formula.Review of the first edition:This is an excellent book. It deserves to, and undoubtedly will, become the standard text for early graduate courses in Lie group theory ... an important addition to the textbook literature ... it is highly recommended.— The Mathematical Gazette

<p>New edition extensively revised and updated</p><p>Covers the core topics of Lie theory from an elementary point of view</p><p>Includes many new exercises</p>

Brian Hall is Professor of Mathematics at the University of Notre Dame, IN.

9783319134666

Michael Miloro, University of Illinois, Chicago, IL, USA; G. E. Ghali, Louisiana State University Health Science, Shreveport, LA, USA; Peter E. Larsen, The Ohio State University, Columbus, OH, USA; Peter Waite, University of Alabama at Birmingham School of Dentistry and Medicine, Birmingham, AL, USA

XXII, 2328 p. 2397 illus., 1970 illus. in color. With online files/update. In 2 volumes, not available separately.

<div>Wound Healing.- Medical Management and Preoperative Patient Assessment.- Pharmacology of Outpatient Anesthesia Medications.- Outpatient Anesthesia.- Impacted Teeth.- Pre-Prosthetic Surgery.- Pediatric Dentoalveolar Surgery.- Utilization of Three-dimensional Imaging Technology to Enhance Maxillofacial Surgical Applications.- Dynamic Navigation for Dental Implants.- Implant Prosthodontics.- The Science of Osseointegrated Implant Reconstruction.- Comprehensive Implant Site Preparation: Mandible.- A Graft-less Approach for Treatment of the Edentulous Maxilla: Contemporary considerations for Treatment planning, Biomechanical principles and surgical protocol.- Soft Tissue Management in Implant Therapy.- Craniofacial Implant Surgery.- Initial Management of the Trauma Patient.- Soft Tissue Injuries.- Rigid versus Nonrigid Fixation.- Dentoalveolar and Intraoral Soft Tissue Trauma.- Contemporary Management of Mandibular Fractures.- Fractures of the Mandibular Condyle.- Management of Maxillary Fractures.- Management of Zygomatic Complex Fractures.- Orbital and Ocular Trauma.- Management of Frontal Sinus and Naso-orbitoethmoid Complex Fractures.- Nasal Fractures.- Maxillofacial Firearm Injuries.- Paediatric Facial Trauma.- Management of Panfacial Fractures.- Differential Diagnosis of Oral Disease.- Odontogenic Cysts and Tumors.- Benign Nonodontogenic Lesions of the Jaws.- Oral Cancer: Classification, Diagnosis, and Staging.- Oral Cancer Management.- Lip Cancer.- Head and Neck Skin Cancer.- Salivary Gland Disease.- Mucosal and Related Dermatologic Diseases.- Pediatric Maxillofacial Pathology.- Odontogenic Infections.- Osteomyelitis, Osteoradionecrosis(ORN) and Medication Related Osteonecrosis of the Jaws(MRONJ).- Local and Regional Flaps.- Nonvascularized Reconstruction.- Vascularized Reconstruction.- Microneurosurgery.- Comprehensive Management of Facial Clefts.- Alveolar Cleft Reconstruction.- Nonsyndromic Craniosynostosis.- Craniofacial Dysostosis Syndromes: Evaluation and Treatment of the Skeletal Deformities.- Technology in Oral and Maxillofacial Reconstruction.- Anatomy and Pathophysiology of the Temporomandibular Joint.- Nonsurgical Management of Temporomandibular Disorders.- Arthroscopy and Arthrocentesis of the Temporomandibular Joint.- Internal Derangement of the Temporomandibular Joint.- Hypomobility and Hypermobility Disorders of the Temporomandibular Joint.- Pediatric temporomandibular disorders: Juvenile Idiopathic Arthritis.- Vascularized Reconstruction.- Craniofacial Growth and Development.- Digital Data Acquisition and Treatment Planning in Orthognathic Surgery.- Orthodontics for Orthognathic Surgery.- Model Surgery and Computer-aided Surgical Simulation for Orthognathic Surgery.- Mandibular Orthognathic Surgery.- Maxillary Orthognathic Surgery.- Sequencing in Orthognathic Surgery.- Concomitant Orthognathic and Temporomandibular Joint Surgery.- Facial Asymmetry.- Soft Tissue Changes and Prediction with Orthognathic Surgery.- Complications in Orthognathic Surgery.- Cleft Orthognathic Surgery.- Distraction Osteogenesis of the Craniomaxillofacial Skeleton.- Surgical and Non-surgical Management of Obstructive Sleep Apnea.- Blepharoplasty.- Basic Principles of Rhinoplasty.- Rhytidectomy.- Forehead and Brow Procedures.- Otoplastic Surgery for the Protruding Ear.- Adjunctive Facial Cosmetic Procedures.
</div>

The new edition of this outstanding reference textbook, in two volumes, offers comprehensive and authoritative coverage of the contemporary specialty of oral and maxillofacial surgery. The aim is to provide an all-encompassing, user-friendly source of information that will meet the needs of residents and experienced surgeons in clinical practice and will also serve as an ideal companion during preparation for board certification or recertification examinations. All of the authors, numbering some 100, are distinguished experts in the areas that they address. The new edition takes full account of the significant changes in clinical practice and guidelines that have occurred during recent years. Readers will find clear explanations of the practical application of surgical principles, with a wealth of supporting illustrative material, including atlas-type illustrations to complement the descriptions of specific procedures. The fourth edition of Peterson’s Principles of Oral and Maxillofacial Surgery is a truly exceptional resource for clinicians and students alike.

The new edition of this outstanding reference textbook, in two volumes, offers comprehensive and authoritative coverage of the contemporary specialty of oral and maxillofacial surgery. The aim is to provide an all-encompassing, user-friendly source of information that will meet the needs of residents and experienced surgeons in clinical practice and will also serve as an ideal companion during preparation for board certification or recertification examinations. All of the authors, numbering some 100, are distinguished experts in the areas that they address. The new edition takes full account of the significant changes in clinical practice and guidelines that have occurred during recent years. Readers will find clear explanations of the practical application of surgical principles, with a wealth of supporting illustrative material, including atlas-type illustrations to complement the descriptions of specific procedures. The fourth edition of Peterson’s Principles of Oral and Maxillofacial Surgery is a truly exceptional resource for clinicians and students alike.

<p>Offers comprehensive coverage of the contemporary specialty of oral and maxillofacial surgery</p><p>Written by approximately 100 distinguished experts</p><p>Represents an ideal reference for both clinicians and those preparing for board exams</p>

Michael Miloro, DMD, MD, FACS, is Professor and Departmental Head of the Department of Oral and Maxillofacial Surgery at the University of Illinois at Chicago. Dr. Miloro is a Diplomate of, and past-Examiner for, the American Board of Oral and Maxillofacial Surgery, a Faculty Fellow of the American Association of Oral and Maxillofacial Surgeons, a Fellow of the International Association of Oral and Maxillofacial Surgeons, and a Fellow of the American College of Surgeons. Dr. Miloro has major clinical and research interests in orthognathic surgery, TMJ surgery, implant surgery, and trigeminal nerve injuries and reconstruction. Dr. Miloro has lectured nationally and internationally on many subjects, and has been the recipient of a number of honors and awards. Dr. Miloro has published extensively in the medical and dental literature with over 100 peer-reviewed publications and textbook chapters. Dr. Miloro currently serves as the Section Editor of the Journal of Oral and Maxillofacial Surgery, and is Editor of three major textbooks including Peterson's Principles of Oral and Maxillofacial Surgery, Management of Complications in Oral and Maxillofacial Surgery, and Trigeminal Nerve Injuries.

G. E. Ghali, DDS, MD, FACS, FRCS(Ed), is Professor and Chairman of the Department of Oral & Maxillofacial Surgery at Louisiana State University Health Sciences Center - Shreveport, where he is also Chancellor and holds the Jack W. Gamble Chair in Oral & Maxillofacial Surgery. Dr. Ghali is a Fellow of the American Dental Society of Anesthesiology, the American Association of Oral and Maxillofacial Surgeons (AAOMS), the American College of Surgeons, and the Royal College of Surgeons of Edinburgh. He has served on various national professional committees and is a past president of the American Board of Oral and Maxillofacial Surgery. Dr. Ghali is an editorial board member for the Journal of Craniomaxillofacial Surgery and Oral and Maxillofacial Surgery Cases. He has authored 100 peer-reviewed journal articles, as well as, many book chapters. In 2012 Dr. Ghali received the Robert V. Walker Distinguished Service Award from AAOMS.

Peter E. Larsen, DDS, FACS, is chair of the Division of Oral and Maxillofacial Surgery and Anesthesiology at The Ohio State University College of Dentistry, Columbus, Ohio, where he holds the Larry J. Peterson Endowed Professorship in Oral and Maxillofacial Surgery. He has also been Chief of Oral and Maxillofacial Surgery at Nationwide Children’s Hospital of Columbus since 1995. Dr. Larsen is a Fellow of the American College of Dentists, the American College of Surgeons, and the American Association of Oral and Maxillofacial Surgeons. He is also a past president of the American Board of Oral and Maxillofacial Surgery. Dr. Larsen served on the editorial board of Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology from 1993 to 2017 and was editor in chief of the journal in 2002–3. He has also been an editorial board member for the Journal of Oral and Maxillofacial Surgery. He is the author of numerous journal articles and book chapters. Dr. Larsen was the recipient of the 2019 Donald B. Osbon Award for Outstanding Educator.

Peter D. Waite, MPH, DDS, MD, FACS, is professor and former chairman for 27years of the Department of Oral and Maxillofacial Surgery at the University of Alabama Medicine/Dentistry and currently holds the Charles A McCallum endowed chair of OMS. He received his MPH and DDS from the University of Minnesota, and went on to UAB school of Medicine for advanced training. He enjoys a very busy faculty practice and teaches medical/dental students and residents. Dr Waite directs an advanced fellowship program in Orthognathic and Cosmetic surgery. He performs

9783030919191

470211_4_En

Robert H. Shumway, University of California, Davis, Davis, CA, USA; David S. Stoffer, University of Pittsburgh, Pittsburgh, PA, USA

,978-1-4419-7864-6,978-1-4614-2759-9,978-1-4419-7866-0,978-1-4419-7865-3

1. Characteristics of Time Series.- 2. Time Series Regression and Exploratory Data Analysis.- 3. ARIMA Models.- 4. Spectral Analysis and Filtering.- 5. Additional Time Domain Topics.- 6. State-Space Models.- 7. Statistical Methods in the Frequency Domain.- 8. Appendix A: Large Sample Theory.- Appendix B: Time Domain Theory.- Appendix C: Spectral Domain Theory.- Appendix R: R Supplement.<div>
</div>

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods.This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.<div>Student-tested and improvedAccessible and complete treatment of modern time series analysisPromotes understanding of theoretical concepts by bringing them into a more practical context
Comprehensive appendices covering the necessities of understanding the mathematics of time series analysis
Instructor's Manual available for adopters</div><div>New to this edition:Introductions to each chapter replaced with one-page abstractsAll graphics and plots redone and made uniform in styleBayesian section completely rewritten, covering linear Gaussian state space models onlyR code for each example provided directly in the text for ease of data analysis replication
Expanded appendices with tutorials containing basic R and R time series commandsData sets and additional R scripts available for download on Springer.comInternal online links to every reference (equations, examples, chapters, etc.)
</div>

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods.This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.

<p>Student-tested and improved</p><p>Accessible and complete treatment of modern time series analysis</p><p>Promotes understanding of theoretical concepts by bringing them into a more practical context</p><p>Comprehensive appendices covering the necessities of understanding the mathematics of time series analysis</p><p>Instructor's Manual available for adopters</p><p>New to this edition:</p><p>Introductions to each chapter replaced with one-page abstracts</p><p>All graphics and plots redone and made uniform in style</p><p>Bayesian section completely rewritten, covering linear Gaussian state space models only</p><p>R code for each example provided directly in the text for ease of data analysis replication</p><p>Expanded appendices with tutorials containing basic R and R time series commands</p><p>Data sets and additional R scripts available for download on Springer.com</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Robert H. Shumway, PhD, is Professor Emeritus of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is also the author of a Prentice-Hall text on applied time series analysis and served as a Departmental Editor for the Journal of Forecasting and Associate Editor for the Journal of the American Statistical Association.

<div>David S. Stoffer, PhD, is Professor of Statistics at the University of Pittsburgh. He is a Fellow of the American Statistical Association and has made seminal contributions to the analysis of categorical time series. David won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently a Departmental Editor of the Journal of Forecasting and an Associate Editor of the Annals of Statistical Mathematics. He has served as Program Director in the Division of Mathematical Sciences at the National Science Foundation and as Associate Editor for the Journal of the American Statistical Association.</div><div>
</div><div>
</div>

9783319524511

Jaap Hage, Maastricht University Faculty of Law, Maastricht, The Netherlands; Antonia Waltermann, Maastricht University, Maastricht, The Netherlands; Bram Akkermans, Maastricht University Faculty of Law, Maastricht, The Netherlands

,978-3-319-06911-1,978-3-319-06909-8,978-3-319-06910-4,978-3-319-36073-7

1 Sources of Law by Jaap Hage.- 2 Legal Reasoning by Jaap Hage.- 3 Basic Concepts of Law by Jaap Hage.- 4 The Law of Contract by Jan Smits.- 5 Property Law by Bram Akkermans.- 6 Tort Law by Jaap Hage.- 7 Criminal Law by Johannes Keiler, Michele Panzavolta, and David Roef.- 8 Constitutional Law by Aalt Willem Heringa.- 9 Administrative Law by Chris Backes and Mariolina Eliantonio.- 10 The Law of Europe by Jaap Hage.- 11 Tax Law by Marcel Schaper.- 12 International Law by Menno T. Kamminga.- 13 Human Rights by Gustavo Arosemena.- 14 Elements of Procedural Law by Fokke Fernhout and Remco van Rhee.- 15 Philosophy of Law by Jaap Hage.

This book is exceptional in the sense that it provides an introduction to law in general rather than the law of one specific jurisdiction, and it presents a unique way of looking at legal education. It is crucial for lawyers to be aware of the different ways in which societal problems can be solved and to be able to discuss the advantages and disadvantages of different legal solutions. In this respect, being a lawyer involves being able to reason like a lawyer, even more than having detailed knowledge of particular sets of rules. Introduction to Law reflects this view by focusing on the functions of rules and on ways of arguing the relative qualities of alternative legal solutions. Where ‘positive’ law is discussed, the emphasis is on the legal questions that must be addressed by a field of law, and on the different solutions which have been adopted by, for instance, the common law and civil law tradition. The law of specific jurisdictions is discussed to illustrate possible answers to questions such as when the existence of a valid contract is assumed.

This book is exceptional in the sense that it provides an introduction to law in general rather than the law of one specific jurisdiction, and it presents a unique way of looking at legal education. It is crucial for lawyers to be aware of the different ways in which societal problems can be solved and to be able to discuss the advantages and disadvantages of different legal solutions. In this respect, being a lawyer involves being able to reason like a lawyer, even more than having detailed knowledge of particular sets of rules. Introduction to Law reflects this view by focusing on the functions of rules and on ways of arguing the relative qualities of alternative legal solutions. Where ‘positive’ law is discussed, the emphasis is on the legal questions that must be addressed by a field of law and on the different solutions which have been adopted by, for instance, the common law and civil law tradition. The law of specific jurisdictions is discussed to illustrate possible answers to questions such as when the existence of a valid contract is assumed.

<p>Includes a new chapter on Tax Law</p><p>Introduces to law in general, rather than to law of a particular jurisdiction</p><p>Focuses on problems which law must solve, rather than on particular solutions (functional approach to law)</p><p>Comparative introduction to law</p>

Jaap Hage is Professor of Jurisprudence at Maastricht University and Fellow of the Maastricht European Private Law Institute (M-EPLI), Maastricht University.Antonia Waltermann is Assistant Professor at the Department of Foundations and methods of Law, Faculty of Law, Maastricht University.Bram Akkermans is Assistant Professor European Private Law and Associate-Director of the Maastricht European Private Law Institute (M-EPLI), Maastricht University.

9783319572512

325356_2_En

978-0-387-09505-9

Prologue.- Analyze.- Design.- Develop.- Implement.- Evaluate.- Epilogue.

The Analyze, Design, Develop, Implement, and Evaluate (ADDIE) process is used to introduce an approach to instruction design that has a proven record of success. Instructional Design: The ADDIE Approach is intended to serve as an overview of the ADDIE concept. The primary rationale for this book is to respond to the need for an instruction design primer that addresses the current proliferation of complex educational development models, particularly non-traditional approaches to learning, multimedia development and online learning environments. Many entry level instructional designers and students enrolled in related academic programs indicate they are better prepared to accomplish the challenging work of creating effective training and education materials after they have a thorough understanding of the ADDIE principles. However, a survey of instructional development applications indicate that the overwhelming majority of instructional design models are based on ADDIE, often do not present the ADDIE origins as part of their content, and are poorly applied by people unfamiliar with the ADDIE paradigm. The purpose of this book is to focus on fundamental ADDIE principles, written with a minimum of professional jargon. This is not an attempt to debate scholars or other educational professionals on the finer points of instructional design, however, the book's content is based on sound doctrine and supported by valid empirical research. The only bias toward the topic is that generic terms will be used as often as possible in order to make it easy for the reader to apply the concepts in the book to other specific situations.

The Analyze, Design, Develop, Implement, and Evaluate (ADDIE) process is used to introduce an approach to instruction design that has a proven record of success. Instructional Design: The ADDIE Approach is intended to serve as an overview of the ADDIE concept. The primary rationale for this book is to respond to the need for an instruction design primer that addresses the current proliferation of complex educational development models, particularly non-traditional approaches to learning, multimedia development and online learning environments. Many entry level instructional designers and students enrolled in related academic programs indicate they are better prepared to accomplish the challenging work of creating effective training and education materials after they have a thorough understanding of the ADDIE principles. However, a survey of instructional development applications indicate that the overwhelming majority of instructional design models are based on ADDIE, often do not present the ADDIE origins as part of their content, and are poorly applied by people unfamiliar with the ADDIE paradigm. The purpose of this book is to focus on fundamental ADDIE principles, written with a minimum of professional jargon. This is not an attempt to debate scholars or other educational professionals on the finer points of instructional design, however, the book's content is based on sound doctrine and supported by valid empirical research. The only bias toward the topic is that generic terms will be used as often as possible in order to make it easy for the reader to apply the concepts in the book to other specific situations.

<p>Utilizes a simple, yet robust organizing framework</p><p>Uses a thematic approach to the content</p><p>Presents the concept, theory and practice for ADDIE</p><p>Contains a glossary</p><p>Includes supplementary material: sn.pub/extras</p>

Robert Maribe Branch is a tenured Professor of Instructional Design and Technology at the University of Georgia. Rob earned an Associate degree from New York City Technical College in Brooklyn, New York; a Bachelor of Science degree from Elizabeth City State University, North Carolina; and a Masters degree from Ball State University in Muncie, Indiana. Dr. Branch taught high school in Botswana as a Peace Corps volunteer and later returned to the United States, and completed a Doctor of Education degree from Virginia Tech in Blacksburg, Virginia in 1989 specializing in curriculum development and instructional design. Dr. Branch joined the faculty at Syracuse University and taught graduate courses and conducted research in the Department of Instructional Design, Development and Evaluation, and earned tenure during his seven years there. Dr. Branch is a former Fulbright Lecturer/Researcher to the University of Natal in South Africa where he helped to inaugurate a Masters degree program in Media Studies. Dr. Branch has co-edited the Educational Media and Technology Yearbook since 1997, and co-authored the two recent editions of the popular Survey of Instructional Development Models book. Dr. Branch emphasizes student-centered learning, teaches courses related to instructional systems design, and consults regularly with governments, businesses and other educational institutions. Dr. Branch’s published research focuses on diagramming complex conceptual relationships and other flow processes.

9780387095059

148419_1_En

10.1007/978-0-387-09506-6

978-0-306-44790-7

1. Mathematical Introduction.- 1.1. Linear Vector Spaces: Basics.- 1.2. Inner Product Spaces.- 1.3. Dual Spaces and the Dirac Notation.- 1.4. Subspaces.- 1.5. Linear Operators.- 1.6. Matrix Elements of Linear Operators.- 1.7. Active and Passive Transformations.- 1.8. The Eigenvalue Problem.- 1.9. Functions of Operators and Related Concepts.- 1.10. Generalization to Infinite Dimensions.- 2. Review of Classical Mechanics.- 2.1. The Principle of Least Action and Lagrangian Mechanics.- 2.2. The Electromagnetic Lagrangian.- 2.3. The Two-Body Problem.- 2.4. How Smart Is a Particle?.- 2.5. The Hamiltonian Formalism.- 2.6. The Electromagnetic Force in the Hamiltonian Scheme.- 2.7. Cyclic Coordinates, Poisson Brackets, and Canonical Transformations.- 2.8. Symmetries and Their Consequences.- 3. All Is Not Well with Classical Mechanics.- 3.1. Particles and Waves in Classical Physics.- 3.2. An Experiment with Waves and Particles (Classical).- 3.3. The Double-Slit Experiment with Light.- 3.4. Matter Waves (de Broglie Waves).- 3.5. Conclusions.- 4. The Postulates—a General Discussion.- 4.1. The Postulates.- 4.2. Discussion of Postulates I -III.- 4.3. The Schrödinger Equation (Dotting Your i’s and Crossing your ?’s).- 5. Simple Problems in One Dimension.- 5.1. The Free Particle.- 5.2. The Particle in a Box.- 5.3. The Continuity Equation for Probability.- 5.4. The Single-Step Potential: a Problem in Scattering.- 5.5. The Double-Slit Experiment.- 5.6. Some Theorems.- 6. The Classical Limit.- 7. The Harmonic Oscillator.- 7.1. Why Study the Harmonic Oscillator?.- 7.2. Review of the Classical Oscillator.- 7.3. Quantization of the Oscillator (Coordinate Basis).- 7.4. The Oscillator in the Energy Basis.- 7.5. Passage from the Energy Basis to the X Basis.- 8. The Path Integral Formulation of Quantum Theory.- 8.1. The Path Integral Recipe.- 8.2. Analysis of the Recipe.- 8.3. An Approximation to U(t) for the Free Particle.- 8.4. Path Integral Evaluation of the Free-Particle Propagator.- 8.5. Equivalence to the Schrödinger Equation.- 8.6. Potentials of the Form V=a + bx + cx2 + d? + ex?.- 9. The Heisenberg Uncertainty Relations.- 9.1. Introduction.- 9.2. Derivation of the Uncertainty Relations.- 9.3. The Minimum Uncertainty Packet.- 9.4. Applications of the Uncertainty Principle.- 9.5. The Energy-Time Uncertainty Relation.- 10. Systems with N Degrees of Freedom.- 10.1. N Particles in One Dimension.- 10.2. More Particles in More Dimensions.- 10.3. Identical Particles.- 11. Symmetries and Their Consequences.- 11.1. Overview.- 11.2. Translational Invariance in Quantum Theory.- 11.3. Time Translational Invariance.- 11.4. Parity Invariance.- 11.5. Time-Reversal Symmetry.- 12. Rotational Invariance and Angular Momentum.- 12.1. Translations in Two Dimensions.- 12.2. Rotations in Two Dimensions.- 12.3. The Eigenvalue Problem of Lz.- 12.4. Angular Momentum in Three Dimensions.- 12.5. The Eigenvalue Problem of L2 and Lz.- 12.6. Solution of Rotationally Invariant Problems.- 13. The Hydrogen Atom.- 13.1. The Eigenvalue Problem.- 13.2. The Degeneracy of the Hydrogen Spectrum.- 13.3. Numerical Estimates and Comparison with Experiment.- 13.4. Multielectron Atoms and the Periodic Table.- 14. Spin.- 14.1. Introduction.- 14.2. What is the Nature of Spin?.- 14.3. Kinematics of Spin.- 14.4. Spin Dynamics.- 14.5. Return of Orbital Degrees of Freedom.- 15. Addition of Angular Momenta.- 15.1. A Simple Example.- 15.2. The General Problem.- 15.3. Irreducible Tensor Operators.- 15.4. Explanation of Some “Accidental” Degeneracies.- 16. Variational and WKB Methods.- 16.1. The Variational Method.- 16.2. The Wentzel-Kramers-Brillouin Method.- 17. Time-Independent Perturbation Theory.- 17.1. The Formalism.- 17.2. Some Examples.- 17.3. Degenerate Perturbation Theory.- 18. Time-Dependent Perturbation Theory.- 18.1. The Problem.- 18.2. First-Order Perturbation Theory.- 18.3. Higher Order

Reviews from the First Edition:

'An excellent text … The postulates of quantum mechanics and the mathematical underpinnings are discussed in a clear, succinct manner.' (American Scientist)

'No matter how gently one introduces students to the concept of Dirac’s bras and kets, many are turned off. Shankar attacks the problem head-on in the first chapter, and in a very informal style suggests that there is nothing to be frightened of.' (Physics Bulletin)

Reviews of the Second Edition:

'This massive text of 700 and odd pages has indeed an excellent get-up, is very verbal and expressive, and has extensively worked out calculational details---all just right for a first course. The style is conversational, more like a corridor talk or lecture notes, though arranged as a text. … It would be particularly useful to beginning students and those in allied areas like quantum chemistry.' (Mathematical Reviews)


<R. Shankar has introduced major additions and updated key presentations in this second edition of Principles of Quantum Mechanics. New features of this innovative text include an entirely rewritten mathematical introduction, a discussion of Time-reversal invariance, and extensive coverage of a variety of path integrals and their applications. Additional highlights include:

- Clear, accessible treatment of underlying mathematics
- A review of Newtonian, Lagrangian, and Hamiltonian mechanics
- Student understanding of quantum theory is enhanced by separate treatment of mathematical theorems and physical postulates
- Unsurpassed coverage of path integrals and their relevance in contemporary physics

The requisite text for advanced undergraduate- and graduate-level students, Principles of Quantum Mechanics, Second Edition is fully referenced and is supported by many exercises and solutions. The book’s self-contained chapters also make it suitable for independent study as well as for courses in applied disciplines.

