Since UV curing (light induced polymerisation of multifunctional oligomers) is a very ecoefficient and energy saving curing method, the growth rates of UV curable coatings are in the range of 10% per year. The typical UV coatings are solvent free (100% solids), thus helping the industry and the environment to reduce significantly VOC (volatile organic compounds). Recently, the automotive industry has discovered that UV cured coatings are very scratch resistant, which stimulated very extensive work into the development of UV coatings for automotive applications. Since UV curing is very universal, also other systems besides the 100% solid (typical) UV coatings are developed, like waterbased UV- , UV powder and Dual cure (UV and thermal) systems.UV Coatings contains an overview of the technology, the curing process including the equipment necessary, the raw materials (resins, diluents, photoinitiators) used, the advantages and drawbacks of this fast emerging technology, as well as proposed technical solutions to tackle the disadvantages. Structure-property relationships will be given, especially regarding the mechanical properties of coatings as well as scratch resistance, mainly dealing with automotive performance criteria. The main part of the book will deal with new developments, like water-based UV coatings, UV powder coatings and dual cure systems, cured by UV and thermal energy, which have been developed to cure the coating on three dimensional substrates in shadow areas. The main applications of UV Coatings will be described, starting with the classical ones on temperature sensitive substrates, like wood, paper and plastics, where the UV curable coatings are already well established.* Looking at UV curing as a key to scratch resistant automotive clear coats* Ecoefficiency of UV Coatings* Comprehensive overview of the technology, materials and markets
Explores the uses of TXRF in micro- and trace analysis, and in surface- and near-surface-layer analysis • Pinpoints new applications of TRXF in different fields of biology, biomonitoring, material and life sciences, medicine, toxicology, forensics, art history, and archaeometry • Updated and detailed sections on sample preparation taking into account nano- and picoliter techniques • Offers helpful tips on performing analyses, including sample preparations, and spectra recording and interpretation • Includes some 700 references for further study
Be ready to prescribe and administer drugs safely and effectively—and grasp all the vitals of pharmacology—with the fully updated Pharmacotherapeutics for Advanced Practice, 4th edition. Written by pharmacology nursing experts, this easy-to-read text offers proven frameworks for treating more than 50 common diseases and disorders. Learn how to identify disorders, review possible therapies, then prescribe and monitor drug treatment, accurately. Based on current evidence and real-life patient scenarios, this is the perfect pharmacology learning guide and on-the-spot clinical resource. Absorb the key principles and practical methods for accurate prescribing and monitoring, with . . . NEW chapter on Parkinson’s disease, osteoarthritis, and rheumatoid arthritis NEW and updated therapies, and updated and additional case studies, with sample questions NEW content on the impacts of the Affordable Care Act Updated chapters on complementary and alternative medicine (CAM) and pharmacogenomics Updated evidence-based algorithms and drug tables – Listing uses, mechanisms, adverse effects, drug interactions, contraindications, and monitoring parameters, organized by drug class; quick access to generic and trade names and dosages Quick-scan format organizes information by body system Chapter features include: Brief overview – Pathophysiology of each disorder, and relevant classes of drugs Monitoring Patient Response section – What to monitor, and when Patient Education section – Includes information on CAM for each disorder Drug Overview tables – Usual dose, contraindications and side effects, and special considerations Algorithms – Visual cues on how to approach treatment Updated Recommended Order of Treatment tables – First-, second- and third-line drug therapies for each disorder Answers to Case Study Questions for each disorder – Strengthens critical thinking skills Selecting the Most Appropriate Agent section – The thought process for choosing an initial drug therapy Principles of Therapeutics unit – Avoiding medication errors; pharmacokinetics and pharmacodynamics; impact of drug interactions and adverse events; principles of pharmacotherapy for pediatrics, pregnancy/lactation, and geriatrics Disorders units – Pharmacotherapy for disorders in various body systems Pharmacotherapy in Health Promotion unit – Smoking cessation, immunizations, weight management Women’s Health unit – Including contraception, menopause, and osteoporosis Integrative Approach to Patient Care unit – Issues to consider when presented with more than one diagnosis Standard pharmacotherapeutics text for nurse practitioners, students, and physician assistants Ancillaries – Case Study answers, multiple choice questions and answers for every chapter, PowerPoints, Acronyms List
I didn't want the biography to end. Mordecai Richler seemed so vividly alive...From now on, nobody can write about Richler without reading this book." The Globe and Mail
It is a great privilege and pleasure to write a foreword for a book honor ing Wolfgang Gaul on the occasion of his sixtieth birthday. Wolfgang Gaul is currently Professor of Business Administration and Management Science and the Head of the Institute of Decision Theory and Management Science, Faculty of Economics, University of Karlsruhe (TH), Germany. He is, by any measure, one of the most distinguished and eminent scholars in the world today. Wolfgang Gaul has been instrumental in numerous leading research initia tives and has achieved an unprecedented level of success in facilitating com munication among researchers in diverse disciplines from around the world. A particularly remarkable and unique aspect of his work is that he has been a leading scholar in such diverse areas of research as graph theory and net work models, reliability theory, stochastic optimization, operations research, probability theory, sampling theory, cluster analysis, scaling and multivariate data analysis. His activities have been directed not only at these and other theoretical topics, but also at applications of statistical and mathematical tools to a multitude of important problems in computer science (e.g., w- mining), business research (e.g., market segmentation), management science (e.g., decision support systems) and behavioral sciences (e.g., preference mea surement and data mining). All of his endeavors have been accomplished at the highest level of professional excellence.
Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.
This volume contains revised versions of selected papers presented dur ing the 23rd Annual Conference of the German Classification Society GfKl (Gesellschaft fiir Klassifikation). The conference took place at the Univer sity of Bielefeld (Germany) in March 1999 under the title "Classification and Information Processing at the Turn of the Millennium". Researchers and practitioners - interested in data analysis, classification, and information processing in the broad sense, including computer science, multimedia, WWW, knowledge discovery, and data mining as well as spe cial application areas such as (in alphabetical order) biology, finance, genome analysis, marketing, medicine, public health, and text analysis - had the op portunity to discuss recent developments and to establish cross-disciplinary cooperation in their fields of interest. Additionally, software and book pre sentations as well as several tutorial courses were organized. The scientific program of the conference included 18 plenary or semi plenary lectures and more than 100 presentations in special sections. The peer-reviewed papers are presented in 5 chapters as follows: • Data Analysis and Classification • Computer Science, Computational Statistics, and Data Mining • Management Science, Marketing, and Finance • Biology, Genome Analysis, and Medicine • Text Analysis and Information Retrieval As an unambiguous assignment of results to single chapters is sometimes difficult papers are grouped in a way that the editors found appropriate.
This book focuses on exploratory data analysis, learning of latent structures in datasets, and unscrambling of knowledge. Coverage details a broad range of methods from multivariate statistics, clustering and classification, visualization and scaling as well as from data and time series analysis. It provides new approaches for information retrieval and data mining and reports a host of challenging applications in various fields.
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