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\"Computational Fluid-Structure Interaction is a complete, self-contained reference that takes the reader from the fundamentals of computational fluid and solid mechanics all the way to the state-of-the-art in CFSI research\"--

A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.

Synthesizing knowledge acquired as a result of significant research and development over recent years, Smart Structures clearly illustrates why these structures are of such intense current interest. Gaudenzi offers valuable insight into both how they behave and how and at what cost they could be designed and produced for real life applications in cutting edge fields such as vibration control, shape morphing, structural health monitoring and energy transduction.   Smart Structures offers a basic and fundamental description of smart structures from the physical, mathematical and engineering viewpoint. It explains the basic physics relating to the behaviour of active materials, gives the mathematical background behind the phenomena, and provides tools for numerical simulation. It also offers an insight into considerations related to the manufacturing, assembly and integration of smart structures.   Smart Structures is divided into 5 sections: in the first part a definition of smart structures is proposed, the motivation for developing a smart structure presented and the basic physics of active materials such aspiezoelectrics, electrostrictives, magnetostrictives and shape memory alloys briefly recalled. A second part is devoted to the mathematical modelling of piezoelectric bodies. The third part discusses actuation and sensing mechanisms based on which the active part of a smart structure will produce \"results\" on the passive one. The fourth part deals with active composites at the micromechanical and macromechanical level, and the fifth part is devoted to applications of smart structures with examples taken from the aerospace field.   This introduction to smart structures will be useful both for structural and mechanical designers, and for students and researchers at graduate level or beyond. The diverse industries involved in this rapidly evolving field include aerospace, automotive and bioengineering.

Modelling forms a vital part of all engineering design, yet many hydraulic engineers are not fully aware of the assumptions they make. These assumptions can have important consequences when choosing the best model to inform design decisions. Considering the advantages and limitations of both physical and mathematical methods, this book will help you identify the most appropriate form of analysis for the hydraulic engineering application in question. All models require the knowledge of their background, good data and careful interpretation and so this book also provides guidance on the range of accuracy to be expected of the model simulations and how they should be related to the prototype. Applications for models include: Open channel systems; Closed conduit flows; Storm drainage systems; Estuaries; Coastal and nearshore structures; Hydraulic structures. An invaluable guide for students and professionals.

Electronic Structure Calculations on Graphics Processing Units: From Quantum Chemistry to Condensed Matter Physics provides an overview of computing on graphics processing units (GPUs), a brief introduction to GPU programming, and the latest examples of code developments and applications for the most widely used electronic structure methods. The book covers all commonly used basis sets including localized Gaussian and Slater type basis functions, plane waves, wavelets and real-space grid-based approaches. The chapters expose details on the calculation of two-electron integrals, exchange-correlation quadrature, Fock matrix formation, solution of the self-consistent field equations, calculation of nuclear gradients to obtain forces, and methods to treat excited states within DFT. Other chapters focus on semiempirical and correlated wave function methods including density fitted second order Møller-Plesset perturbation theory and both iterative and perturbative single- and multireference coupled cluster methods. Electronic Structure Calculations on Graphics Processing Units: From Quantum Chemistry to Condensed Matter Physics presents an accessible overview of the field for graduate students and senior researchers of theoretical and computational chemistry, condensed matter physics and materials science, as well as software developers looking for an entry point into the realm of GPU and hybrid GPU/CPU programming for electronic structure calculations.

A novel spacetime theory was developed to model the atomic structure and the law of electronic motion. Four space dimensions are four geometric elements in a sphere: two periphery points, two semicircular arcs, two hemispherical surfaces, and the inner and outer solid spheres that correspond to the electron octet in a neon shell. The dimension stairs within the atoms are the theoretical basis of electronic orbital quantization in quantum mechanics. The law of nature is dynamic calculus of spherical quantities that defines the motion of an electron from one dimension to another featuring general harmonic oscillation. The fresh mindset will subvert the traditional worldview. Two-dimensional spacetime is described with the instantiation of a helium shell in rigorous mathematics and extended to life phenomena. A husband and a wife are two dimensions of the family; and animals and plants are two kingdoms of the advanced lives. The interplay and transformation between both dimensions are the eternal theme of nature and can be abstracted as a mathematical rope. A DNA molecule, composed of space and time strands, is a stepwise LC oscillatory circuitry or a rope; so is a human lineage with both sexes. Under the four-dimensional space framework, we formulate the wave functions of all electrons within inert atoms. The electronic structure of a chiral carbon conforms to the yin and yang theory and the five element theory in traditional Chinese medicine. It constitutes a physical instance of spherical quantity solutions to three-dimensional Schrödinger's equation. Spherical quantities in dynamic calculus complement physical quantities with linear algebra, comply with the Pythagorean theorem and Maxwell's equations, and characterize the rhythms of entities essentially.

Discrete Mathematics for Computer Science: An Example-Based Introduction is intended for a first- or second-year discrete mathematics course for computer science majors. It covers many important mathematical topics essential for future computer science majors, such as algorithms, number representations, logic, set theory, Boolean algebra, functions, combinatorics, algorithmic complexity, graphs, and trees. Features Designed to be especially useful for courses at the community college level Ideal as a first or second-year textbook for computer science majors, or as a general introduction to discrete mathematics Written to be accessible to those with a limited mathematics background and to aid with the transition to abstract thinking Filled with over 200 worked examples, boxed for easy reference, and over 200 practice problems with answers Contains approximately 40 simple algorithms to aid students in becoming proficient with algorithm control structures and pseudocode An appendix on basic circuit design provides a real-world motivational example for computer science majors by drawing on multiple topics covered in the book to design a circuit that adds two eight-digit binary numbers

The need for a comprehensive survey-type exposition on formal languages and related mainstream areas of computer science has been evident for some years. In the early 1970s, when . the book Formal Languages by the second­ mentioned editor appeared, it was still quite feasible to write a comprehensive book with that title and include also topics of current research interest. This would not be possible anymore. A standard-sized book on formal languages would either have to stay on a fairly low level or else be specialized and restricted to some narrow sector of the field. The setup becomes drastically different in a collection of contributions, where the best authorities in the world join forces, each of them concentrat­ ing on their own areas of specialization. The present three-volume Handbook constitutes such a unique collection. In these three volumes we present the current state of the art in formal language theory. We were most satisfied with the enthusiastic response given to our request for contributions by specialists representing various subfields. The need for a Handbook of Formal Languages was in many answers expressed in different ways: as an easily accessible his­ torical reference, a general source of information, an overall course-aid, and a compact collection of material for self-study. We are convinced that the final result will satisfy such various needs. The theory of formal languages constitutes the stem or backbone of the field of science now generally known as theoretical computer science.

Since their first applications, Convolutional Neural Networks (CNNs) have solved problems that have advanced the state-of-the-art in several domains. CNNs represent information using real numbers. Despite encouraging results, theoretical analysis shows that representations such as hyper-complex numbers can achieve richer representational capacities than real numbers, and that Hamilton products can capture intrinsic interchannel relationships. Moreover, in the last few years, experimental research has shown that Quaternion-valued CNNs (QCNNs) can achieve similar performance with fewer parameters than their real-valued counterparts. This paper condenses research in the development of QCNNs from its very beginnings. We propose a conceptual organization of current trends and analyze the main building blocks used in the design of QCNN models. Based on this conceptual organization, we propose future directions of research.