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Institution

University of Texas at Arlington

EducationArlington, Texas, United States
About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.


Papers
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Journal ArticleDOI
TL;DR: For example, trace-metal/TOC ratios can provide insight into the degree of watermass restriction and estimates of deepwater renewal times in restricted anoxic marine systems.

388 citations

Journal ArticleDOI
TL;DR: Homeostatic grazers appear to establish an unstable equilibrium in the N: P in the algal pool and thus, presumably, in the nutrient-limitation patterns of the algae, which predicts a role for grazers not predicted by other theoretical approaches.
Abstract: The influence of pelagic herbivores on the competitive arena of their prey is examined in three models of herbivore physiology. One hallmark of pelagic herbivory is the rapid and fight cycling of nutrients among algae, herbivores,and the dissolved phase. An implication of this cycling is that the ratio of elements released by the herbivore is a "supply ratio" as defined in resource-competition theory. The nitrogen (N)-to-phosphorus (P) supply ratio depends on the assumptions made regarding grazer physiology. Three alternative models are considered: (1) a constant, mass-specific basal metabolic release of N and P; (2) a constant efficiency of accumulating N and P in grazer biomass; and (3) an adjusting efficiency of N and P accumulation that maintains a homeostatic ratio of N to P (N:P) in the bodies of the grazers. All three models predict a positive correlation between the N:P in the algal pool and that released by the animals. Previously published data provided strong supportive evidence for this relati...

388 citations

Book ChapterDOI
01 Jan 1989
TL;DR: In addition, the influence of zooplankton on algal succession is not limited to their selective effect on the algal numbers, but also indirectly with phytoplankon by making some nutrients more available to them as discussed by the authors.
Abstract: At times, freshwater zooplankton consume phytoplankton populations at rates similar to or faster than that at which they are growing (Hargrave and Geen, 1970; Gulati, 1975; Horn, 1981; Persson, 1985; Borsheim and Anderson, 1987). Such high losses certainly must help direct seasonal succession as they force a subset of algal species to suffer high mortality rates. Some studies have concluded that losses in general (Kalff and Knoechel, 1978; Reynolds, et al., 1982) and grazing losses in particular (Porter, 1973, 1976, 1977; Lynch and Shapiro, 1981; Crumpton and Wetzel, 1982; Kerfoot, 1987) are important in seasonal succession. In addition, the influence of zooplankton on algal succession is not limited to their selective effect on algal numbers. Zooplankton also interact indirectly with phytoplankton by making some nutrients more available to them (Gliwicz, 1975; Lehman, 1980a, b; Redfield, 1980; Lehman and Scavia, 1982; Sterner, 1986a). Zooplankton thus act not only as predators in the classic sense, but they also have an effect on the competition among algae (Elser et al., 1988).

387 citations

Journal ArticleDOI
TL;DR: A distributed algorithm is presented to solve the economic power dispatch with transmission line losses and generator constraints based on two consensus algorithms running in parallel using a consensus strategy called consensus on the most up-to-date information.
Abstract: A distributed algorithm is presented to solve the economic power dispatch with transmission line losses and generator constraints. The proposed approach is based on two consensus algorithms running in parallel. The first algorithm is a first-order consensus protocol modified by a correction term which uses a local estimation of the system power mismatch to ensure the generation-demand equality. The second algorithm performs the estimation of the power mismatch in the system using a consensus strategy called consensus on the most up-to-date information. The proposed approach can handle networks of different size and topology using the information about the number of nodes which is also evaluated in a distributed fashion. Simulations performed on standard test cases demonstrate the effectiveness of the proposed approach for both small and large systems.

384 citations

Journal ArticleDOI
TL;DR: In this article, a longitudinal analysis of large-scale secondary data from multiple sources was conducted to investigate the effect of customer satisfaction on advertising and promotion efficiency and human capital performance, and the authors found that customer satisfaction boosts the efficiency of future advertising investments.
Abstract: Although there is significant evidence that customer satisfaction is an important driver of firm profitability, extant literature has largely neglected two intermediate outcomes of customer satisfaction, namely, a firm's advertising and promotion efficiency and its human capital performance. On the basis of longitudinal analyses of large-scale secondary data from multiple sources, the authors find that customer satisfaction boosts the efficiency of future advertising and promotion investments. This finding can be explained by the possibility that customer satisfaction generates free word-of-mouth advertising and saves subsequent marketing costs. In addition, customer satisfaction has a positive influence on a company's excellence in human capital (employee talent and manager superiority). This finding is highly novel, indicating that human resources managers should have a strong interest in customer satisfaction as well. Finally, the authors investigate the moderating influence of market concentr...

384 citations


Authors

Showing all 11918 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Hyun-Chul Kim1764076183227
David H. Adams1551613117783
Andrew White1491494113874
Kaushik De1391625102058
Steven F. Maier13458860382
Andrew Brandt132124694676
Amir Farbin131112583388
Evangelos Gazis131114784159
Lee Sawyer130134088419
Fernando Barreiro130108283413
Stavros Maltezos12994379654
Elizabeth Gallas129115785027
Francois Vazeille12995279800
Sotirios Vlachos12878977317
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202353
2022243
20211,722
20201,664
20191,493
20181,462