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
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TL;DR: Extending previous theorizing on cultural diversity's organizational effects by integrating value-in-diversity and social identity perspectives with the framework of Blau's (1977) theory of heterog...
Abstract: Extending previous theorizing on cultural diversity's organizational effects by integrating value-in-diversity and social identity perspectives with the framework of Blau's (1977) theory of heterog...
734 citations
TL;DR: This paper found that first-generation students tended to be less engaged and gained less from college than their counterparts with college-educated parents did, due to having lower educational aspirations and living off campus.
Abstract: Students who are the first in their family to attend college are less likely to graduate compared to students with one or both parents who have baccalaureate degrees. However, surprisingly little is known about the college experiences of first-generation students. This study examined the self-reported college experiences of 1,127 first-year students at a variety of four-year colleges and universities. First-generation students tended to be less engaged and gained less from college than their counterparts with college-educated parents did. These differences were primarily due to first-generation students having lower educational aspirations and living off campus.
730 citations
TL;DR: Overall, results suggest that the predictive validity of self-efficacy is attenuated in the presence of individual differences, though this attenuation does depend on the context.
Abstract: The present study estimated the unique contribution of self-efficacy to work-related performance controlling for personality (the Big 5 traits), intelligence or general mental ability, and job or task experience. Results, based on a meta-analysis of the relevant literatures, revealed that overall, across all studies and moderator conditions, the contribution of self-efficacy relative to purportedly more distal variables is relatively small. Within moderator categories, there were several cases in which self-efficacy made unique contributions to work-related performance. For example, self-efficacy predicted performance in jobs or tasks of low complexity but not those of medium or high complexity, and self-efficacy predicted performance for task but not job performance. Overall, results suggest that the predictive validity of self-efficacy is attenuated in the presence of individual differences, though this attenuation does depend on the context.
721 citations
Goethe University Frankfurt1, University of Maryland, College Park2, University of Guelph3, Duke University4, Swedish University of Agricultural Sciences5, Radboud University Nijmegen6, Federal University of Mato Grosso do Sul7, University of Alberta8, Royal Veterinary College9, Wildlife Conservation Society10, Mississippi State University11, Sao Paulo State University12, Michigan Department of Natural Resources13, University of California, Davis14, Aarhus University15, Max Planck Society16, University of Potsdam17, Middle Tennessee State University18, Mammal Research Institute19, Edmund Mach Foundation20, Harvard University21, Smithsonian Conservation Biology Institute22, University of Évora23, University of Montpellier24, Parks Victoria25, Monash University26, Ohio State University27, Fiji National University28, University of Massachusetts Amherst29, United States Geological Survey30, Save the Elephants31, University of Oxford32, German Primate Center33, Technische Universität München34, Institute of Ecosystem Studies35, University of British Columbia36, University of Zurich37, University of Wyoming38, University of Washington39, University of Montana40, University of Freiburg41, Bavarian Forest National Park42, University of Toulouse43, University of Veterinary Medicine Vienna44, University College Cork45, North Carolina Museum of Natural Sciences46, North Carolina State University47, Karatina University48, University of Lethbridge49, Lamont–Doherty Earth Observatory50, University of Valencia51, Stony Brook University52, International Union for Conservation of Nature and Natural Resources53, University of Alicante54, Empresa Brasileira de Pesquisa Agropecuária55, University of Glasgow56, New York University57, University of Oslo58, Hebrew University of Jerusalem59, Norwegian University of Science and Technology60, Field Museum of Natural History61, University of Grenoble62, University of Bayreuth63, University of New South Wales64, Pennsylvania Game Commission65, Princeton University66, University of Konstanz67, University of Haifa68, Polish Academy of Sciences69, University of Lisbon70, Instituto Superior de Agronomia71, University of Porto72, University of California, Santa Cruz73, University of Pretoria74, Colorado State University75
TL;DR: Using a unique GPS-tracking database of 803 individuals across 57 species, it is found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in area with a low human footprint.
Abstract: Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
719 citations
TL;DR: This paper presents a computational technique for optimal control problems including state and control inequality constraints based on spectral collocation methods used in the solution of differential equations that is easy to implement, capable of handling various types of constraints, and yields very accurate results.
Abstract: This paper presents a computational technique for optimal control problems including state and control inequality constraints. The technique is based on spectral collocation methods used in the solution of differential equations. The system dynamics are collocated at Legendre-Gauss-Lobatto points. The derivative x/spl dot/(t) of the state x(t) is approximated by the analytic derivative of the corresponding interpolating polynomial. State and control inequality constraints are collocated at Legendre-Gauss-Lobatto nodes. The integral involved in the definition of the performance index is discretized based on the Gauss-Lobatto quadrature rule. The optimal control problem is thereby converted into a mathematical programming program. Thus existing, well-developed optimization algorithms may be used to solve the transformed problem. The method is easy to implement, capable of handling various types of constraints, and yields very accurate results. Illustrative examples are included to demonstrate the capability of the proposed method, and a comparison is made with existing methods in the literature. >
703 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 |