Institution
University of Texas at Austin
Education•Austin, 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.
Topics: Population, Poison control, Galaxy, Stars, Finite element method
Papers published on a yearly basis
Papers
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TL;DR: The InTBIR Participants and Investigators have provided informed consent for the study to take place in Poland.
Abstract: Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Soderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbuchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigators
1,354 citations
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TL;DR: This chapter should acquaint the reader with the fundamentals of the electrochemistry of glucose and provide a perspective of the evolution of the Electrochemical glucose assays and monitors helping diabetic people, who constitute about 5 % of the world’s population.
Abstract: Over 7,000 peer reviewed articles have been published on electrochemical glucose assays and sensors over recent years. Their number makes a full review of the literature, or even of the most recent advances, impossible. Nevertheless, this chapter should acquaint the reader with the fundamentals of the electrochemistry of glucose and provide a perspective of the evolution of the electrochemical glucose assays and monitors helping diabetic people, who constitute about 5 % of the world’s population. Because of the large number of diabetic people, no assay is performed more frequently than that of glucose. Most of these assays are electrochemical. The reader interested also in nonelectrochemical assays used in, or proposed for, the management of diabetes is referred to a 2007 excellent review of Kondepati and Heise [1].
1,353 citations
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TL;DR: It is found that optical deformability is sensitive enough to monitor the subtle changes during the progression of mouse fibroblasts and human breast epithelial cells from normal to cancerous and even metastatic state, and suggests using optical deformable as an inherent cell marker for basic cell biological investigation and diagnosis of disease.
1,352 citations
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17 May 2004TL;DR: This work proposes an information fidelity criterion that quantifies the Shannon information that is shared between the reference and distorted images relative to the information contained in the reference image itself, and demonstrates the performance of the algorithm by testing it on a data set of 779 images.
Abstract: Measurement of image quality is crucial for many image-processing algorithms. Traditionally, image quality assessment algorithms predict visual quality by comparing a distorted image against a reference image, typically by modeling the human visual system (HVS), or by using arbitrary signal fidelity criteria. We adopt a new paradigm for image quality assessment. We propose an information fidelity criterion that quantifies the Shannon information that is shared between the reference and distorted images relative to the information contained in the reference image itself. We use natural scene statistics (NSS) modeling in concert with an image degradation model and an HVS model. We demonstrate the performance of our algorithm by testing it on a data set of 779 images, and show that our method is competitive with state of the art quality assessment methods, and outperforms them in our simulations.
1,349 citations
University of Connecticut1, University of Texas at Austin2, Massey University3, Centre for Addiction and Mental Health4, University of Western Ontario5, Pacific Institute6, Griffith University7, Turning Point Alcohol and Drug Centre8, National Institutes of Health9, University of Melbourne10, Norwegian Institute for Alcohol and Drug Research11
TL;DR: In this paper, the authors describe recent advances in alcohol research which have direct relevance for the development of effective alcohol policies at the local, national and international levels, and the central purpose of the book is to empower those responsible for public health and social welfare.
Abstract: From a public health perspective, alcohol is a major contributor to morbidity and mortality. This book describes recent advances in alcohol research which have direct relevance for the development of effective alcohol policies at the local, national and international levels. The central purpose of the book is to empower those responsible for public health and social welfare.
1,346 citations
Authors
Showing all 95138 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Eugene Braunwald | 230 | 1711 | 264576 |
Yi Chen | 217 | 4342 | 293080 |
Robert J. Lefkowitz | 214 | 860 | 147995 |
Joseph L. Goldstein | 207 | 556 | 149527 |
Eric N. Olson | 206 | 814 | 144586 |
Hagop M. Kantarjian | 204 | 3708 | 210208 |
Rakesh K. Jain | 200 | 1467 | 177727 |
Francis S. Collins | 196 | 743 | 250787 |
Gordon B. Mills | 187 | 1273 | 186451 |
Scott M. Grundy | 187 | 841 | 231821 |
Michael S. Brown | 185 | 422 | 123723 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Aaron R. Folsom | 181 | 1118 | 134044 |
Jiaguo Yu | 178 | 730 | 113300 |