R. Shankar has introduced major additions and updated key presentations in this second edition of Principles of Quantum Mechanics. New features of this innovative text include an entirely rewritten mathematical introduction, a discussion of Time-reversal invariance, and extensive coverage of a variety of path integrals and their applications. Additional highlights include:


- Clear, accessible treatment of underlying mathematics
- A review of Newtonian, Lagrangian, and Hamiltonian mechanics
- Student understanding of quantum theory is enhanced by separate treatment of mathematical theorems and physical postulates
- Unsurpassed coverage of path integrals and their relevance in contemporary physics

The requisite text for advanced undergraduate- and graduate-level students, Principles of Quantum Mechanics, Second Edition is fully referenced and is supported by many exercises and solutions. The book’s self-contained chapters also make it suitable for independent study as well as for courses in applied disciplines.

9780306447907

100398_2_En

10.1007/978-1-4757-0576-8

Jakub M. Tomczak, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Why Deep Generative Modeling?.- Autoregressive Models.- Flow-based Models.- Latent Variable Models.- Hybrid Modeling.- Energy-based Models.- Generative Adversarial Networks.- Deep Generative Modeling for Neural Compression.- Useful Facts from Algebra and Calculus.- Useful Facts from Probability Theory and Statistics.- Index.

This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective 'deep' comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions.<div>
</div><div>Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github.
</div>

This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective 'deep' comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions.

Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github.

The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.

<p>This approach combines probability theory with deep learning to obtain powerful AI systems</p><p>Outlines the most important techniques in deep generative modeling, enabling readers to formulate new models</p><p>All chapters include code snippets to help understand how the presented methods can be implemented</p>

Jakub Tomczak is an assistant professor of Artificial Intelligence in the Computational Intelligence group at Vrije Universiteit Amsterdam since November 2019. Before, from October 2018 to October 2019, he was a deep learning researcher (Staff Engineer) in Qualcomm AI Research in Amsterdam. From October 2016 to September 2018, he was a Marie Sklodowska-Curie Individual Fellow in Prof. Max Welling’s group at the University of Amsterdam. He obtained his Ph.D. in machine learning from the Wroclaw University of Technology. His research interests include probabilistic modeling, deep learning, approximate Bayesian modeling, and deep generative modeling (with special focus on Variational Auto-Encoders and Flow-based model).

9783030931575

524333_1_En

978-3-030-36720-6

Introductory Problems.- Activation Functions.- Cost Functions.- Finding Minima Algorithms.- Abstract Neurons.- Neural Networks.- Approximation Theorems.- Learning with One-dimensional Inputs.- Universal Approximators.- Exact Learning.- Information Representation.- Information Capacity Assessment.- Output Manifolds.- Neuromanifolds.- Pooling.- Convolutional Networks.- Recurrent Neural Networks.- Classification.- Generative Models.- Stochastic Networks.- Hints and Solutions.

This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter.

This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.

This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter.This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.

<p>Contains a fair number of end-of chapter exercises</p><p>Full solutions provided to all exercises</p><p>Appendices including topics needed in the book exposition</p>

Ovidiu Calin, a graduate from University of Toronto, is a professor at Eastern Michigan University and a former visiting professor at Princeton University and University of Notre Dame. He has delivered numerous lectures at several universities in Japan, Hong Kong, Taiwan, and Kuwait over the last 15 years. His publications include over 60 articles and 8 books in the fields of machine learning, computational finance, stochastic processes, variational calculus and geometric analysis.

9783030367206

488635_1_En

978-3-030-66048-2

Scott R. Steele; Tracy L. Hull; Neil Hyman; Justin A. Maykel; Thomas E. Read; Charles B. Whitlow

Scott R. Steele, Cleveland Clinic, Cleveland, OH, USA; Tracy L. Hull, Cleveland Clinic, Cleveland, OH; Neil Hyman, University of Chicago Medical Center, Chicago, IL; Justin A. Maykel, University of Massachusetts Medical School, Worcester, MA, USA; Thomas E. Read, University of Florida, Gainesville, FL; Charles B. Whitlow, Ochsner Clinic, New Orleans, LA

XX, 1216 p. 588 illus., 508 illus. in color. In 2 volumes, not available separately.

Jointly published with The American Society of Colon and Rectal Surgeons, Arlington Heights, IL, USA

,978-3-319-25968-0,978-3-319-25969-7,978-3-319-25970-3,978-3-319-79867-7

Anatomy and Embryology of the Colon, Rectum and Anus.- Colonic Physiology.- Anorectal Physiology.- Endoscopy.- Endoscopic management of polyps and endolumenal surgery.- Pre-operative evaluation in the colorectal patient.- Optimizing Outcomes with Enhanced Recovery.- General Postoperative Complications.- Anastomotic Construction.- Anastomotic Complications.- Hemorrhoids.- Anal Fissure and Anal Stenosis.- Cryptoglandular Abscess and Fistula.- Rectourethral and complex fistulas: evaluation and management.- Rectovaginal Fistula.- Pilonidal Disease and Hidradenitis Suppurativa.- Dermatology and Pruritus Ani.- Sexually transmitted infections of the Colon and Rectum.- Anal intraepithelial neoplasia.- Anal Cancer .- Presacral Tumors.- Sporadic and Inherited Colorectal Cancer: How Epidemiology and Molecular Biology Guide Screening and Treatment.- Management of Malignant Polyps.- Colorectal cancer: Preoperative evaluation and staging.- Colon Cancer Surgical Treatment: Principles of Colectomy.- Rectal Cancer: Neoadjuvant Therapy.- Rectal Cancer: Local Excision.- Rectal Cancer: Non-operative management.- Proctectomy for Rectal Cancer.- Colorectal Cancer: Postoperative Adjuvant Therapy and Surveillance.- Colorectal Cancer: Management of Distant Metastases.- Locally Recurrent Rectal Cancer.- Appendiceal Neoplasms.- Gastrointestinal Stromal Tumors, Neuroendocrine Tumors, and Lymphoma.- Cytoreductive Surgery (CRS) and Hyperthermic Intraperitoneal Chemotherapy (HIPEC).- Colorectal cancer: minimally invasive surgery.- Minimally Invasive Complete Mesocolic Excision with Extended Lymphadenectomy for Colon Cancer.- Colonic Diverticular Disease.- Large Bowel Obstruction.- Lower GI Hemorrhage.- Endometriosis.- Benign Colorectal Disease Trauma of the Colon and Rectum.- Inflammatory Bowel Disease: Pathobiology.- IBD Diagnosis and Evaluation.- Medical Management of Ulcerative Colitis.- Medical Therapy for Crohn’s Disease.- Anorectal Crohn’s Disease.- Crohn’s Disease: Surgical Management.- Ulcerative Colitis – Surgical Management.- Complications of the Pelvic Pouch.- Infectious Colitis.- Clostridium difficile Infection.- Radiation, Microscopic, and Ischemic Colitis.- Intestinal Stomas.- Abdominal Wall Reconstruction and Parastomal Hernia Repair.- Functional Disorders after Colorectal Surgery/ IBS.- Common Tests for the Pelvic Floor.- Evaluation of Constipation and Treatment of Abdominal Component.- Treatment of Difficult/Obstructive Defecation.- Rectal Prolapse.- Fecal Incontinence: Evaluation and Treatment.- Low Anterior Resection Syndrome (LARS).- Sexual Function After Colorectal Surgery in Women.- Male Genitourinary Dysfunction as a Consequence of Colorectal Surgery.- Middle and Anterior Pelvic Compartment: Issues for the Colorectal Surgeon.- Pediatric Colorectal Disorders.- Considerations for Geriatric Patients Undergoing Colorectal Surgery.- Healthcare Economics.- Ethical Considerations (Conflict of Interest, Surgical Innovation, End of Life).- Welcome to Litigation.- Quality.- Practice Management.

<div>This book serves as a valuable resource for surgeons and health care providers at all stages of their career caring for patients with colorectal disease. This edition provides all newly written chapters, organized around the “pillars” of colorectal disease: perioperative (including endoscopy); anorectal disease; benign disease (including inflammatory bowel disease); malignancy; pelvic floor disorders; and a “miscellaneous” section that covers aspects both inside and beyond the operating room. Chapters are formatted to follow that of a “how to” manual as well as an algorithm-based guide to allow the reader to understand the thought process behind a proposed treatment strategy. By making use of evidence-based recommendations, each chapter includes not only background information and diagnostic/therapeutic guidelines, but also provides operative technical details and perioperative “tips and tricks” that are utilized in the management of these complex surgical challenges. Chapters also include the assessment of risk and methods utilized to minimize perioperative complications. In addition, the book incorporates sections covering the medical and surgical therapies for abdominal, pelvic and anorectal disease.</div><div> </div><div>Written by experts in the field from around the world, The ASCRS Textbook of Colon and Rectal Surgery 4th Edition exposes the many critical gaps in our knowledge base and inspires the next generation to answer them through thoughtful and high level scientific inquiry.
</div>

This book serves as a valuable resource for surgeons and health care providers at all stages of their career caring for patients with colorectal disease. This edition provides all newly written chapters, organized around the “pillars” of colorectal disease: perioperative (including endoscopy); anorectal disease; benign disease (including inflammatory bowel disease); malignancy; pelvic floor disorders; and a “miscellaneous” section that covers aspects both inside and beyond the operating room. Chapters are formatted to follow that of a “how to” manual as well as an algorithm-based guide to allow the reader to understand the thought process behind a proposed treatment strategy. By making use of evidence-based recommendations, each chapter includes not only background information and diagnostic/therapeutic guidelines, but also provides operative technical details and perioperative “tips and tricks” that are utilized in the management of these complex surgical challenges. Chapters also include the assessment of risk and methods utilized to minimize perioperative complications. In addition, the book incorporates sections covering the medical and surgical therapies for abdominal, pelvic and anorectal disease. <div> </div><div>Written by experts in the field from around the world, The ASCRS Textbook of Colon and Rectal Surgery 4th Edition exposes the many critical gaps in our knowledge base and inspires the next generation to answer them through thoughtful and high level scientific inquiry.
</div>

<p>Provides videos that give the reader an upfront look into technical aspects of colorectal surgery</p><p>Format follows that of both a “how to” manual as well as an algorithm-based guide</p><p>Authors provide “tips and tricks” utilized in the management of these complex surgical challenges</p>

9783030660482

10.1007/978-3-030-66049-9

978-3-030-46813-2

Vickie A. Vaclavik, University of Texas Southwestern Medical Center, Dallas, TX, USA; Elizabeth W. Christian, Texas Women’s University, Denton, TX, USA; Tad Campbell, UT Southwestern School of Health Professions, Dallas, TX, USA

Part I. Introduction to Food Components.- Evaluation of Food Quality.- Water.- Part II. Carbohydrates in Food.- Carbohydrates in Food: An Introduction.- Starches in Food.- Pectins and Gums.- Grains: Cereals, Flour, Rice, and Pasta.- Vegetables and Fruits.- Part III. Proteins in Food.- Proteins in Foods: An Introduction.- Meat, Poultry, Fish, and Dry Beans.- Eggs and Egg Products.- Milk and Milk Products.- Part IV. Fats in Food.- Fats and Oils in Products.- Food Emulsions and Foams.- Part V. Sugars, Sweeteners.- Sugars, Sweeteners, and Confections.- Part VI. Baked Products.- Baked Products: Batters and Dough.- Part VII. Aspects of Food Preservation.- Food Preservation.- Food Additives.- Food Packaging.- Part VIII. Food Safety.- Food Safety.- Part IX. Government Regulation of the Food Supply.- Government Regulation of the Food Supply and Labeling.- Appendices.

The fifth edition of the Essential of Food Science text continues its approach of presenting the essential information of food chemistry, food technology, and food preparations while providing a single source of information for the non-major food science student.

This latest edition includes new discussions of food quality and new presentations of information around biotechnology and genetically modified foods. Also new in this edition is a discussion of the Food Safety Modernization Act (FSMA), a comparison chart for Halal and Kosher foods and introductions to newly popular products like pea starchand the various plant-based meat analogues that are now available commercially and for household use.

Each chapter ends with a glossary of terms, references, and a bibliography. The popular “Culinary Alert!” features are scattered throughout the text and provide suggestions for the reader to easily apply the information in the text to his or her cooking application.

Appendices at the end of the book include a variety of current topics such as Processed Foods, Biotechnology, Genetically Modified Foods, Functional Foods, Nutraceuticals, Phytochemicals, Medical Foods, and a Brief History of Foods Guides including USDA Choosemyplate.gov.

V.A. Vaclavik, Ph.D., RD. has taught classes in nutrition, food science and management and culinary arts for over 25 years at the college level in Dallas, Texas. She is a graduate of Cornell University, human nutrition and food; Purdue University, restaurant, hotel, institution management; and Texas Woman’s University, institution management and food science.

Elizabeth Christian, Ph.D. has been an adjunct faculty member at Texas Woman’s University for more than 25 years, teaching both face-to-face and online classes in the Nutrition and Food Science department. She obtained her B.S. and her PhD. In Food Science from Leeds University, England, and then worked as a research scientist at the Hannah Dairy Research Institute in Scotland for Five years before moving to the United States.

Tad Campbell, MCN, RDN, LD is a clinical instructor at The University of Texas Southwestern Medical Center at Dallas, where he teaches Food Science and Technology as well as other nutrition courses in the Master of Clinical Nutrition – Coordinated Program. He holds a Bachelor of Business Administration degree from Baylor University as well as a Master of Clinical Nutrition from UT Southwestern where he studied Food Science under Dr. Vickie Vaclavik.

The fifth edition of the Essential of Food Science text continues its approach of presenting the essential information of food chemistry, food technology, and food preparations while providing a single source of information for the non-major food science student.

This latest edition includes new discussions of food quality and new presentations of information around biotechnology and genetically modified foods. Also new in this edition is a discussion of the Food Safety Modernization Act (FSMA), a comparison chart for Halal and Kosher foods and introductions to newly popular products like pea starchand the various plant-based meat analogues that are now available commercially and for household use.

Each chapter ends with a glossary of terms, references, and a bibliography. The popular “Culinary Alert!” features are scattered throughout the text and provide suggestions for the reader to easily apply the information in the text to his or her cooking application.

Appendices at the end of the book include a variety of current topics such as Processed Foods, Biotechnology, Genetically Modified Foods, Functional Foods, Nutraceuticals, Phytochemicals, Medical Foods, and a Brief History of Foods Guides including USDA Choosemyplate.gov.

V.A. Vaclavik, Ph.D., RD. has taught classes in nutrition, food science and management and culinary arts for over 25 years at the college level in Dallas, Texas. She is a graduate of Cornell University, human nutrition and food; Purdue University, restaurant, hotel, institution management; and Texas Woman’s University, institution management and food science.

Elizabeth Christian, Ph.D. has been an adjunct faculty member at Texas Woman’s University for more than 25 years, teaching both face-to-face and online classes in the Nutrition and Food Science department. She obtained her B.S. and her PhD. In Food Science from Leeds University, England, and then worked as a research scientist at the Hannah Dairy Research Institute in Scotland for Five years before moving to the United States.

Tad Campbell, MCN, RDN, LD is a clinical instructor at The University of Texas Southwestern Medical Center at Dallas, where he teaches Food Science and Technology as well as other nutrition courses in the Master of Clinical Nutrition – Coordinated Program. He holds a Bachelor of Business Administration degree from Baylor University as well as a Master of Clinical Nutrition from UT Southwestern where he studied Food Science under Dr. Vickie Vaclavik.

<p>Uses Choose My Plate, the new health guidelines from the USDA</p><p>Major updates to chapters on food processing</p><p>Instructor’s Manual available for download</p>

Vickie A. Vaclavik, Ph. D., R.D., Retired.

Dr. Vickie Vaclavik taught for over 25 years at the college level in Dallas, Texas. Included among her students were nutrition students at the Dallas County Community College District; Food Science, and Food Service Management students at The University of Texas Southwestern Medical Center at Dallas, Nutrition Department Graduate School; and culinary students at the International Culinary School at the Art Institute of Dallas. She is a graduate of Cornell University, human nutrition and food; Purdue University, restaurant, hotel, institution management; and Texas Woman’s University, institution management and food science.

Personally, she really likes passing on what she knows and enjoys. Prior to teaching and writing, Dr. Vaclavik worked in various foodservice operations—including hotel restaurants, Meals-on-Wheels, hospital foodservice management and more. Two of her three sons are married with children of their own!


Elizabeth W. Christian, Ph. D., Retired.

Dr. Elizabeth Christian was an adjunct faculty member at Texas Woman’s University in Denton for 25 years, teaching both face-to-face and online classes in the Nutrition and Food Science Department. Food Science has been her passion since she was a freshman in high school. She obtained her B.S. and her Ph. D. in Food Science from the Leeds University, England. After working for five years as a research scientist at the Hannah Dairy Research Institute in Scotland, she married an American and moved to the United States. Elizabeth has two grown daughters, and currently lives in Longview, TX, with her adorable dog, Winston!

Best wishes and God bless!We would like to welcome to authorship Tad Campbell!


Tad Campbell, MCN, R.D.N., L.D.Tad Campbell is a clinical instructor at The University of Texas Southwestern Medical Center at Dallas, Clinical Nutrition Department where he teaches Food Science and Technology as well as other nutrition courses in the Master of Clinical Nutrition – Coordinated Program. He holds a Bachelor of Business Administration degree from Baylor University as well as a Master of Clinical Nutrition from UT Southwestern. While at UT Southwestern, he took Food Science under Dr. Vickie Vaclavik. In addition to teaching, Tad provides individual weight management counseling and provides Medical Nutrition Therapy focusing on Neuromuscular disorders in several multi-disciplinary clinics.

9783030468132

105372_5_En

10.1007/978-3-030-46814-9

Jonathan Passmore, University of Reading, Henley-on-Thames, UK; Tracy Sinclair, International Coaching Federation, Lexington, KY, USA

Introduction: Marshall Goldsmith.- Section 1.- Chapter 1. What is coaching?.- Chapter 2. Who am I?.- Chapter 3. Understanding clients.- Chapter 4. Coach maturity.- Section 2. Developing core coaching competences.- Chapter 5. Ethics & professional conduct (competency 1).- Chapter 6. Contracting (competency 2).- Chapter 7. Relationship (competency 3).- Chapter 8. Presence (competency 4).- Chapter 9. Active listening (competency 5).- Chapter 10. Powerful questions (competency 6).- Chapter 11. Direct communication (competency 7).- Chapter 12. Creating awareness (competency 8).- Chapter 13. Moving to action (competency 9, 10 & 11).- Chapter 14. Integrating the behaviors (Summary).- Section 3. Approaches to coaching.- Chapter 15. The Henley Eclectic Model .- Chapter 16. Behavioural approach and the GROW model.

Authored by masters in the field of coaching, this book is designed as a course textbook for those studying coaching in general, but with a specific reference to the updated competences introduced by the International Coaching Federation in 2020. It focuses on core coaching skills, knowledge, and developing self-awareness. This is a definitive text for coach training and go-to guide for those undertaking ICF-accredited programmes throughout the world.This book helps readers equip themselves with the skills and knowledge needed to develop as a professional coach. It encourages readers to reflect on who they are, what they can do, and how they can enhance their skills. By drawing on the Gold Standard for coach training and the latest coaching research, this book ensures that a trainer's practice is well informed by evidence and is up to the highest professional standards.'Becoming a Coach is the perfect place to start your coach development journey. The book provides a comprehensive coverage of the issues in coaching and offers an essential guide to the new ICF coach competencies for new and developing coaches'. - Marshall Goldsmith - Thinkers 50 #1 Executive Coach for 10 years.<div>'Whether you are becoming a coach, or are a seasoned coach supervisor, mentor, trainer, or educator, this book is your vital companion. The authors bring decades of experience and research into one powerful resource. Grounded in evidence-based models, plus tools, activities, reflective exercises and more, this book is a must-read!”

<div> Dr. Laura L. Hauser, MCC, MCEC | Training Director, Team Coaching Operating System® | Faculty, Fielding Graduate University coaching program | Executive Officer, GSAEC.orgThis is one of those rare books which has something for everyone. One of the most comprehensive guides to becoming a powerful coach which starts from the basics and takes us to the essentials of mastery.This book has embraced the complexity of coaching literature, approaches and tools. It has then structured and presented them in a fashion that brings together the chaos to a usable format. I can safely say that this book would offer a new idea, approach or perspective even to the most experienced of coaches.Shweta HandaGupta, MCC, Change Leadership Coach, QuadraBrain® Transformation Solutions, Global ICF Young Leader Award Recipient, 2018
“In this crowded confusing profession called coaching, Sinclair and Passmore have written the guidebook that clears the fog for coaches on their path to coaching excellence. Becoming a Coach clarifies the distinction of coaching and why it is so effective, provides specific practices for embodying a coaching mindset, and is full of tools that will elevate your coaching impact. No matter where you are on your journey, this book will give you a bright light to follow”.
Dr. Marcia Reynolds, MCC, ICF Global Board Past Chair, Author of Coach the Person, Not the Problem: A Guide to Using Reflective Inquiry

</div></div>

Authored by masters in the field of coaching, this book is designed as a course textbook for those studying coaching in general, but with a specific reference to the updated competences introduced by the International Coaching Federation in 2020. It focuses on core coaching skills, knowledge, and developing self-awareness. This is a definitive text for coach training and go-to guide for those undertaking ICF-accredited programs throughout the world.This book helps readers equip themselves with the skills and knowledge needed to develop as a professional coach. It encourages readers to reflect on who they are, what they can do, and how they can enhance their skills. By drawing on the Gold Standard for coach training and the latest coaching research, this book ensures that a trainer's practice is well informed by evidence and is up to the highest professional standards.

<p>Includes detailed coverage of the core issues, from contracting to ethics, and from coaching model to tools and techniques</p><p>Is an essential resource for any coach progressing through ACC, PCC towards MCC coach credentials</p><p>Written by two highly experienced authors, who combine academic understanding with executive coaching experience</p>

Jonathan Passmore is an award winning and internationally respected chartered psychologist based in the UK. He has written or edited over 30 books including Excellence in Coaching and Top Business Psychology Models, which have been widely translated in to multiple languages, and over 100 book chapters and articles. He holds five degrees and is the director of the Centre for Coaching at Henley Business School, University of Reading, UK, which delivers post-graduate coach training to over 300 students per year in the UK and internationally. The latest book, Mastering Executive Coaching is co-authored with Marshall Goldsmith and Brain Underhill.

