Institution
University of New Hampshire
Education•Durham, New Hampshire, United States•
About: University of New Hampshire is a education organization based out in Durham, New Hampshire, United States. It is known for research contribution in the topics: Population & Solar wind. The organization has 9379 authors who have published 24025 publications receiving 1020112 citations. The organization is also known as: UNH.
Topics: Population, Solar wind, Poison control, Magnetosphere, Heliosphere
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the vertical gradients of NO x, HONO, and HNO 3 were measured in the lower 1-2 m above the snowpack at Summit, Greenland, during summer 2000.
214 citations
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TL;DR: In this article, a process-based model, Manure-DNDC, is proposed to describe manure organic matter turnover and gas emissions, which can construct a virtual farm by selecting and integrating one or more of the candidate farm facilities parameterized in the model.
Abstract: From the point of view of biogeochemistry, manure is a complex of organic matter containing minor minerals. When manure is excreted by animals, it undergoes a series of reactions such as decomposition, hydrolysis, ammonia volatilization, nitrification, denitrification, fermentation etc., from which carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4) and ammonia (NH3) can be produced. Based on the principles of thermodynamics and reaction kinetics, these reactions are commonly controlled by a group of environmental factors such as temperature, moisture, redox potential, pH, substrate concentration gradient etc. The relations among the environmental factors, the reactions and the gas production have been incorporated in a process-based model, Manure-DNDC, to describe manure organic matter turnover and gas emissions. Using Manure-DNDC, the users can construct a virtual farm by selecting and integrating one or more of the candidate farm facilities (i.e., feedlot, compost, lagoon, anaerobic digester and cropping field) parameterized in the model. Manure-DNDC calculates variations of the environmental factors for each component facility based on its technical specifications, and then utilizes the environmental factors to drive the biogeochemical reactions. To verify the applicability of Manure-DNDC for livestock farms, seven datasets of air emissions measured from farms across the U.S. plus a Scotland pasture were utilized for model tests with encouraging results. A dairy farm in New York was used to assess the impacts of alternative management practices on the gas mitigation. The modeled results showed that a combination of changes in the feed quality, the lagoon coverage and the planted crop type could reduce greenhouse gas emission by 30 % and NH3 by 36 % at the farm scale.
214 citations
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TL;DR: This work biochemically characterized the ERS1 protein by heterologous expression in yeast and found 1-MCP to be both a potent inhibitor of the ethylene-induced seedling triple response, as well as ethylene binding by yeast expressing ETR1 and E RS1.
Abstract: Ethylene perception in Arabidopsis is controlled by a family of five genes, including ETR1 , ERS1 (ethylene response sensor 1), ERS2 , ETR2 , and EIN4 . ERS1 , the most highly conserved gene with ETR1 , encodes a protein with 67% identity to ETR1. To clarify the role of ERS1 in ethylene sensing, we biochemically characterized the ERS1 protein by heterologous expression in yeast. ERS1, like ETR1, forms a membrane-associated, disulfide-linked dimer. In addition, yeast expressing the ERS1 protein contains ethylene-binding sites, indicating ERS1 is also an ethylene-binding protein. This finding supports previous genetic evidence that isoforms of ETR1 also function in plants as ethylene receptors. Further, we used the ethylene antagonist 1-methylcyclopropene (1-MCP) to characterize the ethylene-binding sites of ERS1 and ETR1. We found 1-MCP to be both a potent inhibitor of the ethylene-induced seedling triple response, as well as ethylene binding by yeast expressing ETR1 and ERS1. Yeast expressing ETR1 and ERS1 showed nearly identical sensitivity to 1-MCP, suggesting that the ethylene-binding sites of ETR1 and ERS1 have similar affinities for ethylene.
214 citations
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TL;DR: In this article, the influence of competitive strategy on the relationship between suppliers and their distribution networks is examined and hypotheses are developed specifying the appropriate match between manufacturer strategies and systems of control within distribution channels.
Abstract: This paper examines the influence of competitive strategy on the relationship between suppliers and their distribution networks. Drawing on agency theory, hypotheses are developed specifying the appropriate match between manufacturer strategies and systems of control within distribution channels. Cluster analysis is used to show distinct differences in channel management and structure for the three generic strategies of cost leadership, differentiation and focus. Results suggest that variation in control relationships may be explained by the demands posed by manufacturers' competitive strategies. This study therefore extends the applicability of Porter's typology to the specific structure of distribution channels and shows that agency theory can provide insights into the economic basis of interorganizational relationships.
214 citations
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TL;DR: The authors found that Moody's downgrades, indicators of increasing risk, are associated with negative abnormal equity returns that are increasing in the bank's reliance on insured deposits and that banks raise their use of insured deposits following increases in risk.
214 citations
Authors
Showing all 9489 results
Name | H-index | Papers | Citations |
---|---|---|---|
Derek R. Lovley | 168 | 582 | 95315 |
Peter B. Reich | 159 | 790 | 110377 |
Jerry M. Melillo | 134 | 383 | 68894 |
Katja Klein | 129 | 1499 | 87817 |
David Finkelhor | 117 | 382 | 58094 |
Howard A. Stone | 114 | 1033 | 64855 |
James O. Hill | 113 | 532 | 69636 |
Tadayuki Takahashi | 112 | 932 | 57501 |
Howard Eichenbaum | 108 | 279 | 44172 |
John D. Aber | 107 | 204 | 48500 |
Andrew W. Strong | 99 | 563 | 42475 |
Charles T. Driscoll | 97 | 554 | 37355 |
Andrew D. Richardson | 94 | 282 | 32850 |
Colin A. Chapman | 92 | 491 | 28217 |
Nicholas W. Lukacs | 91 | 367 | 34057 |