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Evolution of Private Law
Once again, we are pleased to present this book which is the result of the conference held in Katowice in 2022 and the effect of the international cooperation between the Research Group of the Commercial Law acting at the Faculty of Law and Administration of the University of Silesia in Katowice and representatives of foreign university departments of private law from the Czech Republic, Slovakia, and Ukraine. The publication is the continuation of the international cooperation that began in 2014. The idea of the sixth collective publication was to analyze the directions of legislative changes in the field of private law in individual countries. In this edition, the entire publication consists of fourteen articles devoted to the issues of company law, commercial contract law, including the development contract, capital market issues, and bankruptcy law. This publication is dedicated primarily to civil and commercial law academics, but it also addresses the issues relevant to legal practice. The presented papers may, to a large extent, constitute material for comparative research.
Distinction
Examines differences in taste between modern French classes, discusses the relationship between culture and politics, and outlines the strategies of pretension.
The Adult Attachment Projective Picture System
This book presents cutting-edge research on adult attachment together with a complete overview of the Adult Attachment Projective Picture System (AAP), the authors' validated developmental assessment. In addition to identifying attachment classification groups, the AAP yields important information about dimensions--including defensive processes--not evaluated by other available measures. Detailed case illustrations show what the AAP looks like "in action" and what it reveals about individuals' early experiences, sense of self, and capacity to engage in close, protective relationships. The AAP can be used in clinical or research settings; the concluding chapter discusses promising applications to studying the neurobiology of attachment.
The Great Divergence
A landmark comparative history of Europe and China that examines why the Industrial Revolution emerged in the West The Great Divergence sheds light on one of the great questions of history: Why did sustained industrial growth begin in Northwest Europe? Historian Kenneth Pomeranz shows that as recently as 1750, life expectancy, consumption, and product and factor markets were comparable in Europe and East Asia. Moreover, key regions in China and Japan were no worse off ecologically than those in Western Europe, with each region facing corresponding shortages of land-intensive products. Pomeranz’s comparative lens reveals the two critical factors resulting in Europe's nineteenth-century divergence—the fortunate location of coal and access to trade with the New World. As East Asia’s economy stagnated, Europe narrowly escaped the same fate largely due to favorable resource stocks from underground and overseas. This Princeton Classics edition includes a preface from the author and makes a powerful historical work available to new readers.
Machine Learning for Future Wireless Communications
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in w...
Convex Optimization of Power Systems
A mathematically rigorous guide to convex optimization for power systems engineering.
An Introduction to Matrix Concentration Inequalities
Random matrices now play a role in many areas of theoretical, applied, and computational mathematics. It is therefore desirable to have tools for studying random matrices that are flexible, easy to use, and powerful. Over the last fifteen years, researchers have developed a remarkable family of results, called matrix concentration inequalities, that achieve all of these goals. This monograph offers an invitation to the field of matrix concentration inequalities. It begins with some history of random matrix theory; it describes a flexible model for random matrices that is suitable for many problems; and it discusses the most important matrix concentration results. To demonstrate the value of these techniques, the presentation includes examples drawn from statistics, machine learning, optimization, combinatorics, algorithms, scientific computing, and beyond.
