The book, based on memories of a native son and the research of a scholar, is an amalgam of descriptions and discussions, peppered with conversations, personal observations and an acute observer's reflections, focused on the fabric of life in the city of Lodz and its vicinity. The author describes the "court" of the Hasidic Rabbis of Alexander, with which his family was affiliated, the rival camps of Hasidim and Zionists, industrialists and laborers, struggles with the Polish authorities, and more. Detailed chapters are dedicated to a description of studies at a modern Jewish-Zionist high school (Gymnasium) - its exhilarating goals, directors and teachers, to the Lodz poet Yitzhak Katzenelson before and during the Holocaust, and to life in a small Polish shtetl. The concluding chapter "Return to Poland" examines the cities and towns described earlier in the book, as well as Breslau-Wroclaw, where the author had completed his rabbinic and university studies in 1933, as they appeared to him during his visit in 1982, nearly fifty years after his departure from Europe for Israel. The author's aim was to produce a portrait, sympathetic, intimate, but also knowledgeable and critical, of a generation that did not have the time to take stock of itself before its obliteration. He has thus rendered palpable the experiences and quandaries of many of his contemporaries.

This book contains original research chapters related to the interdisciplinary field of complex networks spanning biological and environmental networks, social, technological, and economic networks. Many natural phenomena can be modeled as networks where nodes are the primitive compounds and links represent their interactions, similarities, or distances of sorts. Complex networks have an enormous impact on research in various fields like biology, social sciences, engineering, and cyber-security to name a few. The topology of a network often encompasses important information on the functionality and dynamics of the system or the phenomenon it represents. Network science is an emerging interdisciplinary discipline that provides tools and insights to researchers in a variety of domains. NetSci-X is the central winter conference within the field and brings together leading researchers and innovators to connect, meet, and establish interdisciplinary channels for collaboration. It is the largest and best known event in the area of network science. This text demonstrates how ideas formulated by authors with different backgrounds are transformed into models, methods, and algorithms that are used to study complex systems across different domains and will appeal to researchers and students within in the field.

In this volume, Professor Shmueli, a distinguished Israeli scholar, has synthesized history, philosophy, biblical scholarship, sociology, literature and psychology into an original and profound view of Jewish history. Jewish history is viewed as an unfolding of seven successive systems of cultures, where each culture emerges in its time both as a rebel and a successor of previous cultures. Each presents itself as a distinct and often startlingly different framework in which the meaning of Jewish life is always interpreted anew. In this sense, Jewish history may be said to have undergone seven great 'Renaissances'. Seven Jewish Cultures emphasizes the chasm which divides the five 'cultures of faith' from the secular cultures of the Emancipation and nationalist-Israeli periods. Shmueli argues that the cultures of modernity have created a new frame of reference for the Jewish people. No longer is Jewish history viewed as a divine drama, and no longer is the Bible seen as the hermeneutical key to all Jewish problems.

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

The book, based on memories of a native son and the research of a scholar, is an amalgam of descriptions and discussions, peppered with conversations, personal observations and an acute observer's reflections, focused on the fabric of life in the city of Lodz and its vicinity. The author describes the "court" of the Hasidic Rabbis of Alexander, with which his family was affiliated, the rival camps of Hasidim and Zionists, industrialists and laborers, struggles with the Polish authorities, and more. Detailed chapters are dedicated to a description of studies at a modern Jewish-Zionist high school (Gymnasium) - its exhilarating goals, directors and teachers, to the Lodz poet Yitzhak Katzenelson before and during the Holocaust, and to life in a small Polish shtetl. The concluding chapter "Return to Poland" examines the cities and towns described earlier in the book, as well as Breslau-Wroclaw, where the author had completed his rabbinic and university studies in 1933, as they appeared to him during his visit in 1982, nearly fifty years after his departure from Europe for Israel. The author's aim was to produce a portrait, sympathetic, intimate, but also knowledgeable and critical, of a generation that did not have the time to take stock of itself before its obliteration. He has thus rendered palpable the experiences and quandaries of many of his contemporaries.

