Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Male Fertility and Lipid Metabolism
Interest in lipid metabolism and polyunsaturated fatty acids in relation to sperm production has increased during the last decade. The motivation for the research described in this book originates from the discovery that sperm lipids contain extremely high proportions of long-chain polyunsaturated fatty acids, thus establishing a link between lipid biochemistry and male fertility. Moreover, the fact that polyunsaturated fatty acids must, in some form, be supplied in the diet suggests a relationship between fertility and nutrition and raises the possibility of improving male fertility by dietary means. This book gives the reader an up-to-date view of several aspects of male fertility in relation to lipid and fatty acid metabolism. Researchers in the domain of male fertility, fatty acid metabolism, and antioxidants; medical personnel involved in the treatment of male infertility; fat technologists; students in nutrition, dietetics, biochemistry, pharmacy, and medicine; and everybody interested in the field will find this book useful.
Spherical NeurO(n)s for Geometric Deep Learning
Felix Klein’s Erlangen Programme of 1872 introduced a methodology to unify non-Euclidean geometries. Similarly, geometric deep learning (GDL) constitutes a unifying framework for various neural network architectures. GDL is built from the first principles of geometry—symmetry and scale separation—and enables tractable learning in high dimensions. Symmetries play a vital role in preserving structural information of geometric data and allow models (i.e., neural networks) to adjust to different geometric transformations. In this context, spheres exhibit a maximal set of symmetries compared to other geometric entities in Euclidean space. The orthogonal group O(n) fully encapsulates the sym...
Machine Learning for Cyber Security
This three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Fifth recent advances in quantitative remote sensing
The Fifth International Symposium on Recent Advances in Quantitative Remote Sensing was held in Torrent, Spain from 18 to 22 September 2018. It was sponsored and organized by the Global Change Unit (GCU) from the Image Processing Laboratory (IPL), University of Valencia (UVEG), Spain. This Symposium addressed the scientific advances in quantitative remote sensing in connection with real applications. Its main goal was to assess the state of the art of both theory and applications in the analysis of remote sensing data, as well as to provide a forum for researcher in this subject area to exchange views and report their latest results. In this book 89 of the 262 contributions presented in both plenary and poster sessions are arranged according to the scientific topics selected. The papers are ranked in the same order as the final programme.
Chinese Asianism, 1894-1945
Chinese Asianism examines Chinese intellectual discussions of East Asian solidarity, analyzing them in connection with Chinese nationalism and Sino–Japanese relations. Beginning with texts written after the first Sino–Japanese War of 1894 and concluding with Wang Jingwei’s failed government in World War II, Craig Smith engages with a period in which the Chinese empire had crumbled and intellectuals were struggling to adapt to imperialism, new and hegemonic forms of government, and radically different epistemes. He considers a wide range of writings that show the depth of the pre-war discourse on Asianism and the influence it had on the rise of nationalism in China. Asianism was a “ca...
Sustainable Management of Environmental Pollutants through Phytoremediation
Traditional remedial technologies can be cost-prohibitive and sometimes contribute to environmental contamination themselves. In order to better manage the issues of global pollution, phytoremediation, a plant-based cleanup method, has gained attention as an efficient, affordable, and environmentally sustainable alternative to traditional remedial technologies for the cleanup of a variety of hazardous pollutants. The demand for advanced technologies having potential to sustainably manage waste and pollutants in the environment will help to continue the quest for more novel treatment methods. Sustainable Management of Environmental Pollutants through Phytoremediation discusses all the aspects of sustainable environmental management through phytoremediation, making it a valuable resource for both academics and researchers in developing and developed countries. Examines technology advancements made toward the recycling and management of waste. Designed in a way to cover scientific principles, modeling and methods, designs, and reference data. Discusses the utilization of waste for renewable energy for economic growth and further social benefits.
