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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
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Journal ArticleDOI
TL;DR: Support is provided for the claim that sociocultural processes foster body dissatisfaction, which in turn increase the risk for bulimic pathology, and it is suggested that prevention and treatment interventions might be enhanced by focusing greater attention on body image disturbances.

1,314 citations

Journal ArticleDOI
18 Mar 2000-BMJ
TL;DR: Although operating theatres are not cockpits, medicine could learn from aviation and aviation has developed standardised methods of investigating, documenting, and disseminating errors and their lessons.
Abstract: Pilots and doctors operate in complex environments where teams interact with technology. In both domains, risk varies from low to high with threats coming from a variety of sources in the environment. Safety is paramount for both professions, but cost issues can influence the commitment of resources for safety efforts. Aircraft accidents are infrequent, highly visible, and often involve massive loss of life, resulting in exhaustive investigation into causal factors, public reports, and remedial action. Research by the National Aeronautics and Space Administration into aviation accidents has found that 70% involve human error.1 In contrast, medical adverse events happen to individual patients and seldom receive national publicity. More importantly, there is no standardised method of investigation, documentation, and dissemination. The US Institute of Medicine estimates that each year between 44 000 and 98 000 people die as a result of medical errors. When error is suspected, litigation and new regulations are threats in both medicine and aviation. #### Summary points In aviation, accidents are usually highly visible, and as a result aviation has developed standardised methods of investigating, documenting, and disseminating errors and their lessons Although operating theatres are not cockpits, medicine could learn from aviation Observation of flights in operation has identified failures of compliance, communication, procedures, proficiency, and decision making in contributing to errors Surveys in operating theatres have confirmed that pilots and doctors have common interpersonal problem areas and similarities in professional culture Accepting the inevitability of error and the importance of reliable data on error and its management will allow systematic efforts to reduce the frequency and severity of adverse events Error results from physiological and psychological limitations of humans.2 Causes of error include fatigue, workload, and fear as well as cognitive overload, poor interpersonal communications, imperfect information processing, and flawed decision making.3 In both aviation …

1,312 citations

Proceedings ArticleDOI
07 Dec 2015
TL;DR: In this article, an end-to-end sequence to sequence model was proposed to generate captions for videos, which can learn the temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model.
Abstract: Real-world videos often have complex dynamics, methods for generating open-domain video descriptions should be senstive to temporal structure and allow both input (sequence of frames) and output (sequence of words) of variable length. To approach this problem we propose a novel end-to-end sequence-to-sequence model to generate captions for videos. For this we exploit recurrent neural networks, specifically LSTMs, which have demonstrated state-of-the-art performance in image caption generation. Our LSTM model is trained on video-sentence pairs and learns to associate a sequence of video frames to a sequence of words in order to generate a description of the event in the video clip. Our model naturally is able to learn the temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model. We evaluate several variants of our model that exploit different visual features on a standard set of YouTube videos and two movie description datasets (M-VAD and MPII-MD).

1,311 citations

Journal ArticleDOI
TL;DR: Using a text-analysis computer program, it was discovered that those who benefit maximally from writing tend to use a high number of positive-emotion words, a moderate amount of negative-emotional words, and increase their use of cognitive words over the days of writing.
Abstract: Writing about important personal experiences in an emotional way for as little as 15 minutes over the course of three days brings about improvements in mental and physical health. This finding has been replicated across age, gender, culture, social class, and personality type. Using a text-analysis computer program, it was discovered that those who benefit maximally from writing tend to use a high number of positive-emotion words, a moderate amount of negative-emotion words, and increase their use of cognitive words over the days of writing. These findings suggest that the formation of a narrative is critical and is an indicator of good mental and physical health. Ongoing studies suggest that writing serves the function of organizing complex emotional experiences. Implications for these findings for psychotherapy are briefly discussed. © 1999 John Wiley & Sons, Inc. J Clin Psychol 55: 1243–1254, 1999.

1,309 citations

Journal ArticleDOI
TL;DR: This analysis provides global distributions for fine root biomass, length, and surface area with depth in the soil, and global estimates of nutrient pools in fine roots.
Abstract: Global biogeochemical models have improved dramatically in the last decade in their representation of the biosphere. Although leaf area data are an important input to such models and are readily available globally, global root distributions for modeling water and nutrient uptake and carbon cycling have not been available. This analysis provides global distributions for fine root biomass, length, and surface area with depth in the soil, and global estimates of nutrient pools in fine roots. Calculated root surface area is almost always greater than leaf area, more than an order of magnitude so in grasslands. The average C:N:P ratio in living fine roots is 450:11:1, and global fine root carbon is more than 5% of all carbon contained in the atmosphere. Assuming conservatively that fine roots turn over once per year, they represent 33% of global annual net primary productivity.

1,309 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
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023304
20221,210
202110,141
202010,331
20199,727
20188,973