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Titlebook: Language and Legal Proceedings; Analysing Courtroom Endurence Midinette Koumassol Dissake Book 2021 The Editor(s) (if applicable) and The

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Peter LaxIncludes point of injury to pre and in-hospital care.Focuses on basic physiological principles through to current controversies.Written by expert consultants (both military and civilian) across a rang
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https://doi.org/10.1007/978-94-007-7293-9Cloud-managemenet and Service Oriented Computing; Data Analytics; Data Mining and Knowledge Discovery;
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Fatigue Damage Map as a Virtual Tool for Fatigue Damage Tolerance,ds to develop a virtual tool able to predict the limits and the corresponding crack tip propagation rates characterising each of the fatigue stages, namely crack arrest, microstructurally and physically short crack (Stage I), long crack growth (Stage II), and Stage III growth.
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https://doi.org/10.1007/978-3-322-97388-7ion active users, surely indicates that social media is not a fad. Healthcare will not go untouched by social media. The combination of social media and healthcare (medicine 2.0) will be a powerful one. Social media will impact healthcare in many ways, including reducing information asymmetry, incre
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Karl Bosch, all of which are common to labeled techniques but may introduce artifacts in assay results. Addressing several fundamental and practical aspects as to how to implement label-free methods in the drug discovery process, this book covers a wide range of topics, including binding kinetics determinatio
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H. A. Wassenberghcating, and self-cleaning materials with applications to gre.Biomimetics in Materials Science. provides a comprehensive theoretical and practical review of biomimetic materials with self-healing, self-lubricating and self-cleaning properties. These three topics are closely related and constitute rap
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V. Čermáklmost beyond measure. But what if that data is either unavailable or problematic to access? That’s where synthetic data comes in. This book will show you how to generate synthetic data and use it to maximum effect...Synthetic Data for Deep Learning. begins by tracing the need for and development of
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