Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications.

Deep Learning (DL) is a method of machine learning, running over Artificial Neural Networks, that uses multiple layers to extract high-level features from large amounts of raw data. Deep Learning methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of Deep Learning and its applications in the field of Biomedical Engineering. Deep learning has been rapidly developed in recent years, in terms of both methodological constructs and practical applications. Deep Learning provides computational models of multiple processing layers to learn and represent data with higher levels of abstraction. It is able to implicitly capture intricate structures of large-scale data and is ideally suited to many of the hardware architectures that are currently available. The ever-expanding amount of data that can be gathered through biomedical and clinical information sensing devices necessitates the development of machine learning and AI techniques such as Deep Learning and Convolutional Neural Networks to process and evaluate the data. Some examples of biomedical and clinical sensing devices that use Deep Learning include: Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications provides the most complete coverage of Deep Learning applications in biomedical engineering available, including detailed real-world applications in areas such as computational neuroscience, neuroimaging, data fusion, medical image processing, neurological disorder diagnosis for diseases such as Alzheimer's, ADHD, and ASD, tumor prediction, as well as translational multimodal imaging analysis.

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.

Nanoemulsions are produced by mixing an oil phase with an aqueous phase under shear pressure. This procedure yields uniform populations of oil droplets ranging in diameter from 200 to 8 nm that are kinetically stable colloidal substances with enhanced properties compared to the conventional emulsion substances. Nanoemulsions have broad potential applications in agriculture, food, health, and biomedical sciences. Nanoemulsion Applications in Agriculture, Food, Health, and Biomedical Sciences focuses on the aspects of nanoemulsion-like synthesis, characterization, and more and examines recent trends in their applications within a variety of relevant fields. Nanoemulsions have broad application in many different fields; without emulsification, process product development would not be possible. Covering topics such as cancer treatment, healthcare applications, and food manufacturing, this book is essential for scientists, doctors, researchers, post-graduate students, medical students, government officials, hospital directors, professors, and academicians.

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks.

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.

Terahertz Biomedical and Healthcare Technologies: Materials to Devices reviews emerging advances in terahertz biomedical and healthcare technologies, including advances in fundamental materials science research, device design and fabrication, applications, and challenges and opportunities for improved performance. In addition, the improvement of materials, optical elements, and measuring techniques are also explored. Other sections cover the design and development of wide bandgap semiconductors for terahertz device applications, including their physics, device modeling, characterization and fabrication concepts. Finally, the book touches on potential defense, medical imaging, internet of things, and the machine learning applications of terahertz technologies.

3D Printing in Medicine and Surgery: Applications in Healthcare is an advanced book on surgical and enhanced medical applications that can be achieved with 3D printing. It is an essential handbook for medical practitioners, giving access to a range of practical methods, while also focusing on applied knowledge. This comprehensive resource features practical experiments and processes for preparing 3D printable materials. Early chapters cover foundational knowledge and background reading, while later chapters discuss and review the current technologies used to engineer specific tissue types, experiments and methods, medical approaches and the challenges that lie ahead for future research. The book is an indispensable reference guide to the various methods used by current medical practitioners working at the forefront of 3D printing applications in medicine.

""I wish to be the thinnest girl at school, or maybe even the thinnest eleven-year-old on the entire planet,"" confides Lori Gottlieb to her diary. "I mean, what are girls supposed to wish for, other than being thin?"
For a girl growing up in Beverly Hills in 1978, the motto "You can never be too rich or too thin" is writ large. Precocious Lori learns her lessons well, so when she's told that "real women don't eat dessert" and "no one could ever like a girl who has thunder thighs," she decides to become a paragon of dieting. Soon Lori has become the "stick figure" she's longed to resemble. But then what? "Stick Figure" takes the reader on a gripping journey, as Lori struggles to reclaim both her body and her spirit.
By turns painful and wry, Lori's efforts to reconcile the conflicting messages society sends women ring as true today as when she first recorded these impressions. "One diet book says that if you drink three full glasses of water one hour before every meal to fill yourself up, you'll lose a pound a day. Another book says that once you start losing weight, everyone will ask, 'How did you do it?' but you shouldn't tell them because it's 'your little secret.' Then right above that part it says, "'New York Times" bestseller.' Some secret."
With an edgy wit and keenly observant eye, "Stick Figure" delivers an engrossing glimpse into the mind of a girl in transition to adulthood. This raw, no-holds-barred account is a powerful cautionary tale about the dangers of living up to society's expectations.

Rehabilitation helps individuals maintain and optimize independence. Historically, people with dementia have received little rehabilitation and the focus has been on care to replace lost function. Dementia Rehabilitation is a resource for health and social professionals, service planners, policy makers, and academics. The book makes a compelling case for rehabilitation for people with dementia, including the views of people with dementia and the research evidence. For each area of function, the research evidence and relevant theory is summarized, followed by practical information on clinical assessment, and delivery of therapies.

