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This book describes recent important advancements in protein folding dynamics and stability research, as well as explaining fundamentals and examining potential methodological approaches in protein science. In vitro, in silico, and in vivo method based research of how the stability and folding of proteins help regulate the cellular dynamics and impact cell function that are crucial in explaining various physiological and pathological processes. This book offers a comprehensive coverage on various techniques and related recent developments in the experimental and computational methods of protein folding, dynamics, and stability studies. The book is also structured in such a way as to summarize the latest developments in the fiddle and key concepts to ensure that readers can understand advanced concepts as well as the fundamental big picture. And most of all, fresh insights are provided into the convergence of protein science and technology. Protein Folding Dynamics and Stability is an ideal guide to the field that will be of value for all levels of researchers and advanced graduate students with training in biochemical laboratory research.
Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.
In the past decades, interdisciplinary investigations overlapping biology, medicine, information science, and engineering have formed a very exciting and active field that attracts scientists, medical doctors, and engineers with knowledge in different domains. A few examples of such investigations include neural prosthetic implants that aim to improve the quality of life for patients suffering from neurologic disease and injury; brain machine interfaces that sense, analyze, and translate electrical signals from the brain to build closed-loop, biofeedback systems; and fundamental studies of intelligence, cognitive functions, and psychological behaviors correlated to their neurological basis. ...
This study explores the relations between SME intellectual asset management, innovation and competitiveness in different national and sectoral contexts.
In the evolving environment of bioinformatics, genomics, and computational biology, academic scholars are facing a challenging challenge – keeping informed about the latest research trends and findings. With unprecedented advancements in sequencing technologies, computational algorithms, and machine learning, these fields have become indispensable tools for drug discovery, disease research, genome sequencing, and more. As scholars strive to decode the language of DNA, predict protein structures, and navigate the complexities of biological data analysis, the need for a comprehensive and up-to-date resource becomes paramount. The Research Anthology on Bioinformatics, Genomics, and Computatio...