scispace - formally typeset
Search or ask a question
Institution

University of Texas at Austin

EducationAustin, Texas, United States
About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.


Papers
More filters
Journal ArticleDOI
TL;DR: The authors found that news about the costs of immigration boosted white opposition far more when Latino immigrants, rather than European immigrants, were featured, and that group cues influence opinion and political action by triggering emotions not simply by changing beliefs about the severity of the immigration problem.
Abstract: We examine whether and how elite discourse shapes mass opinion and action on immigration policy. One popular but untested suspicion is that reactions to news about the costs of immigration depend upon who the immigrants are. We confirmthissuspicioninanationallyrepresentativeexperiment:newsaboutthecostsofimmigrationboostswhiteopposition far more when Latino immigrants, rather than European immigrants, are featured. We find these group cues influence opinion and political action by triggering emotions—in particular, anxiety—not simply by changing beliefs about the severity of the immigration problem. A second experiment replicates these findings but also confirms their sensitivity to the stereotypic consistency of group cues and their context. While these results echo recent insights about the power of anxiety, they also suggest the public is susceptible to error and manipulation when group cues trigger anxiety independently of the actual threat posed by the group.

954 citations

Journal ArticleDOI
TL;DR: In this article, the authors characterized natural fractures in four Barnett Shale cores in terms of orientation, size, and sealing properties, and they measured a mechanical rock property, the subcritical crack index, which governs fracture pattern development.
Abstract: Gas production from the Barnett Shale relies on hydraulic fracture stimulation. Natural opening-mode fractures reactivate during stimulation and enhance efficiency by widening the treatment zone. Knowledge of both the present-day maximum horizontal stress, which controls the direction of hydraulic fracture propagation, and the geometry of the natural fracture system, which we discuss here, is therefore necessary for effective hydraulic fracture treatment design. We characterized natural fractures in four Barnett Shale cores in terms of orientation, size, and sealing properties. We measured a mechanical rock property, the subcritical crack index, which governs fracture pattern development. Natural fractures are common, narrow (0.05 mm; 0.002 in.), sealed with calcite, and present in en echelon arrays. Individual fractures have high length/width aspect ratios (1000:1). They are steep (75), and the dominant trend is west-northwest. Other sets trend north-south. The narrow fractures are sealed and cannot contribute to reservoir storage or enhance permeability, but the population may follow a power-law size distribution where the largest fractures are open. The subcritical crack index for the Barnett Shale is high, indicating fracture clustering, and we suggest that large open fractures exist in clusters spaced several hundred feet apart. These fracture clusters may enhance permeability locally, but they may be problematic for hydraulic fracture treatments. The smaller sealed fractures act as planes of weakness and reactivate during hydraulic fracture treatments. Because the maximum horizontal stress trends northeast-southwest and is nearly normal to the dominant natural fractures, reactivation widens the treatment zone along multiple strands.

954 citations

Proceedings Article
01 Apr 2006
TL;DR: A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia and significantly outperforms a less informed baseline.
Abstract: We present a new method for detecting and disambiguating named entities in open domain text. A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia. The resulting model significantly outperforms a less informed baseline.

953 citations

Journal ArticleDOI
TL;DR: In this paper, the authors compared the performance of gyrokinetic and gyrofluid simulations of ion-temperature gradient (ITG)instability and turbulence in tokamak plasmas as well as some tokak plasma thermal transportmodels.
Abstract: The predictions of gyrokinetic and gyrofluid simulations of ion-temperature-gradient(ITG)instability and turbulence in tokamak plasmas as well as some tokamak plasma thermal transportmodels, which have been widely used for predicting the performance of the proposed International Thermonuclear Experimental Reactor (ITER) tokamak [Plasma Physics and Controlled Nuclear Fusion Research, 1996 (International Atomic Energy Agency, Vienna, 1997), Vol. 1, p. 3], are compared. These comparisons provide information on effects of differences in the physics content of the various models and on the fusion-relevant figures of merit of plasma performance predicted by the models. Many of the comparisons are undertaken for a simplified plasma model and geometry which is an idealization of the plasma conditions and geometry in a Doublet III-D [Plasma Physics and Controlled Nuclear Fusion Research, 1986 (International Atomic Energy Agency, Vienna, 1987), Vol. 1, p. 159] high confinement (H-mode) experiment. Most of the models show good agreements in their predictions and assumptions for the linear growth rates and frequencies. There are some differences associated with different equilibria. However, there are significant differences in the transport levels between the models. The causes of some of the differences are examined in some detail, with particular attention to numerical convergence in the turbulence simulations (with respect to simulation mesh size, system size and, for particle-based simulations, the particle number). The implications for predictions of fusion plasma performance are also discussed.

953 citations

Journal ArticleDOI
08 Aug 2002-Nature
TL;DR: A clear negative relationship between precipitation and changes in soil organic carbon and nitrogen content when grasslands were invaded by woody vegetation is found, with drier sites gaining, and wetter sites losing, soilorganic carbon.
Abstract: The invasion of woody vegetation into deserts, grasslands and savannas is generally thought to lead to an increase in the amount of carbon stored in those ecosystems. For this reason, shrub and forest expansion (for example, into grasslands) is also suggested to be a substantial, if uncertain, component of the terrestrial carbon sink1,2,3,4,5,6,7,8,9,10,11,12,13,14. Here we investigate woody plant invasion along a precipitation gradient (200 to 1,100 mm yr-1) by comparing carbon and nitrogen budgets and soil δ13C profiles between six pairs of adjacent grasslands, in which one of each pair was invaded by woody species 30 to 100 years ago. We found a clear negative relationship between precipitation and changes in soil organic carbon and nitrogen content when grasslands were invaded by woody vegetation, with drier sites gaining, and wetter sites losing, soil organic carbon. Losses of soil organic carbon at the wetter sites were substantial enough to offset increases in plant biomass carbon, suggesting that current land-based assessments may overestimate carbon sinks. Assessments relying on carbon stored from woody plant invasions to balance emissions may therefore be incorrect.

952 citations


Authors

Showing all 95138 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Eugene Braunwald2301711264576
Yi Chen2174342293080
Robert J. Lefkowitz214860147995
Joseph L. Goldstein207556149527
Eric N. Olson206814144586
Hagop M. Kantarjian2043708210208
Rakesh K. Jain2001467177727
Francis S. Collins196743250787
Gordon B. Mills1871273186451
Scott M. Grundy187841231821
Michael S. Brown185422123723
Eric Boerwinkle1831321170971
Aaron R. Folsom1811118134044
Jiaguo Yu178730113300
Network Information
Related Institutions (5)
Stanford University
320.3K papers, 21.8M citations

97% related

Columbia University
224K papers, 12.8M citations

96% related

University of California, San Diego
204.5K papers, 12.3M citations

96% related

University of Michigan
342.3K papers, 17.6M citations

96% related

University of Washington
305.5K papers, 17.7M citations

95% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023304
20221,210
202110,141
202010,331
20199,727
20188,973