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Institution

University of Texas at Arlington

EducationArlington, Texas, United States
About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.


Papers
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Journal ArticleDOI
TL;DR: In this article, the Atacama Large Millimeter/Submillimeter Array was used to observe SN 1987A, one of the best-observed supernovae since the invention of the telescope.
Abstract: Supernova (SN) explosions are crucial engines driving the evolution of galaxies by shock heating gas, increasing the metallicity, creating dust, and accelerating energetic particles. In 2012 we used the Atacama Large Millimeter/Submillimeter Array to observe SN 1987A, one of the best-observed supernovae since the invention of the telescope. We present spatially resolved images at 450 mu m, 870 mu m, 1.4 mm, and 2.8 mm, an important transition wavelength range. Longer wavelength emission is dominated by synchrotron radiation from shock-accelerated particles, shorter wavelengths by emission from the largest mass of dust measured in a supernova remnant (>0.2 M-circle dot). For the first time we show unambiguously that this dust has formed in the inner ejecta (the cold remnants of the exploded star's core). The dust emission is concentrated at the center of the remnant, so the dust has not yet been affected by the shocks. If a significant fraction survives, and if SN 1987A is typical, supernovae are important cosmological dust producers.

181 citations

Journal ArticleDOI
TL;DR: The results of the speciation modeling and the voltammetric titrations all point towards control of dissolved rare earth elements in Great Dismal Swamp waters by complexation of these heavy metals with natural organic matter.

181 citations

Journal ArticleDOI
V. M. Abazov1, Brad Abbott2, M. Abolins3, Bobby Samir Acharya4  +550 moreInstitutions (82)
TL;DR: The first measurement of the integrated forward-backward charge asymmetry in top-quark-top-antiquark pair (t (t) over bar) production in proton-antiproton (p (p)over bar) collisions in the lepton+jets final state was presented in this article.
Abstract: We present the first measurement of the integrated forward-backward charge asymmetry in top-quark-top-antiquark pair (t (t) over bar) production in proton-antiproton (p (p) over bar) collisions in the lepton+jets final state. Using a b-jet tagging algorithm and kinematic reconstruction assuming t (t) over bar +X production and decay, a sample of 0.9 fb(-1) of data, collected by the D0 experiment at the Fermilab Tevatron Collider, is used to measure the asymmetry for different jet multiplicities. The result is also used to set upper limits on t (t) over bar +X production via a Z' resonance.

181 citations

Proceedings ArticleDOI
10 Apr 2011
TL;DR: A novel greedy matching pursuit algorithm (GMP) that complements the well-known signal recovery algorithms in CS theory and proves that GMP can accurately recover a sparse signal with a high probability.
Abstract: In this paper, we propose a novel compressive sensing (CS) based approach for sparse target counting and positioning in wireless sensor networks. While this is not the first work on applying CS to count and localize targets, it is the first to rigorously justify the validity of the problem formulation. Moreover, we propose a novel greedy matching pursuit algorithm (GMP) that complements the well-known signal recovery algorithms in CS theory and prove that GMP can accurately recover a sparse signal with a high probability. We also propose a framework for counting and positioning targets from multiple categories, a novel problem that has never been addressed before. Finally, we perform a comprehensive set of simulations whose results demonstrate the superiority of our approach over the existing CS and non-CS based techniques.

181 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a new control strategy to compensate for the inertia of the wind farm, which can improve variable-speed wind turbine generators' temporary frequency support based on the coordinated control of the WTGs and the energy storage (ES) system.
Abstract: With the increasing penetration of wind power in power systems, it is desirable for wind turbines to have similar characteristics as conventional synchronous generators Conventional generators provide frequency support to the grid through the methods of inertial response and primary and secondary frequency regulation, whereas variable-speed wind turbine generators (WTGs) do not have those desired abilities because they are integrated into the power grid via power electronic converters Although many different control strategies have already been published to enable WTGs to temporarily support the transient frequency, the published strategies may bring various negative effects to the system This paper proposes a new control strategy to compensate for inertia of the wind farm It can improve WTGs' temporary frequency support based on the coordinated control of the WTGs and the energy storage (ES) system The simulation results show that this strategy could provide better performance of temporary frequency support and overcome problems such as system frequency oscillation and a secondary frequency drop The proposed control strategy can be realized in all wind speed conditions with a small-scale ES system

181 citations


Authors

Showing all 11918 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Hyun-Chul Kim1764076183227
David H. Adams1551613117783
Andrew White1491494113874
Kaushik De1391625102058
Steven F. Maier13458860382
Andrew Brandt132124694676
Amir Farbin131112583388
Evangelos Gazis131114784159
Lee Sawyer130134088419
Fernando Barreiro130108283413
Stavros Maltezos12994379654
Elizabeth Gallas129115785027
Francois Vazeille12995279800
Sotirios Vlachos12878977317
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202353
2022243
20211,721
20201,664
20191,493
20181,462