An evidence-based guide to hemodynamic monitoring procedures and patient care, Hemodynamic Monitoring: Evolving Technologies & Clinical Practice describes invasive, non-invasive, and minimally invasive techniques in monitoring blood pressure and oxygen levels within the circulatory system. It provides a clear, illustrated discussion of the anatomy and physiology related to hemodynamics, explains the technologies involved in each measurement, and includes quick-reference tables of normal and abnormal values. Written by cardiovascular nursing expert Mary E. Lough, Hemodynamic Monitoring is a detailed, comprehensive text designed for critical care nurses and respiratory therapists. Case Studies in each clinical chapter include a patient scenario with assessment details, allowing you to envision real-life patient care and prepare for adverse outcomes or complications. Coverage of patient safety includes a discussion of important measures that will help you provide safe and effective patient-centered care. UNIQUE! Coverage of patient comfort includes a discussion of methods to increase patient comfort during invasive procedures. Clinical Reasoning Pearls provide practical advice from experts and describe how to implement a procedure or improve patient care. A table of Important Values and Formulas is located inside the back cover for quick and easy reference.

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.

As old age is increasing globally, some challenges arise such as multimorbidity, a unique medical condition that has multiple potential complications and thus needs high-quality care directed by qualified healthcare providers. Multimorbidity is an important daily challenge to internists worldwide due to its many difficulties. Junior physicians dealing with multimorbidity must have the knowledge to practice high-quality care for their elderly patients. Cases on Multimorbidity and Its Impact on Elderly Patients considers approaches to manage multimorbidity and its unique complications and challenges to aid in appropriate daily decision making. Covering key topics such as weight loss, aging, and frailty, this reference work is ideal for medical professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

The most comprehensive and up-to-date high-yield review available for the USMLE (R) Step 2 CK-completely revised and better than ever! The expert author team that guided students to success on the USMLE (R) Step 1 presents the latest edition of this skill-sharpening review for the USMLE (R) Step 2 CK. With an easy-to-follow bulleted presentation of must-know diseases and disorders, this one-of-a-kind study companion offers the most current overview of all core areas on the boards. Included is a host of learning tools, from key facts and mnemonics to full-color illustrations and proven test-taking strategies everything students need to pass the exam with flying colors. * Co-written by students who excelled on the recent exam and reviewed by top faculty * Concise summaries of more than 1,000 commonly tested clinical topics for fast, high-yield study * Key Facts and mnemonics reinforce must-know concepts * Expert coverage of best initial steps in diagnosis and management * Updated Rapid Review section facilitates last-minute cramming * Hundreds of full-color photographs and illustrations * Revised study and test-taking strategies * A completely updated listing of top-rated review sources

Mathematical and numerical modelling of engineering problems in medicine is aimed at unveiling and understanding multidisciplinary interactions and processes and providing insights useful to clinical care and technology advances for better medical equipment and systems. When modelling medical problems, the engineer is confronted with multidisciplinary problems of electromagnetism, heat and mass transfer, and structural mechanics with, possibly, different time and space scales, which may raise concerns in formulating consistent, solvable mathematical models. Computational Medical Engineering presents a number of engineering for medicine problems that may be encountered in medical physics, procedures, diagnosis and monitoring techniques, including electrical activity of the heart, hemodynamic activity monitoring, magnetic drug targeting, bioheat models and thermography, RF and microwave hyperthermia, ablation, EMF dosimetry, and bioimpedance methods. The authors discuss the core approach methodology to pose and solve different problems of medical engineering, including essentials of mathematical modelling (e.g., criteria for well-posed problems); physics scaling (homogenization techniques); Constructal Law criteria in morphing shape and structure of systems with internal flows; computational domain construction (CAD and, or reconstruction techniques based on medical images); numerical modelling issues, and validation techniques used to ascertain numerical simulation results. In addition, new ideas and venues to investigate and understand finer scale models and merge them into continuous media medical physics are provided as case studies.

ODE/PDE Analysis of Antibiotic/Antimicrobial Resistance: Programming in R presents mathematical models for antibiotic/antimicrobial resistance based on ordinary and partial differential equations (ODE/PDEs). Sections cover the basic ODE model, the detailed PDE model that gives the spatiotemporal distribution of four dependent variable components, including susceptible bacteria population density, resistant bacteria population density, plasmid number, and antibiotic concentration. The computer-based implementation of the example models is presented through routines coded (programmed) in R, a quality, open-source scientific computing system that is readily available from the Internet. As such, formal mathematics is minimized and no theorems and proofs are required. The PDE analysis is based on the method of lines (MOL), an established general algorithm for PDEs that is implemented with finite differences. Routines are available from a download link so that the example models can be executed without having to first study numerical methods and computer coding. Routines can then be applied to variations and extensions of the antibiotic/antimicrobial models, such as changes in the ODE/PDE parameters (constants) and the form of the model equations.