الصفحة 15
الصفحة 15
Analgesia
Analgesics are among the oldest drugs described, albeit not necessarily for medicinaluse. Forexample,theSumeriansisolatedopioids(probablyfortheir euphoric effects) in the third millennium b. c. and the use of willow bark (salicin) for fever was ?rst reported in the eighteenth century. Both types of drugs are still in use, but today they are supplemented by a wide array of substances ranging from antidepressants to ion channel blockers. Not all of theseareprescribedbyphysicians. Manycompoundsaresoldoverthecounter and thus available to the public for self-medication. As a result, analgesics are also the most misused class of drugs and are the culprit for a multitude of healthproblemsdueto untoward sideeffects. Thisvolumeattemptstosummarizethecurrentstateofknowledgeonme- anisms underlying the various effects of these drugs, their side effect pro?les, and their indications and contraindications in clinical use.
An Invitation to Statistics in Wasserstein Space
This book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation.
An Introduction to the Mathematics of Money : Saving and Investing
This is an undergraduate textbook on the basic aspects of personal savings and investing with a balanced mix of mathematical rigor and economic intuition. It uses routine financial calculations as the motivation and basis for tools of elementary real analysis rather than taking the latter as given. Proofs using induction, recurrence relations and proofs by contradiction are covered. Inequalities such as the Arithmetic-Geometric Mean Inequality and the Cauchy-Schwarz Inequality are used. Basic topics in probability and statistics are presented.
An Introduction to Queueing Theory: and Matrix-Analytic Methods
The present textbook contains the recordsof a two–semester course on que- ing theory, including an introduction to matrix–analytic methods. This book provides a mathematical introduction to the theory of queuing theory and matrix-analytic methods … . The style of the text … is concise and rigorous. The proofs are presented for study. Each chapter concludes with a set of exercises inviting readers to prove supplementary results and review particular aspects of the theory. The book under review attempts to give an introduction to the theory of queues without losing contact with its applicability. … For instructors who prefer the topics covered, this book is a nice candidate as they do not need to choose the topics but only need to elaborate on them. Nevertheless, it would be a good reference book for an introductory course in queuing theory, stochastic modelling, or applied probability
An Introduction to Mathematical Cryptography
This self-contained introduction to modern cryptography emphasizes the mathematics behind the theory of public key cryptosystems and digital signature schemes. The book focuses on these key topics while developing the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Only basic linear algebra is required of the reader; techniques from algebra, number theory, and probability are introduced and developed as required.
An Introduction to Kolmogorov Complexity and Its Applications
Written by two experts in the field, this book is ideal for advanced undergraduate students, graduate students, and researchers in all fields of science. It is self-contained: it contains the basic requirements from mathematics, probability theory, statistics, information theory, and computer science. Included are history, theory, new developments, a wide range of applications, numerous (new) problem sets, comments, source references, and hints to solutions of problems. This is the only comprehensive treatment of the central ideas of Kolmogorov complexity and their applications.
An Introduction to Infinite-Dimensional Analysis
In this revised and extended version of his course notes from a 1-year course at Scuola Normale Superiore, Pisa, the author provides an introduction – for an audience knowing basic functional analysis and measure theory but not necessarily probability theory – to analysis in a separable Hilbert space of infinite dimension.Starting from the definition of Gaussian measures in Hilbert spaces, concepts such as the Cameron-Martin formula, Brownian motion and Wiener integral are introduced in a simple way. These concepts are then used to illustrate some basic stochastic dynamical systems (including dissipative nonlinearities) and Markov semi-groups, paying special attention to their long-time behavior: ergodicity, invariant measure. Here fundamental results like the theorems of Prokhorov, Von Neumann, Krylov-Bogoliubov and Khas'minski are proved. The last chapter is devoted to gradient systems and their asymptotic behavior.
An Introduction to Copulas
Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Amartya Sens Capability Approach: Theoretical Insights and Empirical Applications
Kuklys examines how Nobel Prize-winning economist Amartya Sen’s approach to welfare measurement can be put in practice for poverty and inequality measurement in affluent societies such as the UK. Sen argues that an individual’s welfare should not be measured in terms of her income, but in terms what she can actually do or be, her capabilities. In Chapters 1 and 2, Kuklys describes the capability approach from a standard welfare economic point of view and provides a comprehensive literature review of the empirical applications in this area of research. In the remaining chapters, novel econometric techniques are employed to operationalise the concepts of functionings and capability to investigate inequality and poverty in terms of capability in the UK. Kuklys finds that capability measurement is always a useful complement to traditional monetary analysis, and particularly so in the case of capability-deprived disabled individuals.
