A nonsimple (complex) system indicates a mix of crucial and non-crucial events, with very different statistical properties. It is the crucial events that determine the efficiency of information exchange between complex networks. For a large class of nonsimple systems, crucial events determine catastrophic failures - from heart attacks to stock market crashes.This interesting book outlines a data processing technique that separates the effects of the crucial from those of the non-crucial events in nonsimple time series extracted from physical, social and living systems. Adopting an informal conversational style, without sacrificing the clarity necessary to explain, the contents will lead the reader through concepts such as fractals, complexity and randomness, self-organized criticality, fractional-order differential equations of motion, and crucial events, always with an eye to helping to interpret what mathematics usually does in the development of new scientific knowledge.Both researchers and novitiate will find Crucial Events useful in learning more about the science of nonsimplicity.

This book describes a new strategy for rehabilitation from injury and/or disease using Crucial Event Therapy. Recent studies have shown that individuals can recuperate more rapidly from surgery and other invasive procedures intended to correct the negative effects of disease or injury through the use of life support systems that operate at the body's natural biofrequencies. The same observation has been clinically shown to reverse the degenerative effects of neurodegenerative diseases such as Parkinson’s and Alzheimer's Disease. Crucial Event Therapy describes medicine as the operational control of the functions of the human body treated as a network-of-networks, with 1/f-variable crucial events coding the dynamic states of health and disease through information flow within a network and information exchange between biomedical networks. A new way of thinking based on the statistics of Cortical Events is presented and the relevant literature is suitably referenced. This is an ideal book for biophysicists and data scientists seeking to understand the connection of complexity measures for the study of consciousness with the clinical aspects of designing a rehabilitation strategy.

Contemporary events management is a diverse and challenging field. This introductory textbook fully explores the multidisciplinary nature of events management and provides the student with all the practical skills and professional knowledge they need to succeed in the events industry. It introduces every core functional area of events management, such as marketing, finance, project management, strategy, operations, event design and human resources, in a vast array of different event settings from sport to political events. This new edition has been updated to include: New and updated content on technological developments in events such as virtual/hybrid events, artificial intelligence, virtual/augmented reality, holograms in music events, software for event planning and projection mapping. New content on eSports, the sustainability sector, employability skills, policy changes, diversity and inclusion, ethics and responsibility in events, and contemporary event safety and security issues including the threat of terrorism. New and updated case studies that cover a wider range of regions. A fully updated and extended companion website that includes web and video links, quizzes and a case study archive for students, as well as PowerPoint slides for instructors and a brand-new instructor manual full of teaching strategy ideas. Every topic is brought to life through vivid case studies, personal biographies and examples of best practice from the real world of events management. Written by a team of authors with many years’ experience of working in the events industry, Events Management: An Introduction is the essential course text for any events management programme.

Memory Observed brings together classic and contemporary essays to explore the processes of memory in real-life contexts. Covering such issues as childhood recollections, eyewitness testimony, special memory feats, and memories of famous individuals, the writings support the authors' thesis that understanding how human memory works requires greater emphasis on everyday situations and less on controlled laboratory experiments. The much-anticipated new edition has been thoroughly updated with over 40% new essays, increased coverage of early childhood memories and memories of traumatic events, and an expanded introductory section. Neisser offers a thought-provoking supplement for courses in memory, learning and cognition.

The biological basis of physiological signals is incredibly complex. While many types of research certainly appreciate molecular, cellular and systems approach to unravel overall biological complexity, in the recent decades the interest for mathematical and computational characterization of structural and functional basis underlying biological phenomena gain wide popularity among scientists. Nowadays, we witnessed wide range applications of nonlinear quantitative analysis that produced measures such as fractal dimension, power-law scaling, Hurst exponent, Lyapunov exponent, approximate entropy, sample entropy, Lempel–Ziv complexity, as well as other metrics for predictions of onset and progression of many pathological conditions, especially in the central nervous systems (CNS). In this Research Topic, we seek to bring together the recent practical and theoretical advances in the development and application of nonlinear methods or narrower fractal-based methods for characterizing the complex physiological systems at multiple levels of the organization. We will discuss the use of various complexity measures and appropriate parameters for characterizing the variety of physiological signals up to the systems level. There are multiple aims in this topic. The recent advancement in the application of nonlinear methods for both normal and pathological physiological conditions is the first. The second aim is to emphasize the more recent successful attempt to apply these methods across animal species. Finally, a comprehensive understanding of advantages and disadvantages of each method, especially between its mathematical assumptions and real-world applicability, can help to find out what is at stake regarding the above aims and to direct us toward the more fruitful application of nonlinear measures and statistics in physiology and biology in general.

This book constitutes the refereed proceedings of the 20th International Conference on Computer Aided Verification, CAV 2008, held in Princeton, NJ, USA, in July 2008. The 33 revised full papers presented together with 14 tool papers and 2 invited papers and 4 invited tutorials were carefully reviewed and selected from 104 regular paper and 27 tool paper submissions. The papers are organized in topical sections on concurrency, memory consistency, abstraction/refinement, hybrid systems, dynamic verification, modeling and specification formalisms, decision procedures, program verification, program and shape analysis, security and program analysis, hardware verification, model checking, space efficient algorithms, and model checking.

Complex Webs synthesises modern mathematical developments with a broad range of complex network applications of interest to the engineer and system scientist, presenting the common principles, algorithms, and tools governing network behaviour, dynamics, and complexity. The authors investigate multiple mathematical approaches to inverse power laws and expose the myth of normal statistics to describe natural and man-made networks. Richly illustrated throughout with real-world examples including cell phone use, accessing the Internet, failure of power grids, measures of health and disease, distribution of wealth, and many other familiar phenomena from physiology, bioengineering, biophysics, and informational and social networks, this book makes thought-provoking reading. With explanations of phenomena, diagrams, end-of-chapter problems, and worked examples, it is ideal for advanced undergraduate and graduate students in engineering and the life, social, and physical sciences. It is also a perfect introduction for researchers who are interested in this exciting new way of viewing dynamic networks.