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Proceedings
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Handbook of Drug Interactions
A concise compilation of the known interactions of the most commonly prescribed drugs, as well as their interaction with nonprescription compounds. The agents covered include CNS drugs, cardiovascular drugs, antibiotics, and NSAIDs. For each class of drugs the authors review the pharmacology, pharmacodynamics, pharmacokinetics, chemistry, metabolism, epidemiological occurrences, adverse reactions, and significant interactions. Environmental and social pharmacological issues are also addressed in chapters on food and alcohol drug interactions, nicotine and tobacco, and anabolic doping agents. Comprehensive and easy-to-use, Handbook of Drug Interactions: A Clinical and Forensic Guide provides physicians with all the information needed to avoid prescribing drugs with undesirable interactions, and toxicologists with all the data necessary to interpret possible interactions between drugs found simultaneously in patient samples.
Statement of Disbursements of the House
Covers receipts and expenditures of appropriations and other funds.
American King
They say that every tragic hero has a fatal flaw, a secret sin, a tiny stitch sewn into his future since birth. And here I am. My sins are no longer secret. My flaws have never been more fatal. And I’ve never been closer to tragedy than I am now. I am a man who loves, a man whose love demands much in return. I am a king, a king who was foolish enough to build a kingdom on the bones of the past. I am a husband and a lover and a soldier and a father and a president. And I will survive this. Long live the king.
Machine Learning
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. - Provides a non-technical introduction to machine learning and applications to brain disorders - Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches - Covers the main methodological challenges in the application of machine learning to brain disorders - Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python
African Accents
This is a comprehensive workbook for actors, covering the key characteristics and profiles of a wide range of African accents of English. Its unique approach not only addresses the methods and processes by which to go about learning an accent, but also looks in detail at each example. This lets the reader plot their own route through the learning process and tailor not only their working methods but also their own personal idiolect. Full breakdowns of each accent cover: an introduction giving a brief history of the accent, its ethnic background, and its language of origin preparatory warm-up exercises specific to each accent a directory of research materials including documentaries, plays, f...