Algorithms in Bioinformatics ; Vol. 3692 ; 5th international workshop, WABI 2005, Mallorca, Spain, October 3-6, 2005, Proceedings
this book present the proceedings of the 5th Workshop on Algorithmsin Bioinformatics (WABI 2005) which took place in Spain, 2005. The Workshop on Algorithms in Bioinformatics highlights research workspecifically developed to address algorithmic problems in biosequence analysis. The emphasis is therefore on statistical and probabilistic algorithms that addressimportant problems in the field of molecular and structural biology. the workshop aims to present recent research results, includingsignificant work in progress, and to identify and explore directions of futureresearch.Original research papers (including significant work in progress) or state-of-the-art surveys were solicited on all aspects of algorithms in bioinformatics,including, but not limited to: exact and approximate algorithms for genomics,genetics, sequence analysis, gene and signal recognition, alignment, molecularevolution, phylogenetics, structure determination or prediction, gene expressionand gene networks, proteomics, functional genomics, and drug design.
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithmic Aspects in Information and Management ; 4th International Conference, AAIM 2008, Shanghai, China, June 23-25, 2008. Proceedings
This book constitutes the refereed proceedings of the 4th International Conference on Algorithmic Aspects in Information and Management, AAIM 2008, held in Shanghai, China, in June 2008.
Algebraic and Proof-theoretic Aspects of Non-classical Logics : Papers in Honor of Daniele Mundici on the Occasion of His 60th Birthday
It profound connections between logic and such diverse fields of research as functional analysis, probability and measure theory, the geometry of toric varieties, piecewise linear geometry, and error-correcting codes. Several prominent logicians, mathematicians, and computer scientists
Algebra and Coalgebra in Computer Science; First International Conference, CALCO 2005, Swansea, UK, September 3-6, 2005, Proceedings
CALCO, the Conference on Algebra and Coal-gebra in Computer Science, was created to bring together researchers and practitio-ners to exchange new results related to foundational aspects, and both traditional and emerging uses of algebras and coalgebras in computer science. CALCO 2005 was the first instance of this new conference. The interest that it generated in the scientific community suggests that it will not be the last. Indeed, it attracted as many as 62 submissions covering a wide range of topics roughly divided into two areas: Algebras and Coalgebras as Mathematical Objects: Automata and languages; categorical semantics; hybrid, probabilistic, and timed systems; inductive and coin-ductive methods; modal logics; relational systems and term rewriting.
Aging, shaking, and cracking of infrastructures : From mechanics to concrete dams and nuclear structures
Focuses on the safety assessment of existing structures subjected to multi-hazard scenarios through advanced numerical methods. Whereas the focus is on concrete dams and nuclear containment structures, the presented methodologies can also be applied to other large-scale ones. This book is composed of seven sections: Fundamentals: theoretical coverage of solid mechnics, plasticity, fracture mechanics, creep, / seismology, dynamic analysis, probability and statistics / Damage: that can affect concrete structures, such as cracking of concrete, AAR, chloride ingress, and rebar corrosion, / Finite Element: formulation for both linear and nonlinear analysis including stress, heat and fracture mechanics, / Engineering Models: for soil/fluid-structure interaction, uncertainty quantification, probablilistic and random finite element analysis, machine learning, performance based earthquake engineering, ground motion intensity measures, seismic hazard analysis, capacity/fragility functions and damage indeces, / Applications to dams through potential failure mode analyses, risk-informed decision making, deterministic and probabilistic examples, / Applications to nuclear structures through modeling issues, aging management programs, critical review of some analyses, / Other applications and case studies: massive RC structures and bridges, detailed assessment of a nuclear containment structure evaluation for license renewal.
Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advances in mathematical economics ; Vol. 9
A lot of economic problems can formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who were seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking for effective mathematical tools for their researchers.
Advances in mathematical economics ; Vol. 7
A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories.
Advances in mathematical economics ; Vol. 11
A lot of economic problems can formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who were seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking for effective mathematical tools for their researchers.
