Complexity, Chaos, and Biological Evolution
From time to time, perhaps a few times each century, a revolution occurs that questions some of our basic beliefs and sweeps across otherwise well guarded disciplinary boundaries. These are the periods when science is fun, when new paradigms have to be formulated, and when young scientists can do serious work without first having to acquire all the knowledge of their teachers. The emergence of nonlinear science appears to be one such revolution. In a surprising manner, this new science has disclosed a number of misconceptions in our traditional understanding of determinism. In particular, it has been shown that the notion of predictability, according to which the trajectory of a system can be precisely determined if one knows the equations of motion and the initial conditions, is related to textbook examples of simple; integrable systems. This predictability does not extend to nonlinear, conservative systems in general. Dissipative systems can also show unpredictability, provided that the motion is sustained by externally supplied energy and/or resources. These discoveries, and the associated discovery that even relatively simple nonlinear systems can show extremely complex behavior, have brought about an unprecedented feeling of common interest among scientists from many different disciplines. During the last decade or two we have come to understand that there are universal routes to chaos, we have learned about stretching and folding, and we have discovered the beautiful fractal geometry underlying chaotic attractors.
1000847629
Complexity, Chaos, and Biological Evolution
From time to time, perhaps a few times each century, a revolution occurs that questions some of our basic beliefs and sweeps across otherwise well guarded disciplinary boundaries. These are the periods when science is fun, when new paradigms have to be formulated, and when young scientists can do serious work without first having to acquire all the knowledge of their teachers. The emergence of nonlinear science appears to be one such revolution. In a surprising manner, this new science has disclosed a number of misconceptions in our traditional understanding of determinism. In particular, it has been shown that the notion of predictability, according to which the trajectory of a system can be precisely determined if one knows the equations of motion and the initial conditions, is related to textbook examples of simple; integrable systems. This predictability does not extend to nonlinear, conservative systems in general. Dissipative systems can also show unpredictability, provided that the motion is sustained by externally supplied energy and/or resources. These discoveries, and the associated discovery that even relatively simple nonlinear systems can show extremely complex behavior, have brought about an unprecedented feeling of common interest among scientists from many different disciplines. During the last decade or two we have come to understand that there are universal routes to chaos, we have learned about stretching and folding, and we have discovered the beautiful fractal geometry underlying chaotic attractors.
54.99 In Stock
Complexity, Chaos, and Biological Evolution

Complexity, Chaos, and Biological Evolution

Complexity, Chaos, and Biological Evolution

Complexity, Chaos, and Biological Evolution

Paperback(1991)

$54.99 
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Overview

From time to time, perhaps a few times each century, a revolution occurs that questions some of our basic beliefs and sweeps across otherwise well guarded disciplinary boundaries. These are the periods when science is fun, when new paradigms have to be formulated, and when young scientists can do serious work without first having to acquire all the knowledge of their teachers. The emergence of nonlinear science appears to be one such revolution. In a surprising manner, this new science has disclosed a number of misconceptions in our traditional understanding of determinism. In particular, it has been shown that the notion of predictability, according to which the trajectory of a system can be precisely determined if one knows the equations of motion and the initial conditions, is related to textbook examples of simple; integrable systems. This predictability does not extend to nonlinear, conservative systems in general. Dissipative systems can also show unpredictability, provided that the motion is sustained by externally supplied energy and/or resources. These discoveries, and the associated discovery that even relatively simple nonlinear systems can show extremely complex behavior, have brought about an unprecedented feeling of common interest among scientists from many different disciplines. During the last decade or two we have come to understand that there are universal routes to chaos, we have learned about stretching and folding, and we have discovered the beautiful fractal geometry underlying chaotic attractors.

Product Details

ISBN-13: 9781468478495
Publisher: Springer US
Publication date: 11/26/2012
Series: NATO Science Series B: , #270
Edition description: 1991
Pages: 431
Product dimensions: 7.01(w) x 10.00(h) x 0.04(d)

Table of Contents

Section I: An Introductory Overview.- Structure, Complexity and Chaos in Living Systems.- Probing Dynamics of the Cerebral Cortex.- Chaos and Bifurcations During Voiced Speech.- The Ultradian Clock: Timekeeping for Intracellular Dynamics.- Section II: Complex Dynamics in Physiological Control Systems.- Complex Dynamics in the Kidney Microcirculation.- Aspects of Oscillatory Insulin Secretion.- The Dynamic Code: Information Transfer in Hormonal Systems.- Structural Amplification in Chemical Networks.- Section III: Membrane Activity and Cell to Cell Signalling.- Periodicity and Chaos in cAMP, Hormonal and Ca2+ Signalling.- Fractal, Chaotic, and Self-Organizing Critical System: Descriptions of the Kinetics of Cell Membrane Ion Channels.- A Discontinuous Model for Membrane Activity.- Chaos in Coupled Nerve Cells.- Analysis of the Adenine Nucleotide Pool in an Oscillating Extract of Yeast Saccharomyces uvarum.- Boundary Operator and Distance Measure for the Cell Lineage of Caenorhabditis elegans and for the Pattern in Fusarium solani.- Section IV: Evolutionary Dynamics and Artificial Life.- Mutations and Selection in Evolutionary Processes.- Considerations of Stability in Models of Primitive Life: Effect of Errors and Error Propagation.- Information Dynamics of Self-Programmable Matter.- The Problem of Medium-Independence in Artificial Life.- An Optimality Approach to Ageing.- Modelling of Complex Systems by Simulated Annealing.- Section V: Biological Structures and Morphogenesis.- Generic Dynamics of Morphogenesis.- Models of Biological Pattern Formation and Their Application to the Early Development of Drosophila.- Reaction-Diffusion Prepatterns (Turing Structures): Supercomputer Simulation of Cytokinesis, Mitosis and Early Drosophila Morphogenesis.- Vortex Formation in Excitable Media.- Bone Remodeling.- Section VI: Chaos and Hyperchaos.- Childhood Infections — Examples of “Chaos in the Wild”.- Multifractal Analysis of Morphological Patterns in Normal and Malignant Human Tissues.- Method of Compatible Vectorfield in Studying Integrability of 3-Dimensional Dynamical Systems.- Discrete Steps Up the Dynamic Hierarchy.- Hyperchaotic Phenomena in Dynamic Decision Making.- Participants.
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