The "smart mobile" has become an essential and inseparable part of our lives. This powerful tool enables us to perform multi-tasks in different modalities of voice, text, gesture, etc. The user plays an important role in the mode of operation, so multimodal interaction provides the user with new complex multiple modalities of interfacing with a system, such as speech, touch, type and more. The book will discuss the new world of mobile multimodality, focusing on innovative technologies and design which create a state-of-the-art user interface. It will examine the practical challenges entailed in meeting commercial deployment goals, and offer new approaches to the designing such interfaces. A multimodal interface for mobile devices requires the integration of several recognition technologies together with sophisticated user interface and distinct tools for input and output of data. The book will address the challenge of designing devices in a synergetic fashion which does not burden the user or to create a technological overload.

Machine learning --also known as data mining or predictive analytics-- is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Analytic Solver Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

Machine learning --also known as data mining or data analytics-- is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the seventh edition of Machine Learning for Business Analytics, and the first using RapidMiner software. This edition also includes: A new co-author, Amit Deokar, who brings experience teaching business analytics courses using RapidMiner Integrated use of RapidMiner, an open-source machine learning platform that has become commercially popular in recent years An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

Machine learning --also known as data mining or data analytics-- is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: - A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R - An expanded chapter focused on discussion of deep learning techniques - A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning - A new chapter on responsible data science - Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students - A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques - End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented - A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

This book contains original research chapters related to the interdisciplinary field of complex networks spanning biological and environmental networks, social, technological, and economic networks. Many natural phenomena can be modeled as networks where nodes are the primitive compounds and links represent their interactions, similarities, or distances of sorts. Complex networks have an enormous impact on research in various fields like biology, social sciences, engineering, and cyber-security to name a few. The topology of a network often encompasses important information on the functionality and dynamics of the system or the phenomenon it represents. Network science is an emerging interdisciplinary discipline that provides tools and insights to researchers in a variety of domains. NetSci-X is the central winter conference within the field and brings together leading researchers and innovators to connect, meet, and establish interdisciplinary channels for collaboration. It is the largest and best known event in the area of network science. This text demonstrates how ideas formulated by authors with different backgrounds are transformed into models, methods, and algorithms that are used to study complex systems across different domains and will appeal to researchers and students within in the field.

International Tables for Crystallography is the definitive resource and reference work for crystallography and structural science. Volume B presents accounts of the numerous aspects of reciprocal space in crystallographic research. This volume is a vital addition to the library of scientists engaged in crystal structure determination, crystallographic computing, crystal physics and other fields of crystallographic research. Graduate students specializing in crystallography will find much material suitable for self-study and a rich source of references to the relevant literature. New to this edition: A new chapter on modern extensions of the Ewald method for Coulomb interactions in crystals. Three new sections on electron diffraction and electron microscopy in structure determination, describing point-group and space-group determination by convergent-beam electron diffraction, three-dimensional reconstruction, and single-particle reconstruction. Substantial revisions to the chapters on space-group representations in reciprocal space, direct methods, Patterson and molecular replacement techniques, and disorder diffuse scattering More information on the series can be found at: http: //it.iucr.org

This Brief provides a contextual framework for exploring the settlement rights of Israel's Bedouin population of the Negev desert, a traditionally pastoral nomadic Arab population. In 1948, the Israeli government relocated this population from the Negev region to settlements in Siyag. The explicit aim was to control the Negev area for security purposes, sedentarize a nomadic people, and to improve their living conditions and bring them into the modern economy. Since then, many of the Bedouin population have continued to urbanize, moving into smaller towns and cities, while some remain in the settlement. The Israeli government's has recently proposed a new settlement policy towards the Bedouin population, that would expel many from their current homes, which came into recent controversy with the UN Human Rights commission, causing it to be withdrawn. Israel as a whole has very complex social, cultural, and political fabric with territorial uncertainties. This Brief aims to provide an overview of the current situation, provide a theoretical, historical and legal context, explore barriers to implementation of previously proposed policies, and provide potential solutions to improve individual and collective stability and balance the cultural and territorial needs of the Bedouin population with the larger goals of the Israeli government. This work will be of interest to researchers studying Israel specifically, as well as researchers in urban planning, public policy, and issues related to indigenous populations and human rights.

