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Institution

University of Notre Dame

EducationNotre Dame, Indiana, United States
About: University of Notre Dame is a education organization based out in Notre Dame, Indiana, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 22238 authors who have published 55201 publications receiving 2032925 citations. The organization is also known as: University of Notre Dame du Lac & University of Notre Dame, South Bend.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors derived nonlinear relationships based on fundamental laws of continuum mechanics and identified the source of nonlinearity in equations and derived the Forchheimer equation to account for nonlinear effects.
Abstract: Experimental observations have established that the proportionality between pressure head gradient and fluid velocity does not hold for high rates of fluid flow in porous media. Empirical relations such as Forchheimer equation have been proposed to account for nonlinear effects. The purpose of this work is to derive such nonlinear relationships based on fundamental laws of continuum mechanics and to identify the source of nonlinearity in equations.

305 citations

Journal ArticleDOI
TL;DR: This paper found that voter preferences predict the aggregate roll call behavior of Senators while non-voter preferences do not, and they also presented evidence supporting the three explanations advanced to account for the preferential treatment of voters.
Abstract: Studies of political participation and representation often contend that elected officials respond more to the preferences of voters than those of nonvoters, but seldom test this claim. This is a critical assumption because if true, biases in who participates will lead to biased representation. Office holders might respond disproportionately to voters’ preferences because voters tend to select like-minded representatives, voters tend to communicate their preferences more, and only voters can reelect representatives. We find that voter preferences predict the aggregate roll-call behavior of Senators while nonvoter preferences do not. We also present evidence supporting the three explanations advanced to account for the preferential treatment of voters.

305 citations

Journal ArticleDOI
17 Jan 2003-Langmuir
TL;DR: In this article, a reproducibly ultrasmooth octadecyltrichlorosilane (OTS) monolayer (2.6 ± 0.2 nm) was obtained by exposing clean native SiO2 surfaces to a dry solution of OTS in Isop...
Abstract: Ultrasmooth octadecyltrichlorosilane (OTS) monolayers (2.6 ± 0.2 nm thick, RMS roughness ∼1.0 A) can be obtained reproducibly by exposing clean native SiO2 surfaces to a dry solution of OTS in Isop...

305 citations

Journal ArticleDOI
04 Oct 2010
TL;DR: A number of unique switches have been proposed as replacements for CMOS, many of which do not even use electron charge as the state variable and pass tokens in the spin, excitonic, photonic, magnetic, quantum, or even heat domains.
Abstract: Sooner or later, fundamental limitations destine complementary metal-oxide-semiconductor (CMOS) scaling to a conclusion. A number of unique switches have been proposed as replacements, many of which do not even use electron charge as the state variable. Instead, these nanoscale structures pass tokens in the spin, excitonic, photonic, magnetic, quantum, or even heat domains. Emergent physical behaviors and idiosyncrasies of these novel switches can complement the execution of specific algorithms or workloads by enabling quite unique architectures. Ultimately, exploiting these unusual responses will extend throughput in high-performance computing. Alternative tokens also require new transport mechanisms to replace the conventional chip wire interconnect schemes of charge-based computing. New intrinsic limits to scaling in post-CMOS technologies are likely to be bounded ultimately by thermodynamic entropy and Shannon noise.

305 citations

Journal ArticleDOI
D. S. Aguado, Romina Ahumada1, Andres Almeida2, Scott F. Anderson3  +244 moreInstitutions (78)
TL;DR: The Sloan Digital Sky Survey (SDSS) as discussed by the authors released data taken by the fourth phase of SDSS-IV across its first three years of operation (2014 July-2017 July).
Abstract: Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data.

305 citations


Authors

Showing all 22586 results

NameH-indexPapersCitations
George Davey Smith2242540248373
David Miller2032573204840
Patrick O. Brown183755200985
Dorret I. Boomsma1761507136353
Chad A. Mirkin1641078134254
Darien Wood1602174136596
Wei Li1581855124748
Timothy C. Beers156934102581
Todd Adams1541866143110
Albert-László Barabási152438200119
T. J. Pearson150895126533
Amartya Sen149689141907
Christopher Hill1441562128098
Tim Adye1431898109010
Teruki Kamon1422034115633
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023115
2022543
20212,777
20202,925
20192,774
20182,624