Tracy Sinclair is a Past Global Chair of the International Coaching Federation, an ICF credentialed coach, a coaching supervisor, mentor coach and ICF assessor. She has practiced as a coach for 13 years and now leads a coaching, coach mentor, coach training and coaching consultancy business helping clients, organizations and coaches in their development journeys. In recognition of her efforts to develop the field of coaching, she was named as one of the Leading Global Coaches winners of the Thinkers50 Marshall Goldsmith Coaching Awards 2019

9783030531607

482445_1_En

978-3-030-92704-2

Phyllis Thompson, East Tennessee State University, Johnson City, TN, USA; Janice Carello, Edinboro University, Edinboro, PA, USA

Introduction.- Section I. INFUSING TRAUMA-INFORMED PRINCIPLES.- 1. Employing Trauma-Informed Principles through a Feminist Model of Practice.- 2. Leveraging the Neuroscience of Now to Cultivate a Pedagogy of Purpose and Empowerment.- 3. Building Resiliency through the Trauma Informed Classroom.- 4. Fostering a Spirit of Collaboration by Sharing Power with Students about Course Decisions.- Section II. TRAUMA-INFORMED TEACHING ACROSS THE CURRICULUM.- 5. Processing Critical Knowledge Through Trauma-Informed Musical Travel.- 6. Stumbling My Way to Trauma-Informed Teaching and Learning.- 7. Humanizing Social Work Education: Resetting for Healing Purposes.- 8. Section III. APPROACHES TO WORKING WITH SPECIFIC POPULATIONS.- 9. Trauma-Informed Approaches to Teaching Students with Marginalized Identities during Times of Crisis.- 10. How Trauma-Informed Care Principles Can Contribute to Academic Success for Students in Hispanic-Serving Institutions.- 11. Trauma Informed Educational Practices at Community College.- 12. Not a Hero and not a Stranger: Serving Veterans in Higher Education.- 13. The Benefits of Reflective Journaling during COVID-19: Contingent Faculty Exploring Teaching and Learning during a Crisis.- 14. Developing Trauma-Informed Practice: Coordinating Indigenous Adult Education Programs as a Non-Indigenous Educator.- Section IV. (RE)ASSESSMENT.- 15. Measuring Trauma Resilience in Higher Education Settings.- 16. An Educator's Scope of Practice: How Do I Know What Is Mine?.- 17. What are We Centering?: Developing a Trauma-Informed Syllabus.- 18. Utilizing an Ecological, Trauma-Informed, Equity Lens to Build an Understanding of the Context for and Experience of Self-Care in Higher Education.- Section V. TRAUMA-INFORMED TEACHING TOOLBOX.- 19. Higher Education Trauma Resilience Assessment.- 20. Educator and Department Self-Assessment Tools.- 21. Creation of Brave Space.- 22. First Day of Class Introductions: Trans Inclusion in Teaching.- 23. The Basket: Setting the Stage for Learning.- 24. Moment of Action.- 25. Trauma-Informing your Attendance (Policy).- 26. No Questions Asked Late Days.- 27. The Revise & Resubmit.- 28. Content Warnings.- 29. Panels and Pain: Teaching with Comics During Times of Trauma.- 30. Partner Exams.- 31. Best Practices for Online Content Design.
<div>
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This book centers equity in the approach to trauma-informed practice and provides the first evidence-based guide to trauma-informed teaching and learning in higher education. The book is divided into four main parts. Part I grounds the collection in an equity approach to trauma-informed care and illustrates one or more trauma-informed principles in practice. Chapters in Part II describe trauma-informed approaches to teaching in specific disciplines. In Part III, chapters demonstrate trauma-informed approaches to teaching specific populations. Part IV focuses on instruments and strategies for assessment at the institutional, organizational, departmental, class, and employee levels. The book also includes a substantial appendix with more than a dozen evidence-based and field-tested tools to support college educators on their trauma-informed teaching journey. Phyllis Thompson is Associate Professor and Director of Women’s, Gender, and Sexuality Studies at East Tennessee State University, USA. Thompson co-edited Lessons from the Pandemic: Trauma-Informed Approaches to College, Crisis, Change and publishes on women’s medicinal recipe books.Janice Carello is Assistant Professor and MSW Program Director at Edinboro University, USA. She co-edited Lessons from the Pandemic and Trauma and Human Rights and publishes trauma-informed teaching and learning resources on her blog: traumainformedteaching.blog. “Carello and Thompson have created a much-needed reference describing trauma-informed care for everyone working in higher education. Anyone who serves as faculty, administrators, or staff in academic settings must understand what this means for the ways in which they teach and interact with their students.”
—Sandra L. Bloom, Associate Professor, Health Management and Policy, Drexel University, USA “This book is nothing short of a miracle for higher education professionals who are eager to answer the call for trauma-informed change in a tumultuous world. It provides thoughtful, evidence-based approaches to light the path ahead, addressing the seismic shift in college student demographics, the knowledge gained from two decades of scientific studies into adversity and brain development, and the urgent need for inclusion and equity in higher education. As a whole, this book is simply indispensable.”
—Karen Oehme, Director, Student Resilience Project, Florida State University, USA, and Chairperson, Academic Resilience Consortium (ARC)

This book centers equity in the approach to trauma-informed practice and provides the first evidence-based guide to trauma-informed teaching and learning in higher education. The book is divided into four main parts. Part I grounds the collection in an equity approach to trauma-informed care and illustrates one or more trauma-informed principles in practice. Chapters in Part II describe trauma-informed approaches to teaching in specific disciplines. In Part III, chapters demonstrate trauma-informed approaches to teaching specific populations. Part IV focuses on instruments and strategies for assessment at the institutional, organizational, departmental, class, and employee levels. The book also includes a substantial appendix with more than a dozen evidence-based and field-tested tools to support college educators on their trauma-informed teaching journey.

<p>Offers the first evidence-based guide to trauma-informed teaching and learning in higher education</p><p>Includes a trauma-informed teaching "toolbox" with field-tested tools for teachers </p><p>Features a collection of resources that amplifies diverse voices across sectors and disciplines</p>

Phyllis Thompson is Associate Professor and Director of Women’s, Gender, and Sexuality Studies at East Tennessee State University, USA. Thompson co-edited Lessons from the Pandemic: Trauma-Informed Approaches to College, Crisis, Change and publishes on women’s medicinal recipe books.Janice Carello is Assistant Professor and MSW Program Director at Edinboro University, USA. She co-edited Lessons from the Pandemic and Trauma and Human Rights and publishes trauma-informed teaching and learning resources on her blog: traumainformedteaching.blog.<div><div>
</div></div>

9783030927042

511414_1_En

978-981-16-6045-0

Jong Chul Ye, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

Part I Basic Tools for Machine Learning: 1. Mathematical Preliminaries.- 2. Linear and Kernel Classifiers.- 3. Linear, Logistic, and Kernel Regression.- 4. Reproducing Kernel Hilbert Space, Representer Theorem.- Part II Building Blocks of Deep Learning: 5. Biological Neural Networks.- 6. Artificial Neural Networks and Backpropagation.- 7. Convolutional Neural Networks.- 8. Graph Neural Networks.- 9. Normalization and Attention.- Part III Advanced Topics in Deep Learning.- 10. Geometry of Deep Neural Networks.- 11. Deep Learning Optimization.- 12. Generalization Capability of Deep Learning.- 13. Generative Models and Unsupervised Learning.- Summary and Outlook.- Bibliography.- Index.

The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems.Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.<div>
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The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems.Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.<div>
</div>

<p>Covers recent developments in deep learning and a wide spectrum of issues, with exercise problems for students</p><p>Employs unified mathematical approaches with illustrative graphics to present various techniques and their results</p><p>Closes the gap between the purely mathematical and implementation-oriented treatments of deep learning </p>

The author is currently a full Professor at Korea Advanced Institute of Science and Technology (KAIST). Also he has been a Fellow of IEEE since January 2020.

9789811660450

504878_1_En

10.1007/978-981-16-6046-7

978-3-030-28732-0

,978-1-4419-3016-3,978-0-387-95468-4,978-1-4684-9255-2,978-0-387-21545-7

The Basics.- Polar Reactions under Basic Conditions.- Polar Reactions under Acidic Conditions.- Pericyclic Reactions.- Free-Radical Reactions.-Transition-Metal-Mediated and -Catalyzed Reactions.- Mixed-Mechanism Problems.

Intended for students of intermediate organic chemistry, this text shows how to write a reasonable mechanism for an organic chemical transformation. The discussion is organized by types of mechanisms and the conditions under which the reaction is executed, rather than by the overall reaction as is the case in most textbooks. The treatment emphasizes unifying principles, showing how common mechanisms link seemingly disparate reactions.

Each chapter discusses common mechanistic pathways and suggests practical tips for drawing them. Worked problems are included in the discussion of each mechanism, and “common error alerts” are scattered throughout the text to warn readers about pitfalls and misconceptions that bedevil students. Each chapter is capped by a large problem set.

The author has drawn on his own research and the current literature to ensure that appropriate attention is given to topics across the range of modern organic chemistry. The text is unique in its inclusion of a chapter on reactions mediated or catalyzed by transition metals, an area in which mechanistic understanding is now essential. More modern topics such as olefin metathesis and cycloaromatization are covered without giving short shrift to more traditional areas such as carbonyl chemistry. The text assumes a basic knowledge of organic chemistry. It can be used either in a formal course or by students working on their own, and will be particularly useful for graduate students studying for qualifying examinations. It will also be useful to students and researchers in biochemistry, pharmacology, and inorganic chemistry.

The third edition includes greater discussion of the reactions of biological cofactors such as thiamine and pyridoxal, and discussions of modern developments such as metal-catalyzed C–H activation reactions have been added. In terms of stylistic improvements, the author has introduced color into drawings to improve visual clarity and has improved the depictions of radical anions and radical chain reactions.

Intended for students of intermediate organic chemistry, this text shows how to write a reasonable mechanism for an organic chemical transformation. The discussion is organized by types of mechanisms and the conditions under which the reaction is executed, rather than by the overall reaction as is the case in most textbooks. The treatment emphasizes unifying principles, showing how common mechanisms link seemingly disparate reactions.

Each chapter discusses common mechanistic pathways and suggests practical tips for drawing them. Worked problems are included in the discussion of each mechanism, and “common error alerts” are scattered throughout the text to warn readers about pitfalls and misconceptions that bedevil students. Each chapter is capped by a large problem set.

The author has drawn on his own research and the current literature to ensure that appropriate attention is given to topics across the range of modern organic chemistry. The text is unique in its inclusion of a chapter on reactions mediated or catalyzed by transition metals, an area in which mechanistic understanding is now essential. More modern topics such as olefin metathesis and cycloaromatization are covered without giving short shrift to more traditional areas such as carbonyl chemistry. The text assumes a basic knowledge of organic chemistry. It can be used either in a formal course or by students working on their own, and will be particularly useful for graduate students studying for qualifying examinations. It will also be useful to students and researchers in biochemistry, pharmacology, and inorganic chemistry.

The third edition includes greater discussion of the reactions of biological cofactors such as thiamine and pyridoxal, and discussions of modern developments such as metal-catalyzed C–H activation reactions have been added. In terms of stylistic improvements, the author has introduced color into drawings to improve visual clarity and has improved the depictions of radical anions and radical chain reactions.

<p>Chapter level solution manuals are available on SpringerLink as Supplementary Material</p><p>Ideal as an independent study guide or reference to organic chemistry</p><p>Helps readers develop the ability to distinguish between diverse reactions</p><p>Includes common error alerts that warns of pitfalls and misconceptions</p><p>Begins with all the basics of the structure and stability of organic compounds</p>

​Robert B. Grossman earned his A.B. degree at Princeton University and his Ph.D. at MIT. He then moved from Cambridge, Massachusetts to Cambridge, England for his postdoctoral work. In 1994, he moved from the United Kingdom (UK) to the University of Kentucky (UK), where he has been ever since. At UK, Dr. Grossman maintains an active research program focused on synthetic methodology, target-directed synthesis, and biosynthesis. He is also the creator of ACE Organic, a Web-based organic chemistry homework program. Dr. Grossman has also served two terms as one of the two faculty representatives on the UK Board of Trustees. <div>
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9783030287320

978-3-030-76907-9

Donald Sannella, University of Edinburgh, Edinburgh, UK; Michael Fourman, University of Edinburgh, Edinburgh, UK; Haoran Peng, University of Edinburgh, Edinburgh, UK; Philip Wadler, University of Edinburgh, Edinburgh, UK

1. Sets.- 2. Types.- 3. Simple Computations.- 4. Venn Diagrams and Logical Connectives.- 5. Lists and Comprehensions.- 6. Features and Predicates.- 7. Testing Your Programs.- 8. Patterns of Reasoning.- 9. More Patterns of Reasoning.- 10. Lists and Recursion.- 11. More Fun with Recursion.- 12. Higher-Order Functions.- 13. Higher and Higher.- 14. Sequent Calculus.- 15. Algebraic Data Types.- 16. Expression Trees.- 17. Karnaugh Maps.- 18. Relations and Quantifiers.- 19. Checking Satisfiability.- 20. Data Representation.- 21. Data Abstraction.- 22. Efficient CNF Conversion.- 23. Counting Satisfying Valuations.- 24. Type Classes.- 25. Search in Trees.- 26. Combinatorial Algorithms.- 27. Finite Automata.- 28. Deterministic Finite Automata.- 29. Non-Deterministic Finite Automata.- 30. Input/Output and Monads.- 31. Regular Expressions.- 32 Non-Regular Languages.- Index.

Computation is a process of calculation involving arithmetic and logical steps, following a given set of rules (an algorithm).This uniquely accessible textbook introduces students to computation using a very distinctive approach, quite rapidly leading them into essential topics with sufficient depth, yet in a highly intuitive manner. The work is anchored in coverage of functional programming (in Haskell), symbolic logic, and finite automata-- each a critical component of the foundations of Informatics, and together offering students a clear glimpse into an intellectual journey beyond mere mastery of technical skills. From core elements like types, Venn diagrams and logic, to patterns of reasoning, sequent calculus, recursion and algebraic data types, the book spans the breadth of key concepts and methods that will enable students to readily progress with their studies in Computer Science.Topics and features:Spans the key concepts and methods that underpin computationDevelops symbolic logic, with a view toward honing clarity of thought; and automata, as a foundation for future study of both their applications and related theoretical topicsIntroduces powerful functional programming ideas that will be useful regardless which programming languages are used laterProvides numerous exercises to support a clear and open, accessible approachOffers a dedicated website with resources for instructors and students, including code and links to online informationIncludes a wide array of marginal notes, empowering readers to 'go beyond' the content presentedApproaches logic and automata through Haskell code, to bring key concepts alive and foster understanding through experimentationAssuming no formal background in programming, this highly practical and accessible textbook provides the grounding fundamentals of computation for undergraduate students. Its flexible, yet clear expository style also makes the book eminently suitable as a self-study instructional guide for professionals or nonspecialists interested in these topics.Prof. Donald Sannella, Prof. Michael Fourman, and Prof. Philip Wadler are each at the University of Edinburgh's School of Informatics, Edinburgh, UK. Mr. Haoran Peng will soon pursue research interests in machine learning and machine intelligence at Cambridge University, Cambridge, UK.

Computation, itself a form of calculation, incorporates steps that include arithmetical and non-arithmetical (logical) steps following a specific set of rules (an algorithm). This uniquely accessible textbook introduces students using a very distinctive approach, quite rapidly leading them into essential topics with sufficient depth, yet in a highly intuitive manner. From core elements like sets, types, Venn diagrams and logic, to patterns of reasoning, calculus, recursion and expression trees, the book spans the breadth of key concepts and methods that will enable students to readily progress with their studies in Computer Science.

<p>Introduces computation, spanning the key concepts and methods</p><p>Highly intuitive and accessible explanatory style</p><p>Firm grounding in logic and automata, with an approach using Haskell</p><p>Request lecturer material: http://www.sn.pub/lecturer-material</p>

Prof. Donald Sannella, Prof. Michael Fourman, and Prof. Philip Wadler are each at the University of Edinburgh's School of Informatics, Edinburgh, UK. Mr. Haoran Peng is also at the same university department.

9783030769079

510588_1_En

10.1007/978-3-030-76908-6

Ian Gibson, University of Twente, Enschede, The Netherlands; David Rosen, Georgia Institute of Technology, Atlanta, GA, USA; Brent Stucker, ANSYS, Park City, UT; Mahyar Khorasani, Deakin University, Armstrong Creek, VIC, Australia

,978-1-4939-2112-6,978-1-4939-2114-0,978-1-4939-2113-3,978-1-4939-4455-2

Chapter 1. Introduction and Basic Principles.- Chapter 2. Development of Additive Manufacturing Technology.- Chapter 3. Generalized Additive Manufacturing Process Chain.- Chapter 4. Vat Photopolymerization.- Chapter 5. Powder Bed Fusion.- Chapter 6. Material Extrusion.- Chapter 7. Material Jetting.- Chapter 8. Binder Jetting.- Chapter 9. Sheet Lamination.- Chapter 10. Directed Energy Deposition.- Chapter 11. Direct Write Technologies.- Chapter 12. Hybrid Additive Manufacturing.- Chapter 13. The Impact of Low-Cost AM Systems.- Chapter 14. Material for Additive Manufacturing.- Chapter 15. Guidelines for Process Selection.- Chapter 16. Post-processing.- Chapter 17. Software for Additive Manufacturing.- Chapter 18. Direct Digital Manufacturing.- Chapter 19. Design for Additive Manufacturing.- Chapter 20. Rapid Tooling.- Chapter 21. Industrial Drivers for AM Adoption.- Chapter 22. Business and Social Implications of AM.

This textbook covers in detail digitally-driven methods for adding materials together to form parts. A conceptual overview of additive manufacturing is given, beginning with the fundamentals so that readers can get up to speed quickly. Well-established and emerging applications such as rapid prototyping, micro-scale manufacturing, medical applications, aerospace manufacturing, rapid tooling and direct digital manufacturing are also discussed. This book provides a comprehensive overview of additive manufacturing technologies as well as relevant supporting technologies such as software systems, vacuum casting, investment casting, plating, infiltration and other systems.Reflects recent developments and trends and adheres to the ASTM, SI and other standards;Includes chapters on topics that span the entire AM value chain, including process selection, software, post-processing, industrial drivers for AM, and more. ;Provides a broad range of technical questions to ensure comprehensive understanding of the concepts covered.

This textbook covers in detail digitally-driven methods for adding materials together to form parts. A conceptual overview of additive manufacturing is given, beginning with the fundamentals so that readers can get up to speed quickly. Well-established and emerging applications such as rapid prototyping, micro-scale manufacturing, medical applications, aerospace manufacturing, rapid tooling and direct digital manufacturing are also discussed. This book provides a comprehensive overview of additive manufacturing technologies as well as relevant supporting technologies such as software systems, vacuum casting, investment casting, plating, infiltration and other systems.Reflects recent developments and trends and adheres to the ASTM, SI and other standards;Includes chapters on topics that span the entire AM value chain, including process selection, software, post-processing, industrial drivers for AM, and more;Provides a broad range of technical questions to ensure comprehensive understanding of the concepts covered.

<p>Reflects recent developments and trends and adheres to the ASTM, SI and other standards;</p><p>Includes chapters on topics that span the entire AM value chain, including process selection, software, post-processing, industrial drivers for AM, and more;</p><p>Provides a broad range of technical questions to ensure comprehensive understanding of the concepts covered.</p>

Professor Ian Gibson is a Professor of Industrial Design and Director of the Fraunhofer Project Centre at The University of Twente.Professor David W. Rosen is a Professor at the Georgia Institute of Technology and Research Director of the Digital Manufacturing and Design Centre at the Singapore University of Technology and Design.
Dr. Brent Stucker is a Distinguished Engineer in Additive Manufacturing at ANSYS.
Dr. Mahyar Khorasani is a Vice-Chancellor Research Fellow in Additive Manufacturing at Deakin University.

9783030561260

302038_3_En

978-1-4614-0714-0

Chris Spear, Synopsys, Inc., Marlborough, MA, USA; Greg Tumbush, Tumbush Enterprises, LLC University of Colorado, Colorado Springs, Colorado Springs, CO, USA

,978-0-387-52324-8,978-1-4419-4561-7,978-0-387-76529-7,978-0-387-76530-3

Verification Guidelines.- Data Types.- Procedural Statements and Routines.- Connecting the Testbench and Design.- Basic OOP.- Randomization.- Threads and Interprocess Communication.- Advanced OOP and Testbench Guidelines.- Functional Coverage.- Advanced Interfaces.- A Complete SystemVerilog Testbench.- Interfacing with C/C++.

Based on the highly successful second edition, this extended edition of SystemVerilog for Verification: A Guide to Learning the Testbench Language Features teaches all verification features of the SystemVerilog language, providing hundreds of examples to clearly explain the concepts and basic fundamentals. It contains materials for both the full-time verification engineer and the student learning this valuable skill.In the third edition, authors Chris Spear and Greg Tumbush start with how to verify a design, and then use that context to demonstrate the language features,  including the advantages and disadvantages of different styles, allowing readers to choose between alternatives. This textbook contains end-of-chapter exercises designed to enhance students’ understanding of the material. Other features of this revision include:New sections on static variables, print specifiers, and DPI from the 2009 IEEE language standardDescriptions of UVM features such as factories, the test registry, and the configuration databaseExpanded code samples and explanations Numerous samples that have been tested on the major SystemVerilog simulatorsSystemVerilog for Verification: A Guide to Learning the Testbench Language Features, Third Edition is suitable for use in a one-semester SystemVerilog course on SystemVerilog at the undergraduate or graduate level. Many of the improvements to this new edition were compiled through feedback provided from hundreds of readers.

Based on the highly successful second edition, this extended edition of SystemVerilog for Verification: A Guide to Learning the Testbench Language Features teaches all verification features of the SystemVerilog language, providing hundreds of examples to clearly explain the concepts and basic fundamentals. It contains materials for both the full-time verification engineer and the student learning this valuable skill.In the third edition, authors Chris Spear and Greg Tumbush start with how to verify a design, and then use that context to demonstrate the language features,  including the advantages and disadvantages of different styles, allowing readers to choose between alternatives. This textbook contains end-of-chapter exercises designed to enhance students’ understanding of the material. Other features of this revision include:New sections on static variables, print specifiers, and DPI from the 2009 IEEE language standardDescriptions of UVM features such as factories, the test registry, and the configuration databaseExpanded code samples and explanations Numerous samples that have been tested on the major SystemVerilog simulatorsSystemVerilog for Verification: A Guide to Learning the Testbench Language Features, Third Edition is suitable for use in a one-semester SystemVerilog course on SystemVerilog at the undergraduate or graduate level. Many of the improvements to this new edition were compiled through feedback provided from hundreds of readers.

<p>Completely updated technical material incorporating more fundamentals, latest changes to IEEE specifications since the second edition, and adding end of chapter problems</p><p>Contains dozens of methodology recommendations plus warnings of common mistakes made by new users of the language</p><p>Includes supplementary material designed to assist instructors with both teaching and assessing their students as well as solutions to all problems</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Chris Spear has been working in the ASIC design and verification field for 30 years. He started his career with Digital Equipment Corporation (DEC) as a / CAD Engineer on DECsim, connecting the first Zycad box ever sold, and then a hardware Verification engineer for the VAX 8600, and a hardware behavioral simulation accelerator. He then moved on to Cadence where he was an Application Engineer for Verilog-XL, followed by a stint at Viewlogic. Chris is currently employed at Synopsys Inc. as a Verification Consultant, a title he created a dozen years ago. He has authored the first and second editions of SystemVerilog for Verification: A Guide to Learning the Testbench Language Features. Chris earned a BSEE from Cornell University in 1981. In his spare time, Chris enjoys road biking in the mountains and traveling with his wife.Greg Tumbush has been designing and verifying ASICs and FPGAs for 13 years. After working as a researcher in the Air Force Research Labs (AFRL) he moved to beautiful Colorado to work with Astek Corp as a Lead ASIC Design Engineer. He then began a 6 year career with Starkey Labs, AMI Semiconductor, and ON Semiconductor where he was an early adopter of SystemC and SystemVerilog. In 2008, Greg left ON Semiconductor to form Tumbush Enterprises, LLC where he has been consulting clients in the areas of design, verification, and backend to ensure first pass success. He is also a part time Instructor at the University of Colorado, Colorado Springs where he teaches senior and graduate level digital design and verification courses. He has numerous publications which can be viewed at www.tumbush.com. Greg earned a Ph.D. from the University of Cincinnati in 1998.

