Kazuyuki Aihara – författare

Modeling Biomolecular Networks in Cells shows how the interaction between the molecular components of basic living organisms can be modelled mathematically and the models used to create artificial biological entities within cells.

Modeling Biomolecular Networks in Cells shows how the interaction between the molecular components of basic living organisms can be modelled mathematically and the models used to create artificial biological entities within cells. Such forward engineering is a difficult task but the nonlinear dynamical methods espoused in this book simplify the biology so that it can be successfully understood and the synthesis of simple biological oscillators and rhythm-generators made feasible. Such simple units can then be co-ordinated using intercellular signal biomolecules. The formation of such man-made multicellular networks with a view to the production of biosensors, logic gates, new forms of integrated circuitry based on "gene-chips" and even biological computers is an important step in the design of faster and more flexible "electronics". The book also provides theoretical frameworks and tools with which to analyze the nonlinear dynamical phenomena which arise from the connection of building units in a biomolecular network.

It discusses the mathematical foundations of recurrence plots and recurrence microstates and links them to future directions, such as machine learning, highlighting the potential for innovative applications.

This book collects selected contributions from the 10th Recurrence Plot Symposium, held at the University of Tsukuba, Japan (August 28-30, 2023). It reflects on the achievements of the previous nine symposia while exploring future prospects of recurrence plots and their quantifications in combination with other key research strategies. The book provides a comprehensive bibliographic overview of the methodology, offering a solid foundation for both new and experienced researchers. It discusses the mathematical foundations of recurrence plots and recurrence microstates and links them to future directions, such as machine learning, highlighting the potential for innovative applications. The text also presents an alternative approach to representing recurrences, offering fresh perspectives on this well-established technique. Additionally, it explores the two-dimensional projections of three-dimensional chromosomal structures as dot maps, opening the door to unique chromosomal descriptions in terms of recurrence quantifiers. Numerous other contributed chapters highlight the active development of this method and its clever applications to real-world systems. The book is intended for researchers working in various fields such as physics, statistics, and mathematics, with its interdisciplinary applications also benefiting experts from psychology, physiology, geosciences, finance, and engineering.

This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.