Maimonides lived in Spain and Egypt in the twelfth century, and is perhaps the most widely studied figure in Jewish history. This book presents, for the first time, Maimonides' complete tort theory and how it compares with other tort theories both in the Jewish world and beyond. Drawing on sources old and new as well as religious and secular, Maimonides and Contemporary Tort Theory offers fresh interdisciplinary perspectives on important moral, consequentialist, economic, and religious issues that will be of interest to both religious and secular scholars. The authors mention several surprising points of similarity between certain elements of theories recently formulated by North American scholars and the Maimonidean theory. Alongside these similarities significant differences are also highlighted, some of them deriving from conceptual-jurisprudential differences and some from the difference between religious law and secular-liberal law.

Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP Pro(R), a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) also includes: * Detailed summaries that supply an outline of key topics at the beginning of each chapter * End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material * Data-rich case studies to illustrate various applications of data mining techniques * A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field. Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks, and book chapters, including Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition, also published by Wiley. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective and co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner (R), Third Edition, both published by Wiley. Mia Stephens is Academic Ambassador at JMP(R), a division of SAS Institute. Prior to joining SAS, she was an adjunct professor of statistics at the University of New Hampshire and a founding member of the North Haven Group LLC, a statistical training and consulting company. She is the co-author of three other books, including Visual Six Sigma: Making Data Analysis Lean, Second Edition, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years. He is co-author of Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition, also published by Wiley.

The Bureaucracy of Empathy revolves around two central questions: What is pain? And how do we recognize, understand, and ameliorate the pain of nonhuman animals? Shira Shmuely investigates these ethical issues through a close and careful history of the origins, implementation, and enforcement of the 1876 Cruelty to Animals Act of Parliament, which for the first time imposed legal restrictions on animal experimentation and mandated official supervision of procedures "calculated to give pain" to animal subjects. Exploring how scientists, bureaucrats, and lawyers wrestled with the problem of animal pain and its perception, Shmuely traces in depth and detail how the Act was enforced, the medical establishment's initial resistance and then embrace of regulation, and the challenges from anti-vivisection advocates who deemed it insufficient protection against animal suffering. She shows how a "bureaucracy of empathy" emerged to support and administer the legislation, navigating incongruent interpretations of pain. This crucial moment in animal law and ethics continues to inform laws regulating the treatment of nonhuman animals in laboratories, farms, and homes around the worlds to the present.

This concise book for chemists, material scientists, and physicists who deal with description of crystalline matter and the determination of its structure, and would like to gain more understanding of the principles involved. The main purpose of the book is to introduce the reader to principles of crystallographic symmetry, to discuss some traditional, as well as modern, experimental techniques, to formulate the phase problem of crystallographic symmetry, to discus some traditional, as well as modern, experimental techniques, to formulate the phase problem of crystallography, and present in some detail the methods for its indirect and direct solution which are indispensable for further work. The book also contains discussions of structure-factor statistics, or value for resolving space-group ambiguities, and atomic displacement parameters, which form an inseparable part of the structure. A discussion of the refinement of structural parameters, conventional, constrained and restrained, concludes the book. Derivations are as far as possible, self contained and wherever mathematical detail might disrupt the line of reasoning the reader is referred to on of four appendices present in the book. The book is of course valuable for students of crystallography at a graduate and upper undergraduate level. No previous course on crystallography is a prerequisite for graduates in the above fields.

Maimonides lived in Spain and Egypt in the twelfth century, and is perhaps the most widely studied figure in Jewish history. This book presents, for the first time, Maimonides' complete tort theory and how it compares with other tort theories both in the Jewish world and beyond. Drawing on sources old and new as well as religious and secular, Maimonides and Contemporary Tort Theory offers fresh interdisciplinary perspectives on important moral, consequentialist, economic, and religious issues that will be of interest to both religious and secular scholars. The authors mention several surprising points of similarity between certain elements of theories recently formulated by North American scholars and the Maimonidean theory. Alongside these similarities significant differences are also highlighted, some of them deriving from conceptual-jurisprudential differences and some from the difference between religious law and secular-liberal law.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. "This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject." --Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization. You can check out the book's website here.

