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Institution

University of Maryland, College Park

EducationCollege Park, Maryland, United States
About: University of Maryland, College Park is a education organization based out in College Park, Maryland, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 60446 authors who have published 155900 publications receiving 7273683 citations. The organization is also known as: The University of Maryland & College Park.


Papers
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Journal ArticleDOI
TL;DR: The surprising discovery of high-temperature superconductivity in a material containing a strong magnet (iron) has led to thousands of publications as discussed by the authors, and it becomes clear what we know and where we are headed.
Abstract: The surprising discovery of high-temperature superconductivity in a material containing a strong magnet—iron—has led to thousands of publications. By placing all the data in context, it becomes clear what we know and where we are headed.

1,224 citations

Journal ArticleDOI
TL;DR: It is suggested that this process can be observed in instances of trauma, in early out-of-sequence transitions, and in the case of undesired changes that disrupt behaviors and relationships in established roles, which must recognize their structural underpinnings.
Abstract: This article proposes several conceptual perspectives designed to advance our understanding of the material and experiential conditions contributing to persistent disparities in rates of morbidity and mortality among groups unequal in their social and economic statuses. An underlying assumption is that these disparities, which are in clear evidence at mid- and late life, may be anchored to earlier circumstances of the life course. Of particular interest are those circumstances resulting in people with the least privileged statuses having the greatest chances of exposure to health-related stressors. Among the stressors closely linked to status and status attainment are those that continue or are repeated across the life course, such as enduring economic strain and discriminatory experiences. Also taking a long-range toll on health are circumstances of stress proliferation, a process that places people exposed to a serious adversity at risk for later exposure to additional adversities. We suggest that this process can be observed in instances of trauma, in early out-of-sequence transitions, and in the case of undesired changes that disrupt behaviors and relationships in established roles. Effective effort to close the systemic health gaps must recognize their structural underpinnings.

1,223 citations

Journal ArticleDOI
TL;DR: Little molecular understanding of plant activities critical to phytoremediation has been achieved, but recent progress in characterizing Fe, Cd and Zn uptake by Arabidopsis and yeast mutants indicates strategies for developing transgenic improved phytOREmediation cultivars for commercial use.

1,218 citations

Journal ArticleDOI
TL;DR: HyperFace as discussed by the authors combines face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNNs) and achieves significant improvement in performance by fusing intermediate layers of a deep CNN using a separate CNN followed by a multi-task learning algorithm that operates on the fused features.
Abstract: We present an algorithm for simultaneous face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNN). The proposed method called, HyperFace, fuses the intermediate layers of a deep CNN using a separate CNN followed by a multi-task learning algorithm that operates on the fused features. It exploits the synergy among the tasks which boosts up their individual performances. Additionally, we propose two variants of HyperFace: (1) HyperFace-ResNet that builds on the ResNet-101 model and achieves significant improvement in performance, and (2) Fast-HyperFace that uses a high recall fast face detector for generating region proposals to improve the speed of the algorithm. Extensive experiments show that the proposed models are able to capture both global and local information in faces and performs significantly better than many competitive algorithms for each of these four tasks.

1,218 citations

Journal ArticleDOI
TL;DR: In this paper, a brief history of the storm-and-stress view and three key aspects of this view are examined: conflict with parents, mood disruptions, and risk behavior.
Abstract: G. S. Hall's (1904) view that adolescence is a period of heightened "storm and stress" is reconsidered in light of contemporary research. The author provides a brief history of the storm-and-stress view and examines 3 key aspects of this view: conflict with parents, mood disruptions, and risk behavior. In all 3 areas, evidence supports a modified storm-and-stress view that takes into account individual differences and cultural variations. Not all adolescents experience storm and stress, but storm and stress is more likely during adolescence than at other ages. Adolescent storm and stress tends to be lower in traditional cultures than in the West but may increase as globalization increases individualism. Similar issues apply to minority cultures in American society. Finally, although the general public is sometimes portrayed by scholars as having a stereotypical view of adolescent storm and stress, both scholars and the general public appear to support a modified storm-and-stress view.

1,214 citations


Authors

Showing all 60868 results

NameH-indexPapersCitations
Timothy M. Heckman170754141237
Donald G. Truhlar1651518157965
Tobin J. Marks1591621111604
Yongsun Kim1562588145619
Richard J. Davidson15660291414
Terrence J. Sejnowski155845117382
Roberto Romero1511516108321
Jongmin Lee1502257134772
Kevin J. Gaston15075085635
Bernard Moss14783076991
Steven L. Salzberg147407231756
Gregory R Snow1471704115677
Fabian Walter14699983016
Timothy P. Hughes14583191357
Marco Zanetti1451439104610
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023162
2022754
20216,744
20207,208
20197,072
20186,716