Great care has been taken to select important concepts and to perfectly describe the anatomy of cells, organs, and organ systems. The plan that has been followed for eight editions of this text is to combine clear and accurate descriptions of anatomy with precise explanations of how structures function and examples of how they work together to maintain life. To emphasize the concepts of anatomy and physiology, the authors provide explanations of how the systems respond to aging, changes in physical activity, and disease, with a special focus on homeostasis and the regulatory mechanisms that maintain it. Timely and interesting examples demonstrate the application of knowledge in a clinical context.

    The authors help students learn key sociological concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables.

    Covering various the materials needed by students in engineering, science, and mathematics, this calculus text makes effective use of computing technology, graphics, and applications. It presents at least two technology projects in each chapter.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    After a brief tale of her own introduction to the paranormal, the author shares funny, poignant, and insightful words straight from the spirit people themselves. Together, the living and the dead seek forgiveness, solve family mysteries, find closure, settle scores, and come together for birthdays, anniversaries, and graduations. Quoting directly from her readings and séances, Priscilla reports the spirit perspective on mental illness, suicide, religion, and even the afterlife itself. For those readers interested in developing their own spirit communication skills, the last section of the book offers meditations and exercises used by the author herself, both personally and with her students. "It Will All Make Sense When You’re Dead" is chock-full of simple and entertaining wisdom, showing us how to live for today, with light hearts and kindness.

    Now an internationally recognized scientist at a top U.S. medical school—one of the leading researchers in the field—sheds light on the extraordinary benefits of these natural health superstars. Thanks to an explosion of research in recent years, one thing is clear: probiotics, the healthy bacteria that inhabit the digestive tract, are the body’s silent partners for good health, optimizing the power of the immune system to fight disease and the “bad” germs we fear. But how do they work? And in the face of factors like stress and poor diet, which decrease their numbers, how do you keep your supply well stocked? Here is an up-to-the-minute, highly accessible guide to probiotics and the foods and supplements that contain and support them—many of which may be in your diet already. Discover:The key role of probiotics and prebiotics in restoring healthy balance to our bodies, improving immune system functioning, and curbing inflammationHow to use probiotic foods and supplements to prevent and relieve allergies, inflammatory bowel disease, irritable bowel syndrome, yeast infections, and the negative side effects of antibiotic useNew evidence that probiotics may help fight asthma, cardiovascular disease, breast and colon cancer, autoimmune diseases, chronic fatigue, fibromyalgia—and even obesityNatural sources of prebiotics, the nutrients that help make the digestive tract more hospitable for probiotic bacteriaThe Probiotics Revolution also includes a step-by-step plan for incorporating the many food sources of probiotics and prebiotics into your diet, a complete buyer’s guide to probiotic supplements, and how to introduce probiotics to your family and children.From the Hardcover edition.

    Genetic susceptibility activated by "triggers" such as pesticides and heavy metals in vaccines can lead to immune system impairment, gut dysfunction, and pathogen invasion such as yeast and viruses in many children. This is the first book written by an experienced clinician that gives a step-by-step treatment guide for parents and doctors based on the understanding that ASD is a complex biomedical illness resulting in significant brain malnutrition. Dr. McCandless, whose grandchild with autism has inspired her "broad spectrum approach," describes important diagnostic tools needed to select appropriate treatment programs. Her book explains major therapies newly available and identifies safe and effective options for parents and physicians working together to improve the health of these special children.Author Biography: Jacquelyn McCandless received her M.D. from the University of Illinois College of Medicine and is certified as a Diplomate of the American Board of Psychiatry and Neurology. Since the early 1990s, her interest in women's issues and sexuality has led to an alternative medicine practice with a focus on anti-aging, brain nutrition, and natural hormone therapy. In 1996, after her granddaughter was diagnosed with autism, she returned even more to basic medicine and began working with biomedical aspects of developmentally delayed children. She now utilizes the knowledge she gained searching for treatments for her grandchild to help other ASD children.

    Fundamentals of Biostatistics with CD-Rom.

    This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

    Mark Plaster takes readers beyond the ambulance bay doors into the stranger-than-fiction world of the Emergency Department. By turns heart-warming and gut-wrenching, "Night Shift" chronicles the ebb and flow of human life, in all of its unvarnished glory, as it passes through the doors of the ED.

    She knew instantly that her decision to work in general practice was the ‘biggest and worst mistake of her life’. Fortunately, however, this did not deter her from continuing in general practice, and this fascinating memoir (spanning half a century) is testament to her resilience and professionalism, as well as her pragmatic and charismatic personality. She shares real stories about real people in this intriguing book. Some stories are truly heart-breaking and will have you reaching for the tissues (such as the times when she has lost patients, and encountered and supported abused children and rape victims). But it isn’t all serious. There are lots of light-hearted and heart-warming moments too, such as the stories about Jessie-dog – her bodyguard when she made home visits, and the time when she helped a large (and desperately in need) family to get rehoused, and her time as a country GP. She also recalls with honesty and candidness, the prejudice and unimaginable pressure she had to contend with, as a young female GP in the 1960s. As well as a plethora of fascinating stories, experiences and case studies, this book also gives us, as 21st Century readers, a glimpse into the rapid changes in general practice and the NHS in general. Whether you’re in general practice, or you’re a medical professional, or you have a penchant for all kinds of autobiographies/memoirs, you will find this a thought-provoking and captivating book that’s impossible to put down. Take a peek at the ‘Look Inside’ feature now and be prepared to be instantly intrigued.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    It is a bridge from the computational courses (such as calculus or differential equations) that students typically encounter in their first year of college to a more abstract outlook. It lays a foundation for more theoretical courses such as topology, analysis and abstract algebra. Although it may be more meaningful to the student who has had some calculus, there is really no prerequisite other than a measure of mathematical maturity. Topics include sets, logic, counting, methods of conditional and non-conditional proof, disproof, induction, relations, functions and infinite cardinality.

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.