9781461407140

124585_3_En

10.1007/978-1-4614-0715-7

David A. Cox, Amherst College, Amherst, MA, USA; John Little, College of the Holy Cross, Worcester, MA, USA; Donal O'Shea, New College of Florida, Sarasota, FL, USA

An Introduction to Computational Algebraic Geometry and Commutative Algebra

,978-0-387-51485-7,978-1-4419-2257-1,978-0-387-35650-1,978-0-387-35651-8

Preface.- Notation for Sets and Functions.- 1. Geometry, Algebra, and Algorithms.- 2. Groebner Bases.- 3. Elimination Theory.- 4.The Algebra-Geometry Dictionary.- 5. Polynomial and Rational Functions on a Variety.- 6. Robotics and Automatic Geometric Theorem Proving.- 7. Invariant Theory of Finite Groups.- 8. Projective Algebraic Geometry.- 9. The Dimension of a Variety.- 10. Additional Groebner Basis Algorithms.- Appendix A. Some Concepts from Algebra.- Appendix B. Pseudocode.- Appendix C. Computer Algebra Systems.- Appendix D. Independent Projects.- References.- Index.

This text covers topics in algebraic geometry and commutative algebra with a strong perspective toward practical and computational aspects. The first four chapters form the core of the book. A comprehensive chart in the preface illustrates a variety of ways to proceed with the material once these chapters are covered. In addition to the fundamentals of algebraic geometry—the elimination theorem, the extension theorem, the closure theorem, and the Nullstellensatz—this new edition incorporates several substantial changes, all of which are listed in the Preface. The largest revision incorporates a new chapter (ten), which presents some of the essentials of progress made over the last decades in computing Gröbner bases. The book also includes current computer algebra material in Appendix C and updated independent projects (Appendix D). The book may serve as a first or second course in undergraduate abstract algebra and, with some supplementation perhaps, for beginning graduate level courses in algebraic geometry or computational algebra. Prerequisites for the reader include linear algebra and a proof-oriented course. It is assumed that the reader has access to a computer algebra system. Appendix C describes features of Maple™, Mathematica®, and Sage, as well as other systems that are most relevant to the text. Pseudocode is used in the text; Appendix B carefully describes the pseudocode used.From the reviews of previous editions:“…The book gives an introduction to Buchberger’s algorithm with applications to syzygies, Hilbert polynomials, primary decompositions. There is an introduction to classical algebraic geometry with applications to the ideal membership problem, solving polynomial equations, and elimination theory. …The book is well-written. …The reviewer is sure that it will be an excellent guide to introduce further undergraduates in the algorithmic aspect of commutative algebra and algebraic geometry.” —Peter Schenzel, zbMATH, 2007“I consider the book to be wonderful. ... The exposition is very clear, there are many helpful pictures, and there are a great many instructive exercises, some quite challenging ... offers the heart and soul of modern commutative and algebraic geometry.” —The American Mathematical Monthly

This text covers topics in algebraic geometry and commutative algebra with a strong perspective toward practical and computational aspects. The first four chapters form the core of the book. A comprehensive chart in the Preface illustrates a variety of ways to proceed with the material once these chapters are covered. In addition to the fundamentals of algebraic geometry—the elimination theorem, the extension theorem, the closure theorem and the Nullstellensatz—this new edition incorporates several substantial changes, all of which are listed in the Preface. The largest revision incorporates a new Chapter (ten), which presents some of the essentials of progress made over the last decades in computing Gröbner bases. The book also includes current computer algebra material in Appendix C and updated independent projects (Appendix D).The book may serve as a first or second course in undergraduate abstract algebra and with some supplementation perhaps, for beginning graduate level courses in algebraic geometry or computational algebra. Prerequisites for the reader include linear algebra and a proof-oriented course. It is assumed that the reader has access to a computer algebra system. Appendix C describes features of Maple™, Mathematica® and Sage, as well as other systems that are most relevant to the text. Pseudocode is used in the text; Appendix B carefully describes the pseudocode used.Readers who are teaching from Ideals, Varieties, and Algorithms, or are studying the book on their own, may obtain a copy of the solutions manual by sending an email to jlittle@holycross.edu.From the reviews of previous editions: “…The book gives an introduction to Buchberger’s algorithm with applications to syzygies, Hilbert polynomials, primary decompositions. There is an introduction to classical algebraic geometry with applications to the ideal membership problem, solving polynomial equations and elimination theory. …The book is well-written. …The reviewer is sure that it will be an excellent guide to introduce further undergraduates in the algorithmic aspect of commutative algebra and algebraic geometry.” —Peter Schenzel, zbMATH, 2007 “I consider the book to be wonderful. ... The exposition is very clear, there are many helpful pictures and there are a great many instructive exercises, some quite challenging ... offers the heart and soul of modern commutative and algebraic geometry.” —The American Mathematical Monthly

<p>New edition extensively revised and updated</p><p>Covers important topics such as the Hilbert Basis Theorem, the Nullstellensatz, invariant theory, projective geometry and dimension theory</p><p>Fourth edition includes updates on the computer algebra and independent projects appendices</p><p>Features new central theoretical results such as the elimination theorem, the extension theorem, the closure theorem and the nullstellensatz</p><p>Discusses some of the newer approaches to computing Groebner bases</p>

David A. Cox is currently Professor of Mathematics at Amherst College. John Little is currently Professor of Mathematics at College of the Holy Cross. Donal O'Shea is currently President and Professor of Mathematics at New College of Florida.

9783319167206

978-3-030-42916-4

Barry S. Levine, 8415 Progress Dr. Suite V, Frederick, MD, USA; SARAH KERRIGAN, Sam Houston State University, Huntsville, TX, USA

Part 1: Introduction.- Post Mortem Forensic Toxicology.- Human Performance Toxicology.- Drug-Facilitated Sexual Assault.- Forensic Drug Testing.- Performance enhancing Drug Testing.- Drug Testing in Pain Management.- Pharmacokinetics and Pharmacodynamics.- Part II. Specimen Preparation.- Spectrophotometry.- Chromatography.- Derivatization.- Immunoassy.- Mass Spectrometry.- Quantitation.- Method Validation.- Measurement Uncertainty and Traceability.- Statistics in Forensic Toxicology.- Part III Analytes.- Alcohol.- Benzodiazapines.- Gammahydroxybutyric acid,- Miscellaneous Central Nervous System Depressants.- Opioids.- Cocanie.- Cannabis.- Amphetamines-Sympathomimetic Amines,- Hallucinogens and Psychedelics.- Antidepressants and Neuroleptics.- Miscellaneous Therapeutic Drugs.- Carbon Monoxide/Cyanide.- Inhalants.- Metals.- Part III Special Topics.- Stability of Drugs of Abuse in Biological Systems.- Postmortem Redistribution of Drugs.- Postmortem Clinical Testing.- Pharmacogenomics.- Hair Drug Testing.- Oral Fluid Testing.- Meconium Drug Testing.- Drugs in Embalmed Tissues.

The fifth edition of the best-selling Principles in Forensic Toxicology continues in the tradition of excellence in academic publishing. With over 10 years of classroom-tested and continually updated content, the new edition contains significant updates and 7 new chapters on new topics including drug-facilitated crimes, derivatization, quantitation, measurement uncertainty/traceability, statistics, oral fluid testing, and drugs in embalmed specimens. Part One covers the major sub-disciplines of forensic toxicology in addition to pharmacological concepts. Part Two addresses specimen preparation, laboratory testing and instrumental analysis, while Part Three discusses common analytes including cocaine, opioids, alcohol, and marijuana. Adopted for courses in many of the top universities for forensic science and used by respected medical examiner’s offices and crime laboratories worldwide, Principles of Forensic Toxicology prepares the next generation of forensic toxicologists and continues to be an important reference in professional practice.<div>
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The fifth edition of the best-selling Principles in Forensic Toxicology continues in the tradition of excellence in academic publishing. With over 10 years of classroom-tested and continually updated content, the new edition contains significant updates and 7 new chapters on new topics including drug-facilitated crimes, derivatization, quantitation, measurement uncertainty/traceability, statistics, oral fluid testing, and drugs in embalmed specimens. Part One covers the major sub-disciplines of forensic toxicology in addition to pharmacological concepts. Part Two addresses specimen preparation, laboratory testing and instrumental analysis, while Part Three discusses common analytes including cocaine, opioids, alcohol, and marijuana. Adopted for courses in many of the top universities for forensic science and used by respected medical examiner’s offices and crime laboratories worldwide, Principles of Forensic Toxicology prepares the next generation of forensic toxicologists and continues to be an important reference in professional practice.

<p>Over 50% updated content</p><p>More than 5 new chapters including ones on drug-facilitated crimes and drugs in embalmed specimens</p><p>Written in collaboration with new editor, Sarah Kerrigan, from Sam Houston State</p><p>Richly illustrated with over 140 figures and photos</p><p>Classroom tested for over 10 years</p><p>Essential information for both forensic science and forensic chemistry students and professional laboratorians</p>

Barry Levine received his B.S. in Chemistry from Loyola College and a Ph.D. in Toxicology from the Medical College of Virginia. He was Chief Toxicologist, Office of the Chief Medical Examiner, State of Maryland and currently consults with the Office. He was also the Director, Forensic Toxicology Laboratory for the Armed Forces Medical Examiner System. He is an Adjunct Professor in the Forensic Sciences Department, Stevenson University, teaching a course every year in forensic toxicology. Dr. Levine is a fellow of the American Board of Forensic Toxicology and a Diplomate of the American Board of Clinical Chemistry – Toxicological Chemistry. He edited the book widely adopted best-selling book, Principles f Forensic Toxicology, which is now in its fifth edition.<div>
</div><div>Dr. Kerrigan is the Chair of Forensic Science and the Director of the Institute for Forensic Research, Training and Innovation at Sam Houston State University. Prior to her academic position, she was employed as a forensic toxicologist, quality assurance manager and laboratory director in ASCLD/LAB, ABFT and ISO/IEC 17025 accredited forensic laboratories. Dr. Kerrigan has been active in the area of forensic reform for more than a decade. She is a long-standing member of the Texas Forensic Science Commission and has served on the Forensic Science Standards Board of the Organization of Scientific Area Committees (OSAC) for Forensic science since its inception.

</div>

9783030429164

468112_5_En

Joel H. Ferziger, Stanford University, Stanford, CA, USA; Milovan Perić, University of Duisburg-Essen, Duisburg, Germany; Robert L. Street, Stanford University, Stanford, CA, USA

Basic Concepts of Fluid Flow.- Introduction to Numerical Methods.- Finite Difference Methods.- Finite Volume Methods.- Solution of Linear Equation Systems.-Methods for Unsteady Problems.- Solution of the Navier-Stokes Equations.- Complex Geometries.- Turbulent Flows.- Compressible Flows.- Efficiency, Accuracy and Grid Quality.- Special Topics.

In its 4th edition, this classic textbook offers an overview of the techniques used to solve problems in fluid mechanics on computers and describes in detail those most often used in practice. Included are advanced methods in computational fluid dynamics, like direct and large-eddy simulation of turbulence, multigrid methods, parallel computing, moving grids, structured, block-structured and unstructured boundary-fitted grids, free surface flows. The book also contains a great deal of practical advice for code developers and users, it is designed to be equally useful to beginners and experts. The issues of numerical accuracy, estimation and reduction of numerical errors are dealt with in detail, with many examples. All computer codes can be accessed from the publishers server on the internet.

<div>
This book is a guide to numerical methods for solving fluid dynamics problems. The most widely used discretization and solution methods, which are also found in most commercial CFD-programs, are described in detail. Some advanced topics, like moving grids, simulation of turbulence, computation of free-surface flows, multigrid methods and parallel computing, are also covered. Since CFD is a very broad field, we provide fundamental methods and ideas, with some illustrative examples, upon which more advanced techniques are built. Numerical accuracy and estimation of errors are important aspects and are discussed in many examples. Computer codes that include many of the methods described in the book can be obtained online. </div><div>This 4th edition includes major revision of all chapters; some new methods are described and references to more recent publications with new approaches are included. Former Chapter 7 on solution of the Navier-Stokes equations has been split into two Chapters to allow for a more detailed description of several variants of the Fractional Step Method and a comparison with SIMPLE-like approaches. In Chapters 7 to 13, most examples have been replaced or recomputed, and hints regarding practical applications are made. Several new sections have been added, to cover, e.g., immersed-boundary methods, overset grids methods, fluid-structure interaction and conjugate heat transfer.</div><div>
</div>

<p>Provides practical advice for students and developers offering access to some fine and well-established programming techniques in CFD</p><p>Constitutes an excellent introduction to the world of CFD equally useful to beginners and experts</p><p>Includes the complete set of computer codes ready for download</p>

<div>Joel H. Ferziger, Dept. Mechanical Engineering, Stanford University, Stanford, CA, USA</div><div>Joel passed away in 2004; he taught numerical methods in engineering and CFD over many years at Stanford and is widely known for his pioneering work on large-eddy simulation methods.</div><div>
<div>Milovan Perić, Faculty of Engineering, University of Duisburg-Essen, and CoMeT Continuum Mechanics Technologies GmbH, Erlangen, Germany</div><div>Milovan taught CFD and fluid dynamics at universities in Erlangen and Hamburg for 15 years and then spent 12 years at CD-adapco (now part of Siemens PLM), working on the development of commercial CFD software. He is currently consultant to Siemens PLM and industrial users of CFD-software and also teaching Applied CFD at the University of Duisburg-Essen.

</div><div>Robert L. Street, School of Engineering, Stanford University, Stanford, CA, USA</div><div>Bob has taught fluid mechanics, numerical methods and turbulence modeling courses at Stanford for the past 56 years; his research focuses on numerical simulation of geophysical flows. In recent years, he has worked on turbulence models for large-eddy simulation of the atmospheric boundary layer and of cloud formation and evolution.</div><div>
</div></div>

9783319996912

978-1-4419-6052-8

,978-1-4419-2955-6,978-0-387-95336-6,978-1-4684-9282-8,978-1-4684-9281-1

The Theorem of Pythagoras.- Greek Geometry.- Greek Number Theory.- Infinity in Greek Mathematics.- Number Theory in Asia.- Polynomial Equations.- Analytic Geometry.- Projective Geometry.- Calculus.- Infinite Series.- The Number Theory Revival.- Elliptic Functions.- Mechanics.- Complex Numbers in Algebra.- Complex Numbers and Curves.- Complex Numbers and Functions.- Differential Geometry.- Non-Euclidean Geometry.- Group Theory.- Hypercomplex Numbers.- Algebraic Number Theory.- Topology.- Simple Groups.- Sets, Logic, and Computation.- Combinatorics.

From the reviews of the second edition:'This book covers many interesting topics not usually covered in a present day undergraduate course, as well as certain basic topics such as the development of the calculus and the solution of polynomial equations. The fact that the topics are introduced in their historical contexts will enable students to better appreciate and understand the mathematical ideas involved...If one constructs a list of topics central to a history course, then they would closely resemble those chosen here.'(David Parrott, Australian Mathematical Society)'The book...is presented in a lively style without unnecessary detail. It is very stimulating and will be appreciated not only by students. Much attention is paid to problems and to the development of mathematics before the end of the nineteenth century... This book brings to the non-specialist interested in mathematics many interesting results. It can be recommended for seminars and will be enjoyed by the broad mathematical community.' (European Mathematical Society)'Since Stillwell treats many topics, most mathematicians will learn a lot from this book as well as they will find pleasant and rather clear expositions of custom materials. The book is accessible to students that have already experienced calculus, algebra and geometry and will give them a good account of how the different branches of mathematics interact.'(Denis Bonheure, Bulletin of the Belgian Society)This third edition includes new chapters on simple groups and combinatorics, and new sections on several topics, including the Poincare conjecture. The book has also been enriched by added exercises.

From the reviews of the second edition:'This book covers many interesting topics not usually covered in a present day undergraduate course, as well as certain basic topics such as the development of the calculus and the solution of polynomial equations. The fact that the topics are introduced in their historical contexts will enable students to better appreciate and understand the mathematical ideas involved...If one constructs a list of topics central to a history course, then they would closely resemble those chosen here.'(David Parrott, Australian Mathematical Society)This third edition includes new chapters on simple groups and combinatorics, and new sections on several topics, including the Poincare conjecture. The book has also been enriched by added exercises.

<p>New edition extensively revised and updated The author’s style and exposition are unique</p><p>Features new exercises throughout the book Contains a new section on the Poincare conjecture Includes new chapters on simple groups and combinatorics</p>

John Stillwell is a professor of mathematics at the University of San Francisco. He is also an accomplished author, having published several books with Springer, including The Four Pillars of Geometry; Elements of Algebra; Numbers and Geometry; and many more.

9781441960528

Jeffrey Hoffstein, Brown University, Providence, RI, USA; Jill Pipher, Brown University, Providence, RI, USA; Joseph H. Silverman, Brown University, Providence, RI, USA

Distribution rights for India: Researchco Book Centre, New Delhi, India

,978-0-387-56970-3,978-1-4419-2674-6,978-0-387-77993-5,978-0-387-77994-2,978-1-4939-7089-6

Preface.- Introduction.- 1 An Introduction to Cryptography.- 2 Discrete Logarithms and Diffie-Hellman.- 3 Integer Factorization and RSA.- 4 Digital Signatures.- 5 Combinatorics, Probability, and Information Theory.- 6 Elliptic Curves and Cryptography.- 7 Lattices and Cryptography.- 8 Additional Topics in Cryptography.- List of Notation.- References.- Index.

This self-contained introduction to modern cryptography emphasizes the mathematics behind the theory of public key cryptosystems and digital signature schemes. The book focuses on these key topics while developing the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Only basic linear algebra is required of the reader; techniques from algebra, number theory, and probability are introduced and developed as required. This text provides an ideal introduction for mathematics and computer science students to the mathematical foundations of modern cryptography. The book includes an extensive bibliography and index; supplementary materials are available online.The book covers a variety of topics that are considered central to mathematical cryptography. Key topics include:

classical cryptographic constructions, such as Diffie–Hellmann key exchange, discrete logarithm-based cryptosystems, the RSA cryptosystem, and digital signatures;

fundamental mathematical tools for cryptography, including primality testing, factorization algorithms, probability theory, information theory, and collision algorithms;

an in-depth treatment of important cryptographic innovations, such as elliptic curves, elliptic curve and pairing-based cryptography, lattices, lattice-based cryptography, and the NTRU cryptosystem.

The second edition of An Introduction to Mathematical Cryptography includes a significant revision of the material on digital signatures, including an earlier introduction to RSA, Elgamal, and DSA signatures, and new material on lattice-based signatures and rejection sampling. Many sections have been rewritten or expanded for clarity, especially in the chapters on information theory, elliptic curves, and lattices, and the chapter of additional topics has been expanded to include sections on digital cash and homomorphic encryption. Numerous new exercises have been included.

This self-contained introduction to modern cryptography emphasizes the mathematics behind the theory of public key cryptosystems and digital signature schemes. The book focuses on these key topics while developing the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Only basic linear algebra is required of the reader; techniques from algebra, number theory, and probability are introduced and developed as required. This text provides an ideal introduction for mathematics and computer science students to the mathematical foundations of modern cryptography. The book includes an extensive bibliography and index; supplementary materials are available online.The book covers a variety of topics that are considered central to mathematical cryptography. Key topics include:

classical cryptographic constructions, such as Diffie–Hellmann key exchange, discrete logarithm-based cryptosystems, the RSA cryptosystem, and digital signatures;

fundamental mathematical tools for cryptography, including primality testing, factorization algorithms, probability theory, information theory, and collision algorithms;

an in-depth treatment of important cryptographic innovations, such as elliptic curves, elliptic curve and pairing-based cryptography, lattices, lattice-based cryptography, and the NTRU cryptosystem.

The second edition of An Introduction to Mathematical Cryptography includes a significant revision of the material on digital signatures, including an earlier introduction to RSA, Elgamal, and DSA signatures, and new material on lattice-based signatures and rejection sampling. Many sections have been rewritten or expanded for clarity, especially in the chapters on information theory, elliptic curves, and lattices, and the chapter of additional topics has been expanded to include sections on digital cash and homomorphic encryption. Numerous new exercises have been included.

<p>New edition extensively revised and updated</p><p>Includes new material on lattice-based signatures, rejection sampling, digital cash, and homomorphic encryption</p><p>Presents a detailed introduction to elliptic curves and how they're used in cryptography, including the "hot" topic of elliptic curve pairing-based cryptography</p><p>May be used in a classroom setting or independent study, and as a standard reference for researchers in the field</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Dr. Jeffrey Hoffstein has been a professor at Brown University since 1989 and has been a visiting professor and tenured professor at several other universities since 1978. His research areas are number theory, automorphic forms and cryptography. He has authored more than 50 publications.Dr. Jill Pipher has been a professor at Brown University since 1989. She has been an invited lecturer and has received numerous awards and honors. Her research areas are harmonic analysis, elliptic PDE, and cryptography. She has authored over 40 publications.Dr. Joseph Silverman has been a professor at Brown University since 1988. He served as the Chair of the Brown Mathematics department from 2001–2004. He has received numerous fellowships, grants and awards and is a frequently invited lecturer. His research areas are number theory, arithmetic geometry, elliptic curves, dynamical systems and cryptography. He has authored more than 130 publications and has had more than 20 doctoral students.

9781493917105

157531_2_En

The Basics.- Matching Covering and Packing.- Connectivity.- Planar Graphs.- Colouring.- Flows.- Extremal Graph Theory.- Infinite Graphs.- Ramsey Theory for Graphs.- Hamilton Cycles.- Random Graphs.- Graph Minors.

This standard textbook of modern graph theory, now in its fifth edition, combines the authority of a classic with the engaging freshness of style that is the hallmark of active mathematics. It covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail.The book can be used as a reliable text for an introductory course, as a graduate text, and for self-study.From the reviews: “This outstanding book cannot be substituted with any other book on the present textbook market. It has every chance of becoming the standard textbook for graph theory.”Acta Scientiarum Mathematiciarum“Deep, clear, wonderful. This is a serious book about the heart of graph theory. It has depth and integrity. ”Persi Diaconis & Ron Graham, SIAM Review“The book has received a very enthusiastic reception, which it amply deserves. A masterly elucidation of modern graph theory.” Bulletin of the Institute of Combinatorics and its Applications“Succeeds dramatically ... a hell of a good ook.” MAA Reviews“A highlight of the book is what is by far the best account in print of the Seymour-Robertson theory of graph minors.” Mathematika“ ... like listening to someone explain mathematics.” Bulletin of the AMS

This standard textbook of modern graph theory, now in its fifth edition, combines the authority of a classic with the engaging freshness of style that is the hallmark of active mathematics. It covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail.

The book can be used as a reliable text for an introductory course, as a graduate text, and for self-study.

From the reviews: “This outstanding book cannot be substituted with any other book on the present textbook market. It has every chance of becoming the standard textbook for graph theory.” Acta Scientiarum Mathematiciarum “Deep, clear, wonderful. This is a serious book about the heart of graph theory. It has
depth and integrity.” Persi Diaconis & Ron Graham, SIAM Review “The book has received a very enthusiastic reception, which it amply deserves. A masterly elucidation of modern graph theory.”
Bulletin of the Institute of Combinatorics and its Applications “Succeeds dramatically ... a hell of a good book.” MAA Reviews “A highlight of the book is what is by far the best account in print of the Seymour-Robertson theory of graph minors.” Mathematika

“ ... like listening to someone explain mathematics.” Bulletin of the AMS

<p>Standard textbook of modern graph theory</p><p>Covers all the basic material in full detail</p><p>Introduces and illustrates the more advanced methods of that field</p>

<div>Reinhard Diestel is Professor at the Department of Mathematics at the University of Hamburg.</div>

9783662536216

978-1-4614-7115-8

1 The Experimental Origins of Quantum Mechanics.- 2 A First Approach to Classical Mechanics.- 3 A First Approach to Quantum Mechanics.- 4 The Free Schrödinger Equation.- 5 A Particle in a Square Well.- 6 Perspectives on the Spectral Theorem.- 7 The Spectral Theorem for Bounded Self-Adjoint Operators: Statements.- 8 The Spectral Theorem for Bounded Sef-Adjoint Operators: Proofs.- 9 Unbounded Self-Adjoint Operators.- 10 The Spectral Theorem for Unbounded Self-Adjoint Operators.- 11 The Harmonic Oscillator.- 12 The Uncertainty Principle.- 13 Quantization Schemes for Euclidean Space.- 14 The Stone–von Neumann Theorem.- 15 The WKB Approximation.- 16 Lie Groups, Lie Algebras, and Representations.- 17 Angular Momentum and Spin.- 18 Radial Potentials and the Hydrogen Atom.- 19 Systems and Subsystems, Multiple Particles.- V Advanced Topics in Classical and Quantum Mechanics.- 20 The Path-Integral Formulation of Quantum Mechanics.- 21 Hamiltonian Mechanics on Manifolds.- 22 Geometric Quantization on Euclidean Space.- 23 Geometric Quantization on Manifolds.- A Review of Basic Material.- References.​- Index.

