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Handbook of Research on Health Systems and Organizations for an Aging Society
"This book explores the development and management of health systems and organizations in relation to individuals aged 65 and over"--Provided by publisher.
Graph Representation Learning
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
The CDC Field Epidemiology Manual
Preceded by Field epidemiology / edited by Michael B. Gregg. 3rd ed. c2008.
Federated Learning
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
Bee Products - Chemical and Biological Properties
This book presents an updated discussion of the chemical composition and biological properties of the main bee products. Specific attention is focused on the beneficial biological activities of bee products in human health. Honey, royal jelly, propolis, bee pollen and bee venom are used as nutriment and in traditional medicine. Their composition is rather variable and depends on the floral source and external factors, such as seasonal, environmental conditions and processing. Bee products are rich in several essential nutrients and non essential nutrients, as sugars, minerals, proteins, free amino acids, vitamins, enzymes and polyphenols, that seem to be closely related to their biological functions. The effects of these products in nutrition, aging and age-related diseases, cancer, neurodegenerative diseases and pathogen infections are discussed.
A Descendência De José Vieira Da Fonseca E Os Ribeiros Do Vale
Genealogia das Familias Ribeiro do Vale, Fonseca, Garcia, Palma, Salgado e Vieira do Ramo de Fartura
Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Earth Stewardship
This book advances Earth Stewardship toward a planetary scale, presenting a range of ecological worldviews, practices, and institutions in different parts of the world and to use them as the basis for considering what we could learn from one another, and what we could do together. Today, inter-hemispheric, intercultural, and transdisciplinary collaborations for Earth Stewardship are an imperative. Chapters document pathways that are being forged by socio-ecological research networks, religious alliances, policy actions, environmental citizenship and participation, and new forms of conservation, based on both traditional and contemporary ecological knowledge and values. “The Earth Stewardship Initiative of the Ecological Society of America fosters practices to provide a stable basis for civilization in the future. Biocultural ethic emphasizes that we are co-inhabitants in the natural world; no matter how complex our inventions may become” (Peter Raven).
The magic of jewels and charms
This book is about the folklore surrounding many aspects of jewelry. The author says that in it will be found "an interesting galaxy of anecdote, research, and information upon a fascinating subject." The book is divided into ten chapters each dealing with a particular type of gem, or, its supposed powers and so on.
