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Elsevier

Academic Press

  • Cognitive Biases in Health and Psychiatric Disorders

    Neurophysiological Foundations
    • 1st Edition
    • Tatjana Aue + 1 more
    • English
    Cognitive Biases in Health and Psychiatric Disorders: Neurophysiological Foundations focuses on the neurophysiological basis of biases in attention, interpretation, expectancy and memory. Each chapter includes a review of each specific bias, including both positive and negative information in both healthy individuals and psychiatric populations. This book provides readers with major theories, methods used in investigating biases, brain regions associated with the related bias, and autonomic responses to specific biases. Its end goal is to provide a comprehensive overview of the neural, autonomic and cognitive mechanisms related to processing biases.

  • The Alkaloids

    • 1st Edition
    • Volume 83
    • Hans-Joachim Knolker
    • English
    The Alkaloids, Volume 83, is the newest release in a series that has covered the topic for more than 60 years. As the esteemed, leading reference in the field of alkaloid chemistry, this series covers all aspects of alkaloids, including their chemistry, biology and pharmacology. Sections are presented as high-quality, timeless reviews written by renowned experts in the field. New chapters in this release include Lamellarin alkaloids: Isolation, synthesis, and biological activity, Chemodiversity, chemotaxonomy and chemoecology of Amaryllidaceae alkaloids, and The indole-based subincanadine alkaloids and their biogenetic congeners.

  • Neutron Crystallography in Structural Biology

    • 1st Edition
    • Volume 634
    • English
    Neutron Crystallography in Structural Biology, Volume 634, the latest volume in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. Chapters in this updated release include Fundamentals of neutron crystallography in structural biology, Large crystal growth for neutron protein crystallography, Prospects for membrane protein crystals in NMX, IMAGINE: The neutron protein crystallography beamline at the high flux isotope reactor, The macromolecular neutron diffractometer at the spallation neutron source, Current status and near future plan of neutron protein crystallography at J-PARC, Neutron macromolecular crystallography at the European spallation source, and much more.

  • Advances in Heterocyclic Chemistry

    • 1st Edition
    • Volume 131
    • English
    Advances in Heterocyclic Chemistry, Volume 131, the latest release in this definitive series in the field, contains highly specialized chapters on a variety of topics, including 1,5-Disubstituted 8-membered ring heterocycles, Recent Developments in the Chemistry of Sydnones and Sydnone imines, Synthesis of fulleroheterocycles, Synthetic approaches to nitroheterocycles by nitration and other methods, 1,3-Amino alcohols and their phenol analogs in heterocyclization reactions, Synthesis of various N-heterocycles using the four component, The Chemistry of Dihydrothienopyrrolo... Part 2, Recent developments in the radiolabeling of heterocyclic rings, Application of Electrochemical Oxidative Methods in the C(sp2)-H Functionalization of Heterocyclic Compounds, and more.

  • The Neuroscience of Meditation

    Understanding Individual Differences
    • 1st Edition
    • Yi-Yuan Tang + 1 more
    • English
    The Neuroscience of Meditation: Understanding Individual Differences explores the individual differences in learning and practicing meditation, while also providing insights on how to learn and practice effectively. The book comprehensively covers the research in brain areas and networks that mediate the positive effects of meditation upon physical and mental health. Though it examines how people differ in how they learn and practice meditation, it underscores how underlying mechanisms differ in learning and practicing meditation and how they remain unclear to researchers. This book addresses the research gap and explores the brain science behind meditation.

  • Microbiomics

    Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research
    • 1st Edition
    • English
    Microbiomics: Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research describes a new, holistic approach to microbiomics. International experts provide in-depth discussion of current research methods for studying human, environmental, viral and fungal microbiomes, as well as the implications of new discoveries for human health, nutrition, disease, cancer research, probiotics and in the food and agricultural industries. Distinct chapters covering culturomics and sub-microbiomes, such as the viriome and mycetobiome, provide an integrative framework for the expansion of microbiomics into new areas of application, as well as crosspollination between research areas. Detailed case studies include the use of microbiomics to develop natural products with antimicrobial properties, microbiomic enhancements in food and beverage technology, microbes for bioprotection and biopreservation, microbial tools to reduce antibiotic resistance, and maintenance and cultivation of human microbial communities.