Although ideas from quantum physics play an important role in many parts of modern mathematics, there are few books about quantum mechanics aimed at mathematicians. This book introduces the main ideas of quantum mechanics in language familiar to mathematicians. Readers with little prior exposure to physics will enjoy the book's conversational tone as they delve into such topics as the Hilbert space approach to quantum theory; the Schrödinger equation in one space dimension; the Spectral Theorem for bounded and unbounded self-adjoint operators; the Stone–von Neumann Theorem; the Wentzel–Kramers–Brillouin approximation; the role of Lie groups and Lie algebras in quantum mechanics; and the path-integral approach to quantum mechanics.The numerous exercises at the end of each chapter make the book suitable for both graduate courses and independent study. Most of the text is accessible to graduate students in mathematics who have had a first course in real analysis, covering the basics of L2 spaces and Hilbert spaces.  The final chapters introduce readers who are familiar with the theory of manifolds to more advanced topics, including geometric quantization.

Although ideas from quantum physics play an important role in many parts of modern mathematics, there are few books about quantum mechanics aimed at mathematicians. This book introduces the main ideas of quantum mechanics in language familiar to mathematicians. Readers with little prior exposure to physics will enjoy the book's conversational tone as they delve into such topics as the Hilbert space approach to quantum theory; the Schrödinger equation in one space dimension; the Spectral Theorem for bounded and unbounded self-adjoint operators; the Stone–von Neumann Theorem; the Wentzel–Kramers–Brillouin approximation; the role of Lie groups and Lie algebras in quantum mechanics; and the path-integral approach to quantum mechanics.The numerous exercises at the end of each chapter make the book suitable for both graduate courses and independent study. Most of the text is accessible to graduate students in mathematics who have had a first course in real analysis, covering the basics of L2 spaces and Hilbert spaces.  The final chapters introduce readers who are familiar with the theory of manifolds to more advanced topics, including geometric quantization.

<p>Explains physical ideas in the language of mathematics</p><p>Provides a self-contained treatment of the necessary mathematics, including spectral theory and Lie theory</p><p>Contains many exercises that will appeal to graduate students</p>

Brian C. Hall is a Professor of Mathematics at the University of Notre Dame.

9781461471158

272900_1_En

978-3-030-61870-4

,978-1-4419-2949-5,978-0-387-95313-7,978-1-4757-4016-5,978-1-4757-4015-8

Introduction and Reading Guide.- I.Measure Theoretic Prerequisites: 1.Sets and functions, measures and integration.- 2.Measure extension and decomposition.- 3.Kernels, disintegration, and invariance.- II.Some Classical Probability Theory: 4.Processes, distributions, and independence.- 5.Random sequences, series, and averages.- 6.Gaussian and Poisson convergence.- 7.Infinite divisibility and general null-arrays.- III.Conditioning and Martingales: 8.Conditioning and disintegration.- 9.Optional times and martingales.- 10.Predictability and compensation.- IV.Markovian and Related Structures:11.Markov properties and discrete-time chains.- 12.Random walks and renewal processes.- 13.Jump-type chains and branching processes.- V.Some Fundamental Processes: 14.Gaussian processes and Brownian motion.- 15.Poisson and related processes.- 16.Independent-increment and Lévy processes.- 17.Feller processes and semi-groups.- VI.Stochastic Calculus and Applications: 18.Itô integration and quadratic variation.- 19.Continuous martingales and Brownian motion.- 20.Semi-martingales and stochastic integration.- 21.Malliavin calculus.- VII.Convergence and Approximation: 22.Skorohod embedding and functional convergence.- 23.Convergence in distribution.- 24.Large deviations.- VIII.Stationarity, Symmetry and Invariance: 25.Stationary processes and ergodic theorems.- 26.Ergodic properties of Markov processes.- 27.Symmetric distributions and predictable maps.- 28.Multi-variate arrays and symmetries.- IX.Random Sets and Measures: 29.Local time, excursions, and additive functionals.- 30.Random mesures, smoothing and scattering.- 31.Palm and Gibbs kernels, local approximation.- X.SDEs, Diffusions, and Potential Theory: 32.Stochastic equations and martingale problems.- 33.One-dimensional SDEs and diffusions.- 34.PDE connections and potential theory.- 35.Stochastic differential geometry.- Appendices.- 1.Measurable maps.- 2.General topology.- 3.Linear spaces.- 4.Linear operators.- 5.Function and measure spaces.- 6.Classes and spaces of sets,- 7.Differential geometry.- Notes and References.- Bibliography.- Indices: Authors.- Topics.- Symbols.

This new, thoroughly revised and expanded 3rd edition of a classic gives a comprehensive coverage of modern probability in a single book. It is a truly modern text, providing not only classical results but also material that will be important for future research. Much has been added to the previous edition, including eight entirely new chapters on subjects like random measures, Malliavin calculus, multivariate arrays, and stochastic differential geometry. Apart from important improvements and revisions, some of the earlier chapters have been entirely rewritten. To help the reader, the material has been grouped together into ten major areas, each arguably indispensable to any serious graduate student and researcher, regardless of their specialization.

Each chapter is largely self-contained and includes plenty of exercises, making the book ideal for self-study and for designing graduate-level courses and seminars in different areas and at different levels. Extensive notes and a detailed bibliography make it easy to go beyond the presented material if desired. From the reviews of the first edition: “…readers are likely to regard the book as an ideal reference. Indeed the monograph has the potential to become a (possibly even “the”) major reference book on large parts of probability theory for the next decade or more.” M. Scheutzow, zbMATH “…great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers … are in very capable hands.” F. B. Knight, Mathemtical Reviews “… this is precisely what Professor Kallenberg has attempted … and he has accomplished it brilliantly... It is astonishing that a single volume of just over five hundred pages could contain so much material presented with complete rigor and still be at least formally self-contained...' R.K. Getoor, MetrikaFrom the reviews of the second edition: “This … edition presents … more material in the concise and elegant style of the former edition which by now has become a highly praised standard reference book for many areas of probability theory.” M. Reiß, zbMATH “… the … monograph is a modern classic in probability theory… …every … expert in one of the various topics covered by this monograph will reconsider his own point of view and gain deeper insight into his subject.” Klaus D. Schmidt, Mathematical Reviews

This new, thoroughly revised and expanded 3rd edition of a classic gives a comprehensive coverage of modern probability in a single book. It is a truly modern text, providing not only classical results but also material that will be important for future research. Much has been added to the previous edition, including eight entirely new chapters on subjects like random measures, Malliavin calculus, multivariate arrays, and stochastic differential geometry. Apart from important improvements and revisions, some of the earlier chapters have been entirely rewritten. To help the reader, the material has been grouped together into ten major areas, each arguably indispensable to any serious graduate student and researcher, regardless of their specialization. Each chapter is largely self-contained and includes plenty of exercises, making the book ideal for self-study and for designing graduate-level courses and seminars in different areas and at different levels. Extensive notes and a detailed bibliography make it easy to go beyond the presented material if desired.From the reviews of the first edition: “…readers are likely to regard the book as an ideal reference. Indeed the monograph has the potential to become a (possibly even “the”) major reference book on large parts of probability theory for the next decade or more.” M. Scheutzow, zbMATH “…great edifice of material, clearly and ingeniously presented, without any non-mathematical distractions. Readers … are in very capable hands.” F. B. Knight, Mathemtical Reviews“… this is precisely what Professor Kallenberg has attempted … and he has accomplished it brilliantly... It is astonishing that a single volume of just over five hundred pages could contain so much material presented with complete rigor and still be at least formally self-contained...' R.K. Getoor, MetrikaFrom the reviews of the second edition: “This … edition presents … more material in the concise and elegant style of the former edition which by now has become a highly praised standard reference book for many areas of probability theory.” M. Reiß, zbMATH“…the … monograph is a modern classic in probability theory… …every … expert in one of the various topics covered by this monograph will reconsider his own point of view and gain deeper insight into his subject.” Klaus D. Schmidt, Mathematical Reviews

<p>Due to its size, and for the convenience of the reader, the print version of this book come in two separate volumes</p><p>Presents a unified treatment of probability theory in a thoroughly revised and substantially extended 3rd edition of this classic text</p><p>Invites the reader to go beyond the presented material via its extensive notes and detailed bibliography</p><p>Includes supplementary material: sn.pub/extras</p>

Olav Kallenberg (Ph.D., Chalmers University, Gothenburg, Sweden, 1972) is an Emeritus Professor at Auburn University. He has held research positions in Sweden and abroad and taught in the US for more than 30 years. In 1977 he was awarded the Rollo Davidson Prize by Cambridge University, in 1989 he was elected a Fellow of the IMS, and in 1991–94 he served as the editor of PTRF. He has given plenary talks at major conferences all over the world, and was the opening lecturer at both the Vilnius Conference in 2006 and at the SPA Conference in Gothenburg in 2018. Apart from his numerous research papers, he is known for his Springer books Probabilistic Symmetries and Invariance Principles (2005) and Random Measures, Theory and Applications (2017). His book Foundations of Modern Probability (1997, 2002, and 2021) has become a classic reference work.

9783030618704

978-1-4419-7939-1

,978-0-387-95026-6,978-0-387-98759-0,978-1-4757-7431-3,978-0-387-22727-6

Preface.- 1 Introduction.- 2 Topological Spaces.- 3 New Spaces from Old.- 4 Connectedness and Compactness.- 5 Cell Complexes.- 6 Compact Surfaces.- 7 Homotopy and the Fundamental Group.- 8 The Circle.- 9 Some Group Theory.- 10 The Seifert-Van Kampen Theorem.- 11 Covering Maps.- 12 Group Actions and Covering Maps.- 13 Homology.- Appendix A: Review of Set Theory.- Appendix B: Review of Metric Spaces.- Appendix C: Review of Group Theory.- References.- Notation Index.- Subject Index.

This book is an introduction to manifolds at the beginning graduate level. It contains the essential topological ideas that are needed for the further study of manifolds, particularly in the context of differential geometry, algebraic topology, and related fields. Its guiding philosophy is to develop these ideas rigorously but economically, with minimal prerequisites and plenty of geometric intuition.Although this second edition has the same basic structure as the first edition, it has been extensively revised and clarified; not a single page has been left untouched. The major changes include a new introduction to CW complexes (replacing most of the material on simplicial complexes in Chapter 5); expanded treatments of manifolds with boundary, local compactness, group actions, and proper maps; and a new section on paracompactness.This text is designed to be used for an introductory graduate course on the geometry and topology of manifolds. It should be accessible to any student who has completed a solid undergraduate degree in mathematics. The author’s book Introduction to Smooth Manifolds is meant to act as a sequel to this book.

This book is an introduction to manifolds at the beginning graduate level. It contains the essential topological ideas that are needed for the further study of manifolds, particularly in the context of differential geometry, algebraic topology, and related fields. Its guiding philosophy is to develop these ideas rigorously but economically, with minimal prerequisites and plenty of geometric intuition.Although this second edition has the same basic structure as the first edition, it has been extensively revised and clarified; not a single page has been left untouched. The major changes include a new introduction to CW complexes (replacing most of the material on simplicial complexes in Chapter 5); expanded treatments of manifolds with boundary, local compactness, group actions, and proper maps; and a new section on paracompactness.This text is designed to be used for an introductory graduate course on the geometry and topology of manifolds. It should be accessible to any student who has completed a solid undergraduate degree in mathematics. The author’s book Introduction to Smooth Manifolds is meant to act as a sequel to this book.

<p>New edition extensively revised and updated</p><p>New introduction to CW complexes (along with a brief and streamlined introduction to simplicial complexes)</p><p>Expanded treatments of manifolds with boundary, local compactness, group actions, proper maps, and a new section on paracompactness</p>

John M. Lee is a professor of mathematics at the University of Washington. His previous Springer textbooks in the Graduate Texts in Mathematics series include the first edition of Introduction to Topological Manifolds, Introduction to Smooth Manifolds, and Riemannian Manifolds: An Introduction.

9781441979391

10.1007/978-1-4419-7940-7

978-0-387-96890-2

,978-1-4757-1695-5,978-1-4757-1694-8,978-0-387-90314-9,978-1-4757-1693-1

I Newtonian Mechanics.- 1 Experimental facts.- 2 Investigation of the equations of motion.- II Lagrangian Mechanics.- 3 Variational principles.- 4 Lagrangian mechanics on manifolds.- 5 Oscillations.- 6 Rigid bodies.- III Hamiltonian Mechanics.- 7 Differential forms.- 8 Symplectic manifolds.- 9 Canonical formalism.- 10 Introduction to perturbation theory.- Appendix 1 Riemannian curvature.- Appendix 2 Geodesics of left-invariant metrics on Lie groups and the hydrodynamics of ideal fluids.- Appendix 3 Symplectic structures on algebraic manifolds.- Appendix 4 Contact structures.- Appendix 5 Dynamical systems with symmetries.- Appendix 6 Normal forms of quadratic hamiltonians.- Appendix 7 Normal forms of hamiltonian systems near stationary points and closed trajectories.- Appendix 8 Theory of perturbations of conditionally periodic motion, and Kolmogorov’s theorem.- Appendix 9 Poincaré’s geometric theorem, its generalizations and applications.- Appendix 10 Multiplicities of characteristic frequencies, and ellipsoids depending on parameters.- Appendix 11 Short wave asymptotics.- Appendix 12 Lagrangian singularities.- Appendix 13 The Korteweg-de Vries equation.- Appendix 14 Poisson structures.- Appendix 15 On elliptic coordinates.- Appendix 16 Singularities of ray systems.

In this text, the author constructs the mathematical apparatus of classical mechanics from the beginning, examining all the basic problems in dynamics, including the theory of oscillations, the theory of rigid body motion, and the Hamiltonian formalism. This modern approch, based on the theory of the geometry of manifolds, distinguishes iteself from the traditional approach of standard textbooks. Geometrical considerations are emphasized throughout and include phase spaces and flows, vector fields, and Lie groups. The work includes a detailed discussion of qualitative methods of the theory of dynamical systems and of asymptotic methods like perturbation techniques, averaging, and adiabatic invariance.

9780387968902

978-0-387-96412-6

Serge Lang, Yale University Dept. Mathematics, New Haven, CT, USA

I Vector Spaces.- II Matrices.- III Linear Mappings.- IV Linear Maps and Matrices.- V Scalar Products and Orthogonality.- VI Determinants.- VII Symmetric, Hermitian, and Unitary Operators.- VIII Eigenvectors and Eigenvalues.- IX Polynomials and Matrices.- X Triangulation of Matrices and Linear Maps.- XI Polynomials and Primary Decomposition.- XII Convex Sets.- Appendix I Complex Numbers.- Appendix II Iwasawa Decomposition and Others.

Linear Algebra is intended for a one-term course at the junior or senior level. It begins with an exposition of the basic theory of vector spaces and proceeds to explain the fundamental structure theorems for linear maps, including eigenvectors and eigenvalues, quadric and hermitian forms, diagonalization of symmetric, hermitian, and unitary linear maps and matrices, triangulation, and Jordan canonical form. The book also includes a useful chapter on convex sets and the finite-dimensional Krein-Milman theorem. The presentation is aimed at the student who has already had some exposure to the elementary theory of matrices, determinants, and linear maps. However, the book is logically self-contained. In this new edition, many parts of the book have been rewritten and reorganized, and new exercises have been added.

9780387964126

10.1007/978-1-4757-1949-9

978-3-662-53044-3

Hannu Karttunen; Pekka Kröger; Heikki Oja; Markku Poutanen; Karl Johan Donner

Hannu Karttunen, University of Turku Tuorla Observatory, Piikkiö, Finland; Pekka Kröger, Helsinki, Finland; Heikki Oja, University of Helsinki Observatory and, Helsinki, Finland; Markku Poutanen, Finnish Geodetic Institute Dept. Geodesy & Geodynamics, Masala, Finland; Karl Johan Donner, Finnish Geodetic Institute, Helsinki, Finland

,978-3-540-82383-4,978-3-540-34143-7,978-3-642-42110-5,978-3-540-34144-4

1. Introduction.- 2. Spherical Astronomy.- 3. Observations and Instruments.- 4. Photometric Concepts and Magnitudes.- 5. Radiation Mechanisms.- 6. Celestial Mechanics.- 7. The Solar System Part I.- 8. The Solar System Part II.- 9. Stellar Spectra.- 10. Binary Stars and Stellar Masses.- 11. <Stellar Structure.- 12. Stellar Evolution.- 13. The Sun.- 14. Variable Stars.- 15. Compact Stars.- 16. The Interstellar Medium.- 17. Star Clusters and Associations.- 18. The MilkyWay.- 19. Galaxies.- 20. Cosmology.- 21. Exoplanets.- 22. Astrobiology.-

Now in its sixth edition this successful undergraduate textbook gives a well-balanced and comprehensive introduction to the topics of classical and modern astronomy. While emphasizing both the astronomical concepts and the underlying physical principles, the text provides a sound basis for more profound studies in the astronomical sciences. The chapters on galactic and extragalactic astronomy as well as cosmology were extensively modernized in the previous edition. In this new edition they have been further revised to include more recent results. The long chapter on the solar system has been split into two parts: the first one deals with the general properties, and the other one describes individual objects. A new chapter on exoplanets has been added to the end of the book next to the chapter on astrobiology.In response to the fact that astronomy has evolved enormously over the last few years, only a few chapters of this book have been left unmodified.Long considered a standard text for physical science majors, Fundamental Astronomy is also an excellent reference and entrée for dedicated amateur astronomers. For their benefit the introductory chapter has been extended to give a brief summary of the different types of celestial objects.From reviews of earlier editions:
'… The wide range of expertise gives the book an authority that would be almost impossible for a single-author text ... There are other aids to the reader: worked examples ... starred sections in small print take the inquisitive reader beyond the general level of the book.' (Nature)
“This textbook, suitable for a university first course in astronomy, is the outgrowth of a long and outstanding astronomical tradition in Finland, and the result of an extensive collaborative effort, which included also teaching and interaction with many people. … I highly recommend this book for class use … it will be useful for professionals as well.” (Bruno Bertotti, Prometeo, Vol. 24 (3-4), 2008)

Now in its sixth edition, this successful undergraduate textbook gives a well-balanced and comprehensive introduction to the topics of classical and modern astronomy. While emphasizing both the astronomical concepts and the underlying physical principles, the text provides a sound basis for more profound studies in the astronomical sciences.
The chapters on galactic and extragalactic astronomy as well as cosmology were extensively modernized in the previous edition. In this new edition they have been further revised to include more recent results. The long chapter on the solar system has been split into two parts: the first one deals with the general properties, and the other one describes individual objects. A new chapter on exoplanets has been added to the end of the book next to the chapter on astrobiology.In response to the fact that astronomy has evolved enormously over the last few years, only a few chapters of this book have been left unmodified.Long considered a standard text for physical science majors, Fundamental Astronomy is also an excellent reference and entrée for dedicated amateur astronomers. For their benefit the introductory chapter has been extended to give a brief summary of the different types of celestial objects

<p>The established, widely-adopted textbook for physical science majors as well as serious amateurs that gives a comprehensive, calculus-based introduction to the topics of classical and modern astronomy and astrophysics</p><p>Richly illustrated with more than 400 images, including 36 color plates, that take you on a visual tour of the cosmos</p><p>The sixth edition has further updated on extragalactic astronomy, cosmology and now includes a separate chapter on extra-solar planets</p><p>Provides a sound basis for more profound studies in the astronomical sciences through its comprehensive approach</p>

Hannu Karttunen is a Finnish astronomer and science writer. He is an associate professor at Turku University and works at Tuorla Observatory. Besides astronomical articles Dr. Karttunen has published astronomy textbooks and teaching material as well as articles for anthologies and encyclopedias. Karttunen has also produced a radio lecture series on astronomy. Hannu Karttunen received the 1998 Tieto-Finlandia Award for his book Oldest science: Astronomy Stone Age to the mission to the moon, and, in2007, the Finnish News Writers Association Tietopöllö Award for his writings and books for children and young people. Heikki Oja is a Finnish astronomer and associate professor at the University of Helsinki, as well as the former director of the Almanac Office. Dr. Oja has written dozens of non-technical non-fiction books and appeared frequently on the radio to talk about astronomy and space research. He has received several awards for his outreach activities.

9783662530443

Preface.- Chapter 1. Curvature and Vector Fields.- 1. Riemannian Manifolds.- 2. Curves.- 3. Surfaces in Space.- 4. Directional Derivative in Euclidean Space.- 5. The Shape Operator.- 6. Affine Connections.- 7. Vector Bundles.- 8. Gauss's Theorema Egregium.- 9. Generalizations to Hypersurfaces in Rn+1.- Chapter 2. Curvature and Differential Forms.- 10. Connections on a Vector Bundle.- 11. Connection, Curvature, and Torsion Forms.- 12. The Theorema Egregium Using Forms.- Chapter 3. Geodesics.- 13. More on Affine Connections.- 14. Geodesics.- 15. Exponential Maps.- 16. Distance and Volume.- 17. The Gauss-Bonnet Theorem.- Chapter 4. Tools from Algebra and Topology.- 18. The Tensor Product and the Dual Module.- 19. The Exterior Power.- 20. Operations on Vector Bundles.- 21. Vector-Valued Forms.- Chapter 5. Vector Bundles and Characteristic Classes.- 22. Connections and Curvature Again.- 23. Characteristic Classes.- 24. Pontrjagin Classes.- 25. The Euler Class and Chern Classes.- 26. Some Applications of Characteristic Classes.- Chapter 6. Principal Bundles and Characteristic Classes.- 27. Principal Bundles.- 28. Connections on a Principal Bundle.- 29. Horizontal Distributions on a Frame Bundle.- 30. Curvature on a Principal Bundle.- 31. Covariant Derivative on a Principal Bundle.- 32. Character Classes of Principal Bundles.- A. Manifolds.- B. Invariant Polynomials.- Hints and Solutions to Selected End-of-Section Problems.- List of Notations.- References.- Index.

This text presents a graduate-level introduction to differential geometry for mathematics and physics students. The exposition follows the historical development of the concepts of connection and curvature with the goal of explaining the Chern–Weil theory of characteristic classes on a principal bundle. Along the way we encounter some of the high points in the history of differential geometry, for example, Gauss' Theorema Egregium and the Gauss–Bonnet theorem. Exercises throughout the book test the reader’s understanding of the material and sometimes illustrate extensions of the theory. Initially, the prerequisites for the reader include a passing familiarity with manifolds. After the first chapter, it becomes necessary to understand and manipulate differential forms. A knowledge of de Rham cohomology is required for the last third of the text.

Prerequisite material is contained in author's text An Introduction to Manifolds, and can be learned in one semester. For the benefit of the reader and to establish common notations, Appendix A recalls the basics of manifold theory. Additionally, in an attempt to make the exposition more self-contained, sections on algebraic constructions such as the tensor product and the exterior power are included.Differential geometry, as its name implies, is the study of geometry using differential calculus. It dates back to Newton and Leibniz in the seventeenth century, but it was not until the nineteenth century, with the work of Gauss on surfaces and Riemann on the curvature tensor, that differential geometry flourished and its modern foundation was laid. Over the past one hundred years, differential geometry has proven indispensable to an understanding of the physical world, in Einstein's general theory of relativity, in the theory of gravitation, in gauge theory, and now in string theory. Differential geometry is also useful in topology, several complex variables, algebraic geometry, complex manifolds, and dynamical systems, among other fields. The field has even found applications to group theory as in Gromov's work and to probability theory as in Diaconis's work. It is not too far-fetched to argue that differential geometry should be in every mathematician's arsenal.

This text presents a graduate-level introduction to differential geometry for mathematics and physics students. The exposition follows the historical development of the concepts of connection and curvature with the goal of explaining the Chern–Weil theory of characteristic classes on a principal bundle. Along the way we encounter some of the high points in the history of differential geometry, for example, Gauss' Theorema Egregium and the Gauss–Bonnet theorem. Exercises throughout the book test the reader’s understanding of the material and sometimes illustrate extensions of the theory. Initially, the prerequisites for the reader include a passing familiarity with manifolds. After the first chapter, it becomes necessary to understand and manipulate differential forms. A knowledge of de Rham cohomology is required for the last third of the text.Prerequisite material is contained in author's text An Introduction to Manifolds, and can be learned in one semester. For the benefit of the reader and to establish common notations, Appendix A recalls the basics of manifold theory. Additionally, in an attempt to make the exposition more self-contained, sections on algebraic constructions such as the tensor product and the exterior power are included.Differential geometry, as its name implies, is the study of geometry using differential calculus. It dates back to Newton and Leibniz in the seventeenth century, but it was not until the nineteenth century, with the work of Gauss on surfaces and Riemann on the curvature tensor, that differential geometry flourished and its modern foundation was laid. Over the past one hundred years, differential geometry has proven indispensable to an understanding of the physical world, in Einstein's general theory of relativity, in the theory of gravitation, in gauge theory, and now in string theory. Differential geometry is also useful in topology, several complex variables, algebraic geometry, complex manifolds, and dynamical systems, among other fields. The field has even found applications to group theory as in Gromov's work and to probability theory as in Diaconis's work. It is not too far-fetched to argue that differential geometry should be in every mathematician's arsenal.