Professor Shmueli has synthesized history, philosophy, biblical scholarship, sociology, literature and psychology into an original and profound new view of Jewish history. Jewish history is viewed as an unfolding of seven successive systems of cultures, where each culture emerges in its time both as a rebel and a successor of previous cultures. Each presents itself as a distinct and often startlingly different framework in which the meaning of Jewish life is always interpreted anew. In this sense, Jewish history may be said to have undergone seven great "Renaissances." This study emphasizes the chasm that divides the five "cultures of faith" from the secular cultures of the Emancipation and nationalist-Israeli periods. Shmueli argues that the cultures of modernity have created a new frame of reference for the Jewish people. No longer is Jewish history viewed as a divine drama, and no longer is the Bible seen as the hermeneutical key to all Jewish problems. Both in Israel and outside it, claims Shmueli, there is a need for a new balance that will retain the creative elements of the past and, at the same time, permit reinterpretation and change.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft(R) Office Excel(R) add-in XLMiner(R) to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: * Real-world examples to build a theoretical and practical understanding of key data mining methods * End-of-chapter exercises that help readers better understand the presented material * Data-rich case studies to illustrate various applications of data mining techniques * Completely new chapters on social network analysis and text mining * A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint(R) slides * Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition " full of vivid and thought-provoking anecdotes...needs to be read by anyone with a serious interest in research and marketing." Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.

Modern structural applications of crystallography make extensive use of statistical methods, in particular the probability density function (pdf) of the magnitude of the structure factor. Similarly, direct methods of phase determination have been responsible for much of the success of crystallography - methods based on properties of joint pdfs. This monograph, from two authorities in the field of structure factor statics, presents a survey of techniques and theories in this field of research in a self-contained and consistent way, with an emphasis on the probabilistic principles involved.

The Bureaucracy of Empathy revolves around two central questions: What is pain? And how do we recognize, understand, and ameliorate the pain of nonhuman animals? Shira Shmuely investigates these ethical issues through a close and careful history of the origins, implementation, and enforcement of the 1876 Cruelty to Animals Act of Parliament, which for the first time imposed legal restrictions on animal experimentation and mandated official supervision of procedures "calculated to give pain" to animal subjects. Exploring how scientists, bureaucrats, and lawyers wrestled with the problem of animal pain and its perception, Shmuely traces in depth and detail how the Act was enforced, the medical establishment's initial resistance and then embrace of regulation, and the challenges from anti-vivisection advocates who deemed it insufficient protection against animal suffering. She shows how a "bureaucracy of empathy" emerged to support and administer the legislation, navigating incongruent interpretations of pain. This crucial moment in animal law and ethics continues to inform laws regulating the treatment of nonhuman animals in laboratories, farms, and homes around the worlds to the present.

Kierkegaard's philosophy is the description of the structure and behavior of human consciousness. Adi Shmueli reconstructs that philosophy by showing that it always reflects the structure in question, and thus provides a useful key to Kierkegaard's work. Mr. Shmueli approaches his task by analyzing first the aesthetic, ethical, and religious stages of life as successive steps in the gradual awakening of consciousness. He then describes the alienation of consciousness, of which Kierkegaard speaks in all his works, and discusses Kierkegaard's theory of indirect communication, philosophical action whose aim is to awaken consciousness in order to rescue it from alienation. Studying Kierkegaard's observations on Christianity as indirect communication, Professor Shmueli deals also with his reflections on the philosophical problem of truth. His concluding chapter discusses the temporality and historicity of human consciousness. Quotations, taken primarily from accessible English translations, are generously provided to put the reader in direct contact with Kierkegaard's own words. Originally published in 1971. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Kierkegaard's philosophy is the description of the structure and behavior of human consciousness. Adi Shmueli reconstructs that philosophy by showing that it always reflects the structure in question, and thus provides a useful key to Kierkegaard's work. Mr. Shmueli approaches his task by analyzing first the aesthetic, ethical, and religious stages of life as successive steps in the gradual awakening of consciousness. He then describes the alienation of consciousness, of which Kierkegaard speaks in all his works, and discusses Kierkegaard's theory of indirect communication, philosophical action whose aim is to awaken consciousness in order to rescue it from alienation. Studying Kierkegaard's observations on Christianity as indirect communication, Professor Shmueli deals also with his reflections on the philosophical problem of truth. His concluding chapter discusses the temporality and historicity of human consciousness. Quotations, taken primarily from accessible English translations, are generously provided to put the reader in direct contact with Kierkegaard's own words. Originally published in 1971. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.