Institution
Mississippi State University
Education•Starkville, Mississippi, United States•
About: Mississippi State University is a education organization based out in Starkville, Mississippi, United States. It is known for research contribution in the topics: Population & Catfish. The organization has 14115 authors who have published 28594 publications receiving 700030 citations. The organization is also known as: The Mississippi State University of Agriculture and Applied Science & Mississippi State University of Agriculture and Applied Science.
Topics: Population, Catfish, Hyperspectral imaging, Ictalurus, Poison control
Papers published on a yearly basis
Papers
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01 Jul 2007TL;DR: In this paper, the authors examine the process through which multilevel network structures translate into knowledge acquisition from alliance partners and argue that the degree of knowledge transfer a multidivisional company achieves from its network of alliance partners is determined by the organization's external network structure, but also by the structure of relationships among its business units.
Abstract: This article examines the process through which multilevel network structures translate into knowledge acquisition from alliance partners. The degree of knowledge transfer a multidivisional company achieves from its network of alliance partners is determined not only by the organization's external network structure, but also by the structure of relationships among its business units. By distinguishing two perspectives on the distribution of social capital's benefits – private versus collective – this article's approach reconciles the competing views on what types of network structures create social capital, that is, the brokerage and closure views of the social network literature. Private benefits of brokerage and centrality are more beneficial in interfirm networks, whereas collective benefits provided by network closure and low levels of centralization are more beneficial in intrafirm networks.
208 citations
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Mississippi State University1, Lawrence Berkeley National Laboratory2, Northwestern University3, Texas A&M University4, University of Cambridge5, University College London6, University of Maryland, Baltimore7, Princeton University8, European Bioinformatics Institute9, Medical College of Wisconsin10, New York University11, Stanford University12, Carnegie Institution for Science13, Tufts University14, University of Southern California15, California Institute of Technology16, University of Oregon17
TL;DR: The Gene Ontology (GO) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies and continues to expand and improve as a result of targeted ontology development.
Abstract: The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources.
207 citations
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TL;DR: A classifier that couples nearest-subspace classification with a distance-weighted Tikhonov regularization with a competitive process among the classes is proposed to simplify parameter tuning for hyperspectral imagery.
Abstract: A classifier that couples nearest-subspace classification with a distance-weighted Tikhonov regularization is proposed for hyperspectral imagery. The resulting nearest-regularized-subspace classifier seeks an approximation of each testing sample via a linear combination of training samples within each class. The class label is then derived according to the class which best approximates the test sample. The distance-weighted Tikhonov regularization is then modified by measuring distance within a locality-preserving lower-dimensional subspace. Furthermore, a competitive process among the classes is proposed to simplify parameter tuning. Classification results for several hyperspectral image data sets demonstrate superior performance of the proposed approach when compared to other, more traditional classification techniques.
207 citations
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TL;DR: It appears that this newly developed Bt cotton expressing two toxins will be more effective and have a wider range of activity on these lepidopteran pests.
Abstract: A series of laboratory assays were performed to compare the relative impact of commercial and experimental cultivars of cotton, Gossypium hirsutum (L.), expressing zero, one, or two insecticidal proteins of Bacillus thuringiensis Berliner, on several lepidopteran pests. Assays in which larvae were fed fresh plant tissue indicated that dual-toxin B. thuringiensis (Bt) cultivars, expressing both Cry1Ac and Cry2Ab endotoxins of B. thuringiensis, were more toxic to bollworms, Helicoverpa zea (Boddie), fall armyworms, Spodoptera frugiperda (J. E. Smith), and beet armyworms, Spodoptera exigua (Hubner), than single-toxin cultivars expressing Cry1Ac. Assays in which lyophilized plant tissue was incorporated into artificial diet also indicated improved activity of the dual-toxin Bt cultivar compared with single-toxin plants. Both bollworm and tobacco budworm, Heliothis virescens (F.), growth was reduced by Bt cotton, particularly the dual-toxin cultivar. Although assays with lyophilized tissues were done using largely sublethal doses, bollworm survival was reduced by the dual-toxin cultivar. It appears that this newly developed Bt cotton expressing two toxins will be more effective and have a wider range of activity on these lepidopteran pests.
207 citations
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TL;DR: It is concluded that the combination of a commercial antioxidant and biocide is synergistic, which implies that extractives may protect wood by more than simply being fungicidal.
206 citations
Authors
Showing all 14277 results
Name | H-index | Papers | Citations |
---|---|---|---|
Naomi J. Halas | 140 | 435 | 82040 |
Bin Liu | 138 | 2181 | 87085 |
Shuai Liu | 129 | 1095 | 80823 |
Vijay P. Singh | 106 | 1699 | 55831 |
Liangpei Zhang | 97 | 839 | 35163 |
K. L. Dooley | 95 | 320 | 63579 |
Feng Chen | 95 | 2138 | 53881 |
Marco Cavaglia | 93 | 372 | 60157 |
Tuan Vo-Dinh | 86 | 698 | 24690 |
Nicholas H. Barton | 84 | 267 | 32707 |
S. Kandhasamy | 81 | 235 | 50363 |
Michael S. Sacks | 80 | 386 | 20510 |
Dinesh Mohan | 79 | 283 | 35775 |
James Mallet | 78 | 209 | 21349 |
George D. Kuh | 77 | 248 | 30346 |