This book caters to the needs of students taking courses in Nondestructive Testing Techniques all over the world. Besides serving the primary purpose of providing a textbook on the subject, it also provides a much-needed reference to various engineers and research scientists that use Nondestructive Testing Techniques for inspection purposes or for material behavioral research studies. Persons working in the area of nondestructive testing in large fabrication industries, chemical and nuclear industries, aerospace and transportation will also find the book useful. The subject has been introduced in a very lucid way. It provides a comprehensive view of Ultrasonic Testing, Eddy-Current Testing, Magnetic Particle Flaw Detection, Liquid Penetrant Inspection, X-Radiography, and Acoustic Emission Testing and Acousto-Ultrasonic Testing.

Includes prospective cost effective, eco-friendly, and safe nanomaterials, synthesized through a facile path Covers synergistic effect of phytochemicals and nano-Ag antimicrobial agents from an antiviral perspective Includes surface coating systems and super absorbent materials for biomedical purposes Discusses nanobiotechnological applications for generating nanoalloys with synchronized nanostructural arrangement of alkaline earth metals and nanoscale dots of transition metal Explores life cycle assessment of the synthesized nanomaterials

This manual offers a stand-alone reading companion, unique in simplifying the practical components of Bioinformatics in a unique and user-friendly manner. It covers the practical component of syllabi used at most leading universities and discusses the most extensively used tools and methodologies in Bioinformatics. Research in the biological sciences has made tremendous strides in recent years due in part to the increased automation in data generation. At the same time, storing, managing and interpreting huge volumes of data has become one of the most challenging tasks for scientists. These two aspects have ultimately necessitated the application of computers, giving rise to a highly interdisciplinary discipline-Bioinformatics. Despite the richness of bioinformatics resources and methods, the exposure of life sciences undergraduates and postgraduates to bioinformatics is extremely limited. Though the internet offers various tools for free, and provides guides for using them, it fails to help users interpret the processed data. Moreover, most sites fail to update their help pages to accommodate software upgrades. Though the market is flooded with books discussing the theoretical concepts in Bioinformatics, a manual of this kind is rarely found. The content developed to meet the needs of readers from diverse background and to incorporate the syllabi of undergraduate and postgraduate courses at various universities.

This manual offers a stand-alone reading companion, unique in simplifying the practical components of Bioinformatics in a unique and user-friendly manner. It covers the practical component of syllabi used at most leading universities and discusses the most extensively used tools and methodologies in Bioinformatics. Research in the biological sciences has made tremendous strides in recent years due in part to the increased automation in data generation. At the same time, storing, managing and interpreting huge volumes of data has become one of the most challenging tasks for scientists. These two aspects have ultimately necessitated the application of computers, giving rise to a highly interdisciplinary discipline-Bioinformatics. Despite the richness of bioinformatics resources and methods, the exposure of life sciences undergraduates and postgraduates to bioinformatics is extremely limited. Though the internet offers various tools for free, and provides guides for using them, it fails to help users interpret the processed data. Moreover, most sites fail to update their help pages to accommodate software upgrades. Though the market is flooded with books discussing the theoretical concepts in Bioinformatics, a manual of this kind is rarely found. The content developed to meet the needs of readers from diverse background and to incorporate the syllabi of undergraduate and postgraduate courses at various universities.

A very hot topic at the 2010 AASLD meeting, hepatic encephalopathy is being brought to the Clinics in Liver Disease for the very first time by top experts, Dr. Mullen and Dr. Prakash. Authors have written articles that fully discuss the clinical aspects of hepatic encephalopathy (HE). Articles presented include History, Nomenclature and Classification; Theories involved in the pathogenesis of HE; Clinical Assessment and utility of clinical scales for semi-quantification of Overt HE;? Assessment of Minimal HE
( with emphasis on computerized psychometric tests); Brain Imaging and HE; Management of Overt HE; Management of Minimal HE; Nutritional Interventions for HE; TIPS and HE; Liver Transplantation and Reversibility of HE; Minimal HE and Driving; and HE and Quality of Life.

Existing robotics technology is still mostly limited to being used by expert programmers who can adapt the systems to new required conditions, but not flexible and adaptable by non-expert workers or end-users. Imitation Learning (IL) has obtained considerable attention as a potential direction for enabling all kinds of users to easily program the behavior of robots or virtual agents. Interactive Imitation Learning (IIL) is a branch of Imitation Learning (IL) where human feedback is provided intermittently during robot execution allowing an online improvement of the robot's behavior. In this monograph, research in IIL is presented and low entry barriers for new practitioners are facilitated by providing a survey of the field that unifies and structures it. In addition, awareness of its potential is raised, what has been accomplished and what are still open research questions being covered. Highlighted are the most relevant works in IIL in terms of human-robot interaction (i.e., types of feedback), interfaces (i.e., means of providing feedback), learning (i.e., models learned from feedback and function approximators), user experience (i.e., human perception about the learning process), applications, and benchmarks. Furthermore, similarities and differences between IIL and Reinforcement Learning (RL) are analyzed, providing a discussion on how the concepts offline, online, off-policy and on-policy learning should be transferred to IIL from the RL literature. Particular focus is given to robotic applications in the real world and their implications are discussed, and limitations and promising future areas of research are provided.