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| Registros recuperados: 1.470 | |
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| Richard Evans. |
| Delaware Water Gap National Recreation Area (“the park”) covers 28,000 ha along the Delaware River in Pennsylvania and New Jersey. Eastern hemlock forests cover 2,200 ha (8%) of the park, and are often associated with trout streams and scenic waterfalls. Activities like trout fishing, bird watching, and hiking are concentrated in hemlock forests, and many of these areas are officially designated as “Outstanding Natural Features” having “high intrinsic or unique values.” In 1989 hemlock woolly adelgid (HWA) was detected in the park, and since 1993 the park has conducted a program to address the threats that hemlock woolly adelgid and hemlock decline poses to park resources. This program... |
| Tipo: Presentation |
Palavras-chave: Ecology. |
| Ano: 2011 |
URL: http://precedings.nature.com/documents/5520/version/1 |
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| S Sharma; Rakesh Sharma. |
| Excised mice kidney, heart and skin MRI visible features were quantitated using ex vivo 21 Tesla MRI microimager. The fast MRI acquisition protocols of FLASH, gradient echo flow compensated (GEFC) techniques were used to visualize microvasculature of mice kidney, mice heart including cardiac arteries, veins, cordate tendons and mice skin epidermis with hair follicle features. |
| Tipo: Presentation |
Palavras-chave: Biotechnology. |
| Ano: 2009 |
URL: http://precedings.nature.com/documents/3484/version/1 |
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| C. E. Timothy Paine; Toby Marthews; Deborah Vogt; Drew Purves; Mark Rees; Andy Hector; Lindsay Turnbull. |
| Plant growth is an essential ecological process, integrating across scales from physiology to community dynamics. Predicting the growth of plants is essential to understand a wide range of ecological issues, including competition, plant-herbivore interactions and ecosystem functioning.
A challenge in modeling plant growth is that growth rates almost universally decrease with increasing size, for a variety of reasons. Traditional analyses of growth are hampered by the need to remain within the structures of linear models, which handle this slowing poorly. We demonstrate the implementation of a variety of non-linear models that are more appropriate for modeling plant growth than are the traditional, linear,... |
| Tipo: Presentation |
Palavras-chave: Ecology; Plant Biology. |
| Ano: 2010 |
URL: http://precedings.nature.com/documents/5257/version/1 |
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| Gowen, Rebecca; Rolfe, John; Donaghy, Peter. |
| The Carbon Farming Initiative (CFI) and other carbon trading programs have been promoted as alternative sources of income for agricultural producers, particularly those on marginal land. This paper presents the results of a bioeconomic model developed to compare the relative returns from a beef enterprise against changing regrowth management practices to sequester additional carbon and sell carbon offsets. The model is constructed based on a 1000 hectare parcel of land in Central Queensland and is calculated for two landtypes; Brigalow and Eucalypt. Assuming zero transaction costs and a 20 year contract period, a carbon-cattle enterprise has higher returns that a cattle-only enterprise at relatively low carbon prices for both land types. However, results... |
| Tipo: Presentation |
Palavras-chave: Carbon; Bioeconomic modelling; Grazing economics; Environmental Economics and Policy; Livestock Production/Industries. |
| Ano: 2012 |
URL: http://purl.umn.edu/124311 |
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| Niu, Luyuan; Wohlgenant, Michael K.. |
| This study examines demand for fruits and vegetables segmented by income levels in a complete demand system framework using the Consumer Expenditure Survey (CEX) from 2002 to 2006. Results show that disparities are found between high-income households and low-income households. Seasonal effects and demographic variables, such as household heads’ race and gender, region, household size and household composition, play an important role in fruit and vegetable consumption for both categories of household. In contrast, urban status, household heads’ educational level and age are not found to have a statistically significant impact for low-income households. Conditional price elasticities indicate that processed fruits and vegetables, fresh fruits and fresh... |
| Tipo: Presentation |
Palavras-chave: Agricultural and Food Policy; Consumer/Household Economics; Demand and Price Analysis; Food Consumption/Nutrition/Food Safety. |
| Ano: 2012 |
URL: http://purl.umn.edu/123946 |
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| Pascale Gaudet. |
| Biocuration is a difficult mission: biological data is highly heterogeneous, and there are few areas where guidelines for data preservation and exchange exist. This has hampered the speed, quantity and diversity of data possible to capture. Hence, a major challenge for the biocuration community is to explore innovative ways to capture, represent and display information. It is also essential to increase the involvement of researchers, publishers and funding agencies in this process. I will discuss the work of the International Society for Biocuration to build a community of biocurators to achieve these goals. |
| Tipo: Presentation |
Palavras-chave: Bioinformatics; Data Standards. |
| Ano: 2010 |
URL: http://precedings.nature.com/documents/5134/version/1 |
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| Mandal, Maitreyi; Lagerkvist, Carl Johan. |
| Mean-Variance theory of portfolio construction is still regarded as the main building block of modern portfolio theory. However, many authors have suggested that the mean-variance criterion, conceived by Markowitz (1952), is not optimal for asset allocation, because the investor expected utility function is better proxied by a function that uses higher moments and because returns are distributed in a non-Normal way, being asymmetric and/or leptokurtic, so the mean-variance criterion cannot correctly proxy the expected utility with non-Normal returns. Copulas are a very useful tool to deal with non standard multivariate distribution. Value at Risk (VaR) and Conditional Value at Risk (CVaR) have emerged as a golden measure of risk in recent times. Though... |
| Tipo: Presentation |
Palavras-chave: Portfolio Choice; Downside Risk Protection; Value at risk; Copula; Agricultural Finance; Risk and Uncertainty; C52; G11; Q14. |
| Ano: 2012 |
URL: http://purl.umn.edu/124387 |
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| Registros recuperados: 1.470 | |
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