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Institution

University of Utah

EducationSalt Lake City, Utah, United States
About: University of Utah is a education organization based out in Salt Lake City, Utah, United States. It is known for research contribution in the topics: Population & Medicine. The organization has 52894 authors who have published 124076 publications receiving 5265834 citations. The organization is also known as: The U & The University of Utah.


Papers
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Journal ArticleDOI
TL;DR: Diagnostic criteria for pseudotumor cerebri syndrome are proposed to incorporate advances and insights into the disorder realized over the past 10 years.
Abstract: The pseudotumor cerebri syndrome (PTCS) may be primary (idiopathic intracranial hypertension) or arise from an identifiable secondary cause. Characterization of typical neuroimaging abnormalities, clarification of normal opening pressure in children, and features distinguishing the syndrome of intracranial hypertension without papilledema from intracranial hypertension with papilledema have furthered our understanding of this disorder. We propose updated diagnostic criteria for PTCS to incorporate advances and insights into the disorder realized over the past 10 years.

863 citations

Proceedings Article
25 Jul 2004
TL;DR: WordNet::Similarity is a freely available software package that makes it possible to measure the semantic similarity and relatedness between a pair of concepts (or synsets).
Abstract: WordNet: Similarity is a freely available software package that makes it possible to measure the semantic similarity or relatedness between a pair of concepts (or word senses). It provides six measures of similarity, and three measures of relatedness, all of which are based on the lexical database WordNet. These measures are implemented as Perl modules which take as input two concepts, and return a numeric value that represents the degree to which they are similar or related.

863 citations

Journal ArticleDOI
TL;DR: How the peroxisome proliferator-activated receptors, a subset of the nuclear-hormone-receptor superfamily, have important regulatory roles in innate and adaptive immunity is described.
Abstract: Lipids and lipid metabolism have well-documented regulatory effects on inflammatory processes. Recent work has highlighted the role of the peroxisome proliferator-activated receptors (PPARs)--a subset of the nuclear-hormone-receptor superfamily that are activated by various lipid species--in regulating inflammatory responses. Here, we describe how the PPARs, through their interactions with transcription factors and other cell-signalling systems, have important regulatory roles in innate and adaptive immunity.

862 citations

Proceedings ArticleDOI
01 Mar 2001
TL;DR: The algorithm is extended to allow direct user input for interactive control over the texture synthesis process, which allows the user to indicate large-scale properties of the texture appearance using a standard painting-style interface, and to choose among various candidate textures the algorithm can create by performing different number of iterations.
Abstract: We present a simple texture synthesis algorithm that is well-suited for a specific class of naturally occurring textures. This class includes quasi-repeating patterns consisting of small objects of familiar but irregular size, such as flower fields, pebbles, forest undergrowth, bushes and tree branches. The algorithm starts from a sample image and generates a new image of arbitrary size the appearance of which is similar to that of the original image. This new image does not change the basic spatial frequencies the original image; instead it creates an image that is a visually similar, and is of a size set by the user. This method is fast and its implementation is straightforward. We extend the algorithm to allow direct user input for interactive control over the texture synthesis process. This allows the user to indicate large-scale properties of the texture appearance using a standard painting-style interface, and to choose among various candidate textures the algorithm can create by performing different number of iterations.

861 citations

Journal ArticleDOI
TL;DR: The authors examined the relationship between book-to-market equity, distress risk, and stock returns among firms with the highest distress risk as proxied by Ohlson's ~1980! O-score, finding that the difference in returns between high and low book-tomarket securities is more than twice as large as that in other firms.
Abstract: This paper examines the relationship between book-to-market equity, distress risk, and stock returns Among firms with the highest distress risk as proxied by Ohlson’s ~1980! O-score, the difference in returns between high and low book-tomarket securities is more than twice as large as that in other firms This large return differential cannot be explained by the three-factor model or by differences in economic fundamentals Consistent with mispricing arguments, firms with high distress risk exhibit the largest return reversals around earnings announcements, and the book-to-market effect is largest in small firms with low analyst coverage ONE PROMINENT EXPLANATION OF THE book-to-market equity premium in returns is that high book-to-market equity firms are assigned a higher risk premium because of the greater risk of distress 1 Consistent with this view, Fama and French ~1995! and Chen and Zhang ~1998! show that firms with high bookto-market equity ~BE0ME! have persistently low earnings, higher financial leverage, more earnings uncertainty, and are more likely to cut dividends compared to their low BE0ME counterparts In contrast, Dichev ~1998! uses measures of bankruptcy risk proposed by Ohlson ~1980! and Altman ~1968! to identify firms with a high likelihood of financial distress and finds that these firms tend to have low average stock returns Dichev’s results appear to be inconsistent with the view that firms with high BE0ME earn high returns as a premium for distress risk 2

857 citations


Authors

Showing all 53431 results

NameH-indexPapersCitations
Bert Vogelstein247757332094
George M. Whitesides2401739269833
Hongjie Dai197570182579
Robert M. Califf1961561167961
Frank E. Speizer193636135891
Yusuke Nakamura1792076160313
David L. Kaplan1771944146082
Marc G. Caron17367499802
George M. Church172900120514
Steven P. Gygi172704129173
Lily Yeh Jan16246773655
Tobin J. Marks1591621111604
David W. Bates1591239116698
Alfred L. Goldberg15647488296
Charles M. Perou156573202951
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023203
2022769
20217,364
20207,015
20196,309
20185,651