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This book explores the impact of nonlinearity on a broad range of areas, including time-honored fields such as biology, geometry, and topology, but also modern ones such as quantum mechanics, networks, metamaterials and artificial intelligence. The concept of nonlinearity is a universal feature in mathematics, physics, chemistry and biology, and is used to characterize systems whose behavior does not amount to a superposition of simple building blocks, but rather features complex and often chaotic patterns and phenomena. Each chapter of the book features a synopsis that not only recaps the recent progress in each field but also charts the challenges that lie ahead. This interdisciplinary book presents contributions from a diverse group of experts from various fields to provide an overview of each field’s past, present and future. It will appeal to both beginners and seasoned researchers in nonlinear science, numerous areas of physics (optics, quantum physics, biophysics), and applied mathematics (ODEs, PDEs, dynamical systems, machine learning) as well as engineering.
For almost ten years chaos and fractals have been enveloping many areas of mathematics and the natural sciences in their power, creativity and expanse. Reaching far beyond the traditional bounds of mathematics and science to the realms of popular culture, they have captured the attention and enthusiasm of a worldwide audience. The fourteen chapters of the book cover the central ideas and concepts, as well as many related topics including, the Mandelbrot Set, Julia Sets, Cellular Automata, L-Systems, Percolation and Strange Attractors, and each closes with the computer code for a central experiment. In the two appendices, Yuval Fisher discusses the details and ideas of fractal image compression, while Carl J.G. Evertsz and Benoit Mandelbrot introduce the foundations and implications of multifractals.
This book is comprised of the latest research into CSS methods, uses, and results, as presented at the 2020 annual conference of the Computational Social Science Society of the Americas (CSSSA). Computational social science (CSS) is the science that investigates social and behavioral dynamics through social simulation, social network analysis, and social media analysis. The CSSSA is a professional society that aims to advance the field of computational social science in all areas, including basic and applied orientations, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing research findings and results. The above-mentioned conference was held virtually, October 8 – 11, 2020. What follows is a diverse representation of new results and approaches to using the tools of CSS and agent-based modeling (ABM) in exploring complex phenomena across many different domains. Readers will therefore not only have the results of these specific projects upon which to build, along with a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities, they will also gain a greater appreciation for the broad scope of CSS.
Utilization of electrodiagnosis; namely electromyography (EMG), nerve conduction studies, late responses, repetitive nerve stimulation techniques, quantitative EMG and evoked potentials, has long been discussed in many text books as basic principles. However the usage of electroneuromyography is rather new in some aspects when compared with tasks of daily practise. This book, we believe, will cover and enlighten those aspects where electrodiagnosis has begun to play important roles nowadays.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks.
This forward-looking Research Handbook showcases cutting-edge research on the relationship between international migration and digital technology. It sheds new light on the interlinkages between digitalisation and migration patterns and processes globally, capturing the latest research technologies and data sources. Featuring international migration in all facets from the migration of tech sector specialists through to refugee displacement, leading contributors offer strategic insights into the future of migration and mobility.
In a financial revolution, new determinants of performance arise and interest in the way performance is measured and communicated to stakeholders grows. This book presents a wide and accurate analysis of the impact that regulation, structural changes and new financial products have on the performance of markets and intermediaries.
The 2nd edition of this book provides novel topics and studyies in boundaries of networks and Big Data Systems.The central theme of this book is the extent to which the structure of the free dynamical boundaries of a system controls the evolution of the system as a whole. Applying three orthogonal types of thinking - mathematical, constructivist and morphological, it illustrates these concepts using applications to selected problems from the social and life sciences, as well as economics. In a broader context, it introduces and reviews some modern mathematical approaches to the science of complex systems. Standard modeling approaches (based on non-linear differential equations, dynamic systems, graph theory, cellular automata, stochastic processes, or information theory) are suitable for studying local problems. However they cannot simultaneously take into account all the different facets and phenomena of a complex system, and new approaches are required to solve the challenging problem of correlations between phenomena at different levels and hierarchies, their self-organization and memory-evolutive aspects, the growth of additional structures and are ultimately required to explain why and how such complex systems can display both robustness and flexibility. This graduate-level text addresses a broader interdisciplinary audience, keeping the mathematical level essentially uniform throughout the book, and involving only basic elements from calculus, algebra, geometry and systems theory.
Nowadays, graph theory is an important analysis tool in mathematics and computer science. Because of the inherent simplicity of graph theory, it can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. The purpose of this book is not only to present the latest state and development tendencies of graph theory, but to bring the reader far enough along the way to enable him to embark on the research problems of his own. Taking into account the large amount of knowledge about graph theory and practice presented in the book, it has two major parts: theoretical researches and applications. The book is also intended for both graduate and postgraduate students in fields such as mathematics, computer science, system sciences, biology, engineering, cybernetics, and social sciences, and as a reference for software professionals and practitioners.