Support vector machines (SVMs) are used in a range of applications, including drug design, food quality control, metabolic fingerprint analysis, and microarray data-based cancer classification. While most mathematicians are well-versed in the distinctive features and empirical performance of SVMs, many chemists and biologists are not as familiar wi
Winner of 2018 PROSE Award for MULTIVOLUME REFERENCE/SCIENCE This encyclopedia offers a comprehensive and easy reference to physical organic chemistry (POC) methodology and techniques. It puts POC, a classical and fundamental discipline of chemistry, into the context of modern and dynamic fields like biochemical processes, materials science, and molecular electronics. Covers basic terms and theories into organic reactions and mechanisms, molecular designs and syntheses, tools and experimental techniques, and applications and future directions Includes coverage of green chemistry and polymerization reactions Reviews different strategies for molecular design and synthesis of functional molecules Discusses computational methods, software packages, and more than 34 kinds of spectroscopies and techniques for studying structures and mechanisms Explores applications in areas from biology to materials science The Encyclopedia of Physical Organic Chemistry has won the 2018 PROSE Award for MULTIVOLUME REFERENCE/SCIENCE. The PROSE Awards recognize the best books, journals and digital content produced by professional and scholarly publishers. Submissions are reviewed by a panel of 18 judges that includes editors, academics, publishers and research librarians who evaluate each work for its contribution to professional and scholarly publishing. You can find out more at: proseawards.com Also available as an online edition for your library, for more details visit Wiley Online Library
This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.
The prevailing global environmental crisis is primarily because of non-standardized parameters for environmental regulation. Unplanned expansion of economic activities, consideration for environmental conservation and several associated problems are emerging due to degradation in quality of ambient environment such as clean air, safe drinking water and quality of food, particularly in developing nations. Due to poor/casual execution of EIA protocol, newly developing countries are preferred destination for establishing pollution emitting industries, which results in degradation and depletion of natural resources. Lack of environmental policy intervention is another major attraction for establishing such industries in these nations. In order to ensure sustainable development, the highest priority issues include the monitoring and eradication of environmental problems which arise due to economic development. Initiation of any form of economic development primarily results in loss of forests and thus biodiversity, followed by deterioration in quality of air and contamination of natural resources. The worst impact of non-standardized economic development is the contamination of air, water and soil. Sustainable development ensures responsible interface with the environment to minimize the depletion or degradation of natural resources and ensure long term environmental quality. It involves integrated approaches in understanding the importance of environmental management systems and policy inventions leading to improved environmental performance. The present book is proposed to address the environmental concerns associated with economic development and approaches involved to attain sustainable economic development, which include monitoring of the quality of air, deforestation, quality of water resources, soil erosion and degradation of the natural environment.
Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.
"This book is a timely compendium of key elements that are crucial for the study of machine learning in chemoinformatics, giving an overview of current research in machine learning and their applications to chemoinformatics tasks"--Provided by publisher.
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
The Opuntia fruits, commonly known as cactus pears or prickly pears, have been suggested by the Food and Agriculture Organization to be a promising and strategic crop in regions suffering from lack of water. In Mexico, India, South Africa, and the Mediterranean, the Opuntia fruits have become popular due to their nutritive value and health-promoting benefits, including antioxidant, antiulcerogenic and antiatherogenic traits and protective effects against LDL oxidation. Additionally, readily absorbable sugars, high vitamin C and mineral content, and a pleasant flavour make Opuntia tailor-made for novel foods. Due to their ecological advantages, high functional value, and health-related traits, Opuntia fruits can be highly exploited in different food processing applications. For instance, Opuntia cactus fruits are used for the preparation of juices and marmalades; Opuntia cactus plants are used to feed animals in African and Latin American countries; Peruvian farmers cultivate Opuntia cactus for growing the cochineal (Dactylopius coccus) insect and producing the natural dye carmine; and the commercial production of food and non-food products from Opuntia has been established in Mexico, USA and several Mediterranean countries. Opuntia spp.: Chemistry, Bioactivity and Industrial Applications creates a multidisciplinary forum of discussion on Opuntia cactus with special emphasis on its horticulture, post-harvest, marketability, chemistry, functionality, health-promoting properties, technology and processing. The text includes detailed discussion of the impact of traditional and innovative processing on the recovery of high-added value compounds from Opuntia spp. by-products. Later chapters explore the potential applications of Opuntia spp. in food, cosmetics and pharmaceutical products.
Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany’s mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA). Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today’s minerology and petroleum engineers. Key Features • Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. • Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. • Includes over 200 equations that illustrate how to follow examples in the book.
Endophytes are the plant symbionts that live inside the plant tissue without causing any symptoms of disease for a part of their life-cycle, as compared to the rhizosphere and phyllosphere microbes that live on the plant’s surface, and pathogens that cause disease. Bacteria and fungi are the two most common groups that are included in endophytes. They find their way into plants’ endosphere to become extremely important plant symbionts that improve metabolite profile, fitness and stress tolerance of the host. Endophytes are an important untapped reservoir of biological resources. During the last few decades, endophytes have attracted scientists working in the field of agriculture, environment and industry due to the possibilities of diverse biotechnological applications in such fields. Endophytes promote plant growth by improving the physiological and metabolic functions of the host plants via nutrient acquisition, nitrogen fixation, phytohormone production, enhancing abiotic/biotic stress tolerance, and disease resistance. These benefits conferred by the endophytes can be used to promote agriculture yield and food quality. In addition endophytes are known to produce novel antibiotics; secondary metabolites including alkaloids, flavonoids, steroids, phenolic acids, quinines; siderophores; and enzymes such as chitinases and cellulases. These natural compounds have use in pharmaceutical, food and agricultural industries. Endophytes have usage in biodegradation, bioextraction or bioaccumulation of environmental pollutants. They also have potential application in enhanced phytoremediation. More recently, endophytic bacteria and fungi have also been used for the green synthesis of nanoparticles for different medical and industrial applications. Functional genomics studies of endophytes provided more information and better understanding of network of the complex host-endophyte interactions and other associated microbes to harness the biotechnological potential of endophytes more efficiently and sustainably.
