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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 & Context (language use). 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, a new explanation for variation in maternal characteristics was proposed, which was found to be driven by women trying to conceive, rather than conditions at conception, and no seasonality among unwanted births.
Abstract: Season of birth is associated with later outcomes; what drives this association remains unclear. We consider a new explanation: variation in maternal characteristics. We document large changes in maternal characteristics for births throughout the year; winter births are disproportionally realized by teenagers and the unmarried. Family background controls explain nearly half of season-of-birth's relation to adult outcomes. Seasonality in maternal characteristics is driven by women trying to conceive; we find no seasonality among unwanted births. Prior seasonality-in-fertility research focuses on conditions at conception; here expected conditions at birth drive variation in maternal characteristics while conditions at conception are unimportant.

319 citations

Journal ArticleDOI
TL;DR: In this paper, the electronic structures of direct-band-gap semiconductors with fundamental band gaps ranging from orange through the blue-green to the ultraviolet are predicted and these materials are found to be direct-and indirect-bandgap semiconductor alloys.
Abstract: The electronic structures of InN, ${\mathrm{In}}_{\mathrm{x}}$${\mathrm{Ga}}_{1\mathrm{\ensuremath{-}}\mathrm{x}}$N, and ${\mathrm{In}}_{\mathrm{x}}$${\mathrm{Al}}_{1\mathrm{\ensuremath{-}}\mathrm{x}}$N are predicted and these materials are found to be direct-band-gap semiconductors with fundamental band gaps ranging from orange through the blue-green to the ultraviolet. The deep levels associated with substitutional s- and p-bonded impurities are predicted, and, for InN we find (i) that the native defect responsible for naturally occurring n-type InN is a nitrogen vacancy (not ${\mathrm{N}}_{\mathrm{In}}$); (ii) that the nitrogen vacancy also produces a deep level just below the conduction-band edge, which is responsible for an observed 0.2-eV optical-absorption feature; (iii) that p-type doping should be achievable by inserting column-II impurities on In sites; (iv) that n-type conductivity should result from oxygen atoms on N sites; (v) that ${\mathrm{In}}_{\mathrm{N}}$ produces s- and p-like deep levels near midgap that are responsible for an optical-absorption feature near 1 eV; (vi) that column-IV impurities on either anion or cation sites will tend to make the material semi-insulating, and (vii) that an isoelectronic electron trap should be produced by ${\mathrm{B}}_{\mathrm{In}}$, whereas column-V impurities on the N site should produce deep isoelectronic hole traps. Similar results hold for the alloys ${\mathrm{In}}_{\mathrm{x}}$${\mathrm{Ga}}_{1\mathrm{\ensuremath{-}}\mathrm{x}}$N and ${\mathrm{In}}_{\mathrm{x}}$${\mathrm{Al}}_{1\mathrm{\ensuremath{-}}\mathrm{x}}$N. Some impurities undergo shallow-deep transitions in the alloys, as functions of alloy composition.

319 citations

Journal ArticleDOI
TL;DR: Eye movement patterns clearly established that the initial interpretation of the ambiguous phrase was the one consistent with the context, consistent with a broad theoretical framework in which real-time language comprehension immediately takes into account a rich array of relevant nonlinguistic context.

318 citations

Journal ArticleDOI
TL;DR: It is shown that a network's large-scale topological organization and its local subgraph structure mutually define and predict each other, as confirmed by direct measurements in five well studied cellular networks.
Abstract: Recent evidence indicates that the abundance of recurring elementary interaction patterns in complex networks, often called subgraphs or motifs, carry significant information about their function and overall organization. Yet, the underlying reasons for the variable quantity of different subgraph types, their propensity to form clusters, and their relationship with the networks' global organization remain poorly understood. Here we show that a network's large-scale topological organization and its local subgraph structure mutually define and predict each other, as confirmed by direct measurements in five well studied cellular networks. We also demonstrate the inherent existence of two distinct classes of subgraphs, and show that, in contrast to the low-density type II subgraphs, the highly abundant type I subgraphs cannot exist in isolation but must naturally aggregate into subgraph clusters. The identified topological framework may have important implications for our understanding of the origin and function of subgraphs in all complex networks.

318 citations

Journal ArticleDOI
TL;DR: In this paper, the authors describe the implementation and optimization of the ESSENCE supernova survey, which they have undertaken to measure the dark energy equation-of-state parameter, w = P/(rho c(2)).
Abstract: We describe the implementation and optimization of the ESSENCE supernova survey, which we have undertaken to measure the dark energy equation-of-state parameter, w = P/(rho c(2)). We present a meth ...

318 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
20192,775
20182,624