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This volume presents the growth of macrostructures in first-order nonequilibrium phase transitions in physical, chemical and biological multicomponent systems. Nonequilibrium thermodynamics and modern problems of crystallization synergetics are discussed. An introduction to computer physics of dendrites is also given. Wonderful variety in growth structures appears to be the consequence of different nonequilibrium alloy crystallization conditions and concerns problems of crystallization synergetics. This book has computer simulation results of the origin and development of the observed variety of primary macroscopic growth structures — cells, dendrites and grains should be regarded as one of the fundamental problems of alloy crystallization. Special attention is paid to the physical nature of phenomena of dendrite formation in alloys.
This is a collection of papers on Fragmentation Phenomena. It includes reviews and reports on the latest developments in fragmentation of soft matter and materials (polymers, colloids, cells, droplets and rocks), fragmentation of microscopic objects (atomic clusters and nuclei), general topics and theoretical approaches. The book addresses students and young scientists as well as researchers in theoretical and experimental aspects of fragmentation phenomena.
This monograph describes mathematical models that enable prediction of phase compositions for various technological processes, as developed on the base of a complex physico-chemical analysis of reaction. It studies thermodynamics and kinetics of specific stages of complex pyrometallurgical processes involving boron, carbon, sulfur, tungsten, phosphorus, and many more, as well as their exposure to all sorts of factors. First and foremost, this enables to optimize processes and technologies at the stage of design, while traditional empirical means of development of new technologies are basically incapable of providing an optimal solution. Simulation results of metals and alloys production, welding and coating technologies allow obtaining materials with pre-given composition, structure and properties in a cost-saving and conscious manner. Moreover, a so-called "inverse problem", i.e., selecting source materials which would ensure the required results, cannot be solved by any other means.
Advances in Low-Temperature Biology
Dendrites form the major receiving part of neurons. This text presents a survey of knowledge on dendrites, from their morphology and development, through to their electrical chemical, and computational properties.
Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.
Manufacturing Techniques for Materials: Engineering and Engineered provides a cohesive and comprehensive overview of the following: (i) prevailing and emerging trends, (ii) emerging developments and related technology, and (iii) potential for the commercialization of techniques specific to manufacturing of materials. The first half of the book provides the interested reader with detailed chapters specific to the manufacturing of emerging materials, such as additive manufacturing, with a valued emphasis on the science, technology, and potentially viable practices specific to the manufacturing technique used. This section also attempts to discuss in a lucid and easily understandable manner the specific advantages and limitations of each technique and goes on to highlight all of the potentially viable and emerging technological applications. The second half of this archival volume focuses on a wide spectrum of conventional techniques currently available and being used in the manufacturing of both materials and resultant products. Manufacturing Techniques for Materials is an invaluable tool for a cross-section of readers including engineers, researchers, technologists, students at both the graduate level and undergraduate level, and even entrepreneurs.
This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs.The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.
Neuronal dendritic trees are complex structures that endow the cell with powerful computing capabilities and allow for high neural interconnectivity. Studying the function of dendritic structures has a long tradition in theoretical neuroscience, starting with the pioneering work by Wilfrid Rall in the 1950s. Recent advances in experimental techniques allow us to study dendrites with a new perspective and in greater detail. The goal of this volume is to provide a résumé of the state-of-the-art in experimental, computational, and mathematical investigations into the functions of dendrites in a variety of neural systems. The book first looks at morphological properties of dendrites and summarizes the approaches to measure dendrite morphology quantitatively and to actually generate synthetic dendrite morphologies in computer models. This morphological characterization ranges from the study of fractal principles to describe dendrite topologies, to the consequences of optimization principles for dendrite shape. Individual approaches are collected to study the aspects of dendrite shape that relate directly to underlying circuit constraints and computation. The second main theme focuses on how dendrites contribute to the computations that neurons perform. What role do dendritic morphology and the distributions of synapses and membrane properties over the dendritic tree have in determining the output of a neuron in response to its input? A wide range of studies is brought together, with topics ranging from general to system-specific phenomena—some having a strong experimental component, and others being fully theoretical. The studies come from many different neural systems and animal species ranging from invertebrates to mammals. With this broad focus, an overview is given of the diversity of mechanisms that dendrites can employ to shape neural computations.