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Institution

Lehigh University

EducationBethlehem, Pennsylvania, United States
About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.


Papers
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Proceedings ArticleDOI
20 Jun 2011
TL;DR: This work proposes a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence, and consistently outperformed existing saliency detection methods.
Abstract: Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

3,653 citations

Journal ArticleDOI
TL;DR: The results indicate that the revised CHARMM 36 parameters represent an improved model for the modeling and simulation studies of proteins, including studies of protein folding, assembly and functionally relevant conformational changes.
Abstract: While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large number of applications, limitations in the model with respect to the equilibrium between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non Gly, Pro) backbone CMAP potential has been refined against experimental solution NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mechanical energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mechanical energy surfaces, followed by additional empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against data not used to guide parametrization: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equilibrium folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for the modeling and simulation studies of proteins, including studies of protein folding, assembly and functionally relevant conformational changes.

3,421 citations

Journal ArticleDOI
TL;DR: Evidence from a selection of research topics relevant to pandemics is discussed, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping.
Abstract: The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

3,223 citations

Journal ArticleDOI
07 Jul 2008-Polymer
TL;DR: In this paper, the technology involved with exfoliated clay-based nanocomposites and also include other important areas including barrier properties, flammability resistance, biomedical applications, electrical/electronic/optoelectronic applications and fuel cell interests.

2,917 citations

Journal ArticleDOI
TL;DR: The Transiting Exoplanet Survey Satellite (TESS) as discussed by the authors will search for planets transiting bright and nearby stars using four wide-field optical charge-coupled device cameras to monitor at least 200,000 main-sequence dwarf stars.
Abstract: The Transiting Exoplanet Survey Satellite (TESS) will search for planets transiting bright and nearby stars. TESS has been selected by NASA for launch in 2017 as an Astrophysics Explorer mission. The spacecraft will be placed into a highly elliptical 13.7-day orbit around the Earth. During its 2-year mission, TESS will employ four wide-field optical charge-coupled device cameras to monitor at least 200,000 main-sequence dwarf stars with I C ≈4−13 for temporary drops in brightness caused by planetary transits. Each star will be observed for an interval ranging from 1 month to 1 year, depending mainly on the star’s ecliptic latitude. The longest observing intervals will be for stars near the ecliptic poles, which are the optimal locations for follow-up observations with the James Webb Space Telescope. Brightness measurements of preselected target stars will be recorded every 2 min, and full frame images will be recorded every 30 min. TESS stars will be 10 to 100 times brighter than those surveyed by the pioneering Kepler mission. This will make TESS planets easier to characterize with follow-up observations. TESS is expected to find more than a thousand planets smaller than Neptune, including dozens that are comparable in size to the Earth. Public data releases will occur every 4 months, inviting immediate community-wide efforts to study the new planets. The TESS legacy will be a catalog of the nearest and brightest stars hosting transiting planets, which will endure as highly favorable targets for detailed investigations.

2,604 citations


Authors

Showing all 12785 results

NameH-indexPapersCitations
Yang Yang1712644153049
Gang Chen1673372149819
Yi Yang143245692268
Mark D. Griffiths124123861335
Michael Gill12181086338
Masaki Mori110220066676
Kai Nan An10995351638
James R. Rice10827868943
Vinayak P. Dravid10381743612
Andrew M. Jones10376437253
Israel E. Wachs10342732029
Demetrios N. Christodoulides10070451093
Bert M. Weckhuysen10076740945
José Luis García Fierro100102747228
Mordechai Segev9972940073
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202338
2022140
20211,040
20201,054
2019933
2018935