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Institution

Rutgers University

EducationNew Brunswick, New Jersey, United States
About: Rutgers University is a education organization based out in New Brunswick, New Jersey, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 68736 authors who have published 159418 publications receiving 6713860 citations. The organization is also known as: Rutgers, The State University of New Jersey & Rutgers.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the exchange-correlation energy of a jellium metal surface is analyzed in terms of the wavelength of the fluctuations that contribute to it, using a three-dimensional scheme different from that used by other authors.
Abstract: The exchange-correlation energy of a jellium metal surface is analyzed in terms of the wavelength of the fluctuations that contribute to it, using a three-dimensional scheme different from that used by other authors. It is shown that with this scheme there exists an exact limiting form at long wavelengths which includes all many-body correlations and which is independent of the surface density profile. The local-density approximation is formulated as a function of wavelength, and it is shown to be exact at short wavelength. The interpolation scheme between these limits, which was discussed previously, is formulated and checked more completely and used to calculate surface energies.

798 citations

Book
18 Jun 2007
TL;DR: The concept of depression has been studied from ancient times through the nineteenth century as discussed by the authors, and depression in the twentieth century has been classified as depression with and without cause in the DSM-IV and DSM-III.
Abstract: 1 The concept of depression 2 The anatomy of normal sadness 3 Sadness with and without cause: depression from ancient times through the nineteenth century 4 Depression in the twentieth century 5 Depression in the DSM-IV 6 Importing pathology into the community 7 The surveillance of sadness 8 The DSM and biological research about depression 9 The rise of antidepressant drug treatments 10 The failure of the social sciences to distinguish sadness from depressive disorder 11 Conclusion

797 citations

Journal ArticleDOI
TL;DR: In this article, the authors examine the co-evolution of MNE activities and institutions external and internal to the firm, and highlight the scope for firm-level creativity and institutional entrepreneurship that may lead to coevolution with the environment.
Abstract: This paper examines the co-evolution of MNE activities and institutions external and internal to the firm. We develop a theoretical framework for this analysis that draws on the more recent writings of Douglass North on institutions as a response to complex forms of uncertainty associated with the rise in global economic interconnectedness, and of Richard Nelson on the co-evolution of technology and institutions. We link historical changes in the character of MNE activities to changes in the institutional environment, and highlight the scope for firm-level creativity and institutional entrepreneurship that may lead to co-evolution with the environment. We argue that the main drivers for institutional entrepreneurship are now found in the increasing autonomy of MNE subsidiaries. Thus MNE agency derives from more decentralized forms of experimentation in international corporate networks, which competence-creating nodes of new initiatives can co-evolve with local institutions. Unlike most other streams of related literature, our approach connects patterns of institutional change in wider business systems with more micro processes of variety generation and experimentation within and across individual firms. This form of co-evolutionary analysis is increasingly important to understanding the interrelationships between MNE activities and public policy.

795 citations

Journal ArticleDOI
John L. Falk1
TL;DR: The similarities among the various behaviors induced as adjuncts to the behaviors under direct schedule control are described in terms of their intensities, temporal loci, and the variables which produce them.

794 citations

Journal ArticleDOI
TL;DR: This work focuses on the best-studied subclasses, the neural cell adhesion molecule NCAM and the L1 family of adhesion molecules, which share important structural and functional features and are instructive for elucidating the mechanisms by which other recognition molecules may guide cell interactions during development or modify their function as a result of injury, learning and memory.
Abstract: Recognition molecules of the immunoglobulin superfamily have important roles in neuronal interactions during ontogeny, including migration, survival, axon guidance and synaptic targeting. Their downstream signal transduction events specify whether a cell changes its place of residence or projects axons and dendrites to targets in the brain, allowing the construction of a dynamic neural network. A wealth of recent discoveries shows that cell adhesion molecules interact with attractant and repellent guidance receptors to control growth cone and cell motility in a coordinate fashion. We focus on the best-studied subclasses, the neural cell adhesion molecule NCAM and the L1 family of adhesion molecules, which share important structural and functional features. We have chosen these paradigmatic molecules and their interactions with other recognition molecules as instructive for elucidating the mechanisms by which other recognition molecules may guide cell interactions during development or modify their function as a result of injury, learning and memory.

793 citations


Authors

Showing all 69437 results

NameH-indexPapersCitations
Salim Yusuf2311439252912
Daniel Levy212933194778
Eugene V. Koonin1991063175111
Eric Boerwinkle1831321170971
David L. Kaplan1771944146082
Derek R. Lovley16858295315
Mark Gerstein168751149578
Gang Chen1673372149819
Hongfang Liu1662356156290
Robert Stone1601756167901
Mark E. Cooper1581463124887
Michael B. Sporn15755994605
Cumrun Vafa15750988515
Wolfgang Wagner1562342123391
David M. Sabatini155413135833
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023274
20221,028
20218,250
20208,150
20197,397
20186,594