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Nunn's Applied Respiratory Physiology
Nunn's Applied Respiratory Physiology.
Neurobiology of Respiration
Respiration is an area of the medical study that undergoes fast developments. A better understanding of the neural and cellular mechanisms underlying respiratory disorders and lung function is essential for the evidence-based pharmacotherapy and for optimizing the patient care and prophylactic measures to improve the health and quality of life. This comprehensive book is a blend of basic and clinical research. The book is thought to promote the translation of science into clinical practice. The book presents an update on the areas of current research and clinical interest in the neurobiology of the respiratory system. Recent innovations in detection and management of respiratory diseases are described. The book will be a base of reference in the field of respiration for years to come and a source of future research ideas. This book is a required text for respiratory scientists, neuropathologists, and for clinicians searching for ‘bench to bedside’ treatments of lung diseases.
An Introduction to Lifted Probabilistic Inference
Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field. After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.
Automata Networks
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