  • Durable Phase-Change Memory Architectures

    • 1st Edition
    • Volume 118
    • English
    Advances in Computers, Volume 118, the latest volume in this innovative series published since 1960, presents detailed coverage of new advancements in computer hardware, software, theory, design and applications. Chapters in this updated release include Introduction to non-volatile memory technologies, The emerging phase-change memory, Phase-change memory architectures, Inter-line level schemes for handling hard errors in PCMs, Handling hard errors in PCMs by using intra-line level schemes, and Addressing issues with MLC Phase-change Memory.

  • GPCR Signaling in Cancer

    • 1st Edition
    • Volume 145
    • English
    GPCR Signaling in Cancer, Volume 145, the latest release in the Advances in Cancer Research series, highlights recent developments in the area of GPCRs and cancer biology. Chapters included in this volume cover several GPCRs and their downstream effectors as case examples to highlight their fundamental understanding and therapeutic potential. Specific chapters address the Role of GRKs and beta-arrestins in cancer, Atypical GPCRs in cancer, the Role of a chemokine receptor (CCR) 5 in cancer, Targeting G protein-coupled receptors for therapeutics in cancer, Emerging GPCR signaling pathways in cancer, and more. G protein-coupled receptors (GPCRs) constitute a large family of cell surface receptors which are involved in nearly every cellular and physiological event. These receptors can recognize a broad array of ligands and they are targeted by nearly one third of the currently prescribed drugs including anti-cancer therapeutics.

  • Machine Learning

    A Bayesian and Optimization Perspective
    • 2nd Edition
    • Sergios Theodoridis
    • English
    Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines, Bayesian inference with a focus on the EM algorithm and its approximate inference variational versions, Monte Carlo methods, probabilistic graphical models focusing on Bayesian networks, hidden Markov models and particle filtering. Dimensionality reduction and latent variables modelling are also considered in depth. This palette of techniques concludes with an extended chapter on neural networks and deep learning architectures. The book also covers the fundamentals of statistical parameter estimation, Wiener and Kalman filtering, convexity and convex optimization, including a chapter on stochastic approximation and the gradient descent family of algorithms, presenting related online learning techniques as well as concepts and algorithmic versions for distributed optimization. Focusing on the physical reasoning behind the mathematics, without sacrificing rigor, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. Most of the chapters include typical case studies and computer exercises, both in MATLAB and Python. The chapters are written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as courses on sparse modeling, deep learning, and probabilistic graphical models. New to this edition: Complete re-write of the chapter on Neural Networks and Deep Learning to reflect the latest advances since the 1st edition. The chapter, starting from the basic perceptron and feed-forward neural networks concepts, now presents an in depth treatment of deep networks, including recent optimization algorithms, batch normalization, regularization techniques such as the dropout method, convolutional neural networks, recurrent neural networks, attention mechanisms, adversarial examples and training, capsule networks and generative architectures, such as restricted Boltzman machines (RBMs), variational autoencoders and generative adversarial networks (GANs). Expanded treatment of Bayesian learning to include nonparametric Bayesian methods, with a focus on the Chinese restaurant and the Indian buffet processes.

  • The Friedman-Lucas Transition in Macroeconomics

    A Structuralist Approach
    • 1st Edition
    • Peter Galbács
    • English
    The Friedman-Lucas Transition in Macroeconomics: A Structuralist Approach considers how and to what extent monetarist and new classical theories of the business-cycle can be regarded as approximately true descriptions of a cycle’s causal structure or whether they can be no more than useful predictive instruments. This book will be of interest to upper-division undergraduates, graduate students, researchers and professionals concerned with practical, theoretical and historical aspects of macroeconomics and business-cycle modeling.

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