Imbalance

Assessment and Treatment of Muscle Imbalance: The Janda Approachblends postural techniques, neurology, and functional capabilities in order to alleviate chronic musculoskeletal pain and promote greater functionality. Developed by Vladimir Janda, respected neurologist and physiotherapist , the Janda approach presents a unique perspective to rehabilitation. In contrast to a more traditional structural view, the Janda approach is functional—emphasizing the importance of the sensorimotor system in controlling movement and chronic musculoskeletal pain syndromes from sports and general activities.Assessment and Treatment of Muscle Imbalance: The Janda Approachis the only text to offer practical, evidence-based application of Janda’s theories. Filled with illustrations, photos, and step-by-step instructions, Assessment and Treatment of Muscle Imbalanceuses a systematic approach in presenting information that can be used in tandem with other clinical techniques. This resource for practitioners features the following tools: --A rationale for rehabilitation of the musculoskeletal sytem based on the relationship between the central nervous system and the motor system --A systematic method for the functional examination of the muscular system --Treatment processes focusing on the triad of normalization of peripheral structures, restoration of muscle balance, and facilitation of afferent systems and sensorimotor training --The role of muscle imbalance and functional pathology of sensorimotor systems for specific pain complaints, including cervical pain syndrome, upper- and lower-extremity pain syndromes, and low back pain syndromes Assessment and Treatment of Muscle Imbalanceprovides an evidence-based explanation of muscle imbalance. The step-by-step Janda system of evaluation is explained—including analysis of posture, balance, and gait; evaluation of movement patterns; testing of muscle length; and assessment of the soft tissue. The text explores treatment options for muscle imbalance through facilitation and inhibition techniques and sensorimotor training to restore neuromsucular function. It also includes four case studies examining musculoskeletal conditions and showing how the Janda approach compares with other treatments. This text combines theory, evidence, and applications to assist clinicians in implementing the Janda approach into their practice. Assessment and Treatment of Muscle Imbalance: The Janda Approachfocuses on the neurological aspects of muscle imbalance that are common causes of pain and dysfunction in sports and occupational activities. By distilling the scientific works of Vladimir Janda into a practical, systematic approach, this unique resource will assist health care providers in treating patients with musculoskeletal complaints as well as exercise professionals in developing appropriate exercise prescription and training programs.

A study of how ordinary people deal with everyday problems through self-mastery and mental health care practices. Everyday suffering—those conditions or feelings brought on by trying circumstances that arise in everyone’s lives—is something that humans have grappled with for millennia. But the last decades have seen a drastic change in the way we approach it. In the past, a person going through a time of difficulty might keep a journal or see a therapist, but now the psychological has been replaced by the biological: instead of treating the heart, soul, and mind, we take a pill to treat the brain. Chemically Imbalanced is a field report on how ordinary people dealing with common problems explain their suffering, how they’re increasingly turning to the thin and mechanistic language of the “body/brain,” and what these encounters might tell us. Drawing on interviews with people dealing with struggles such as underperformance in school or work, grief after the end of a relationship, or disappointment with how their life is unfolding, Joseph E. Davis reveals the profound revolution in consciousness that is underway. We now see suffering as an imbalance in the brain that needs to be fixed, usually through chemical means. This has rippled into our social and cultural conversations, and it has affected how we, as a society, imagine ourselves and envision what constitutes a good life. Davis warns that what we envision as a neurological revolution, in which suffering is a mechanistic problem, has troubling and entrapping consequences. And he makes the case that by turning away from an interpretive, meaning-making view of ourselves, we thwart our chances to enrich our souls and learn important truths about ourselves and the social conditions under which we live. Praise for Chemically Imbalanced “Chemically Imbalanced is an excellent addition to the works in social sciences and humanities that examine the distress of ordinary Americans from the second half of the twentieth century onward, a period when commercialized pills and the psychology-based notion of self-improvement entered the minds of Americans.” —Metascience “Chemically Imbalanced raises important questions, offers new insight into the power and reach of the biomedical model and neurobiological thinking, and I highly recommend it. I encourage readers to assign it, especially in graduate-level mental health and illness classes—or any class looking for a discussion on people’s experiences with suffering and the broad impacts of biomedical thinking and treatment.” —Social Forces

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications. Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.