<p>Narrative provides a panorma of some of the high points in the history of differential geometry</p><p>Problems are presented in each chapter with selected solutions and hints given at the end of the book</p><p>Accessible to graduate students of mathematics and physics</p>

<div>Loring W. Tu was born in Taipei, Taiwan, and grew up in Taiwan, Canada, and the United States. He attended McGill and Princeton as an undergraduate, and obtained his Ph.D. from Harvard University under the supervision of Phillip A. Griffiths. He has taught at the University of Michigan, Ann Arbor, and at Johns Hopkins University, and is currently Professor of Mathematics at Tufts University. An algebraic geometer by training, he has done research at the interface of algebraic geometry, topology, and differential geometry, including Hodge theory, degeneracy loci, moduli spaces of vector bundles, and equivariant cohomology. He is the coauthor with Raoul Bott of Differential Forms in Algebraic Topology and the author of An Introduction to Manifolds.</div>

9783319550824

331905_1_En

978-3-540-04758-2

Some Mathematical Preliminaries.- Itô Integrals.- The Itô Formula and the Martingale Representation Theorem.- Stochastic Differential Equations.- The Filtering Problem.- Diffusions: Basic Properties.- Other Topics in Diffusion Theory.- Applications to Boundary Value Problems.- Application to Optimal Stopping.- Application to Stochastic Control.- Application to Mathematical Finance.

<p>This well-established textbook on stochastic differential equations has turned out to be very useful to non-specialists of the subject and has sold steadily in 5 editions, both in the EU and US market</p><p>Includes supplementary material: sn.pub/extras</p>

9783540047582

10.1007/978-3-642-14394-6

Eklas Hossain, Oregon Institute of Technology, Klamath Falls, OR, USA

Introduction to MATLAB.- Vectors and Matrices.- Programs and Functions.- Complex Numbers.- Visualization.- Solving Equations.- Numerical Methods in MATLAB.- Electrical Circuit Analysis.- Control System and MATLAB.- Optimization Problem.- App Designer and Graphical User Interface in MATLAB.- Introduction to Simulink.- Control System in Simulink.- Commonly Used Simulink Blocks.- Electrical Circuit Analysis in Simulink.- Application of Simulink in Power Systems.- Application of Simulink in Power Electronics.- Application of Simulink in Renewable Energy Technology.

​MATLAB and Simulink Crash Course for Engineers is a reader-friendly introductory guide to the features, functions, and applications of MATLAB and Simulink. The book provides readers with real-world examples, exercises, and applications, and offers highly illustrated, step-by-step demonstrations of techniques for the modelling and simulation of complex systems. MATLAB coverage includes vectors and matrices, programs and functions, complex numbers, visualization, solving equations, numerical methods, optimization problems, and graphical user interfaces. The Simulink coverage includes commonly used Simulink blocks, control system simulation, electrical circuit analysis, electric power systems, power electronics, and renewable energy technology. This powerful tutorial is a great resource for students, engineers, and other busy technical professionals who need to quickly acquire a solid understanding of MATLAB and Simulink.

MATLAB and Simulink Crash Course for Engineers is a reader-friendly introductory guide to the features, functions, and applications of MATLAB and Simulink. The book provides readers with real-world examples, exercises, and applications, and offers highly illustrated, step-by-step demonstrations of techniques for the modelling and simulation of complex systems. MATLAB coverage includes vectors and matrices, programs and functions, complex numbers, visualization, solving equations, numerical methods, optimization problems, and graphical user interfaces. The Simulink coverage includes commonly used Simulink blocks, control system simulation, electrical circuit analysis, electric power systems, power electronics, and renewable energy technology. This powerful tutorial is a great resource for students, engineers, and other busy technical professionals who need to quickly acquire a solid understanding of MATLAB and Simulink.

<p>Concise guide to MATLAB and Simulink for modelling and simulating systems</p><p>Provides real-world examples, exercises, and applications</p><p>Offers highly illustrated, step-by-step guidance</p>

​Dr. Eklas Hossain is an Associate Professor in the Department of Electrical Engineering and Renewable Energy and an Associate Researcher with the Oregon Renewable Energy Center (OREC) at Oregon Institute of Technology. He has been working in the area of distributed power systems and renewable energy integration for the last ten years and has published a number of research papers and posters in this field. He is currently involved with several research projects on renewable energy and grid-tiered microgrid systems at Oregon Tech. He received his PhD from the College of Engineering and Applied Science at the University of Wisconsin Milwaukee (UWM), his MS in Mechatronics and Robotics Engineering from International Islamic University of Malaysia, and a BS in Electrical & Electronic Engineering from Khulna University of Engineering and Technology. Dr. Hossain is a registered Professional Engineer (PE) in the state of Oregon, a Certified Energy Manager (CEM) and Renewable Energy Professional (REP), a senior member of the Association of Energy Engineers (AEE), and an Associate Editor for IEEE Access, IEEE Systems Journal, and IET Renewable Power Generation. His research interests include modeling, analysis, design, and control of power electronic devices; energy storage systems; renewable energy sources; integration of distributed generation systems; microgrid and smart grid applications; robotics, and advanced control system. He has authored the book Excel Crash Course for Engineers (Springer, 2021), co-authored the book Renewable Energy Crash Course: A Concise Introduction (Springer, 2021), and is working on several other book projects. He received the Rising Faculty Scholar Award in 2019 and the Faculty Achievement Award in 2020 from Oregon Tech for his outstanding contribution to academia. Dr. Hossain, with his dedicated research team, is looking forward to exploring methods to make the electric power systems more sustainable, cost-effective and secure through extensive research and analysis on energy storage, microgrid system and renewable energy sources.

9783030897611

514066_1_En

10.1007/978-3-030-89762-8

978-3-030-43787-9

A Collection of Sneaky Tricks, Sly Substitutions, and Numerous Other Stupendously Clever, Awesomely Wicked, and Devilishly Seductive Maneuvers for Computing Hundreds of Perplexing Definite Integrals From Physics, Engineering, and Mathematics (Plus Numerous Challenge Problems with Complete, Detailed Solutions)

From the Contents: Preface.- Introduction.- ‘Easy’ Integrals.- Feynman’s Favorite Trick.- Gamma and Beta Function Integrals.- Using Power Series to Evaluate Integrals.- Seven Not-So-Easy Integrals.- Using √(-1) to Evaluate Integrals.- Contour Integration.- Epilogue.- Solutions to the Challenge Problems.

What’s the point of calculating definite integrals since you can’t possibly do them all?What makes doing the specific integrals in this book of value aren’t the specific answers we’ll obtain, but rather the methods we’ll use in obtaining those answers; methods you can use for evaluating the integrals you will encounter in the future.This book, now in its second edition, is written in a light-hearted manner for students who have completed the first year of college or high school AP calculus and have just a bit of exposure to the concept of a differential equation. Every result is fully derived. If you are fascinated by definite integrals, then this is a book for you. New material in the second edition includes 25 new challenge problems and solutions, 25 new worked examples, simplified derivations, and additional historical discussion.

What’s the point of calculating definite integrals since you can’t possibly do them all?What makes doing the specific integrals in this book of value aren’t the specific answers we’ll obtain, but rather the methods we’ll use in obtaining those answers; methods you can use for evaluating the integrals you will encounter in the future.This book, now in its second edition, is written in a light-hearted manner for students who have completed the first year of college or high school AP calculus and have just a bit of exposure to the concept of a differential equation. Every result is fully derived. If you are fascinated by definite integrals, then this is a book for you. New material in the second edition includes 25 new challenge problems and solutions, 25 new worked examples, simplified derivations, and additional historical discussion.

<p>New edition with 25 added challenge problems and solutions and 25 new worked examples</p><p>A "recipe book" with many valuable little-known integration techniques</p><p>Written with an accessible and easy-to-follow style by acclaimed popular science author and engineering professor Paul Nahin</p><p>Includes rarely-taught problem solving techniques including Feynman's favorite: differentiation under the integral</p><p>Features worked-out and thoroughly explained practice problems</p>

Paul J. Nahin is professor emeritus of electrical engineering at the University of New Hampshire. He is the author of 21 books on mathematics, physics, and the history of science, published by Springer, and the university presses of Princeton and Johns Hopkins. He received the 2017 Chandler Davis Prize for Excellence in Expository Writing in Mathematics (for his paper “The Mysterious Mr. Graham,” The Mathematical Intelligencer, Spring 2016). He gave the invited 2011 Sampson Lectures in Mathematics at Bates College, Lewiston, Maine.

9783030437879

310325_2_En

10.1007/978-3-030-43788-6

978-0-387-09493-9

Joseph H. Silverman, Brown University Department of Mathematics, Providence, RI, USA

,978-1-4757-1922-2,978-0-387-96203-0,978-1-4757-1921-5,978-1-4757-1920-8

Algebraic Varieties.- Algebraic Curves.- The Geometry of Elliptic Curves.- The Formal Group of an Elliptic Curve.- Elliptic Curves over Finite Fields.- Elliptic Curves over C.- Elliptic Curves over Local Fields.- Elliptic Curves over Global Fields.- Integral Points on Elliptic Curves.- Computing the Mordell#x2013;Weil Group.- Algorithmic Aspects of Elliptic Curves.

The theory of elliptic curves is distinguished by its long history and by the diversity of the methods that have been used in its study. This book treats the arithmetic theory of elliptic curves in its modern formulation, through the use of basic algebraic number theory and algebraic geometry. The book begins with a brief discussion of the necessary algebro-geometric results, and proceeds with an exposition of the geometry of elliptic curves, the formal group of an elliptic curve, and elliptic curves over finite fields, the complex numbers, local fields, and global fields. Included are proofs of the Mordell–Weil theorem giving finite generation of the group of rational points and Siegel's theorem on finiteness of integral points.

For this second edition of The Arithmetic of Elliptic Curves, there is a new chapter entitled Algorithmic Aspects of Elliptic Curves, with an emphasis on algorithms over finite fields which have cryptographic applications. These include Lenstra's factorization algorithm, Schoof's point counting algorithm, Miller's algorithm to compute the Tate and Weil pairings, and a description of aspects of elliptic curve cryptography. There is also a new section on Szpiro's conjecture and ABC, as well as expanded and updated accounts of recent developments and numerous new exercises.

The book contains three appendices: Elliptic Curves in Characteristics 2 and 3, Group Cohomology, and a third appendix giving an overview of more advanced topics.

<p>Second Edition of highly successful introductory textbook, with new content, from acclaimed author</p><p>Thorough introduction to arithmetic theory of elliptic curves</p><p>Many exercises to hone the reader's knowledge</p><p>Text enlightens proofs through general principles, rather than line-by-line algebraic proof</p><p>Ideal for students to learn the basics of the subject and as a reference for researchers</p><p>Includes supplementary material: sn.pub/extras</p>

Dr. Joseph Silverman is a professor at Brown University and has been an instructor or professors since 1982. He was the Chair of the Brown Mathematics department from 2001-2004. He has received numerous fellowships, grants and awards, as well as being a frequently invited lecturer. He is currently a member of the Council of the American Mathematical Society. His research areas of interest are number theory, arithmetic geometry, elliptic curves, dynamical systems and cryptography. He has co-authored over 120 publications and has had over 20 doctoral students under his tutelage. He has published 9 highly successful books with Springer, including the recently released, An Introduction to Mathematical Cryptography, for Undergraduate Texts in Mathematics.

9780387094939

10.1007/978-0-387-09494-6

Jay L. Devore, California Polytechnic State University, San Luis Obispo, CA, USA; Kenneth N. Berk, Illinois State University, Normal, IL, USA; Matthew A. Carlton, California Polytechnic State University, San Luis Obispo, CA, USA

,978-1-4614-0390-6,978-1-4614-0392-0,978-1-4614-0391-3,978-1-4939-4221-3

Preface.- 1 Overview and Descriptive Statistics.- 2 Probability.- 3 Discrete Random Variables and Probability Distributions.- 4 Continuous Random Variables and Probability Distributions.- 5 Joint Probability Distributions and Their Applications.- 6 Statistics and Sampling Distributions.- 7 Point Estimation.- 8 Statistical Intervals Based on a Single Sample.- 9 Tests of Hypotheses Based on a Single Sample.- 10 Inferences Based on Two Samples.- 11 The Analysis of Variance.- 12 Regression and Correlation.- 13 Chi-Squared Tests.- 14 Chi-Squared Tests.- 15 Introduction to Bayesian Estimation.- Appendix Tables.- Index.

This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles:Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nationsVisualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettesDescribing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical staplerEstimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmetInvestigating the relationship between body mass index and foot load while runningThe main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings.This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.

This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nationsVisualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettesDescribing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical staplerEstimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmetInvestigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings.

This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.

<p>Features an extensive range of real-world and relevant applications to connect students to the concepts and theory, making the volume useful for quantitative courses in a wide variety of majors (business, mathematics, statistics, social sciences, sciences, and engineering, among others)</p><p>Includes updates on the latest methods in statistical practice, as well as the latest in statistical software packages, in this new edition</p><p>Includes sample syllabi for one- and two-term courses in mathematical statistics, which serve as guides for instructors in smoothly adjusting to a new text</p><p>Includes supplementary material: sn.pub/extras</p><p>Request lecturer material: sn.pub/lecturer-material</p>

Jay L. Devore received a B.S. in Engineering Science from the University of California, Berkeley, and a Ph.D. in Statistics from Stanford University. He previously taught at the University of Florida and Oberlin College, and has had visiting positions at Stanford, Harvard, the University of Washington, New York University, and Columbia. He has been at California Polytechnic State University, San Luis Obispo, since 1977, where he was chair of the Department of Statistics for seven years and recently achieved the exalted status of Professor Emeritus.Jay has previously authored or coauthored five other books, including Probability and Statistics for Engineering and the Sciences, which won a McGuffey Longevity Award from the Text and Academic Authors Association for demonstrated excellence over time. He is a Fellow of the American Statistical Association, has been an associate editor for both the Journal of the American Statistical Association and The American Statistician, and received the Distinguished Teaching Award from Cal Poly in 1991. His recreational interests include reading, playing tennis, traveling, and cooking and eating good food.Kenneth N. Berk has a B.S. in Physics from Carnegie Tech (now Carnegie Mellon) and a Ph.D. in Mathematics from the University of Minnesota. He is Professor Emeritus of Mathematics at Illinois State University and a Fellow of the American Statistical As­sociation. He founded the Software Reviews section of The American Statistician and edited it for six years. He served as secretary/treasurer, program chair, and chair of the Statistical Computing Section of the American Statistical Association, and he twice co-chaired the Interface Symposium, the main annual meeting in statistical computing. His published work includes papers on time series, statistical computing, regression analysis, and statistical graphics, as well as the book Data Analysis with Microsoft Excel (with Patrick Carey).Matthew A. Carlton is Professor of Statistics at California Polytechnic State University, San Luis Obispo, where he joined the faculty in 1999. He received a B.A. in Mathematics from the University of California, Berkeley and a Ph.D. in Mathematics from the University of California, Los Angeles, with an emphasis on pure and applied probability; his thesis research involved applications of the Poisson-Dirichlet random process. Matt has published papers in the Journal of Applied Probability, Human Biology, Journal of Statistics Education, and The American Statistician. He was also the lead content adviser for the “Statistically Speaking” video series, designed for community college statistics courses, and he has published a variety of educational materials for high school statistics teachers. Matt was responsible for developing both the applied probability course and the probability and random processes course at Cal Poly, which in turn inspired him to get involved in writing this text. His professional research focus involves applications of probability to genetics and engineering. Personal interests include travel, good wine, and college sports.

9783030551551

217454_3_En

Francis Chen, University of California at Los Angeles, Los Angeles, CA, USA

,978-1-4419-3201-3,978-0-306-41332-2,978-1-4757-5596-1,978-1-4757-5595-4

Introduction.- Single-particle motions.- Plasmas as fluids.- Waves in plasmas.- Diffusion and resistivity.- Equilibrium and stability.- Kinetic theory .- Nonlinear effects.- Special plasmas.- Plasma applications.

The third edition of this classic text presents a complete introduction to plasma physics and controlled fusion, written by one of the pioneering scientists in this expanding field.  It offers both a simple and intuitive discussion of the basic concepts of the subject matter and an insight into the challenging problems of current research. This outstanding text offers students a painless introduction to this important field; for teachers, a large collection of problems; and for researchers, a concise review of the fundamentals as well as original treatments of a number of topics never before explained so clearly. In a wholly lucid manner the second edition covered charged-particle motions, plasmas as fluids, kinetic theory, and nonlinear effects.  For the third edition, two new chapters have been added to incorporate discussion of more recent advances in the field.  The new chapter 9 on Special Plasmas covers non-neutral plasmas, pure electron plasmas, solid and ultra-cold plasmas, pair-ion plasmas, dusty plasmas, helicon plasmas, atmospheric-pressure plasmas, sheath-bounded plasmas, reconnection and turbulence.  Following this, chapter 10 describes Plasma Applications such as magnetic fusion (pinches, mirrors, FRCs, stellarators, tokamaks, spheromaks), plasma accelerators and FELs, inertial fusion, semiconductor etching, and spacecraft propulsion. This new revised edition remains an essential text for those new to the field and an invaluable reference source for established researchers.

This complete introduction to plasma physics and controlled fusion by one of the pioneering scientists in this expanding field offers both a simple and intuitive discussion of the basic concepts of this subject and an insight into the challenging problems of current research. In a wholly lucid manner the work covers single-particle motions, fluid equations for plasmas, wave motions, diffusion and resistivity, Landau damping, plasma instabilities and nonlinear problems. For students, this outstanding text offers a painless introduction to this important field; for teachers, a large collection of problems; and for researchers, a concise review of the fundamentals as well as original treatments of a number of topics never before explained so clearly. This revised edition contains new material on kinetic effects, including Bernstein waves and the plasma dispersion function, and on nonlinear wave equations and solitons. For the third edition, updates was made throughout each existing chapter, and two new chapters were added; Ch 9 on “Special Plasmas” and Ch 10 on Plasma Applications (including Atmospheric Plasmas).

<p>Third edition of this bestselling textbook providing a coherent and easy-to-understand introduction to plasma physics and controlled fusion</p><p>Updates all existing chapters and includes two additional chapters on Special Plasmas and Plasma Applications</p><p>Contains new and advanced problem sets in each chapter</p>

Francis F. Chen, known as Frank in the physics community, got his B.A. from Harvard Observatory in 1950. His all-star oral committee consisted of famous astronomers Harlow Shapley, Bart J. Bok, Donald Menzel, and Earl Whipple. With pulsars and quasars still undiscovered, he switched to High Energy Physics, receiving his Ph.D. from Harvard in 1954. He had been sent by his adviser, Nobelist Norman Ramsey, to Brookhaven National Laboratory, where he worked on the Cosmotron and wrote the first experimental thesis for energies at or above 1 GeV. To avoid the Korean War draft, he then went to work for the astronomer Lyman Spitzer, Jr., who had just started the classified Project Matterhorn at Princeton University. This was one of four initial projects in the U.S. to tame the hydrogen bomb to make energy peacefully from the same reaction. In 1954, Chen was one of the first 15 employees at what is now the Princeton Plasma Physics Laboratory (PPPL). Project Matterhorn started in two old buildings, one formerly a rabbit hutch, and the other a horse operating room. Chen inherited the Model B1 Stellarator, built by James van Allen of the famous van Allen radiation belts around the earth. With the B1, Chen was the first to show that electrons could be trapped by a magnetic field for millions of traverses. By then, it was clear that fusion would require trapping a plasma, a hot, ionized gas of electrons and ions, and not just electrons. Subsequent Model B stellarators, however, failed to do this for longer than milliseconds. Realizing that stellarators were magnetic bottles that were curved and not straight, he convinced Spitzer to allow him to build straight machines to isolate the problem, even though these would have leaks at the ends. Chen then built the L-1 and L-2 machines with straight magnetic fields. Experiments on these showed that the plasma was lost by turbulence, and these random motions were aligned along the magnetic field, with wavelengths longer than any plasma waves known at that time. While on sabbatical in Paris, Chen figured out what these new waves were. They are now known as resistive drift waves and were discovered simultaneously in Russia by Sagdeev and Pogutse. In L-2, Chen and Mosher showed how this turbulence could be suppressed by magnetic fields that were not totally straight but had what is called shear. Modern magnetic bottles (called tokamaks), using advanced methods of stabilization, can hold a hot plasma for minutes. In 1969, Chen went from Princeton to UCLA in California, where he organized an academic program in plasma physics. He wrote the first undergraduate textbook in this field in 1973. Soon after, however, powerful lasers were invented, opening up a whole new field of research. Chen then left magnetic fusion to help start the field of laser fusion. He built the first laser at UCLA. In basic experiments, he and his students were among the first to study Brillouin and Raman scattering, two instabilities that cause problems even in laser-produced plasmas. This interesting field led to John Dawson’s discovery of plasma accelerators, which can shrink the size of machines for high-energy particle research by a factor of 1000! Chen recruited C. Joshi, whose experimental acumen has led his group to spectacular successes. Meanwhile, Chen left the effort to join yet another nascent field: low-temperature plasma physics. This involves partially ionized gases which include neutral atoms as well as ions and electrons. This complexity had led to its reputation as dirty science. By developing helicon plasma sources, which are magnetized, Chen showed that radiofrequency gas discharges contain very interesting physics which can be treated in a logical and interesting manner. Chen’s 57-year career in plasma physics can be divided into four approximately equal parts: magnetic fusion, laser fusion and laser accelerators

9783319223087

Tim Benson, R-Outcomes Ltd, Newbury, UK; Grahame Grieve, Health Intersections Pty Ltd, Melbourne, VIC, Australia

Contents.- Foreword.- Preface.- Part 1 Principles of Health Interoperability.- The Health Information Revolution.- Why Interoperability is Hard.- Terminology, Content, Exchange.- Safety Thinking.- Part 2 FHIR.- FHIR Principles.- FHIR API.- FHIR Resources - Administrative.- FHIR Resources – Clinical Summary.- FHIR Terminology.- FHIR Implementing FHIR.- Part 3 Other Exchange Standards.- HL7 Version 2.- CDA.- IHE XDS.- Part 3 Terminology.- Clinical Terminology / Coding and Classification.- SNOMED CT+ Concept Model.- LOINC.- Terminology & Content models.- Mapping between Terminologies.- Terminology Services.- Part 4 Security & Privacy.- Security : TLS & OAuth.- Integrity: Provenance and Audit Trails.- Privacy and Consent.- Part 5 Supporting Standards.- UML, XML, JSON.- Standards Development Organizations.- The HL7 V3 Framework.- Glossary.- Bibliography.<div>
</div>

This extensively updated fourth edition expands the discussion of FHIR (Fast Health Interoperability Resources), which has rapidly become the most important health interoperability standard globally. FHIR can be implemented at a fraction of the price of existing alternatives and is well suited for use in mobile phone apps, cloud communications and electronic health records. FHIR combines the best features of HL7’s v2, v3 and CDA while leveraging the latest web standards and clinical terminologies, with a tight focus on implementation. Principles of Health Interoperability has been completely re-organised into five sections. The first part covers the core principles of health interoperability, while the second extensively reviews FHIR. The third part includes older HL7 standards that are still widely used, which leads on to a section dedicated to clinical terminology including SNOMED CT and LOINC. The final part of the book covers privacy, models, XML and JSON, standards development organizations and HL7 v3. This vital new edition therefore is essential reading for all involved in the use of these technologies in medical informatics.

This extensively updated fourth edition expands the discussion of FHIR (Fast Health Interoperability Resources), which has rapidly become the most important health interoperability standard globally. FHIR can be implemented at a fraction of the price of existing alternatives and is well suited for use in mobile phone apps, cloud communications and electronic health records. FHIR combines the best features of HL7’s v2, v3 and CDA while leveraging the latest web standards and clinical terminologies, with a tight focus on implementation.

