Ascorbic acid (AsA), vitamin C, is one of the most abundant water-soluble antioxidant in plants and animals. In plants AsA serves as a major redox buffer and regulates various physiological processes controlling growth, development, and stress tolerance. Recent studies on AsA homeostasis have broadened our understanding of these physiological events. At the mechanistic level, AsA has been shown to participate in numerous metabolic and cell signaling processes, and the dynamic relationship between AsA and reactive oxygen species (ROS) has been well documented. Being a major component of the ascorbate-glutathione (AsA-GSH) cycle, AsA helps to modulate oxidative stress in plants by controlling ROS detoxification alone and in co-operation with glutathione. In contrast to the single pathway responsible for AsA biosynthesis in animals, plants utilize multiple pathways to synthesize AsA, perhaps reflecting the importance of this molecule to plant health. Any fluctuations, increases or decreases, in cellular AsA levels can have profound effects on plant growth and development, as AsA is associated with the regulation of the cell cycle, redox signaling, enzyme function and defense gene expression. Although there has been significant progress made investigating the multiple roles AsA plays in stress tolerance, many aspects of AsA-mediated physiological responses require additional research if AsA metabolism is to be manipulated to enhance stress-tolerance. This book summarizes the roles of AsA that are directly or indirectly involved in the metabolic processes and physiological functions of plants. Key topics include AsA biosynthesis and metabolism, compartmentation and transport, AsA-mediated ROS detoxification, as well as AsA signaling functions in plant growth, development and responses to environmental stresses. The main objective of this volume is therefore to supply comprehensive and up-to-date information for students, scholars and scientists interested in or currently engaged in AsA research.

Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.

This issue of the Digest of United Kingdom Energy Statistics (DUKES) continues a series which commenced with the Ministry of Fuel and Power Statistical Digest for the years 1948 and 1949, published in 1950. The Ministry of Fuel and Power Statistical Digest was previously published as a Command Paper, the first being that for the years 1938 to 1943, published in July 1944 (Cmd. 6538). A publication tracing the history of energy production and use over the past 60 years was produced in 2009 to mark the 60th anniversary of DUKES. The current issue updates the figures given in the Department of Energy and Climate Change's (DECC) Digest of United Kingdom Energy Statistics 2013, published in July 2013. This printed and bound issue consists of seven chapters and four annexes. The first chapter deals with overall energy. The other chapters cover the specific fuels, renewable sources of energy and combined heat and power. The annexes cover conversion factors and calorific values, a glossary of terms, further sources of information and major events in the energy industries.

The International Arab Conference on Information Technology (ACIT 2020) is a forum for scientists, engineers, and practitioners to present their latest research, results, ideas, developments, and applications in all areas of information technology ACIT 2020 will include presentations to contributed papers and state of the art lectures by invited keynote speakers Tutorials on current issues and special sessions on new trends related to information technology and software industry could be organized This conference is considered as the official scientific conference for the Colleges of Computer and Information Society, stemming from the Association of Arab Universities

The right to life stands at the heart of human rights protection. Individuals cannot enjoy any of the rights guaranteed to them unless their physical existence is ensured. All human rights instrument list the right to life as the first one of their safeguards. Nonetheless, in many situations human life finds itself under structural threat. Although obligated by law to protect the right to life, State authorities time and again engage in deliberate acts of killing. Fortunately, international review bodies have devised many imaginative counter-strategies. Another one of those structural threats is global warming. Obviously, armed conflict puts human life inevitably at risk; the limits of the ‘license to kill’ given by the laws of war must be scrupulously observed.

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.