This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing methods and algorithm-level solutions, taking also into account those ensemble-learning solutions that embed any of the former alternatives. Furthermore, it focuses on the extension of the problem for multi-class problems, where the former classical methods are no longer to be applied in a straightforward way. This book also focuses on the data intrinsic characteristics that are the main causes which, added to the uneven class distribution, truly hinders the performance of classification algorithms in this scenario. Then, some notes on data reduction are provided in order to understand the advantages related to the use of this type of approaches. Finally this book introduces some novel areas of study that are gathering a deeper attention on the imbalanced data issue. Specifically, it considers the classification of data streams, non-classical classification problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided. This book is highly suitable for technical professionals, senior undergraduate and graduate students in the areas of data science, computer science and engineering. It will also be useful for scientists and researchers to gain insight on the current developments in this area of study, as well as future research directions.

Unearths previously untold stories of African Americans in early Minnesota.

Unique resource from internationally renowned experts details the key role of sagittal spine balance Through evolution, human verticality became associated with a wide range of normal pelvic shapes and associated pelvic incidence angles (PIs). While all types of sagittal alignment generally provide adequate support to young adults, age, stress, and related degeneration can progressively lead to sagittal imbalance and contribute to various spinal pathologies. Sagittal Balance of the Spine by Pierre Roussouly, João Luiz Pinheiro-Franco, Hubert Labelle, Martin Gehrchen, and a cadre of esteemed international contributors focuses on the importance of sagittal alignment and spino-pelvic shape identification in clinical practice. Offering the most comprehensive text on sagittal balance to date, this state-of-the-art, richly illustrated book fills a void in the literature, offering clinical pearls throughout seven sections and 24 chapters. Key Highlights The biomechanics of sagittal balance including spine modeling, primary parameters, spinal curves segmentation, and lumbar lordosis classification The role of sagittal balance in low back pain and degeneration, with discussion of spinal orientation and the contact forces theory, spinal degeneration associated with spinopelvic morphotypes, and compensatory mechanisms Comprehensive analysis of the relationship between sagittal imbalance and isthmic lysis spondylolisthesis, degenerative spondylolisthesis, Scheuermann's kyphosis, adolescent idiopathic scoliosis, and adult scoliosis Posterior and anterior treatment approaches – from spinal fixation and spinal fusion – to spinal osteotomy techniques and management of surgical failure This text is essential reading for every neurosurgical and orthopaedic resident, as well as veteran surgeons who evaluate and treat patients with spine conditions. Clinicians will learn why incorporating sagittal balance evaluations into spinal exams is integral to devising more effective treatment strategies and achieving improved outcomes.

Amerindian societies have an iconic status in classical political thought. For Montaigne, Hobbes, Locke, Hume and Rousseau, the native American ‘state of nature’ operates as a foil for the European polity. Challenging this tradition, The Imbalance of Power demonstrates ethnographically that the Carib speaking indigenous societies of the Guiana region of Amazonia do not fit conventional characterizations of ‘simple’ political units with ‘egalitarian’ political ideologies and ‘harmonious’ relationships with nature. Marc Brightman builds a persuasive and original theory of Amerindian politics: far from balanced and egalitarian, Carib societies are rife with tension and difference; but this imbalance conditions social dynamism and a distinctive mode of cohesion. The Imbalance of Power is based on the author’s fieldwork in partnership with Vanessa Grotti, who is working on a companion volume entitled Living with the Enemy: First Contacts and the Making of Christian Bodies in Amazonia.

Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority data class, which is not acceptable considering imbalanced data is omnipresent in real-life scenarios and is forcing us to learn from imbalanced data for foolproof application design. Imbalanced data is multifaceted and demands a new perception using the novelty at sampling approach of data preprocessing, an active learning approach, and a cost perceptive approach to resolve data imbalance. Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance offers new aspects for imbalanced data learning by providing the advancements of the traditional methods, with respect to big data, through case studies and research from experts in academia, engineering, and industry. The chapters provide theoretical frameworks and the latest empirical research findings that help to improve the understanding of the impact of imbalanced data and its resolving techniques based on data preprocessing, active learning, and cost perceptive approaches. This book is ideal for data scientists, data analysts, engineers, practitioners, researchers, academicians, and students looking for more information on imbalanced data characteristics and solutions using varied approaches.