This book addresses essential principles of research according to the scientific method for medical imaging technology research. The scope of this book covers the nature of scientific research; quantitative and qualitative approaches essentials; research planning; literature review fundamentals; research methods; data collection, analysis, and interpretation; and communicating research findings. The book meets the educational requirements on Research Principles and Concepts (for entry to practice) of the following professional radiologic technology associations: the American Society of Radiologic Technologists (ASRT), the Canadian Association of Medical Radiation Technologists (CAMRT), the College of Radiographers in the United Kingdom, and radiography societies and associations in Asia, Australia, Europe, and Africa. This is an ideal book for radiologic technologists, nuclear medicine technologists, and radiation therapists seeking to get started in research in their profession. Additionally, biomedical imaging engineering technologists, radiologists, and medical imaging physicists may use this as a "guiding principles" textbook.

This book is the first of two volumes that offer a comprehensive, up-to-date account of current knowledge regarding high-density lipoprotein (HDL), the changes that occur in HDL under different conditions, the clinical applications of HDL, and means of enhancing HDL functionality. HDL comprises a diverse group of lipoproteins and its composition and metabolism are dynamic. In this volume, the focus is on the changes observed in HDL under different health statuses, with particular attention to the functional and structural correlations of HDL and apolipoprotein A-1. The impacts of a wide variety of factors on HDL are examined in depth, covering, for example, diet, exercise, smoking, age, diverse diseases, and different forms of environmental pollution. It has long been known that HDL has anti-atherosclerotic and antidiabetic properties, and more recently its anti-aging activities have been recognized. These benefits of HDL are highly dependent on its lipids, proteins, apolipoproteins, and enzymes, and specifically their composition and ratios. In documenting the latest knowledge in this field, this volume will be of interest to both researchers and clinicians.

This book examines the basic cellular and molecular mechanisms associated with aging. It comprehensively describes the genetic, epigenetic, biochemical and metabolic regulation of aging, as well as some important age-related diseases. Divided into two major sections, it takes readers through the various aspects of aging in a story-like manner and suggests various interventions for healthy aging, such as dietary restriction, regular exercise, nutrition and maintaining a balanced and a non-stressful lifestyle. It describes the implications of aging on the nervous system, metabolism, immunity and stem cells as well as care for the elderly. The book is an ideal companion for both new and established researchers in the field and is also useful for educators, clinicians and policy makers.

This book offers a snapshot of cutting-edge applications of digital phenotyping and mobile sensing for studying human behavior and planning innovative e-healthcare interventions. The respective chapters, written by authoritative researchers, cover both theoretical perspectives and good scientific and professional practices related to the use and development of these technologies. They share novel insights into established applications of mobile sensing, such as predicting personality or mental and behavioral health on the basis of smartphone usage patterns, and highlight emerging trends, such as the use of machine learning, big data and deep learning approaches, and the combination of mobile sensing with AI and expert systems. Important issues relating to privacy and ethics are analyzed, together with selected case studies. This thoroughly revised and extended second edition provides researchers and professionals with extensive information on the latest developments in the field of digital phenotyping and mobile sensing. It gives a special emphasis to trends in diagnostics systems and AI applications, suggesting important future directions for research in public health and social sciences.

Artificial Intelligence to Solve Pervasive Internet of Things Issues discusses standards and technologies and wide-ranging technology areas and their applications and challenges, including discussions on architectures, frameworks, applications, best practices, methods and techniques required for integrating AI to resolve IoT issues. Chapters also provide step-by-step measures, practices and solutions to tackle vital decision-making and practical issues affecting IoT technology, including autonomous devices and computerized systems. Such issues range from adopting, mitigating, maintaining, modernizing and protecting AI and IoT infrastructure components such as scalability, sustainability, latency, system decentralization and maintainability. The book enables readers to explore, discover and implement new solutions for integrating AI to solve IoT issues. Resolving these issues will help readers address many real-world applications in areas such as scientific research, healthcare, defense, aeronautics, engineering, social media, and many others.

In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability.

This book highlights the recent advances of thermodynamics and biophysics in drug delivery nanosystems and in biomedical nanodevices. The up-to-date book provides an in-depth knowledge of bio-inspired nanotechnological systems for pharmaceutical applications. Biophysics and thermodynamics, supported by mathematics, are the locomotive by which the drug transportation and the targeting processes will be achieved under the light of the modern pharmacotherapy. They are considered as scientific tools that promote the understanding of physicochemical and thermotropic functionality and behavior of artificial cell membranes and structures like nanoparticulate systems. Therefore, this book focusses on new aspects of biophysics and thermodynamics as important elements for evaluating biomedical nanosystems, and it correlates their physicochemical, biophysical and thermodynamical behaviour with those of a living organism. In 2018, Prof. Demetzos was honored with an award by the Order of Sciences of the Academy of Athens for his scientific contribution in Pharmaceutical Nanotechnology.

