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Institution

University of Massachusetts Amherst

EducationAmherst Center, Massachusetts, United States
About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.


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Book
12 Dec 1990
TL;DR: Human motor control is a complex process that involves the brain, muscles, limbs, and often external objects as mentioned in this paper, and it underlies motion, balance, stability, coordination, and our interaction with others and technology.
Abstract: Motor Control is a complex process that involves the brain, muscles, limbs, and often external objects. It underlies motion, balance, stability, coordination, and our interaction with others and technology. This book is a comprehensive introduction to motor control, covering a complex topic in an approachable way encompassing the psychological, physiological, and computational approaches to motor control. Human Motor Control, 2e cuts across all movement related disciplines: physical education, dance, physical therapy, robotics, etc. This second edition incorporates advances to the field, and integrates throughout the book how research harkens back to four critical questions: how do we select our actions of the many actions possible? How are these behaviors sequenced for appropriate order and timing between them? How does perception integrate with motor control? And how are perceptual-motor skills acquired? As before, the book retains its signature organization around activity systems. These activity systems include walking, looking, reaching, drawing and writing, keyboarding, speaking and singing, and smiling. Chapters here exemplify rather than encompass all the behaviors related to them. Hence smiling discusses physical and neural control of the face used in other expressions besides smiling, as well as the origins of emotional expression, and the importance of emotion expression in social interaction. These chapters on activity systems are preceded by chapters on basics, with an introduction and information on the physiological and psychological foundations of movement. The last section discusses integration of movements, individual differences, theories of motor control, and the contributions of both genetics and technology to motor control. Special features of the second edition: Organization by major activity systems New: brain imaging, social action, embodied cognition, advances in genetics and technology Detailed treatment of motor neuroscience Further Readings section added to each chapter * Retains unique organization of first edition: Part 1 on Preliminaries, Part 2 on Activity Systems, Part 3 on Principles and Prospects * Emphasizes exciting advances in the field and promising new directions * Well-illustrated with entertaining figures

676 citations

Journal ArticleDOI
03 Sep 2009-Nature
TL;DR: A panorama of galaxy structure of the Andromeda galaxy (M31) is reported, which directly confirms the basic tenets of the hierarchical galaxy formation model and reveals the shared history of M31 and M33 in the unceasing build-up of galaxies.
Abstract: In hierarchical cosmological models, galaxies grow in mass through the continual accretion of smaller ones. The tidal disruption of these systems is expected to result in loosely bound stars surrounding the galaxy, at distances that reach 10-100 times the radius of the central disk. The number, luminosity and morphology of the relics of this process provide significant clues to galaxy formation history, but obtaining a comprehensive survey of these components is difficult because of their intrinsic faintness and vast extent. Here we report a panoramic survey of the Andromeda galaxy (M31). We detect stars and coherent structures that are almost certainly remnants of dwarf galaxies destroyed by the tidal field of M31. An improved census of their surviving counterparts implies that three-quarters of M31's satellites brighter than M(v) = -6 await discovery. The brightest companion, Triangulum (M33), is surrounded by a stellar structure that provides persuasive evidence for a recent encounter with M31. This panorama of galaxy structure directly confirms the basic tenets of the hierarchical galaxy formation model and reveals the shared history of M31 and M33 in the unceasing build-up of galaxies.

675 citations

Proceedings ArticleDOI
07 Jun 2015
TL;DR: This work proposes a new texture descriptor, FV-CNN, obtained by Fisher Vector pooling of a Convolutional Neural Network (CNN) filter bank, which substantially improves the state-of-the-art in texture, material and scene recognition.
Abstract: Research in texture recognition often concentrates on the problem of material recognition in uncluttered conditions, an assumption rarely met by applications. In this work we conduct a first study of material and describable texture attributes recognition in clutter, using a new dataset derived from the OpenSurface texture repository. Motivated by the challenge posed by this problem, we propose a new texture descriptor, FV-CNN, obtained by Fisher Vector pooling of a Convolutional Neural Network (CNN) filter bank. FV-CNN substantially improves the state-of-the-art in texture, material and scene recognition. Our approach achieves 79.8% accuracy on Flickr material dataset and 81% accuracy on MIT indoor scenes, providing absolute gains of more than 10% over existing approaches. FV-CNN easily transfers across domains without requiring feature adaptation as for methods that build on the fully-connected layers of CNNs. Furthermore, FV-CNN can seamlessly incorporate multi-scale information and describe regions of arbitrary shapes and sizes. Our approach is particularly suited at localizing “stuff” categories and obtains state-of-the-art results on MSRC segmentation dataset, as well as promising results on recognizing materials and surface attributes in clutter on the OpenSurfaces dataset.

