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Institution

Ohio State University

EducationColumbus, Ohio, United States
About: Ohio State University is a education organization based out in Columbus, Ohio, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 102421 authors who have published 222715 publications receiving 8373403 citations. The organization is also known as: Ohio State & The Ohio State University.


Papers
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Journal ArticleDOI
TL;DR: In this article, structural cohesion is defined as the minimum number of actors who, if removed from a group, would disconnect the group, and a structural dimension of embeddedness can then be defined through the hierarchical nesting of these cohesive structures.
Abstract: Although questions about social cohesion lie at the core of our discipline, definitions are often vague and difficult to operationalize. Here, research on social cohesion and social embeddedness is linked by developing a concept of structural cohesion based on network node connectivity. Structural cohesion is defined as the minimum number of actors who, if removed from a group, would disconnect the group. A structural dimension of embeddedness can then be defined through the hierarchical nesting of these cohesive structures. The empirical applicability of nestedness is demonstrated in two dramatically different substantive settings, and additional theoretical implications with reference to a wide array of substantive fields are discussed.

1,095 citations

Journal ArticleDOI
TL;DR: The REVERSE (REsynchronization reVErses Remodeling in Systolic left vEntricular dysfunction) trial demonstrates that CRT, in combination with optimal medical therapy (+/-defibrillator), reduces the risk for heart failure hospitalization and improves ventricular structure and function in NYHA functional class II and NYHAfunctional class I patients with previous HF symptoms.

1,093 citations

Journal ArticleDOI
TL;DR: It is argued that genetic algorithms are inappropriate for network acquisition and an evolutionary program is described, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks.
Abstract: Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods. >

1,092 citations

Journal ArticleDOI
05 Dec 2013-Nature
TL;DR: The sources, exchanges and fates of carbon in the coastal ocean and how anthropogenic activities have altered the carbon cycle are discussed.
Abstract: The carbon cycle of the coastal ocean is a dynamic component of the global carbon budget. But the diverse sources and sinks of carbon and their complex interactions in these waters remain poorly understood. Here we discuss the sources, exchanges and fates of carbon in the coastal ocean and how anthropogenic activities have altered the carbon cycle. Recent evidence suggests that the coastal ocean may have become a net sink for atmospheric carbon dioxide during post-industrial times. Continued human pressures in coastal zones will probably have an important impact on the future evolution of the coastal ocean's carbon budget.

1,091 citations

Journal ArticleDOI
Rattan Lal1
TL;DR: In this paper, the impact of soil erosion on crop yield, productivity, and soil quality is investigated, and it is shown that erosion-induced losses on crop yields are scale-dependent because of the compensatory beneficial effects on yields from depositional sites, and technology dependent because of masking effects of input such as fertilizers and irrigation.
Abstract: Soil degradation by accelerated erosion is a serious problem and will remain so during the 21st century, especially in developing countries of the tropics and subtropics. Yet, its extent, severity, and economic and environmental impacts are debatable. Estimates of global and regional land area affected are tentative and subjective. Results of field measurements are often technique-dependent. Considerable progress has been made in modeling soil erosion, yet field validation of these models remains to be done for principal soils and ecoregions. Similar to the land area affected, estimates of erosional impacts on crop yield, productivity and soil quality are tentative and subjective. Further, erosion-induced losses on crop yield are scale-dependent because of the compensatory beneficial effects on yields from depositional sites, and technology-dependent because of the masking effects of input such as fertilizers and irrigation. Erosion caused changes in soil carbon dynamics and non-point source water pollution are important environmental impacts. While erosion (e.g., detachment and transport) can lead to emission of trace gases into the atmosphere, deposition can bury and sequester some of the carbon. In addition to improving the database on the land area affected, there is also a need to assess erosional impacts on productivity and soil C balance at the watershed, regional, and global scale. Copyright © 2001 John Wiley & Sons, Ltd.

1,088 citations


Authors

Showing all 103197 results

NameH-indexPapersCitations
Paul M. Ridker2331242245097
George Davey Smith2242540248373
Carlo M. Croce1981135189007
Eric J. Topol1931373151025
Bernard Rosner1901162147661
David H. Weinberg183700171424
Anil K. Jain1831016192151
Michael I. Jordan1761016216204
Kay-Tee Khaw1741389138782
Richard K. Wilson173463260000
Yang Yang1642704144071
Brian L Winer1621832128850
Jian-Kang Zhu161550105551
Elaine R. Mardis156485226700
R. E. Hughes1541312110970
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023261
20221,236
20219,948
20209,945
20199,052
20188,656