Principles of Health Interoperability has been completely re-organised into five sections. The first part covers the core principles of health interoperability, while the second extensively reviews FHIR. The third part includes older HL7 standards that are still widely used, which leads on to a section dedicated to clinical terminology including SNOMED CT and LOINC. The final part of the book covers privacy, models, XML and JSON, standards development organizations and HL7 v3. This vital new edition therefore is essential reading for all involved in the use of these technologies in medical informatics.

<p>Updated edition containing sections on SNOMED CT, HL7 and FHIR</p><p>Authored by two of the most experienced teachers of SNOMED CT, HL7 and FHIR</p><p>Accessible to both relative novices and more experienced practitioners</p>

Tim Benson graduated from the University of Nottingham as a mechanical engineer. He founded one of the first GP computer suppliers (Abies Informatics Ltd). There, with James Read and David Markwell, he helped develop the Read Codes, which became one of the two sources of SNOMED CT. He led the first European project team on open standards for health interoperability and was a co-chair of the HL7 Education Committee for several years. He has developed a family of short generic outcome and experience measures (PROMs and PREMs) with R-Outcomes Ltd. Grahame Grieve is FHIR Product Director at HL7 and is the founder of FHIR. Grahame travels the world giving lectures, guiding connectathons and advising governments, vendors and care providers about all aspects of interoperability. He graduated from the University of Auckland as a biochemist, worked as a clinical diagnostic scientist and medical researcher before joining Kestral Computing P/L, a Laboratory and Imaging Information Systems vendor and then setting up Health Intersections Ltd. A growing involvement in integration and interoperability lead him to the HL7 community where he has led committees and edited standards for HL7 v2, v3 and CDA. The outcome of this was to recognize that something new was needed, which led to the creation of the FHIR specification.

9783030568825

147783_4_En

978-3-030-52814-0

Chapter 1: Vector Spaces.- Chapter 2: Matrix Decompositions.- Chapter 3: Tensors and Multilinearity.- Appendix A: Mathematical Preliminaries.- Appendix B: Additional Proofs.- Appendix C: Selected Exercise Solutions.

This textbook emphasizes the interplay between algebra and geometry to motivate the study of advanced linear algebra techniques. Matrices and linear transformations are presented as two sides of the same coin, with their connection motivating inquiry throughout the book. Building on a first course in linear algebra, this book offers readers a deeper understanding of abstract structures, matrix decompositions, multilinearity, and tensors. Concepts draw on concrete examples throughout, offering accessible pathways to advanced techniques.Beginning with a study of vector spaces that includes coordinates, isomorphisms, orthogonality, and projections, the book goes on to focus on matrix decompositions. Numerous decompositions are explored, including the Shur, spectral, singular value, and Jordan decompositions. In each case, the author ties the new technique back to familiar ones, to create a coherent set of tools. Tensors and multilinearity complete the book, with a study of the Kronecker product, multilinear transformations, and tensor products. Throughout, “Extra Topic” sections augment the core content with a wide range of ideas and applications, from the QR and Cholesky decompositions, to matrix-valued linear maps and semidefinite programming. Exercises of all levels accompany each section.
Advanced Linear and Matrix Algebra offers students of mathematics, data analysis, and beyond the essential tools and concepts needed for further study. The engaging color presentation and frequent marginal notes showcase the author’s visual approach. A first course in proof-based linear algebra is assumed. An ideal preparation can be found in the author’s companion volume, Introduction to Linear and Matrix Algebra.

This textbook emphasizes the interplay between algebra and geometry to motivate the study of advanced linear algebra techniques. Matrices and linear transformations are presented as two sides of the same coin, with their connection motivating inquiry throughout the book. Building on a first course in linear algebra, this book offers readers a deeper understanding of abstract structures, matrix decompositions, multilinearity, and tensors. Concepts draw on concrete examples throughout, offering accessible pathways to advanced techniques.

Beginning with a study of vector spaces that includes coordinates, isomorphisms, orthogonality, and projections, the book goes on to focus on matrix decompositions. Numerous decompositions are explored, including the Shur, spectral, singular value, and Jordan decompositions. In each case, the author ties the new technique back to familiar ones, to create a coherent set of tools. Tensors and multilinearity complete the book, with a study of the Kronecker product, multilinear transformations, and tensor products. Throughout, “Extra Topic” sections augment the core content with a wide range of ideas and applications, from the QR and Cholesky decompositions, to matrix-valued linear maps and semidefinite programming. Exercises of all levels accompany each section.


Advanced Linear and Matrix Algebra offers students of mathematics, data analysis, and beyond the essential tools and concepts needed for further study. The engaging color presentation and frequent marginal notes showcase the author’s visual approach. A first course in proof-based linear algebra is assumed. An ideal preparation can be found in the author’s companion volume, Introduction to Linear and Matrix Algebra.

<p>Motivates a deeper understanding of the abstract structures needed to tackle questions in mathematics, data analysis, and quantum information theory</p><p>Engages readers with a visual approach that uses color to enhance both content and learning</p><p>Features a wide selection of theoretical and applied topics to complement the core material</p><p>Incorporates exercises of all levels</p><p>Includes supplementary material: sn.pub/extras</p>

Nathaniel Johnston is an Associate Professor of Mathematics at Mount Allison University in New Brunswick, Canada. His research makes use of linear algebra, matrix analysis, and convex optimization to tackle questions related to the theory of quantum entanglement. His companion volume, Introduction to Linear and Matrix Algebra, is also published by Springer.

9783030528140

475473_1_En

Tom M. Apostol, California Institute of Technology Dept. Mathematics 253-37, Pasadena, CA, USA

Historical Introduction.- 1 The Fundamental Theorem of Arithmetic.- 2 Arithmetical Functions and Dirichlet Multiplication.- 3 Averages of Arithmetical Functions.- 4 Some Elementary Theorems on the Distribution of Prime Numbers.- 5 Congruences.- 6 Finite Abelian Groups and Their Characters.- 7 Dirichlet’s Theorem on Primes in Arithmetic Progressions.- 8 Periodic Arithmetical Functions and Gauss Sums.- 9 Quadratic Residues and the Quadratic Reciprocity Law.- 10 Primitive Roots.- 11 Dirichlet Series and Euler Products.- 12 The Functions ?(s) and L(s, ?).- 13 Analytic Proof of the Prime Number Theorem.- 14 Partitions.- Index of Special Symbols.

9780387901633

10.1007/978-1-4757-5579-4

Introduction.- Basic Notions of Quantum Mechanics.- Tensor Products and Composite Systems.- Entanglement.- Quantum Gates and Circuits for Elementary Calculations.- On the Use of Entanglement.- Error Correction.- Adiabatic Quantum Computing.- Epilogue Appendices: A Elementary Probability Theory.- B Elementary Arithmetic Operations.- C LANDAU Symbols.- D Modular Arithmetic.- E Continued Fractions.- F Some Group Theory.- G Proof of a Quantum Adiabatic Theorem.- Solutions to Exercises.

This textbook presents the elementary aspects of quantum computing in a mathematical form. It is intended as core or supplementary reading for physicists, mathematicians, and computer scientists taking a first course on quantum computing. It starts by introducing the basic mathematics required for quantum mechanics, and then goes on to present, in detail, the notions of quantum mechanics, entanglement, quantum gates, and quantum algorithms, of which Shor's factorisation and Grover's search algorithm are discussed extensively. In addition, the algorithms for the Abelian Hidden Subgroup and Discrete Logarithm problems are presented and the latter is used to show how the Bitcoin digital signature may be compromised. It also addresses the problem of error correction as well as giving a detailed exposition of adiabatic quantum computing. The book contains around 140 exercises for the student, covering all of the topics treated, together with an appendix of solutions.

This textbook presents the elementary aspects of quantum computing in a mathematical form. It is intended as core or supplementary reading for physicists, mathematicians, and computer scientists taking a first course on quantum computing. It starts by introducing the basic mathematics required for quantum mechanics, and then goes on to present, in detail, the notions of quantum mechanics, entanglement, quantum gates, and quantum algorithms, of which Shor's factorisation and Grover's search algorithm are discussed extensively. In addition, the algorithms for the Abelian Hidden Subgroup and Discrete Logarithm problems are presented and the latter is used to show how the Bitcoin digital signature may be compromised. It also addresses the problem of error correction as well as giving a detailed exposition of adiabatic quantum computing. The book contains around 140 exercises for the student, covering all of the topics treated, together with an appendix of solutions.

<p>Serves as pedagogical introduction including a clear derivation of all main results</p><p>Mathematically rigorous, following the structure: Definition - Theorem - Proof, but interwoven with motivation and discussions</p><p>Alleviates the need to consult any outside material because of its entirely self-contained presentation</p><p>Features many exercises with solutions to support self-study</p>

<div>Wolfgang Scherer was active in research and teaching in the USA and Germany before settling in London where until recently he worked in risk management for a financial institution. His scientific interests include geometric methods in mathematical physics and fundamental problems in quantum mechanics. He takes pleasure in communicating the joy of mathematics to the younger generation, and is an aficionado of two-wheeled vehicles, with and without motor.
</div><div>
</div><div>
</div>

9783030123574

431374_1_En

978-0-8176-3490-2

Manfredo P. do Carmo, Instituto de Matemática Pura e Aplicada (IMPA), Rio de Janeiro, Brazil

0-Differentiable Manifolds.- 1-Riemannian Metrics.- 2-Affine Connections; Riemannian Connections.- 3-Geodesics; Convex Neighborhoods.- 4-Curvature.- 5-Jacobi Fields.- 6-Isometric Immersions.- 7-Complete Manifolds; Hopf-Rinow and Hadamard Theorems.- 8-Spaces of Constant Curvature.- 9-Variations of Energy.- 10-The Rauch Comparison Theorem.- 11-The Morse Index Theorem.- 12-The Fundamental Group of Manifolds of Negative Curvature.- 13-The Sphere Theorem.- References.

Riemannian Geometry is an expanded edition of a highly acclaimed and successful textbook (originally published in Portuguese) for first-year graduate students in mathematics and physics. The author's treatment goes very directly to the basic language of Riemannian geometry and immediately presents some of its most fundamental theorems. It is elementary, assuming only a modest background from readers, making it suitable for a wide variety of students and course structures. Its selection of topics has been deemed 'superb' by teachers who have used the text. A significant feature of the book is its powerful and revealing structure, beginning simply with the definition of a differentiable manifold and ending with one of the most important results in Riemannian geometry, a proof of the Sphere Theorem. The text abounds with basic definitions and theorems, examples, applications, and numerous exercises to test the student's understanding and extend knowledge and insight into the subject. Instructors and students alike will find the work to be a significant contribution to this highly applicable and stimulating subject.

9780817634902

10.1007/978-1-4757-2201-7

978-0-387-94268-1

David Eisenbud, Mathematical Sciences Research Institute (MSRI), Berkeley, CA, USA

Advice for the Beginner.- Information for the Expert.- Prerequisites.- Sources.- Courses.- Acknowledgements.- 0 Elementary Definitions.- 0.1 Rings and Ideals.- 0.2 Unique Factorization.- 0.3 Modules.- I Basic Constructions.- 1 Roots of Commutative Algebra.- 2 Localization.- 3 Associated Primes and Primary Decomposition.- 4 Integral Dependence and the Nullstellensatz.- 5 Filtrations and the Artin-Rees Lemma.- 6 Flat Families.- 7 Completions and Hensel’s Lemma.- II Dimension Theory.- 8 Introduction to Dimension Theory.- 9 Fundamental Definitions of Dimension Theory.- 10 The Principal Ideal Theorem and Systems of Parameters.- 11 Dimension and Codimension One.- 12 Dimension and Hilbert-Samuel Polynomials.- 13 The Dimension of Affine Rings.- 14 Elimination Theory, Generic Freeness, and the Dimension of Fibers.- 15Gröbner Bases.- 16 Modules of Differentials.- III Homological Methods.- 17 Regular Sequences and the Koszul Complex.- 18 Depth, Codimension, and Cohen-Macaulay Rings.- 19 Homological Theory of Regular Local Rings.- 20 Free Resolutions and Fitting Invariants.- 21 Duality, Canonical Modules, and Gorenstein Rings.- Appendix 1 Field Theory.- A1.1 Transcendence Degree.- A1.2 Separability.- A1.3.1 Exercises.- Appendix 2 Multilinear Algebra.- A2.1 Introduction.- A2.2 Tensor Product.- A2.3 Symmetric and Exterior Algebras.- A2.3.1 Bases.- A2.3.2 Exercises.- A2.4 Coalgebra Structures and Divided Powers.- A2.5 Schur Functors.- A2.5.1 Exercises.- A2.6 Complexes Constructed by Multilinear Algebra.- A2.6.1 Strands of the Koszul Comple.- A2.6.2 Exercises.- Appendix 3 Homological Algebra.- A3.1 Introduction.- I: Resolutions and Derived Functors.- A3.2 Free and Projective Modules.- A3.3 Free and Projective Resolutions.- A3.4 Injective Modules and Resolutions.- A3.4.1 Exercises.- Injective Envelopes.- Injective Modules over Noetherian Rings.- A3.5 Basic Constructions with Complexes.- A3.5.1 Notation and Definitions.- A3.6 Maps and Homotopies of Complexes.- A3.7 Exact Sequences of Complexes.- A3.7.1 Exercises.- A3.8 The Long Exact Sequence in Homology.- A3.8.1 Exercises.- Diagrams and Syzygies.- A3.9 Derived Functors.- A3.9.1 Exercise on Derived Functors.- A3.10 Tor.- A3.10.1 Exercises: Tor.- A3.1l Ext.- A3.11.1 Exercises: Ext.- A3.11.2 Local Cohomology.- II: From Mapping Cones to Spectral Sequences.- A3.12 The Mapping Cone and Double Complexe.- A3.12.1 Exercises: Mapping Cones and Double Complexes.- A3.13 Spectral Sequences.- A3.13.1 Mapping Cones Revisited.- A3.13.2 Exact Couples.- A3.13.3 Filtered Differential Modules and Complexes.- A3.13.4 The Spectral Sequence of a Double Complex.- A3.13.5 Exact Sequence of Terms of Low Degree.- A3.13.6 Exercises on Spectral Sequences.- A3.14 Derived Categories.- A3.14.1 Step One: The Homotopy Category of Complexes.- A3.14.2 Step Two: The Derived Category.- A3.14.3 Exercises on the Derived Category.- Appendix 4 A Sketch of Local Cohomology.- A4.1 Local Cohomology and Global Cohomology.- A4.2 Local Duality.- A4.3 Depth and Dimensio.- Appendix 5 Category Theory.- A5.1 Categories, Functors, and Natural Transformations.- A5.2 Adjoint Functors.- A5.2.1 Uniqueness.- A5.2.2 Some Examples.- A5.2.3 Another Characterization of Adjoints.- A5.2.4 Adjoints and Limits.- A5.3 Representable Functors and Yoneda's Lemma.- Appendix 6 Limits and Colimits.- A6.1 Colimits in the Category of Modules.- A6.2 Flat Modules as Colimits of Free Modules.- A6.3 Colimits in the Category of Commutative Algebras.- A6.4 Exercises.- Appendix 7 Where Next?.- References.- Index of Notation.

Commutative Algebra is best understood with knowledge of the geometric ideas that have played a great role in its formation, in short, with a view towards algebraic geometry. The author presents a comprehensive view of commutative algebra, from basics, such as localization and primary decomposition, through dimension theory, differentials, homological methods, free resolutions and duality, emphasizing the origins of the ideas and their connections with other parts of mathematics. Many exercises illustrate and sharpen the theory and extended exercises give the reader an active part in complementing the material presented in the text. One novel feature is a chapter devoted to a quick but thorough treatment of Grobner basis theory and the constructive methods in commutative algebra and algebraic geometry that flow from it. Applications of the theory and even suggestions for computer algebra projects are included. This book will appeal to readers from beginners to advanced students of commutative algebra or algebraic geometry. To help beginners, the essential ideals from algebraic geometry are treated from scratch. Appendices on homological algebra, multilinear algebra and several other useful topics help to make the book relatively self- contained. Novel results and presentations are scattered throughout the text.

9780387942681

978-3-540-77973-5

Mark de Berg, Technische Universiteit Eindhoven Department of Computer Science, Eindhoven, The Netherlands; Otfried Cheong, Korea Advanced Institute of Science & Technology (KAIST), Taejon, Korea, Republic of (South Korea); Marc van Kreveld, Utrecht University Department of Computer Science, Utrecht, The Netherlands; Mark Overmars, Utrecht University Dept. Computer Science, Utrecht, The Netherlands

,978-3-662-04247-2,978-3-540-65620-3,978-3-662-04246-5,978-3-662-04245-8

Computational Geometry: Introduction.- Line Segment Intersection: Thematic Map Overlay.- Polygon Triangulation: Guarding an Art Gallery.- Linear Programming: Manufacturing with Molds.- Orthogonal Range Searching: Querying a Database.- Point Location: Knowing Where You Are.- Voronoi Diagrams: The Post Office Problem.- Arrangements and Duality: Supersampling in Ray Tracing.- Delaunay Triangulations: Height Interpolation.- More Geometric Data Structures: Windowing.- Convex Hulls: Mixing Things.- Binary Space Partitions: The Painter's Algorithm.- Robot Motion Planning: Getting Where You Want to Be.- Quadtrees: Non-Uniform Mesh Generation.- Visibility Graphs: Finding the Shortest Route.- Simplex Range Searching: Windowing Revisited.- Bibliography.- Index.

Computational geometry emerged from the ?eld of algorithms design and analysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The success of the ?eld as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains—computer graphics, geographic information systems (GIS), robotics, and others—in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or dif?cult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simpli?ed many of the previous approaches. In this textbook we have tried to make these modern algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can also be used for self-study.

<p>A broad overview of the major algorithms and data structures of the field</p><p>Motivated from applications</p><p>Covers concepts and techniquesto be presented in any course on computational geometry</p><p>Self-contained and illustrated with 370 figures</p><p>Additional online material available under http://www.cs.uu.nl/geobook/</p><p>Besides revisions to the second edition, new sections discussing Voronoi diagrams of line segments, farthest-point Voronoi diagrams, and realistic input models have been added</p><p>Includes supplementary material: sn.pub/extras</p>

9783540779735

10.1007/978-3-540-77974-2

978-0-387-70913-0

Functional Analysis, Sobolev Spaces and Partial Differential Equations

Preface.- 1. The Hahn–Banach Theorems. Introduction to the Theory of Conjugate Convex Functions.- 2. The Uniform Boundedness Principle and the Closed Graph Theorem. Unbounded Operators. Adjoint. Characterization of Surjective Operators.- 3. Weak Topologies. Reflexive Spaces. Separable Spaces. Uniform Convexity.- 4. L^p Spaces.- 5. Hilbert Spaces.- 6. Compact Operators. Spectral Decomposition of Self-Adjoint Compact Operators.- 7. The Hille–Yosida Theorem.- 8. Sobolev Spaces and the Variational Formulation of Boundary Value Problems in One Dimension.- 9. Sobolev Spaces and the Variational Formulation of Elliptic Boundary Value Problems in N Dimensions.- 10. Evolution Problems: The Heat Equation and the Wave Equation.- 11. Some Complements.- Problems.- Solutions of Some Exercises and Problems.- Bibliography.- Index.

Uniquely, this book presents a coherent, concise and unified way of combining elements from two distinct “worlds,” functional analysis (FA) and partial differential equations (PDEs), and is intended for students who have a good background in real analysis. This text presents a smooth transition from FA to PDEs by analyzing in great detail the simple case of one-dimensional PDEs (i.e., ODEs), a more manageable approach for the beginner. Although there are many books on functional analysis and many on PDEs, this is the first to cover both of these closely connected topics. Moreover, the wealth of exercises and additional material presented, leads the reader to the frontier of research. This book has its roots in a celebrated course taught by the author for many years and is a completely revised, updated, and expanded English edition of the important “Analyse Fonctionnelle” (1983). Since the French book was first published, it has been translated into Spanish, Italian, Japanese, Korean, Romanian, Greek and Chinese. The English version is a welcome addition to this list. The first part of the text deals with abstract results in FA and operator theory. The second part is concerned with the study of spaces of functions (of one or more real variables) having specific differentiability properties, e.g., the celebrated Sobolev spaces, which lie at the heart of the modern theory of PDEs. The Sobolev spaces occur in a wide range of questions, both in pure and applied mathematics, appearing in linear and nonlinear PDEs which arise, for example, in differential geometry, harmonic analysis, engineering, mechanics, physics etc. and belong in the toolbox of any graduate student studying analysis.

This textbook is a completely revised, updated, and expanded English edition of the important Analyse fonctionnelle (1983). In addition, it contains a wealth of problems and exercises (with solutions) to guide the reader. Uniquely, this book presents in a coherent, concise and unified way the main results from functional analysis together with the main results from the theory of partial differential equations (PDEs). Although there are many books on functional analysis and many on PDEs, this is the first to cover both of these closely connected topics. Since the French book was first published, it has been translated into Spanish, Italian, Japanese, Korean, Romanian, Greek and Chinese. The English edition makes a welcome addition to this list.

<p>Major textbook by a well-known and highly regarded author</p><p>The first single-volume textbook to cover related fields of functional analysis and PDEs</p><p>Includes supplementary material: sn.pub/extras</p>

9780387709130

10.1007/978-0-387-70914-7

978-0-387-97245-9

John B Conway, The George Washington Univ Dept of Mathematics, Fairfax, VA

,978-1-4757-3830-8,978-1-4757-3829-2,978-0-387-96042-5,978-1-4757-3828-5

I Hilbert Spaces.- II Operators on Hilbert Space.- III Banach Spaces.- IV Locally Convex Spaces.- V Weak Topologies.- VI Linear Operators on a Banach Space.- VII Banach Algebras and Spectral Theory for Operators on a Banach Space.- VIII C*-Algebras.- IX Normal Operators on Hilbert Space.- X Unbounded Operators.- XI Fredholm Theory.- Appendix A Preliminaries.- §1. Linear Algebra.- §2. Topology.- List of Symbols.

Functional analysis has become a sufficiently large area of mathematics that it is possible to find two research mathematicians, both of whom call themselves functional analysts, who have great difficulty understanding the work of the other. The common thread is the existence of a linear space with a topology or two (or more). Here the paths diverge in the choice of how that topology is defined and in whether to study the geometry of the linear space, or the linear operators on the space, or both. In this book I have tried to follow the common thread rather than any special topic. I have included some topics that a few years ago might have been thought of as specialized but which impress me as interesting and basic. Near the end of this work I gave into my natural temptation and included some operator theory that, though basic for operator theory, might be considered specialized by some functional analysts.

9780387972459

10.1007/978-1-4757-4383-8

Alan Garfinkel, University of California Los Angeles, Los Angeles, CA, USA; Jane Shevtsov, University of California Los Angeles, Los Angeles, CA, USA; Yina Guo, Los Angeles, CA, USA

1. Modeling, Change, and Simulation.- 2. Derivatives and Integrals.- 3. Equilibrium Behavior.- 4. Non-Equilibrium Dynamics: Oscillation.- 5. Chaos.- 6. Linear Algebra.- 7. Multivariable Systems.- Bibliography.- Index.

From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. This book develops the mathematical tools essential for students in the life sciences to describe these interacting systems and to understand and predict their behavior. Complex feedback relations and counter-intuitive responses are common in dynamical systems in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?

This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?

<p>Tackles highly relevant material across the life sciences, using tools best-suited to the field</p><p>Driven by real-world examples drawn from biology, ecology, medicine, and beyond</p><p>Builds effective mathematical modeling skills from beginning to end</p><p>Illustrates every step with engaging, informative graphics in full color</p><p>Includes supplementary material: sn.pub/extras</p>

​Alan Garfinkel received his undergraduate degree from Cornell in Mathematics and Philosophy,<div>and a PhD from Harvard in Philosophy and Mathematics. After some years of practicing philosophy of science, Garfinkel transitioned to medical research, applying qualitative dynamics to phenomena in medicine and physiology. Along with James Weiss and Zhilin Qu, he studies cardiac arrhythmias from the point of view of nonlinear dynamics.</div><div>
</div><div>Jane Shevtsov earned her BS in Ecology, Behavior and Evolution from UCLA, and her PhD in Ecology from the University of Georgia. Her main research interests lie in mathematical models of food webs and ecosystems.</div><div>
</div><div>Yina Guo received her PhD from Nankai University in Control Engineering. Her PhD thesis used partial differential equations to explain the branching structure of the lung. Her computer simulations of branching processes were featured on the cover of the Journal of Physiology. She is particularly interested in the use of graphics and visualization techniques in both research and teaching.</div>

9783319597300

435590_1_En

978-3-030-58720-8

Edward H. Shortliffe, Columbia University, New York, NY, USA; James J. Cimino, University of Alabama at Birmingham, Birmingham, AL, USA

,978-1-4471-4473-1,978-1-4471-4475-5,978-1-4471-4474-8,978-1-4471-6804-1

Biomedical Informatics: The Science and the Pragmatics.- Biomedical Data: Their Acquisition, Storage, and Use.- Biomedical Decision Making: Probabilistic Clinical Reasoning.- Cognitive Science and Biomedical Informatics.- Computer Architectures for Health Care and Biomedicine.- Software Engineering for Health Care and Biomedicine.- Standards in Biomedical Informatics.- Natural Language Processing in Health Care and Biomedicine.- Biomedical Imaging Informatics.- Ethics and Biomedical and Health Informatics: Users, Standards, and Outcomes.- Evaluation of Biomedical and Health Information Resources.- Electronic Health Record Systems.- The Health Information Infrastructure.- Management of Information in Health Care Organizations.- Patient-Centered Care Systems.- Public Health Informatics.- Consumer Health Informatics and Personal Health Records.- Telehealth.- Patient Monitoring Systems.- Imaging Systems in Radiology.- Information Retrieval and Digital Libraries.- Clinical Decision-Support Systems.- Computers in Health Care Education.- Bioinformatics.- Translational Bioinformatics.- Clinical Research Informatics.- Health Information Technology Policy.- The Future of Informatics in Biomedicine.

