Myocarditis and idiopathic dilated cardiomyopathy are being increasingly recognized as important causes of heart disease and heart failure. Immunological mechanisms have long been suspected as playing a role in thesediseases but direct evidence has been lacking. Recently, animal models have be- come available, in which myocarditis can be induced either by infection with cardiotropic viruses or by autoimmuniza- tion with heart-specific antigens. This book presents and analyzes the latest information obtained from experimental models, relating it to the practical problems of diagnosis and treatment of myocarditis.

It is only during the last decade that the functions of sinusoidal endothelial cells, Kupffer cells, hepatic stellate cells, pit cells and other intrahepatic lymphocytes have been better understood. The development of methods for isolation and co-culturing various types of liver cells has established that they communicate and cooperate via secretion of various intercellular mediators. This monograph summarizes multiple data that suggest the important role of cellular cross-talk for the functions of both normal and diseased liver. Special features of the book include concise presentation of the majority of detailed data in 19 tables. Original schemes allow for the clear illustration of complicated intercellular relationships. This is the first ever presentation of the newly emerging field of liver biology, which is important for hepatic function in health and disease and opens new avenues for therapeutic interventions.

Constraint programming is a successful technology for solving a wide range of problems in business and industry which require satisfying a set of constraints. Central to solving constraint satisfaction problems is enforcing a level of local consistency. In this thesis, we propose efficient filtering algorithms for enforcing strong local consistencies. In addition, since such filtering algorithms can be too expensive to enforce all the time, we propose some automated heuristics that can dynamically select the most appropriate filtering algorithm. Published by AI Access, a not-for-profit publisher of open access texts with a highly respected scientific board. We publish monographs and collected works. Our texts are available electronically for free and in hard copy at close to cost.

This is a must-read book for anyone who wants to learn algorithms and data structures from scratch. Written for beginners and intermediate programmers, this book provides a step-by-step guide to understanding the basics of algorithms and data structures and how they can be used to build efficient and scalable software applications. The book begins with an introduction to algorithms and data structures, explaining their importance in software development, and then moves on to cover basic terminology and concepts related to algorithms and data structures. The book provides an overview of commonly used algorithms and data structures, including arrays, linked lists, stacks, queues, trees, graphs, sorting and searching algorithms, dynamic programming, and greedy algorithms. Readers will learn how to measure algorithm performance, identify the best algorithm for a given problem, and analyze algorithm time complexity using Big O notation. The book also provides best practices for implementing algorithms and data structures in programming, highlighting real-world applications of algorithms and data structures. The book concludes with an introduction to advanced algorithms and data structures such as hash tables, tries, and heaps. Throughout the book, readers will find examples and exercises to help them understand and apply the concepts covered in each chapter. With this book, readers will gain a solid foundation in algorithms and data structures and the ability to apply this knowledge to solve real-world problems and build efficient and scalable applications.

As an experienced JavaScript developer moving to server-side programming, you need to implement classic data structures and algorithms associated with conventional object-oriented languages like C# and Java. This practical guide shows you how to work hands-on with a variety of storage mechanisms—including linked lists, stacks, queues, and graphs—within the constraints of the JavaScript environment. Determine which data structures and algorithms are most appropriate for the problems you’re trying to solve, and understand the tradeoffs when using them in a JavaScript program. An overview of the JavaScript features used throughout the book is also included. This book covers: Arrays and lists: the most common data structures Stacks and queues: more complex list-like data structures Linked lists: how they overcome the shortcomings of arrays Dictionaries: storing data as key-value pairs Hashing: good for quick insertion and retrieval Sets: useful for storing unique elements that appear only once Binary Trees: storing data in a hierarchical manner Graphs and graph algorithms: ideal for modeling networks Algorithms: including those that help you sort or search data Advanced algorithms: dynamic programming and greedy algorithms

Mastering Data Structures and Algorithms with Java is an essential guide for anyone looking to build a solid foundation in software development. Whether you're a beginner or an experienced developer, this book offers a comprehensive approach to understanding and implementing key data structures and algorithms using Java. Covering a wide range of topics, from basic structures like arrays, linked lists, and stacks, to advanced topics such as trees, graphs, heaps, and tries, the book provides clear, step-by-step explanations of each concept. In addition to covering foundational data structures, it dives into sorting and searching algorithms, dynamic programming, recursion, and graph traversal techniques like BFS and DFS. Each chapter includes real-world examples and Java implementations to bridge the gap between theory and practice. Designed for both students and professionals, Mastering Data Structures and Algorithms with Java also prepares you for coding interviews, offering a series of problem-solving exercises, coding challenges, and detailed explanations of solutions. The book is not just about learning algorithms; it’s about applying them effectively to solve real-world problems, optimize software performance, and design scalable systems. With this guide, you'll gain the skills needed to excel in technical interviews and in your software development career.

This Festschrift volume, published in honor of Kurt Mehlhorn on the occasion of his 60th birthday, contains 28 papers written by his former Ph.D. students and colleagues as well as by his former Ph.D. advisor, Bob Constable. The volume's title is a translation of the title of Kurt Mehlhorn's first book, "Effiziente Algorithmen", published by Teubner-Verlag in 1977. This Festschrift demonstrates how the field of algorithmics has developed and matured in the decades since then. The papers included in this volume are organized in topical sections on models of computation and complexity; sorting and searching; combinatorial optimization with applications; computational geometry and geometric graphs; and algorithm engineering, exactness and robustness.

Far too many programmers and software designers consider efficient C++ to be an oxymoron. They regard C++ as inherently slow and inappropriate for performance-critical applications. Consequently, C++ has had little success penetrating domains such as networking, operating system kernels, device drivers, and others. Efficient C++ explodes that myth. Written by two authors with first-hand experience wringing the last ounce of performance from commercial C++ applications, this book demonstrates the potential of C++ to produce highly efficient programs. The book reveals practical, everyday object-oriented design principles and C++ coding techniques that can yield large performance improvements. It points out common pitfalls in both design and code that generate hidden operating costs. This book focuses on combining C++'s power and flexibility with high performance and scalability, resulting in the best of both worlds. Specific topics include temporary objects, memory management, templates, inheritance, virtual functions, inlining, reference-counting, STL, and much more. With this book, you will have a valuable compendium of the best performance techniques at your fingertips. 0201379503B04062001

The ALENEX workshop provides a forum for the presentation of original research in the implementation and experimental evaluation of algorithms and data structures. This volume collects extended versions of the 12 papers that were selected for presentation.

Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types. Divided into seven parts, the text begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. The Handbook is invaluable in suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.