Powered Prostheses: Design, Control, and Clinical Applications presents the state-of-the-art in design, control and application of assistive technologies used in rehabilitation, including powered prostheses used in lower and upper extremity amputees and orthosis used in the rehabilitation of various joint disorders. The progress made in this field over the last decade is so vast that any new researcher in this field will have to spend years digesting the main achievements and challenges that remain. This book provides a comprehensive vision of advances, along with the challenges that remain on the path to the development of true bionic technology.

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends.

Signal Processing in Medicine and Biology: Innovations in Big Data Processing provides an interdisciplinary look at state-of-the-art innovations in biomedical signal processing, especially as it applies to large data sets and machine learning. Chapters are presented with detailed mathematics and complete implementation specifics so that readers can completely master these techniques. The book presents tutorials and examples of successful applications and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology at the intersection between healthcare, engineering, and computer science.

Wearable Sensors: Fundamentals, Implementation and Applications has been written by a collection of experts in their field, who each provide you with an understanding of how to design and work with wearable sensors. Together these insights provide the first single source of information on wearable sensors that would be a fantastic addition to the library of any engineers working in this field. Wearable Sensors covers a wide variety of topics associated with development and applications of wearable sensors. It also provides an overview and a coherent summary of many aspects of wearable sensor technology. Both professionals in industries and academic researchers need this package of information in order to learn the overview and each specific technology at the same time. This book includes the most current knowledge on the advancement of light-weight hardware, energy harvesting, signal processing, and wireless communications and networks. Practical problems with smart fabrics, biomonitoring and health informatics are all addressed, plus end user centric design, ethical and safety issues. The new edition is completely reviewed by key figures in the field, who offer authoritative and comprehensive information on the various topics. A new feature for the second edition is the incorporation of key background information on topics to allow the less advanced user access to the field and to make the title more of an auto-didactic book for undergraduates.

Going back at least to the writings of John Stuart Mill and Jean-Jacques Rousseau, people have argued for and against maintaining a state of nature. Is there an inherent virtue in leaving alone a naturally occurring condition, or does the human species thrive when we find ways to improve our circumstances? This volume probes whether "nature" and "the natural" are capable of guiding moral deliberations in policy making.

Drawing on philosophy, religion, and political science, this book examines three questions central to debates over the idea of "nature" in human action. Conceptually, it asks what the term means, how it should be considered, and if it is, even in part, a social construct. From a moral perspective, the contributors question if being "natural" is itself of value or if its worth is only as a means to advance other morally acceptable ends. Politically, essays discuss whether appeals to nature can and should affect public policy and, if so, whether they are moral trump cards or should instead be fitted alongside or weighed against other concerns.

Achieving consensus on these questions has proven elusive and seems unattainable. This should not, however, be an obstacle to moving the debate forward. By bringing together disparate approaches to addressing these concepts, "The Ideal of Nature" suggests the possibility of intermediate positions that move beyond the usual full-throated defense and blanket dismissal found in much of the debate. Scholars of bioethics, environmental philosophy, religious studies, sociology, public policy, and political theory will find much merit in this book's lively discussion.

Through this book, the readers will learn about the different aspects of Actinobacteria- beginning with its ecology and occurrence, to the ways of its adaptation to harsh climates, and finally to its practical applications. The book also presents methods of identifying and characterizing this diverse group of bacteria through advanced techniques like MALDI-TOF, 16S rRNA analysis, etc. Different chapters describe the various biotechnological applications of Actinobacteria, including bioremediation, secondary metabolite production, and in producing antibiotics, anti-cancer therapeutics. It also provides insights into the applications in agriculture and forestry by inhibiting plant pathogenic bacteria's growth.

This book commemorates the scientific contributions of distinguished statistician, Andrei Yakovlev. It reflects upon Dr. Yakovlev's many research interests including stochastic modeling and the analysis of micro-array data, and throughout the book it emphasizes applications of the theory in biology, medicine and public health. The contributions to this volume are divided into two parts. Part A consists of original research articles, which can be roughly grouped into four thematic areas: (i) branching processes, especially as models for cell kinetics, (ii) multiple testing issues as they arise in the analysis of biologic data, (iii) applications of mathematical models and of new inferential techniques in epidemiology, and (iv) contributions to statistical methodology, with an emphasis on the modeling and analysis of survival time data. Part B consists of methodological research reported as a short communication, ending with some personal reflections on research fields associated with Andrei and on his approach to science. The Appendix contains an abbreviated vitae and a list of Andrei's publications, complete as far as we know. The contributions in this book are written by Dr. Yakovlev's collaborators and notable statisticians including former presidents of the Institute of Mathematical Statistics and of the Statistics Section of the AAAS. Dr. Yakovlev's research appeared in four books and almost 200 scientific papers, in mathematics, statistics, biomathematics and biology journals. Ultimately this book offers a tribute to Dr. Yakovlev's work and recognizes the legacy of his contributions in the biostatistics community.

This volume covers current research in the usage of magnetic nanoparticles for drug delivery. It discusses synthesis methods, stabilizers used for surface coating on MNPs, and potential target ligands which can be used to ferry payloads to the targeted disease region. It also highlights the factors affecting delivery efficiency and toxicity, as well as the different routes of administration. The content also focus on the use of these carriers for gene therapy and to target brain tumors. This volume will be of interest to researchers working on drug discovery and delivery platforms.