This 5th edition of this essential textbook continues to meet the growing demand of practitioners, researchers, educators, and students for a comprehensive introduction to key topics in biomedical informatics and the underlying scientific issues that sit at the intersection of biomedical science, patient care, public health and information technology (IT). Emphasizing the conceptual basis of the field rather than technical details, it provides the tools for study required for readers to comprehend, assess, and utilize biomedical informatics and health IT. It focuses on practical examples, a guide to additional literature, chapter summaries and a comprehensive glossary with concise definitions of recurring terms for self-study or classroom use.Biomedical Informatics: Computer Applications in Health Care and Biomedicine reflects the remarkable changes in both computing and health care that continue to occur and the exploding interest in the role that IT must play in care coordination and the melding of genomics with innovations in clinical practice and treatment. New and heavily revised chapters have been introduced on human-computer interaction, mHealth, personal health informatics and precision medicine, while the structure of the other chapters has undergone extensive revisions to reflect the developments in the area. The organization and philosophy remain unchanged, focusing on the science of information and knowledge management, and the role of computers and communications in modern biomedical research, health and health care.

This 5th edition of this essential textbook continues to meet the growing demand of practitioners, researchers, educators, and students for a comprehensive introduction to key topics in biomedical informatics and the underlying scientific issues that sit at the intersection of biomedical science, patient care, public health and information technology (IT). Emphasizing the conceptual basis of the field rather than technical details, it provides the tools for study required for readers to comprehend, assess, and utilize biomedical informatics and health IT. It focuses on practical examples, a guide to additional literature, chapter summaries and a comprehensive glossary with concise definitions of recurring terms for self-study or classroom use.Biomedical Informatics: Computer Applications in Health Care and Biomedicine reflects the remarkable changes in both computing and health care that continue to occur and the exploding interest in the role that IT must play in care coordination and the melding of genomics with innovations in clinical practice and treatment. New and heavily revised chapters have been introduced on human-computer interaction, mHealth, personal health informatics and precision medicine, while the structure of the other chapters has undergone extensive revisions to reflect the developments in the area. The organization and philosophy remain unchanged, focusing on the science of information and knowledge management, and the role of computers and communications in modern biomedical research, health and health care.
<div>
</div>

<p>Includes new and thoroughly revised chapters on human-computer interaction, mHealth, personal health informatics and precision medicine</p><p>Focuses on providing relevant practical examples for users to test their knowledge</p><p>Provides a concise and comprehensive glossary ideal for the classroom and personal study</p>

Edward H. Shortliffe is Chair Emeritus and Adjunct Professor in the Department of Biomedical Informatics at Columbia University's Vagelos College of Physicians and Surgeons. Previously he served as President and CEO of the American Medical Informatics Association. He was Professor of Biomedical Informatics at the University of Texas Health Science Center in Houston and at Arizona State University. A board-certified internist, he was Founding Dean of the University of Arizona College of Medicine – Phoenix and served as Professor of Biomedical Informatics and of Medicine at Columbia University. Before that he was Professor of Medicine and of Computer Science at Stanford University. Honors include his election to membership in the National Academy of Medicine (where he served on the executive council for six years and has chaired the membership committee) and in the American Society for Clinical Investigation. He has also been elected to fellowship in the American College of Medical Informatics and the American Association for Artificial Intelligence. A Master of the American College of Physicians (ACP), he held a position for six years on that organization’s Board of Regents. He is Editor-in-Chief of the Journal of Biomedical Informatics and has served on the editorial boards for several other biomedical informatics publications. In the early 1980s he was recipient of a research career development award from the National Library of Medicine. In addition, he received the Grace Murray Hopper Award of the Association for Computing Machinery in 1976, the Morris F. Collen Award of the American College of Medical Informatics in 2006, and was a Henry J. Kaiser Family Foundation Faculty Scholar in General Internal Medicine. He has served on the oversight committee for the Division of Engineering and Physical Sciences (National Academy of Sciences), the National Committee for Vital and Health Statistics (NCVHS) and on the President's Information Technology Advisory Committee (PITAC). Dr. Shortliffe has authored over 350 articles and books in the fields of biomedical computing and artificial intelligence.<div>
</div><div><div>Dr. James Cimino is a board certified internist who completed a National Library of Medicine informatics fellowship at the Massachusetts General Hospital and Harvard University and then went on to an academic position at Columbia University College of Physicians and Surgeons and the Presbyterian Hospital in New York. He spent 20 years at Columbia, carrying out clinical informatics research, building clinical information systems, teaching medical informatics and medicine, and caring for patients, rising to the rank of full professor in both Biomedical Informatics and Medicine. His principle research areas there included desiderata for controlled terminologies, mobile and Web-based clinical information systems for clinicians and patients, and a context-aware form of clinical decision support called “infobuttons”. In 2008, he moved to the National Institutes of Health, where he was the Chief of the Laboratory for Informatics Development and a Tenured Investigator at the NIH Clinical Center and the National Library of Medicine. His principle project involved the development of the Biomedical Translational Research Information System (BTRIS), an NIH-wide clinical research data resource. In 2015, he left NIH to be the inaugural Director of the Informatics Institute at the University of Alabama at Birmingham. The Institute is charged with improving informatics research, education, and service across the University, supporting the Personalized Medicine Institute, the Center for Genomic Medicine, and the University Health System Foundation, including improvement of and access to electronic health records. He holds the rank of Tenured Professor in Medicine, and is the Chief for the Informatics Section in the Division of

9783030587208

978-3-030-94222-9

John Paul (J.P.) Sánchez, University of New Mexico (UNM), Albuquerque, NM, USA; Nicholas N. Brutus, Albany Medical College Class of 2024, Albany, NY, USA

Chapter 1. Introduction.- Chapter 2. What is Academia All About? Academic Career Roles and Responsibilities.- Chapter 3. Leveraging the Value of Diversity in the Academic Workforce.- Chapter 4. Integrating Community Service into Your Career Success.- Chapter 5. Realizing Your Leadership Potential.- Chapter 6. Building your Social Capital through Mentorship.- Chapter 7. The Scholarly Educator.- Chapter 8. Advancing Change through Discovery.- Chapter 9. Telling Your Story: Resume, CV, and Applications.- Chapter 10. The Profile of a Competitive Applicant.

<div>This book increases undergraduate and graduate students' awareness of, interest in, and preparedness for academic health professions careers. It includes invaluable chapters that emphasize the importance of developing self-efficacy, knowledge, skills, and experiences not just for their resume but to build a foundation to strengthen students for the rest of their professional careers.</div><div>
</div><div>The book provides the reader with basic information, tools, and a competitive edge through inspirational narratives from diverse graduate students and faculty, self-assessment exercises, and case-based discussion. These invaluable, authentic narratives will inspire, hearten, and encourage readers to pursue their health professional and academic careers confidently. Additionally, chapters outline the necessary tools for getting the most out of one's educational, research, service and leadership activities and optimize their competitiveness for graduate school and as pre-faculty.</div><div>
</div><div>Unique, timely, and comprehensive, Health Professions and Academia provides undergraduate and graduate students with content to develop as competitive applicants to health-related graduate school and build a foundation from which they can establish successful careers in academia as future faculty, senior administrative leaders, and change agents.</div>

<div>This book increases undergraduate and graduate students' awareness of, interest in, and preparedness for academic health professions careers. It includes invaluable chapters that emphasize the importance of developing self-efficacy, knowledge, skills, and experiences not just for their resume but to build a foundation to strengthen students for the rest of their professional careers.</div><div>
</div><div>The book provides the reader with basic information, tools, and a competitive edge through inspirational narratives from diverse graduate students and faculty, self-assessment exercises, and case-based discussion. These invaluable, authentic narratives will inspire, hearten, and encourage readers to pursue their health professional and academic careers confidently. Additionally, chapters outline the necessary tools for getting the most out of one's educational, research, service and leadership activities and optimize their competitiveness for graduate school and as pre-faculty.</div><div>
</div><div>Unique, timely, and comprehensive, Health Professions and Academia provides undergraduate and graduate students with content to develop as competitive applicants to health-related graduate school and build a foundation from which they can establish successful careers in academia as future faculty, senior administrative leaders, and change agents.</div>

<p>Provides the reader with basic information, tools, and a competitive edge</p><p>Features inspirational narratives from graduate students and faculty, self-assessments, and case-based discussions</p><p>Includes a diverse authorship from across the health professions</p>

<div><div>John Paul Sánchez MD, MPH</div><div>Executive Associate Vice Chancellor</div><div>Health Sciences Center, Diversity, Equity and Inclusion (DEI), UNM</div><div>Interim Executive Diversity Officer</div><div>Professor with Tenure & Vice Chair DEI, Emergency Medicine</div><div>University of New Mexico School of Medicine (UNM SOM)</div>President, National Center for Pre-Faculty Development and BNGAP Inc. </div><div>Albuquerque, NM</div><div>USA</div><div>
</div><div>Nicholas Brutus BA</div><div>Medical Student, Albany Medical College</div><div>Coordinator, BNGAP Inc.</div><div>Albany, NY</div><div>USA</div><div>
</div><div>Bios: </div><div>
</div>​John Paul Sánchez MD, MPH has worked extensively to promote diversity and inclusion in the health professions academic workforces. He is the Co-Founder/President of Building the Next Generation of Academic Physician (BNGAP). Over the past 11 years, BNGAP has become nationally recognized for developing the concept of pre-faculty development and has collaborated with 60+ academic health centers to educate trainees, faculty, and senior administrators on how to develop the upstream pipeline of diverse learners to become future faculty and senior academic leaders. Dr. Sánchez is also on the Editorial Board of the Journal of Academic Medicine and is Associate Editor of MedEdPORTAL (overseeing the Diversity, Inclusion and Health Equity Collection). He is Executive Director of the Latino Medical Student Association Inc., the largest Latino medical student association in the country with 140+ chapters at allopathic and osteopathic medical schools across the country. Since joining the Health Sciences Center (HSC) at the University of New Mexico he has been selected for numerous leadership positions including as Executive Associate Vice Chancellor for Diversity, Equity, and Inclusion (DEI), whereby he supports ten HSC entities (four graduate schools – medicine, pharmacy, nursing, and population-health; three hospitals; and three centers) in planning, organizing, and aligning DEI activities. He has published 52 peer reviewed publications, 6 book chapters, and served as Editor for a book by Springer Publishing entitled Succeeding in Academic Medicine: A Roadmap for Diverse Medical Students and Residents. He received his medical degree from the Albert Einstein College of Medicine, completed his residency training at Jacobi/Montefiore, and is Board Certified in Emergency Medicine. He completed a Masters of Public Health, with a concentration in the epidemiology of infectious diseases, from the Yale School of Public Health. He is of Puerto Rican ancestry, gay-identified and was raised in the Bronx.<div>
</div><div>
</div>Nicholas Brutus is a medical student at Albany Medical College who serves as the National Coordinator of Building the Next Generation of Academic Physicians (BNGAP) and is an aspiring academic physician. Since entering medical school, he continues to engage in diversity lead initiatives with the aim to increase representation within medical schools and the academic workforce. Nicholas has undertaken several leadership positions to promote inclusion of marginalized populations in medicine since entering medical school, including being elected as the Vice-President of Student Council for the 2020-2021 school year overseeing the student curriculum review committee, and he served as Chair on the Underrepresented Student Alliance (USA). Notably, Nicholas was selected as the President of the Albany Medical College’s BNGAP Chapter for the 2021-2022 school year. As the National Coordinator of BNGAP, he oversees BNGAP student-led chapters across the nation and is involved in implementing and designing conferences to guide diverse learners to a potential career in academia. Nicholas hopes to embody the BNGAP mission of working to impro

9783030942229

518295_1_En

10.1007/978-3-030-94223-6

<div>Gaussian variables and Gaussian processes.- Brownian motion.- Filtrations and martingales.- Continuous semimartingales.- Stochastic integration.- General theory of Markov processes.- Brownian motion and partial differential equations.- Stochastic differential equations.- Local times.- The monotone class lemma.- Discrete martingales.- References.</div>

<div>This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter.</div><div><br/></div><div>Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested in such developments.</div><div><br/></div><div>Beginning graduate or advanced undergraduate students will benefit from this detailed approach to an essential area of probability theory. The emphasis is on concise and efficient presentation, without any concession to mathematical rigor. The material has been taught by the author for several years in graduate courses at two of the most prestigious French universities. The fact that proofs are given with full details makes the book particularly suitable for self-study. The numerous exercises help the reader to get acquainted with the tools of stochastic calculus.</div>

<div>This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter.</div><div><br/></div><div>Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested in such developments.</div><div><br/></div><div>Beginning graduate or advanced undergraduate students will benefit from this detailed approach to an essential area of probability theory. The emphasis is on concise and efficient presentation, without any concession to mathematical rigor. The material has been taught by the author for several years in graduate courses at two of the most prestigious French universities. The fact that proofs are given with full details makes the book particularly suitable for self-study. The numerous exercises help the reader to get acquainted with the tools of stochastic calculus.</div>

<p>Provides a concise and rigorous presentation of stochastic integration and stochastic calculus for continuous semimartingales</p><p>Presents major applications of stochastic calculus to Brownian motion and related stochastic processes</p><p>Includes important aspects of Markov processes with applications to stochastic differential equations and to connections with partial differential equations</p>

<div>Jean-François Le Gall is a well-known specialist of probability theory and stochastic processes. His main research achievements are concerned with Brownian motion, superprocesses and their connections with partial differential equations, and more recently random trees and random graphs. He has been awarded several international prizes in mathematics, including the Loeve Prize and the Fermat Prize, and gave a plenary lecture at the 2014 International Congress of Mathematicians. He is currently a professor of mathematics at Université Paris-Sud and a member of the French Academy of Sciences.</div>

9783319310886

369797_1_En

978-3-030-56401-8

Achim Klenke, Johannes Gutenberg-Universität Mainz, Mainz, Germany

1 Basic Measure Theory.- 2 Independence.- 3 Generating Functions.- 4 The Integral.- 5 Moments and Laws of Large Numbers.- 6 Convergence Theorems.- 7 Lp-Spaces and the Radon–Nikodym Theorem.- 8 Conditional Expectations.- 9 Martingales.- 10 Optional Sampling Theorems.- 11 Martingale Convergence Theorems and Their Applications.- 12 Backwards Martingales and Exchangeability.- 13 Convergence of Measures.- 14 Probability Measures on Product Spaces.- 15 Characteristic Functions and the Central Limit Theorem.- 16 Infinitely Divisible Distributions.- 17 Markov Chains.- 18 Convergence of Markov Chains.- 19 Markov Chains and Electrical Networks.- 20 Ergodic Theory.- 21 Brownian Motion.- 22 Law of the Iterated Logarithm.- 23 Large Deviations.- 24 The Poisson Point Process.- 25 The Itô Integral.- 26 Stochastic Differential Equations.- References.- Notation Index.- Name Index.- Subject Index.

This popular textbook, now in a revised and expanded third edition, presents a comprehensive course in modern probability theory.Probability plays an increasingly important role not only in mathematics, but also in physics, biology, finance and computer science, helping to understand phenomena such as magnetism, genetic diversity and market volatility, and also to construct efficient algorithms. Starting with the very basics, this textbook covers a wide variety of topics in probability, including many not usually found in introductory books, such as: limit theorems for sums of random variables martingales percolation Markov chains and electrical networks construction of stochastic processes Poisson point process and infinite divisibility large deviation principles and statistical physics Brownian motion stochastic integrals and stochastic differential equations. The presentation is self-contained and mathematically rigorous, with the material on probability theory interspersed with chapters on measure theory to better illustrate the power of abstract concepts.This third edition has been carefully extended and includes new features, such as concise summaries at the end of each section and additional questions to encourage self-reflection, as well as updates to the figures and computer simulations. With a wealth of examples and more than 290 exercises, as well as biographical details of key mathematicians, it will be of use to students and researchers in mathematics, statistics, physics, computer science, economics and biology.

This popular textbook, now in a revised and expanded third edition, presents a comprehensive course in modern probability theory.Probability plays an increasingly important role not only in mathematics, but also in physics, biology, finance and computer science, helping to understand phenomena such as magnetism, genetic diversity and market volatility, and also to construct efficient algorithms. Starting with the very basics, this textbook covers a wide variety of topics in probability, including many not usually found in introductory books, such as: limit theorems for sums of random variables martingales percolation Markov chains and electrical networks construction of stochastic processes Poisson point process and infinite divisibility large deviation principles and statistical physics Brownian motion stochastic integrals and stochastic differential equations. The presentation is self-contained and mathematically rigorous, with the material on probability theory interspersed with chapters on measure theory to better illustrate the power of abstract concepts.This third edition has been carefully extended and includes new features, such as concise summaries at the end of each section and additional questions to encourage self-reflection, as well as updates to the figures and computer simulations. With a wealth of examples and more than 290 exercises, as well as biographical details of key mathematicians, it will be of use to students and researchers in mathematics, statistics, physics, computer science, economics and biology.

<p>Provides a complete introduction to probability theory, including measure theory and scientific applications</p><p>New updated edition includes concise summaries of each section, as well as outlooks and questions in the text</p><p>Clearly written to make complicated mathematics accessible</p>

Achim Klenke is a professor at the Johannes Gutenberg University in Mainz, Germany. He is known for his work on interacting particle systems, stochastic analysis, and branching processes, in particular for his pioneering work with Leonid Mytnik on infinite rate mutually catalytic branching processes.

9783030564018

152149_3_En

Charles Chapman Pugh, University of California Dept of Mathematics, Berkeley, CA, USA

,978-1-4419-2941-9,978-0-387-95297-0,978-1-4684-9541-6,978-0-387-21684-3,978-1-4939-7071-1

Real Numbers.- A Taste of Topology.- Functions of a Real Variable.- Function Spaces.- Multivariable Calculus.- Lebesgue Theory.

Based on an honors course taught by the author at UC Berkeley, this introduction to undergraduate real analysis gives a different emphasis by stressing the importance of pictures and hard problems. Topics include: a natural construction of the real numbers, four-dimensional visualization, basic point-set topology, function spaces, multivariable calculus via differential forms (leading to a simple proof of the Brouwer Fixed Point Theorem), and a pictorial treatment of Lebesgue theory. Over 150 detailed illustrations elucidate abstract concepts and salient points in proofs. The exposition is informal and relaxed, with many helpful asides, examples, some jokes, and occasional comments from mathematicians, such as Littlewood, Dieudonné, and Osserman. This book thus succeeds in being more comprehensive, more comprehensible, and more enjoyable, than standard introductions to analysis.<br/><br/>New to the second edition of Real Mathematical Analysis is a presentation of Lebesgue integration done almost entirely using the undergraph approach of Burkill. Payoffs include: concise picture proofs of the Monotone and Dominated Convergence Theorems, a one-line/one-picture proof of Fubini's theorem from Cavalieri’s Principle, and, in many cases, the ability to see an integral result from measure theory. The presentation includes Vitali’s Covering Lemma, density points — which are rarely treated in books at this level — and the almost everywhere differentiability of monotone functions. Several new exercises now join a collection of over 500 exercises that pose interesting challenges and introduce special topics to the student keen on mastering this beautiful subject.

Based on an honors course taught by the author at UC Berkeley, this introduction to undergraduate real analysis gives a different emphasis by stressing the importance of pictures and hard problems. Topics include: a natural construction of the real numbers, four-dimensional visualization, basic point-set topology, function spaces, multivariable calculus via differential forms (leading to a simple proof of the Brouwer Fixed Point Theorem), and a pictorial treatment of Lebesgue theory. Over 150 detailed illustrations elucidate abstract concepts and salient points in proofs. The exposition is informal and relaxed, with many helpful asides, examples, some jokes, and occasional comments from mathematicians, such as Littlewood, Dieudonné, and Osserman. This book thus succeeds in being more comprehensive, more comprehensible, and more enjoyable, than standard introductions to analysis.<br/><br/>New to the second edition of Real Mathematical Analysis is a presentation of Lebesgue integration done almost entirely using the undergraph approach of Burkill. Payoffs include: concise picture proofs of the Monotone and Dominated Convergence Theorems, a one-line/one-picture proof of Fubini's theorem from Cavalieri’s Principle, and, in many cases, the ability to see an integral result from measure theory. The presentation includes Vitali’s Covering Lemma, density points — which are rarely treated in books at this level — and the almost everywhere differentiability of monotone functions. Several new exercises now join a collection of over 500 exercises that pose interesting challenges and introduce special topics to the student keen on mastering this beautiful subject.

<p>Elucidates abstract concepts and salient points in proofs with over 150 detailed illustrations</p><p>Treats the rigorous foundations of both single and multivariable Calculus</p><p>Gives an intuitive presentation of Lebesgue integration using the undergraph approach of Burkill</p><p>Includes over 500 exercises that are interesting and thought-provoking, not merely routine</p>

Charles C. Pugh is Professor Emeritus at the University of California, Berkeley. His research interests include geometry and topology, dynamical systems, and normal hyperbolicity.

9783319177700

978-3-031-06460-9

,978-3-319-73219-0,978-3-319-73220-6,978-3-319-73221-3,978-3-030-10335-4

Introduction.- Mechanics of the Wheel with Tire.- Vehicle Model for Handling and Performance.- Braking Performance.

This textbook offers a comprehensive treatment of vehicle dynamics using an innovative, compelling approach, suitable for engineering students and professionals alike. Written by an authoritative contributor in the fields of applied mathematics and mechanics, it focuses on the development of vehicle models paying special attention to all the relevant assumptions, and providing explanations for each step. Some classical concepts of vehicle dynamics are revisited and reformulated, making this book also interesting for experienced readers. Using clear definitions, sound mathematics, and worked-out exercises, the book helps readers to truly understand the essence of vehicle dynamics for solving practical problems. With respect to the previous edition, which was the recipient of a 2019 TAA Textbook Excellence Award, this thoroughly revised third edition presents a more extensive and in-depth analysis of braking and handling of race cars.

This textbook offers a comprehensive treatment of vehicle dynamics using an innovative, compelling approach, suitable for engineering students and professionals alike. Written by an authoritative contributor in the fields of applied mathematics and mechanics, it focuses on the development of vehicle models paying special attention to all the relevant assumptions, and providing explanations for each step. Some classical concepts of vehicle dynamics are revisited and reformulated, making this book also interesting for experienced readers. Using clear definitions, sound mathematics, and worked-out exercises, the book helps readers to truly understand the essence of vehicle dynamics for solving practical problems. With respect to the previous edition, which was the recipient of a 2019 TAA Textbook Excellence Award, this thoroughly revised third edition presents a more extensive and in-depth analysis of braking and handling of race cars.

3rd edition of a TAA Textbook Excellence Winner 2019With extensive updates concerning handling and braking of race carsPractical and innovative treatment of concepts and misconceptions in vehicle dynamics

Massimo Guiggiani is professor of Applied Mechanics at the Università di Pisa, Italy, where he also teaches Vehicle Dynamics in the MSc degree program in Automotive Engineering.

He has achieved important results also in other fields, such as Guiggiani's algorithm for the evaluation of singular integrals in the Boundary Element Method (1990-1992, ASME Journal of Applied Mechanics), and the invariant approach for gear generation (2005-2007, Mechanism and Machine Theory).

9783031064609

152372_3_En