324 research outputs found

    Capacity Utilization, Income Distribution, and the Urban Informal Sector: An Open-Economy Model

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    Developing economies worldwide have experienced rapid informal sector expansion in response to formal sector unemployment. However, the macroeconomic eects of formal-informal sector dualism have been widely overlooked. This paper develops a two-sector, structuralist, macroeconomic model to analyze the impact of urban informal sector activity on export-led growth policy. The model uses stylized facts from the Johannesburg informal sector and is applicable to countries where informal sector production is concentrated in low-wage goods and commercial services. The paper finds that trade-os between capacity utilization and reduced income inequality could be magnified when the existence of an urban informal sector is incorporated.informal sector, South Africa, macroeconomic policy

    The Effect of Phosphorylated Glucose on Major Pathogens of Bovine Mastitis

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    Mastitis is the number one infectious disease on dairies. Treatment and prevention is mainly through good milking hygiene, proper environmental conditions, and antibiotic usage. For organic dairies, mastitis prevention and control can be problematic as there are major restrictions on the use of antibiotics. Phosphorylated glucose, produced by heating (121ÂșC) a phosphate-buffered solution with added glucose, is bactericidal to Escherichia coli. We tested the bactericidal properties of phosphorylated glucose on three major pathogens of mastitis: E. coli, Staphylococcus aureus, and Streptococcus agalactiae. Phosphorylated glucose was bactericidal on the pathogens tested in phosphate-buffered saline. When in the presence of milk, phosphorylated glucose was not bactericidal on E. coli, but Staph. aureus and Strep. agalactiae are still affected. Further studies of phosphorylated glucose on Mycoplasma, a pathogen of mastitis that is inherently resistant to ÎČ-lactam antibiotics, and on mammary cells are in process. This work will provide organic dairy producers with additional information for the prevention and treatment of mastitis

    The Effect of Phosphorylated Glucose on Major Pathogens of Bovine Mastitis

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    Mastitis is the number one infectious disease on dairies. Treatment and prevention is mainly through good milking hygiene, proper environmental conditions, and antibiotic usage. For organic dairies, mastitis prevention and control can be problematic as there are major restrictions on the use of antibiotics. Phosphorylated glucose, produced by heating (121ÂșC) a phosphate-buffered solution with added glucose, is bactericidal to Escherichia coli. We tested the bactericidal properties of phosphorylated glucose on three major pathogens of mastitis: E. coli, Staphylococcus aureus, and Streptococcus agalactiae. Phosphorylated glucose was bactericidal on the pathogens tested in phosphate-buffered saline. When in the presence of milk, phosphorylated glucose was not bactericidal on E. coli, but Staph. aureus and Strep. agalactiae are still affected. Further studies of phosphorylated glucose on Mycoplasma, a pathogen of mastitis that is inherently resistant to ÎČ-lactam antibiotics, and on mammary cells are in process. This work will provide organic dairy producers with additional information for the prevention and treatment of mastitis

    Generalized Tests for Selection Effects in GRB High-Energy Correlations

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    Several correlations among parameters derived from modelling the high-energy properties of GRBs have been reported. We show that well-known examples of these have common features indicative of strong contamination by selection effects. We focus here on the impact of detector threshold truncation on the spectral peak versus isotropic equivalent energy release (EpkE_{\rm pk}-EisoE_{\rm iso}) relation, extended to a large sample of 218 Swift and 56 HETE-2 GRBs with and without measured redshift. The existence of faint Swift events missing from pre-Swift surveys calls into question inferences based on pre-Swift surveys which must be subject to complicated incompleteness effects. We demonstrate a generalized method for treating data truncation in correlation analyses and apply this method to Swift and pre-Swift data. Also, we show that the EpkE_{\rm pk}-EÎłE_{\gamma} ("Ghirlanda") correlation is effectively independent of the GRB redshifts, which suggests its existence has little to do with intrinsic physics. We suggest that a physically-based correlation, manifest observationally, must show significantly reduced scatter in the rest frame relative to the observer frame and must not persist if the assumed redshifts are scattered. As with the EpkE_{\rm pk}-EÎłE_{\gamma} correlation, we find that the pre-Swift, bright GRB EpkE_{\rm pk}-EisoE_{\rm iso} correlation of \citet{amati06} does not rigorously satisfy these conditions.Comment: 8 pages, 4 figures, ApJ Accepte

    Impact of culture towards disaster risk reduction

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    Number of natural disasters has risen sharply worldwide making the risk of disasters a global concern. These disasters have created significant losses and damages to humans, economy and society. Despite the losses and damages created by disasters, some individuals and communities do not attached much significance to natural disasters. Risk perception towards a disaster not only depends on the danger it could create but also the behaviour of the communities and individuals that is governed by their culture. Within this context, this study examines the relationship between culture and disaster risk reduction (DRR). A comprehensive literature review is used for the study to evaluate culture, its components and to analyse a series of case studies related to disaster risk. It was evident from the study that in some situations, culture has become a factor for the survival of the communities from disasters where as in some situations culture has acted as a barrier for effective DRR activities. The study suggests community based DRR activities as a mechanism to integrate with culture to effectively manage disaster risk

    Dual isotope analyses indicate efficient processing of atmospheric nitrate by forested watersheds in the northeastern U.S.

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    Author Posting. © Springer, 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 90 (2008): 15-27, doi:10.1007/s10533-008-9227-2.Nitrogen from atmospheric deposition serves as the dominant source of new nitrogen to forested ecosystems in the northeastern U.S.. By combining isotopic data obtained using the denitrifier method, with chemistry and hydrology measurements we determined the relative importance of sources and control mechanisms on nitrate (NO3-) export from five forested watersheds in the Connecticut River watershed. Microbially produced NO3- was the dominant source (82-100%) of NO3- to the sampled streams as indicated by the Ύ15N and Ύ18O of NO3-. Seasonal variations in the Ύ18O-NO3- in streamwater are controlled by shifting hydrology and temperature affects on biotic processing, resulting in a relative increase in unprocessed NO3- export during winter months. Mass balance estimates find that the unprocessed atmospherically derived NO3- stream flux represents less than 3% of the atmospherically delivered wet NO3- flux to the region. This suggests that despite chronically elevated nitrogen deposition these forests are not nitrogen saturated and are retaining, removing, and reprocessing the vast majority of NO3- delivered to them throughout the year. These results confirm previous work within Northeastern U.S. forests and extend observations to watersheds not dominated by a snow-melt driven hydrology. In contrast to previous work, unprocessed atmospherically derived NO3- export is associated with the period of high recharge and low biotic activity as opposed to spring snowmelt and other large runoff events.This work was funded by an EPA STAR Fellowship (FP-91637501-1) and a grant from QLF/The Sound Conservancy to RTB

    Interactive feature space extension for multidimensional data projection

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    Projecting multi-dimensional data to a lower-dimensional visual display is a commonly used approach for identifying and analyzing patterns in data. Many dimensionality reduction techniques exist for generating visual embeddings, but it is often hard to avoid cluttered projections when the data is large in size and noisy. For many application users who are not machine learning experts, it is difficult to control the process in order to improve the “readability” of the projection and at the same time to understand their quality. In this paper, we propose a simple interactive feature transformation approach that allows the analyst to de-clutter the visualization by gradually transforming the original feature space based on existing class knowledge. By changing a single parameter, the user can easily decide the desired trade-off between structural preservation and the visual quality during the transforming process. The proposed approach integrates semi-interactive feature transformation techniques as well as a variety of quality measures to help analysts generate uncluttered projections and understand their quality
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