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Institution

Temple University

EducationPhiladelphia, Pennsylvania, United States
About: Temple University is a education organization based out in Philadelphia, Pennsylvania, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32154 authors who have published 64375 publications receiving 2219828 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper presents an efficient implementation of the particle–particle particle-mesh method based on the work by Harvey and De Fabritiis, and provides a performance comparison of the same kernels compiled with both CUDA and OpenCL.

381 citations

Journal ArticleDOI
TL;DR: In this paper, the role of regional cluster composition in the economic performance of industries, clusters and regions is evaluated. And the authors find that the presence of strong clusters in a region enhances growth opportunities in other industries and clusters.

380 citations

Proceedings ArticleDOI
Heng Fan1, Haibin Ling1
15 Jun 2019
TL;DR: C-RPN as discussed by the authors proposes a multi-stage tracking framework, which consists of a sequence of RPNs cascaded from deep high-level to shallow low-level layers in a Siamese network.
Abstract: Recently, the region proposal networks (RPN) have been combined with the Siamese network for tracking, and shown excellent accuracy with high efficiency. Nevertheless, previously proposed one-stage Siamese-RPN trackers degenerate in presence of similar distractors and large scale variation. Addressing these issues, we propose a multi-stage tracking framework, Siamese Cascaded RPN (C-RPN), which consists of a sequence of RPNs cascaded from deep high-level to shallow low-level layers in a Siamese network. Compared to previous solutions, C-RPN has several advantages: (1) Each RPN is trained using the outputs of RPN in the previous stage. Such process stimulates hard negative sampling, resulting in more balanced training samples. Consequently, the RPNs are sequentially more discriminative in distinguishing difficult background (i.e.,, similar distractors). (2) Multi-level features are fully leveraged through a novel feature transfer block (FTB) for each RPN, further improving the discriminability of C-RPN using both high-level semantic and low-level spatial information. (3) With multiple steps of regressions, C-RPN progressively refines the location and shape of the target in each RPN with adjusted anchor boxes in the previous stage, which makes localization more accurate. C-RPN is trained end-to-end with the multi-task loss function. In inference, C-RPN is deployed as it is, without any temporal adaption, for real-time tracking. In extensive experiments on OTB-2013, OTB-2015, VOT-2016, VOT-2017, LaSOT and TrackingNet, C-RPN consistently achieves state-of-the-art results and runs in real-time.

380 citations

Journal ArticleDOI
TL;DR: The results indicate that weak neighborhood social organization is indirectly related to delinquency through its associations with parenting behavior and peer deviance and that a focus on just 1 of these microsystems can lead to oversimplified models of risk for juvenile offending.
Abstract: The present study examined relations among neighborhood structural and social characteristics, parenting practices, peer group affiliations, and delinquency among a group of serious adolescent offenders. The sample of 14-18-year-old boys (N=488) was composed primarily of economically disadvantaged, ethnic-minority youth living in urban communities. The results indicate that weak neighborhood social organization is indirectly related to delinquency through its associations with parenting behavior and peer deviance and that a focus on just 1 of these microsystems can lead to oversimplified models of risk for juvenile offending. The authors also find that community social ties may confer both pro- and antisocial influences to youth, and they advocate for a broad conceptualization of neighborhood social processes as these relate to developmental risk for youth living in disadvantaged communities.

379 citations

Journal ArticleDOI
08 Apr 2016-Science
TL;DR: This work developed an approach to identify DNA inherited from multiple archaic hominin ancestors and applied it to whole-genome sequences from 1523 geographically diverse individuals, including 35 previously unknown Island Melanesian genomes, and recovered Neandertal and Denisovan DNA.
Abstract: Although Neandertal sequences that persist in the genomes of modern humans have been identified in Eurasians, comparable studies in people whose ancestors hybridized with both Neandertals and Denisovans are lacking. We developed an approach to identify DNA inherited from multiple archaic hominin ancestors and applied it to whole-genome sequences from 1523 geographically diverse individuals, including 35 previously unknown Island Melanesian genomes. In aggregate, we recovered 1.34 gigabases and 303 megabases of the Neandertal and Denisovan genome, respectively. We use these maps of archaic sequences to show that Neandertal admixture occurred multiple times in different non-African populations, characterize genomic regions that are significantly depleted of archaic sequences, and identify signatures of adaptive introgression.

378 citations


Authors

Showing all 32360 results

NameH-indexPapersCitations
Robert J. Lefkowitz214860147995
Rakesh K. Jain2001467177727
Virginia M.-Y. Lee194993148820
Yury Gogotsi171956144520
Timothy A. Springer167669122421
Ralph A. DeFronzo160759132993
James J. Collins15166989476
Robert J. Glynn14674888387
Edward G. Lakatta14685888637
Steven Williams144137586712
Peter Buchholz143118192101
David Goldstein1411301101955
Scott D. Solomon1371145103041
Donald B. Rubin132515262632
Jeffery D. Molkentin13148261594
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202366
2022335
20213,475
20203,281
20193,166
20183,019