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Diabetes Without Needles: Non-invasive Diagnostics and Health Management provides a comprehensive and objective compilation of the most promising noninvasive methods for glucose monitoring, including an in-depth analysis of their advantages and disadvantages in terms of biochemical processes. The latest advances in the field are discussed, including methods such as optical measurements, electrochemical measurements, exhaled breath analysis, direct measurements of glucose in the blood using noninvasive techniques, and the indirect analysis of biomarkers that are related to the glycemia. The book's author also presents recommendations for future research directions in this field. This book is a valuable resource for researchers in the areas of diabetes, noninvasive methods and diagnostics development.

Approx.264 pages

Eosinophil Ultrastructure: Atlas of Eosinophil Cell Biology and Pathology entirely focuses on eosinophils and their functional roles in inflammation, host defense, and normal homeostatic activities. The book explores the ultrastructure of human eosinophils, highlighting biological processes observed under normal, experimental, and pathological conditions. Created to fill a void in the eosinophil literature, the book includes an extensive array of electron microscopic images that illustrate the diversity of eosinophil morphology. While the atlas is a learning and teaching tool, it is mainly a helpful  resource for researchers to identify distinguishing features and structural changes that arise during studies of human eosinophils. The book also covers the ultrastructure of mouse eosinophils under normal and activation conditions and in the context of representative diseases.

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation.

Nano-Enabled Agrochemicals in Agriculture presents a targeted overview of the safe implementation of nanotechnologies within agricultural and horticultural settings, with the purpose of achieving enhanced production while maintaining ecological integrity. The growing global request for agricultural crops and products requires high standards of quality and safety, which has stimulated the search for new technologies that preserve their quality and delay their decomposition. Nanotechnology may boost plant production by improving nutrient uptake/use efficiency with nanoformulations of fertilizers and agrochemicals for plant enhancement, detection and treatment of diseases, and host-parasite interactions at the molecular level using nanosensors. It also may improve plant disease diagnostics, removal of contaminants from soil and water, postharvest management of vegetables and flowers, and reclamation of salt-affected soils.  Although the markets for nanoproducts and nanoformulations continue to increase, there are also growing concerns regarding the fate and behavior of nanomaterials in environmental systems. Exploring important topics related to nanotechnology and nanomaterials, the book includes the use of nanochemicals in insect pest management, as nanofungicides, nanoherbicides, micronutrient supply, and nanosensors to monitor crop and soil health conditions, from detection of agrochemicals to their slow release of agrochemicals, and their impact on related environs.  This book will serve as an excellent resource for a wide range of plant scientists who have concerns about nanomaterial interactions with terrestrial and aquatic plants.

Industrial Hemp: Food and Nutraceutical Applications is a comprehensive overview of different value chains for the industrial hemp industry. This excellent reference supports multi-disciplines and presents industrial hemp as a multi-purpose crop, with special attention paid to its food and nutraceutical applications. By combining and presenting multidisciplinary knowledge, readers will be introduced to recent progress in hemp production, processing, utilization and marketing. The book provides a systematic overview of alternative hemp applications, but also serves as a guide to the challenges needed for hemp revitalization to reach its fullness.

Nuclear Engineering Mathematical Modeling and Simulation presents the mathematical modeling of neutron diffusion and transport. Aimed at students and early career engineers, this highly practical and visual resource guides the reader through computer simulations using the Monte Carlo Method which can be applied to a variety of applications, including power generation, criticality assemblies, nuclear detection systems, and nuclear medicine to name a few. The book covers optimization in both the traditional deterministic framework of variational methods and the stochastic framework of Monte Carlo methods. Specific sections cover the fundamentals of nuclear physics, computer codes used for neutron and photon radiation transport simulations, applications of analyses and simulations, optimization techniques for both fixed-source and multiplying systems, and various simulations in the medical area where radioisotopes are used in cancer treatment.

Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions. The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.

Herbal Medicines: A Boon for Healthy Human Life provides a comprehensive overview of the role of herbal medicines for treating a broad variety of human diseases, from neurological disorders to cancer and major disorders such as infectious diseases, metabolic disorders, and more. Each chapter summarizes the current state and future direction of the use of herbal medicines against multiple diseases from a translational point-of-view, making this reference a valuable source of information for a large audience, including researchers and healthcare providers interested in the field of herbal remedies.

Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications.

Approx.228 pages

Approx.340 pages

Rhizosphere Engineering is a guide to applying environmentally sound agronomic practices to improve crop yield while also protecting soil resources. Focusing on the potential and positive impacts of appropriate practices, the book includes the use of beneficial microbes, nanotechnology and metagenomics. Developing and applying techniques that not only enhance yield, but also restore the quality of soil and water using beneficial microbes such as Bacillus, Pseudomonas, vesicular-arbuscular mycorrhiza (VAM) fungi and others are covered, along with new information on utilizing nanotechnology, quorum sensing and other technologies to further advance the science. Designed to fill the gap between research and application, this book is written for advanced students, researchers and those seeking real-world insights for improving agricultural production.

Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis.

Features: The only insect ecology text that emphasizes insect effects on ecosystem properties and services, as well as evolutionary adaptations to environmental conditions. Includes new material on long-term trends in insect abundance, addressing the so-called "insect apocalypse?. Offers crucial updates on mechanisms by which insects affect, and potentially regulate, ecosystem structure and function. Applies ecological principles to improved management of insects for the sustainable delivery of ecosystem services

Approx.366 pages