Tietz Clinical Guide to Laboratory Tests - E-Book


Book Description

This new edition of Norbert Tietz's classic handbook presents information on common tests as well as rare and highly specialized tests and procedures - including a summary of the utility and merit of each test. Biological variables that may affect test results are discussed, and a focus is placed on reference ranges, diagnostic information, clinical interpretation of laboratory data, interferences, and specimen types. New and updated content has been added in all areas, with over 100 new tests added. - Tests are divided into 8 main sections and arranged alphabetically. - Each test includes necessary information such as test name (or disorder) and method, specimens and special requirements, reference ranges, chemical interferences and in vivo effects, kinetic values, diagnostic information, factors influencing drug disposition, and clinical comments and remarks. - The most current and relevant tests are included; outdated tests have been eliminated. - Test index (with extensive cross references) and disease index provide the reader with an easy way to find necessary information - Four new sections in key areas (Preanalytical, Flow Cytometry, Pharmacogenomics, and Allergy) make this edition current and useful. - New editor Alan Wu, who specializes in Clinical Chemistry and Toxicology, brings a wealth of experience and expertise to this edition. - The Molecular Diagnostics section has been greatly expanded due to the increased prevalence of new molecular techniques being used in laboratories. - References are now found after each test, rather than at the end of each section, for easier access.




Accounting in a Nutshell


Book Description

Designed primarily for middle and junior management who deal with financial information without really understanding the content; students who are studying accounting as a non-specialist subject, for example on a business studies or engineering course. The book serves as a basic reference to be used throughout the course. It will also be particularly helpful in providing the basic grounding that is required before moving on to the more technical and in-depth study of the subject that may be required on some courses. Students who are embarking on a course of study to become a professional accountant will also find this book of major benefit. In addition to revisions through out, a new new chapter 'Making long-term investment decisions' covering capital investment decisions, extends and rounds out the final part of the book: using Financial Information to Manage a Business. The chapter deals with the investment appraisal process and covers the main investment appraisal techniques from the point of view of a non-specialist: payback periods, accounting rate of return and discounted cash flow methods are just some of the new topics covered. The focus will be on the level of understanding that a non-specialist requires in the work place as such, in keeping with the rest of the book, the chapter includes practical examples and exercises to enhance the reader's understanding. Jargon free and easy to understand - no prior knowledge of the subject necessary Focuses on the principles and use of accounting information Review questions to assess progress at each stage and many fully worked exercises and examples




Introduction to Applied Linear Algebra


Book Description

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.







Direct Methods for Sparse Linear Systems


Book Description

The sparse backslash book. Everything you wanted to know but never dared to ask about modern direct linear solvers. Chen Greif, Assistant Professor, Department of Computer Science, University of British Columbia.Overall, the book is magnificent. It fills a long-felt need for an accessible textbook on modern sparse direct methods. Its choice of scope is excellent John Gilbert, Professor, Department of Computer Science, University of California, Santa Barbara.Computational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.With a strong emphasis on MATLAB and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.Audience This invaluable book is essential to computational scientists and software developers who want to understand the theory and algorithms behind modern techniques used to solve large sparse linear systems. The book also serves as an excellent practical resource for students with an interest in combinatorial scientific computing.Preface; Chapter 1: Introduction; Chapter 2: Basic algorithms; Chapter 3: Solving triangular systems; Chapter 4: Cholesky factorization; Chapter 5: Orthogonal methods; Chapter 6: LU factorization; Chapter 7: Fill-reducing orderings; Chapter 8: Solving sparse linear systems; Chapter 9: CSparse; Chapter 10: Sparse matrices in MATLAB; Appendix: Basics of the C programming language; Bibliography; Index.




Writing Research Papers


Book Description

The definitive research paper guide, Writing Research Papers combines a traditional and practical approach to the research process with the latest information on electronic research and presentation. This market-leading text provides students with step-by-step guidance through the research writing process, from selecting and narrowing a topic to formatting the finished document. Writing Research Papers backs up its instruction with the most complete array of samples of any writing guide of this nature. The text continues its extremely thorough and accurate coverage of citation styles for a wide variety of disciplines. The fourteenth edition maintains Lester's successful approach while bringing new writing and documentation updates to assist the student researcher in keeping pace with electronic sources.




Foundations of Data Science


Book Description

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.




Introduction to Costing Wise Guide


Book Description

This handy pocket-sized guide provides the perfect study and revision tool for the AAT Level 2 Certificate in Accounting (Basic Costing). Key revision topics are presented in an easy-to-read, portable package that will help you prepare for your exams anywhere at any time.




Planning Algorithms


Book Description

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.