Biomaterials for Organ and Tissue Regeneration: New Technologies and Future Prospects examines the use of biomaterials in applications related to artificial tissues and organs. With a strong focus on fundamental and traditional tissue engineering strategies, the book also examines how emerging and enabling technologies are being developed and applied. Sections provide essential information on biomaterial, cell properties and cell types used in organ generation. A section on state-of-the-art in organ regeneration for clinical purposes is followed by a discussion on enabling technologies, such as bioprinting, on chip organ systems and in silico simulations.

The increasing interest in the bio-impedance analysis in various fields has increased the demand for portable and low-cost impedance analyzers that can be used in the field. Simplifying the hardware is crucial to maintaining low-cost and portability, but this is not an easy task due to the need for accurate phase and magnitude measurements. This book discusses different portable impedance analyzers design techniques. Additionally, complete designs using two different approaches are reported. The first approach utilizes a commercially available single chip solution while the second one is based on a new measurement technique that eliminates the need to measure the phase by using a software algorithm to extract it from the magnitude information. Applications to the measurement of fruit bio-impedance are emphasized and compared with measurements from professional stand-alone impedance analyzers.

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain-computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore-Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology. In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain-computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain-computer technology and virtual reality technology.

Nanomedicines for Breast Cancer Theranostics addresses the translational aspects and clinical perspectives of breast cancer nanomedicine from a multidisciplinary perspective. The book summarizes research efforts at the preclinical and clinical stage of nanostructures and nanomedicine for dealing with the important challenge of nanomedicine translation in breast cancer theranostics. This book is an important resource for those working in both academia and industry, focusing on hot topics in biomaterials, biomedical engineering, drug delivery and oncology.

Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research. First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties. The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners.

This book covers multi-scale biomechanics for oncology, ranging from cells and tissues to whole organ. Topics covered include, but not limited to, biomaterials in mechano-oncology, non-invasive imaging techniques, mechanical models of cell migration, cancer cell mechanics, and platelet-based drug delivery for cancer applications. This is an ideal book for graduate students, biomedical engineers, and researchers in the field of mechanobiology and oncology. This book also: Describes how mechanical properties of cancer cells, the extracellular matrix, tumor microenvironment and immuno-editing, and fluid flow dynamics contribute to tumor progression and the metastatic process Provides the latest research on non-invasive imaging, including traction force microscopy and brillouin confocal microscopy Includes insight into NCIs' role in supporting biomechanics in oncology research Details how biomaterials in mechano-oncology can be used as a means to tune materials to study cancer

Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders.

This book takes the notions of adaptivity and learning from the realm of engineering into the realm of biology and natural processes. It introduces a Hebbian-LMS algorithm, an integration of unsupervised Hebbian learning and supervised LMS learning in neural networks, as a mathematical representation of a general theory for synaptic learning in the brain, and adaptation and functional control of homeostasis in living systems. Written in a language that is able to address students and scientists with different backgrounds, this book accompanies readers on a unique journey through various homeostatic processes in living organisms, such as body temperature control and synaptic plasticity, explaining how the Hebbian-LMS algorithm can help understand them, and suggesting some open questions for future research. It also analyses cell signalling pathways from an unusual perspective, where hormones and hormone receptors are shown to be regulated via the principles of the Hebbian-LMS algorithm. It further discusses addiction and pain, and various kinds of mood disorders alike, showing how they can be modelled with the Hebbian-LMS algorithm. For the first time, the Hebbian-LMS algorithm, which has been derived from a combination of Hebbian theory from the neuroscience field and the LMS algorithm from the engineering field of adaptive signal processing, becomes a potent model for understanding how biological regulation works. Thus, this book is breaking new ground in neuroscience by providing scientists with a general theory for how nature does control synaptic learning. It then goes beyond that, showing that the same principles apply to hormone-mediated regulation of physiological processes. In turn, the book tackles in more depth the concept of learning. It covers computer simulations and strategies for training neural networks with the Hebbian-LMS algorithm, demonstrating that the resulting algorithms are able to identify relationships between unknown input patterns. It shows how this can translate in useful ideas to understand human memory and design cognitive structures. All in all, this book offers an absolutely, unique, inspiring reading for biologists, physiologists, and engineers, paving the way for future studies on what we could call the nature's secret learning algorithm.

This volume of the series Cardiac and Vascular Biology presents the most relevant aspects of vascular mechanobiology along with many more facets of this fascinating, timely and clinically highly relevant field. Mechanotransduction, mechanosensing, fluid shear stress, hameodynamics and cell fate, are just a few topics to name. All important aspects of vascular mechanobiology in health and disease are reviewed by some of the top experts in the field. This volume, together with a second title on cardiac mechanobiology featured in this series, will be of high relevance to scientists and clinical researchers in the area of vascular biology, cardiology and biomedical engineering.