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Institution

University of Wisconsin–Milwaukee

EducationMilwaukee, Wisconsin, United States
About: University of Wisconsin–Milwaukee is a education organization based out in Milwaukee, Wisconsin, United States. It is known for research contribution in the topics: Population & Gravitational wave. The organization has 11839 authors who have published 28034 publications receiving 936438 citations. The organization is also known as: UWM & University of Wisconsin-Milwaukee.


Papers
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Journal ArticleDOI
TL;DR: A meta-analysis of studies of television network news showed small, measurable, but probably insubstantial coverage and statement biases as mentioned in this paper, and no significant biases were found for the newspaper industry.
Abstract: A meta-analysis considered 59 quantitative studies containing data concerned with partisan media bias in presidential election campaigns since 1948. Types of bias considered were gatekeeping bias, which is the preference for selecting stories from one party or the other; coverage bias, which considers the relative amounts of coverage each party receives; and statement bias, which focuses on the favorability of coverage toward one party or the other. On the whole, no significant biases were found for the newspaper industry. Biases in newsmagazines were virtually zero as well. However, meta-analysis of studies of television network news showed small, measurable, but probably insubstantial coverage and statement biases.

442 citations

Journal ArticleDOI
TL;DR: The CA-reduced GO (CA-rGO) showed a high C/O ratio (715) that is among the best rGOs prepared with green reducing reagents as discussed by the authors.
Abstract: Preparation of graphene from chemical reduction of graphene oxide (GO) is recognized as one of the most promising methods for large-scale and low-cost production of graphene-based materials This study reports a new, green and efficient reducing agent (caffeic acid/CA) for GO reduction The CA-reduced GO (CA-rGO) shows a high C/O ratio (715) that is among the best rGOs prepared with green reducing reagents Electronic gas sensors and supercapacitors have been fabricated with the CA-rGO and show good performance, which demonstrates the potential of CA-rGO for sensing and energy storage applications

440 citations

Journal ArticleDOI
TL;DR: A novel method to combine sensitivity encoding (SENSE), one of the standard methods for parallel MRI, and compressed sensing for rapid MR imaging (SparseMRI), a recently proposed method for applying CS in MR imaging with Cartesian trajectories is proposed.
Abstract: Both parallel MRI and compressed sensing (CS) are emerging techniques to accelerate conventional MRI by reducing the number of acquired data. The combination of parallel MRI and CS for further acceleration is of great interest. In this paper, we propose a novel method to combine sensitivity encoding (SENSE), one of the standard methods for parallel MRI, and compressed sensing for rapid MR imaging (SparseMRI), a recently proposed method for applying CS in MR imaging with Cartesian trajectories. The proposed method, named CS-SENSE, sequentially reconstructs a set of aliased reduced-field-of-view images in each channel using SparseMRI and then reconstructs the final image from the aliased images using Cartesian SENSE. The results from simulations and phantom and in vivo experiments demonstrate that CS-SENSE can achieve a reduction factor higher than those achieved by SparseMRI and SENSE individually and outperform the existing method that combines parallel MRI and CS.

439 citations

Journal ArticleDOI
TL;DR: A new class of single state models is defined in which presliding is elastoplastic: under loading, frictional displacement is first purely elastic and then transitions to plastic, to substantially reduce drift while preserving the favorable properties of existing models.
Abstract: For control applications involving small displacements and velocities, friction modeling and compensation can be very important. In particular, the modeling of presliding displacement (motion prior to fully developed slip) can play a pivotal role. In this paper, it is shown that existing single-state friction models exhibit a nonphysical drift phenomenon which results from modeling presliding as a combination of elastic and plastic displacement. A new class of single state models is defined in which presliding is elastoplastic: under loading, frictional displacement is first purely elastic and then transitions to plastic. The new model class is demonstrated to substantially reduce drift while preserving the favorable properties of existing models (e.g., dissipativity) and to provide a comparable match to experimental data.

438 citations

Journal ArticleDOI
Jean-Christophe Golaz1, Peter M. Caldwell1, Luke Van Roekel2, Mark R. Petersen2, Qi Tang1, Jonathan Wolfe2, G. W. Abeshu3, Valentine G. Anantharaj4, Xylar Asay-Davis2, David C. Bader1, Sterling Baldwin1, Gautam Bisht5, Peter A. Bogenschutz1, Marcia L. Branstetter4, Michael A. Brunke6, Steven R. Brus2, Susannah M. Burrows7, Philip Cameron-Smith1, Aaron S. Donahue1, Michael Deakin8, Michael Deakin9, Richard C. Easter7, Katherine J. Evans4, Yan Feng10, Mark Flanner11, James G. Foucar8, Jeremy Fyke2, Brian M. Griffin12, Cecile Hannay13, Bryce E. Harrop7, Mattthew J. Hoffman2, Elizabeth Hunke2, Robert Jacob10, Douglas W. Jacobsen2, Nicole Jeffery2, Philip W. Jones2, Noel Keen5, Stephen A. Klein1, Vincent E. Larson12, L. Ruby Leung7, Hongyi Li3, Wuyin Lin14, William H. Lipscomb13, William H. Lipscomb2, Po-Lun Ma7, Salil Mahajan4, Mathew Maltrud2, Azamat Mametjanov10, Julie L. McClean15, Renata B. McCoy1, Richard Neale13, Stephen Price2, Yun Qian7, Philip J. Rasch7, J. E. Jack Reeves Eyre6, William J. Riley5, Todd D. Ringler2, Todd D. Ringler16, Andrew Roberts2, Erika Louise Roesler8, Andrew G. Salinger8, Zeshawn Shaheen1, Xiaoying Shi4, Balwinder Singh7, Jinyun Tang5, Mark A. Taylor8, Peter E. Thornton4, Adrian K. Turner2, Milena Veneziani2, Hui Wan7, Hailong Wang7, Shanlin Wang2, Dean N. Williams1, Phillip J. Wolfram2, Patrick H. Worley4, Shaocheng Xie1, Yang Yang7, Jin-Ho Yoon17, Mark D. Zelinka1, Charles S. Zender18, Xubin Zeng6, Chengzhu Zhang1, Kai Zhang7, Yuying Zhang1, X. Zheng1, Tian Zhou7, Qing Zhu5 
TL;DR: Energy Exascale Earth System Model (E3SM) project as mentioned in this paper is a project of the U.S. Department of Energy that aims to develop and validate the E3SM model.
Abstract: Energy Exascale Earth System Model (E3SM) project - U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; Climate Model Development and Validation activity - Office of Biological and Environmental Research in the US Department of Energy Office of Science; Regional and Global Modeling and Analysis Program of the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research; National Research Foundation [NRF_2017R1A2b4007480]; Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231]; DOE Office of Science User Facility [DE-AC05-00OR22725]; U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344]; DOE [DE-AC05-76RLO1830]; National Center for Atmospheric Research - National Science Foundation [1852977];[DE-SC0012778]

437 citations


Authors

Showing all 11948 results

NameH-indexPapersCitations
Caroline S. Fox155599138951
Mark D. Griffiths124123861335
Benjamin William Allen12480787750
James A. Dumesic11861558935
Richard O'Shaughnessy11446277439
Patrick Brady11044273418
Laura Cadonati10945073356
Stephen Fairhurst10942671657
Benno Willke10950874673
Benjamin J. Owen10835170678
Kenneth H. Nealson10848351100
P. Ajith10737270245
Duncan A. Brown10756768823
I. A. Bilenko10539368801
F. Fidecaro10556974781
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
2022194
20211,150
20201,189
20191,085
20181,141