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Institution

University of Texas at Austin

EducationAustin, Texas, United States
About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.


Papers
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Journal ArticleDOI
TL;DR: This study addresses the topic of interorganizational network change by exploring factors that affect the choice of alliance and interlock partners and test the hypotheses using data on both interlock and alliance networks for the 300 largest U.S. firms during the 1988-1993 period.
Abstract: In this study, we address the topic of interorganizational network change by exploring factors that affect the choice of alliance and interlock partners. While many studies have been devoted to investigating various factors driving network partner choice, there is also an interesting and unexplored tension in this body of work. On the one hand, much work emphasizes change in social structure--showing that firms expand networks by forming new relationships with new partners. At the same time, other scholars emphasize stability of social structure--showing that firms tend to choose past exchange partners. We seek to reconcile this tension by proposing that firms form new relationships with new partners as a form of exploration, and form additional relationships with existing partners as a form of exploitation (March 1991). Further, whether exploration or exploitation is chosen depends on the type of uncertainty that firms are facing: whether it is firm-specific or market-level uncertainty. We test our hypotheses using data on both interlock and alliance networks for the 300 largest U.S. firms during the 1988-1993 period. The results provide some evidence that whether networks are stable or changing depends on the type of uncertainty experienced by firms.

949 citations

Journal ArticleDOI
01 May 2006-Genetics
TL;DR: The evolution of inversions that capture locally adapted alleles when two populations are exchanging migrants or hybridizing is studied to cause loci responsible for adaptive species-specific differences to map to inversions.
Abstract: We study the evolution of inversions that capture locally adapted alleles when two populations are exchanging migrants or hybridizing. By suppressing recombination between the loci, a new inversion can spread. Neither drift nor coadaptation between the alleles (epistasis) is needed, so this local adaptation mechanism may apply to a broader range of genetic and demographic situations than alternative hypotheses that have been widely discussed. The mechanism can explain many features observed in inversion systems. It will drive an inversion to high frequency if there is no countervailing force, which could explain fixed differences observed between populations and species. An inversion can be stabilized at an intermediate frequency if it also happens to capture one or more deleterious recessive mutations, which could explain polymorphisms that are common in some species. This polymorphism can cycle in frequency with the changing selective advantage of the locally favored alleles. The mechanism can establish underdominant inversions that decrease heterokaryotype fitness by several percent if the cause of fitness loss is structural, while if the cause is genic there is no limit to the strength of underdominance that can result. The mechanism is expected to cause loci responsible for adaptive species-specific differences to map to inversions, as seen in recent QTL studies. We discuss data that support the hypothesis, review other mechanisms for inversion evolution, and suggest possible tests.

948 citations

Journal ArticleDOI
TL;DR: In this article, the authors synthesize palaeoclimate records from the mid-latitude arid Asian region dominated today by the Westerlies ("arid central Asia" (ACA)) to evaluate spatial and temporal patterns of moisture changes during the Holocene.

947 citations

Journal ArticleDOI
TL;DR: Phylogenetic trees from multiple methods provide strong support for the position of Amborella as the earliest diverging lineage of flowering plants, followed by Nymphaeales and Austrobaileyales, and the plastid genome trees also provide strongSupport for a sister relationship between eudicots and monocots, and this group is sister to a clade that includes Chloranthales and magnoliids.
Abstract: Angiosperms are the largest and most successful clade of land plants with >250,000 species distributed in nearly every terrestrial habitat. Many phylogenetic studies have been based on DNA sequences of one to several genes, but, despite decades of intensive efforts, relationships among early diverging lineages and several of the major clades remain either incompletely resolved or weakly supported. We performed phylogenetic analyses of 81 plastid genes in 64 sequenced genomes, including 13 new genomes, to estimate relationships among the major angiosperm clades, and the resulting trees are used to examine the evolution of gene and intron content. Phylogenetic trees from multiple methods, including model-based approaches, provide strong support for the position of Amborella as the earliest diverging lineage of flowering plants, followed by Nymphaeales and Austrobaileyales. The plastid genome trees also provide strong support for a sister relationship between eudicots and monocots, and this group is sister to a clade that includes Chloranthales and magnoliids. Resolution of relationships among the major clades of angiosperms provides the necessary framework for addressing numerous evolutionary questions regarding the rapid diversification of angiosperms. Gene and intron content are highly conserved among the early diverging angiosperms and basal eudicots, but 62 independent gene and intron losses are limited to the more derived monocot and eudicot clades. Moreover, a lineage-specific correlation was detected between rates of nucleotide substitutions, indels, and genomic rearrangements.

943 citations

Journal ArticleDOI
TL;DR: This correspondence proposes a quantized precoding system where the optimal precoder is chosen from a finite codebook known to both receiver and transmitter and performs close to optimal unitary precoding with a minimal amount of feedback.
Abstract: Multiple-input multiple-output (MIMO) wireless systems use antenna arrays at both the transmitter and receiver to provide communication links with substantial diversity and capacity. Spatial multiplexing is a common space-time modulation technique for MIMO communication systems where independent information streams are sent over different transmit antennas. Unfortunately, spatial multiplexing is sensitive to ill-conditioning of the channel matrix. Precoding can improve the resilience of spatial multiplexing at the expense of full channel knowledge at the transmitter-which is often not realistic. This correspondence proposes a quantized precoding system where the optimal precoder is chosen from a finite codebook known to both receiver and transmitter. The index of the optimal precoder is conveyed from the receiver to the transmitter over a low-delay feedback link. Criteria are presented for selecting the optimal precoding matrix based on the error rate and mutual information for different receiver designs. Codebook design criteria are proposed for each selection criterion by minimizing a bound on the average distortion assuming a Rayleigh-fading matrix channel. The design criteria are shown to be equivalent to packing subspaces in the Grassmann manifold using the projection two-norm and Fubini-Study distances. Simulation results show that the proposed system outperforms antenna subset selection and performs close to optimal unitary precoding with a minimal amount of feedback.

943 citations


Authors

Showing all 95138 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Eugene Braunwald2301711264576
Yi Chen2174342293080
Robert J. Lefkowitz214860147995
Joseph L. Goldstein207556149527
Eric N. Olson206814144586
Hagop M. Kantarjian2043708210208
Rakesh K. Jain2001467177727
Francis S. Collins196743250787
Gordon B. Mills1871273186451
Scott M. Grundy187841231821
Michael S. Brown185422123723
Eric Boerwinkle1831321170971
Aaron R. Folsom1811118134044
Jiaguo Yu178730113300
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023304
20221,210
202110,141
202010,331
20199,727
20188,973