675 citations

Journal ArticleDOI
TL;DR: The last line of evidence presented involves the notion that unilateral resistive exercise of a specific limb will also result in training effects in the unexercised contralateral limb (cross-transfer or cross-education).
Abstract: It is generally accepted that neural factors play an important role in muscle strength gains. This article reviews the neural adaptations in strength, with the goal of laying the foundations for practical applications in sports medicine and rehabilitation. An increase in muscular strength without noticeable hypertrophy is the first line of evidence for neural involvement in acquisition of muscular strength. The use of surface electromyographic (SEMG) techniques reveal that strength gains in the early phase of a training regimen are associated with an increase in the amplitude of SEMG activity. This has been interpreted as an increase in neural drive, which denotes the magnitude of efferent neural output from the CNS to active muscle fibres. However, SEMG activity is a global measure of muscle activity. Underlying alterations in SEMG activity are changes in motor unit firing patterns as measured by indwelling (wire or needle) electrodes. Some studies have reported a transient increase in motor unit firing rate. Training-related increases in the rate of tension development have also been linked with an increased probability of doublet firing in individual motor units. A doublet is a very short interspike interval in a motor unit train, and usually occurs at the onset of a muscular contraction. Motor unit synchronisation is another possible mechanism for increases in muscle strength, but has yet to be definitely demonstrated. There are several lines of evidence for central control of training-related adaptation to resistive exercise. Mental practice using imagined contractions has been shown to increase the excitability of the cortical areas involved in movement and motion planning. However, training using imagined contractions is unlikely to be as effective as physical training, and it may be more applicable to rehabilitation. Retention of strength gains after dissipation of physiological effects demonstrates a strong practice effect. Bilateral contractions are associated with lower SEMG and strength compared with unilateral contractions of the same muscle group. SEMG magnitude is lower for eccentric contractions than for concentric contractions. However, resistive training can reverse these trends. The last line of evidence presented involves the notion that unilateral resistive exercise of a specific limb will also result in training effects in the unexercised contralateral limb (cross-transfer or cross-education). Peripheral involvement in training-related strength increases is much more uncertain. Changes in the sensory receptors (i.e. Golgi tendon organs) may lead to disinhibition and an increased expression of muscular force. Agonist muscle activity results in limb movement in the desired direction, while antagonist activity opposes that motion. Both decreases and increases in co-activation of the antagonist have been demonstrated. A reduction in antagonist co-activation would allow increased expression of agonist muscle force, while an increase in antagonist co-activation is important for maintaining the integrity of the joint. Thus far, it is not clear what the CNS will optimise: force production or joint integrity. The following recommendations are made by the authors based on the existing literature. Motor learning theory and imagined contractions should be incorporated into strength-training practice. Static contractions at greater muscle lengths will transfer across more joint angles. Submaximal eccentric contractions should be used when there are issues of muscle pain, detraining or limb immobilisation. The reversal of antagonists (antagonist-to-agonist) proprioceptive neuromuscular facilitation contraction pattern would be useful to increase the rate of tension development in older adults, thus serving as an important prophylactic in preventing falls. When evaluating the neural changes induced by strength training using EMG recording, antagonist EMG activity should always be measured and evaluated.

675 citations

Journal ArticleDOI
09 Apr 2010-ACS Nano
TL;DR: These studies suggest the possibility of tuning the properties of GO composites by altering the density of functional groups on individual platelets, the water content, and possibly the functional groups participating in hydrogen bonding with interlayer water molecules.
Abstract: A multilayered composite structure formed by a random stacking of graphene oxide (GO) platelets is an attractive candidate for novel applications in nanoelectromechanical systems and paper-like composites. We employ molecular dynamics simulations with reactive force fields to elucidate the structural and mechanical properties of GO paper-like materials. We find that the large-scale properties of these composites are controlled by hydrogen bond networks that involve functional groups on individual GO platelets and water molecules within the interlayer cavities. Water content controls both the extent and collective strength of these interlayer hydrogen bond networks, thereby affecting the interlayer spacing and elastic moduli of the composite. Additionally, the chemical composition of the individual GO platelets also plays a critical role in establishing the mechanical properties of the composite—a higher density of functional groups leads to increased hydrogen bonding and a corresponding increase in stiffn...

674 citations


Authors

Showing all 37601 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Joan Massagué189408149951
David H. Weinberg183700171424
David L. Kaplan1771944146082
Michael I. Jordan1761016216204
James F. Sallis169825144836
Bradley T. Hyman169765136098
Anton M. Koekemoer1681127106796
Derek R. Lovley16858295315
Michel C. Nussenzweig16551687665
Alfred L. Goldberg15647488296
Donna Spiegelman15280485428
Susan E. Hankinson15178988297
Bernard Moss14783076991
Roger J. Davis147498103478
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023103
2022535
20213,983
20203,858
20193,712
20183,385