Institution
University of Nebraska–Lincoln
Education•Lincoln, Nebraska, United States•
About: University of Nebraska–Lincoln is a education organization based out in Lincoln, Nebraska, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 28059 authors who have published 61544 publications receiving 2139104 citations. The organization is also known as: Nebraska & UNL.
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TL;DR: This article discusses two design alternatives for optimizing the availability of any technical system - reliability and maintainability and suggests that guiding principles of engineering design offer potentially useful insights.
Abstract: Design engineers share archaeologists' interest in material culture, but unlike archaeologists, engineers have developed concepts for determining the suitability of technical systems to perform specific tasks. Given the difficulty archaeologists face in developing theories of material culture, I suggest that guiding principles of engineering design offer potentially useful insights. In this article I discuss two design alternatives for optimizing the availability of any technical system - reliability and maintainability. Reliable systems are made so that they can be counted on to work when needed. Maintainable ones can easily be made to function if they are broken or not appropriate to the task at hand. Because these design alternatives have markedly different optimal applications and observably different physical characteristics, archaeologists can link the design of prehistoric weapons to environmental constraints and to specific hunting strategies. Ethnographic examples indicate that primitive hunters do use both reliable and maintainable systems in optimal situations.
539 citations
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TL;DR: In this article, the surface composition of stoichiometric Fe3O4 capped with a mixture of monodentate carboxylate and chemisorbed amine was determined by X-ray photoelectron spectroscopy.
539 citations
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TL;DR: In this paper, the authors explore precipitating events, emotions, and decisions associated with older consumers' disposition of special possessions, and emphasize the storied nature of the meanings consumers attach to their cherished possessions and the way in which these storied meanings are bundled with life review and disposition concerns.
Abstract: This article explores precipitating events, emotions, and decisions associated with older consumers’ disposition of special possessions. Findings are based on analyses of semistructured interviews with 80 older consumers, complemented by depth interviews with seven informants. Cherished possessions and their disposition play a significant role in older consumers’ reminiscence and life review. Concerns about disposition of special possessions involve strong and ambivalent emotions. Older consumers voice concern over avoiding intrafamilial conflict, reducing uncertainty, and exercising control over the future life of special possessions. We emphasize the storied nature of the meanings consumers attach to their cherished possessions and the way in which these storied meanings are bundled with life review and disposition concerns. Many older consumers attempt to control meanings transferred with cherished possessions. They seek to pass on personal and familial legacies, achieve symbolic immortality, insure a ...
538 citations
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Agro ParisTech1, Institut national de la recherche agronomique2, University of Florida3, Goddard Institute for Space Studies4, Michigan State University5, University of Basilicata6, Wageningen University and Research Centre7, Empresa Brasileira de Pesquisa Agropecuária8, University of East Anglia9, University of Tübingen10, University of Nebraska–Lincoln11, United States Department of Agriculture12, Pacific Northwest National Laboratory13, Pennsylvania State University14, University of Washington15, Indian Agricultural Research Institute16, Potsdam Institute for Climate Impact Research17, Chinese Academy of Sciences18, Plant & Food Research19
TL;DR: The largest maize crop model intercomparison to date, including 23 different models, is presented, suggesting that using an ensemble of models has merit and there was a large uncertainty in the yield response to [CO2 ] among models.
Abstract: Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per degrees C. Doubling [CO2] from 360 to 720 mu mol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
536 citations
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TL;DR: Gu et al. as discussed by the authors analyzed MODIS normalized difference vegetation index and normalized difference water index (NDWI) data for grassland drought assessment within the central United States, specifically for the Flint Hills of Kansas and Oklahoma.
Abstract: Received 18 December 2006; revised 16 February 2007; accepted 28 February 2007; published 27 March 2007. [1] A five-year (2001–2005) history of moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data was analyzed for grassland drought assessment within the central United States, specifically for the Flint Hills of Kansas and Oklahoma. Initial results show strong relationships among NDVI, NDWI, and drought conditions. During the summer over the Tallgrass Prairie National Preserve, the average NDVI and NDWI were consistently lower (NDVI 0.6 and NDWI>0.4). NDWI values exhibited a quicker response to drought conditions than NDVI. Analysis revealed that combining information from visible, near infrared, and short wave infrared channels improved sensitivity to drought severity. The proposed normalized difference drought index (NDDI) had a stronger response to summer drought conditions than a simple difference between NDVI and NDWI, and is therefore a more sensitive indicator of drought in grasslands than NDVI alone.Citation: Gu, Y., J. F. Brown, J. P. Verdin, and B. Wardlow (2007), A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States, Geophys. Res. Lett., 34, L06407, doi:10.1029/ 2006GL029127.
535 citations
Authors
Showing all 28272 results
Name | H-index | Papers | Citations |
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Donald P. Schneider | 242 | 1622 | 263641 |
Suvadeep Bose | 154 | 960 | 129071 |
David D'Enterria | 150 | 1592 | 116210 |
Aaron Dominguez | 147 | 1968 | 113224 |
Gregory R Snow | 147 | 1704 | 115677 |
J. S. Keller | 144 | 981 | 98249 |
Andrew Askew | 140 | 1496 | 99635 |
Mitchell Wayne | 139 | 1810 | 108776 |
Kenneth Bloom | 138 | 1958 | 110129 |
P. de Barbaro | 137 | 1657 | 102360 |
Randy Ruchti | 137 | 1832 | 107846 |
Ia Iashvili | 135 | 1676 | 99461 |
Yuichi Kubota | 133 | 1695 | 98570 |
Ilya Kravchenko | 132 | 1366 | 93639 |
Andrea Perrotta | 131 | 1380 | 85669 |