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Institution

Carnegie Mellon University

EducationPittsburgh, Pennsylvania, United States
About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.


Papers
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Journal ArticleDOI
TL;DR: Kraut et al. as discussed by the authors reported negative effects of using the Internet on social involvement and psychological well-being among new Internet users in 1995-96 and found that negative effects dissipated.
Abstract: Kraut et al. (1998) reported negative effects of using the Internet on social involvement and psychological well-being among new Internet users in 1995–96. We called the effects a “paradox” because participants used the Internet heavily for communication, which generally has positive effects. A 3-year follow-up of 208 of these respondents found that negative effects dissipated. We also report findings from a longitudinal survey in 1998–99 of 406 new computer and television purchasers. This sample generally experienced positive effects of using the Internet on communication, social involvement, and well-being. However, consistent with a “rich get richer” model, using the Internet predicted better outcomes for extraverts and those with more social support but worse outcomes for introverts and those with less support.

2,064 citations

Journal ArticleDOI
TL;DR: The PVM system, a heterogeneous network computing trends in distributed computing PVM overview other packages, and troubleshooting: geting PVM installed getting PVM running compiling applications running applications debugging and tracing debugging the system.
Abstract: Part 1 Introduction: heterogeneous network computing trends in distributed computing PVM overview other packages. Part 2 The PVM system. Part 3 Using PVM: how to obtain the PVM software setup to use PVM setup summary starting PVM common startup problems running PVM programs PVM console details host file options. Part 4 Basic programming techniques: common parallel programming paradigms workload allocation porting existing applications to PVM. Part 5 PVM user interface: process control information dynamic configuration signalling setting and getting options message passing dynamic process groups. Part 6 Program examples: fork-join dot product failure matrix multiply one-dimensional heat equation. Part 7 How PVM works: components messages PVM daemon libpvm library protocols message routing task environment console program resource limitations multiprocessor systems. Part 8 Advanced topics: XPVM porting PVM to new architectures. Part 9 Troubleshooting: geting PVM installed getting PVM running compiling applications running applications debugging and tracing debugging the system. Appendices: history of PVM versions PVM 3 routines.

2,060 citations

Journal ArticleDOI
S. Hong Lee1, Stephan Ripke2, Stephan Ripke3, Benjamin M. Neale2  +402 moreInstitutions (124)
TL;DR: Empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.
Abstract: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

2,058 citations

Journal ArticleDOI
Andrew G. Clark1, Michael B. Eisen2, Michael B. Eisen3, Douglas Smith  +426 moreInstitutions (70)
08 Nov 2007-Nature
TL;DR: These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution.
Abstract: Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

2,057 citations

Journal ArticleDOI
TL;DR: In this paper, the authors argue that the roles of relational and structural embeddedness play in firm performance can only be understood with reference to the other, and that the influence of these factors on firm performance is contingent on industry context.
Abstract: Network researchers have argued that both relational embeddedness—characteristics of relationships—and structural embeddedness—characteristics of the relational structure—influence firm behavior and performance. Using strategic alliance networks in the semiconductor and steel industries, we build on past embeddedness research by examining the interaction of these factors. We argue that the roles relational and structural embeddedness play in firm performance can only be understood with reference to the other. Moreover, we argue that the influence of these factors on firm performance is contingent on industry context. More specifically, our empirical analysis suggests that strong ties in a highly interconnected strategic alliance network negatively impact firm performance. This network configuration is especially suboptimal for firms in the semiconductor industry. Furthermore, strong and weak ties are positively related to firm performance in the steel and semiconductor industries, respectively. Copyright © 2000 John Wiley & Sons, Ltd.

2,047 citations


Authors

Showing all 36645 results

NameH-indexPapersCitations
Yi Chen2174342293080
Rakesh K. Jain2001467177727
Robert C. Nichol187851162994
Michael I. Jordan1761016216204
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
P. Chang1702154151783
Krzysztof Matyjaszewski1691431128585
Yang Yang1642704144071
Geoffrey E. Hinton157414409047
Herbert A. Simon157745194597
Yongsun Kim1562588145619
Terrence J. Sejnowski155845117382
John B. Goodenough1511064113741
Scott Shenker150454118017
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023120
2022499
20214,980
20205,375
20195,420
20184,972