Empirical Inference


Book Description

This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later developed one of the most successful methods in machine learning, the support vector machine (SVM) – more than just an algorithm, this was a new approach to learning problems, pioneering the use of functional analysis and convex optimization in machine learning. Part I of this book contains three chapters describing and witnessing some of Vladimir Vapnik's contributions to science. In the first chapter, Léon Bottou discusses the seminal paper published in 1968 by Vapnik and Chervonenkis that lay the foundations of statistical learning theory, and the second chapter is an English-language translation of that original paper. In the third chapter, Alexey Chervonenkis presents a first-hand account of the early history of SVMs and valuable insights into the first steps in the development of the SVM in the framework of the generalised portrait method. The remaining chapters, by leading scientists in domains such as statistics, theoretical computer science, and mathematics, address substantial topics in the theory and practice of statistical learning theory, including SVMs and other kernel-based methods, boosting, PAC-Bayesian theory, online and transductive learning, loss functions, learnable function classes, notions of complexity for function classes, multitask learning, and hypothesis selection. These contributions include historical and context notes, short surveys, and comments on future research directions. This book will be of interest to researchers, engineers, and graduate students engaged with all aspects of statistical learning.




Biological Adhesive Systems


Book Description

J. Herbert Waite Like many graduate students before and after me I was There are so many species about which nothing is known, mesmerized by a proposition expressed years earlier by and the curse of not knowing is apathy. Krogh (1929) – namely that “for many problems there is Bioadhesion is the adaptation featured in this book, an animal on which it can be most conveniently studied”. and biology has many adhesive practitioners. Indeed, This opinion became known as the August Krogh Prin- every living organism is adhesively assembled in the ciple and remains much discussed to this day, particu- most exquisite way. Clearly, speci? c adhesion needs to larly among comparative physiologists (Krebs, 1975). be distinguished from the opportunistic variety. I think The words “problems” and “animal” are key because of speci? c adhesion as the adhesion between cells in the they highlight the two fundamental and complementary same tissue, whereas opportunistic adhesion might be the foci of biological research: (1) expertise about an animal adhesion between pathogenic microbes and the urinary (zoo-centric), which is mostly observational and (2) a tract, or between a slug and the garden path. If oppor- mechanistic analysis of some problem in the animal’s life nistic bioadhesion is our theme, then there are still many history or physiology (problem-centric), which is usually practitioners but the subset is somewhat more select than a hypothesis-driven investigation. before.




Neural Fields


Book Description

Neural field theory has a long-standing tradition in the mathematical and computational neurosciences. Beginning almost 50 years ago with seminal work by Griffiths and culminating in the 1970ties with the models of Wilson and Cowan, Nunez and Amari, this important research area experienced a renaissance during the 1990ties by the groups of Ermentrout, Robinson, Bressloff, Wright and Haken. Since then, much progress has been made in both, the development of mathematical and numerical techniques and in physiological refinement und understanding. In contrast to large-scale neural network models described by huge connectivity matrices that are computationally expensive in numerical simulations, neural field models described by connectivity kernels allow for analytical treatment by means of methods from functional analysis. Thus, a number of rigorous results on the existence of bump and wave solutions or on inverse kernel construction problems are nowadays available. Moreover, neural fields provide an important interface for the coupling of neural activity to experimentally observable data, such as the electroencephalogram (EEG) or functional magnetic resonance imaging (fMRI). And finally, neural fields over rather abstract feature spaces, also called dynamic fields, found successful applications in the cognitive sciences and in robotics. Up to now, research results in neural field theory have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. There is no comprehensive collection of results or reviews available yet. With our proposed book Neural Field Theory, we aim at filling this gap in the market. We received consent from some of the leading scientists in the field, who are willing to write contributions for the book, among them are two of the founding-fathers of neural field theory: Shun-ichi Amari and Jack Cowan.




The Biophysics of Cell Membranes


Book Description

This volume focuses on the modulation of biological membranes by specific biophysical properties. The readers are introduced to emerging biophysical approaches that mimick specific states (like membrane lipid asymmetry, membrane curvature, lipid flip-flop, lipid phase separation) that are relevant to the functioning of biological membranes. The first chapter describes innovative methods to mimic the prevailing asymmetry in biological membranes by forming asymmetrical membranes made of monolayers with different compositions. One of the chapters illustrates how physical parameters, like curvature and elasticity, can affect and modulate the interactions between lipids and proteins. This volume also describes the sensitivity of certain ion channels to mechanical forces and it presents an analysis of how cell shape is determined by both the cytoskeleton and the lipid domains in the membrane. The last chapter provides evidence that liposomes can be used as a minimal cellular model to reconstitute processes related to the origin of life. Each topic covered in this volume is presented by leading experts in the field who are able to present clear, authoritative and up-to-date reviews. The novelty of the methods proposed and their potential for a deeper molecular description of membrane functioning are particularly relevant experts in the areas of biochemistry, biophysics and cell biology, while also presenting clear and thorough introductions, making the material suitable for students in these fields as well.




Robotics Research


Book Description

ISRR, the "International Symposium on Robotics Research", is one of robotics pioneering Symposia, which has established over the past two decades some of the field's most fundamental and lasting contributions. This book presents the results of the eighteenth edition of "Robotics Research" ISRR17, offering a collection of a broad range of topics in robotics. This symposium took place in Puerto Varas, Chile from December 11th to December 14th, 2017. The content of the contributions provides a wide coverage of the current state of robotics research, the advances and challenges in its theoretical foundation and technology basis, and the developments in its traditional and new emerging areas of applications. The diversity, novelty, and span of the work unfolding in these areas reveal the field's increased maturity and expanded scope and define the state of the art of robotics and its future direction.




Hydrogels for Tissue Engineering and Regenerative Medicine


Book Description

Hydrogels for Tissue Engineering and Regenerative Medicine: From Fundaments to Applications provides the reader with a comprehensive, concise and thoroughly up-to-date resource on the different types of hydrogels in tissue engineering and regenerative medicine. The book is divided into three main sections that describe biological activities and the structural and physicochemical properties of hydrogels, along with a wide range of applications, including their combination with emerging technologies. Written by a diverse range of international academics for professionals, researchers, undergraduate and graduate students, this groundbreaking publication fills a gap in literature needed in the tissue engineering and regenerative medicine field. Reviews the fundamentals and recent advances of hydrogels in tissue engineering and regenerative medicine applications Presents state-of-the-art methodologies for the synthesis and processing of different types of hydrogels Includes contributions by leading experts in engineering, the life sciences, microbiology and clinical medicine




The Biology of Vines


Book Description

This 1992 book is a treatment of what was known about climbing plants, written by a group of experts.




Nanotechnology Characterization Tools for Tissue Engineering and Medical Therapy


Book Description

Ninth volume of a 40 volume series on nanoscience and nanotechnology, edited by the renowned scientist Challa S.S.R. Kumar. This handbook gives a comprehensive overview about Nanotechnology Characterization Tools for Tissue Engineering and Medical Therapy. Modern applications and state-of-the-art techniques are covered and make this volume an essential reading for research scientists in academia and industry.




Brain Informatics


Book Description

This book constitutes the refereed proceedings of the 14th International Conference on Brain Informatics, BI 2021, held in September 2021. The conference was held virtually due to the COVID-19 pandemic. The 49 full and 2 short papers together with 18 abstract papers were carefully reviewed and selected from 90 submissions. The papers are organized in the following topical sections: cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain-inspired computing.