931 resultados para Victoria University (Great Britain)


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Beginning with v. 12, a list of the papers contained in preceding volumes is issued regularly with each volume.

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At head of title: The Victoria University of Manchester.

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Interpreting the unexplained component of the gender wage gap as indicative of discrimination, the empirical literature to date has tended to ignore the potential impact wage discrimination may have on employment. Employment effects may arise if discrimination lowers the female offered wage and the labour supply curve is upward sloping. The empirical analysis employs the British Household Panel Study and finds evidence of both wage and associated employment effects.

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Thesis (Master's)--University of Washington, 2015

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PV only generates electricity during daylight hours and primarily generates over summer. In the UK, the carbon intensity of grid electricity is higher during the daytime and over winter. This work investigates whether the grid electricity displaced by PV is high or low carbon compared to the annual mean carbon intensity using carbon factors at higher temporal resolutions (half-hourly and daily). UK policy for carbon reporting requires savings to be calculated using the annual mean carbon intensity of grid electricity. This work offers an insight into whether this technique is appropriate. Using half hourly data on the generating plant supplying the grid from November 2008 to May 2010, carbon factors for grid electricity at half-hourly and daily resolution have been derived using technology specific generation emission factors. Applying these factors to generation data from PV systems installed on schools, it is possible to assess the variation in the carbon savings from displacing grid electricity with PV generation using carbon factors with different time resolutions. The data has been analyzed for a period of 363 to 370 days and so cannot account for inter-year variations in the relationship between PV generation and carbon intensity of the electricity grid. This analysis suggests that PV displaces more carbon intensive electricity using half-hourly carbon factors than using daily factors but less compared with annual ones. A similar methodology could provide useful insights on other variable renewable and demand-side technologies and in other countries where PV performance and grid behavior are different.

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This paper re-examines whether it is more advantageous in terms of risk reduction to diversify by sector or region by comparing the performance of the ‘conventional’ regional classification of the UK with one based on modern socio-economic criteria using a much larger real estate data set than any previous study and the MAD portfolio approach. The general conclusion of this analysis is that property market sectors still dominate regions, however defined and so should be the first level of analysis when developing a portfolio diversification strategy. This is in line with previous research. When the performance of Functional groups is compared with the ‘conventional’ administrative regions the results here show that, when functionally based, groupings can in some cases provide greater risk reduction. In addition the underlying characteristics of these functional groups may be much more insightful and acceptable to real estate portfolio managers in considering the assets that a portfolio might contain.

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To investigate the occurrence of antimicrobial resistance genes of human clinical relevance in Salmonella isolated from livestock in Great Britain. Two hundred and twenty-five Salmonella enterica isolates were characterized using an antimicrobial resistance gene chip and disc diffusion assays. Plasmid profiling, conjugation experiments and identification of Salmonella genomic island 1 (SGI1) were performed for selected isolates. Approximately 43% of Salmonella harboured single or multiple antimicrobial resistance genes with pig isolates showing the highest numbers where 96% of Salmonella Typhimurium harboured one or more resistance genes. Isolates harbouring multiple resistances divided into three groups. Group 1 isolates harboured ampicillin/streptomycin/sulphonamide/tetracycline resistance and similar phenotypes. This group contained isolates from pigs, cattle and poultry that were from several serovars including Typhimurium, 4,[5],12:i:-, Derby, Ohio and Indiana. All Group 2 isolates were from pigs and were Salmonella Typhimurium. They contained a non-sul-type class 1 integron and up to 13 transferrable resistances. All Group 3 isolates harboured a class 1 integron and were isolated from all animal species included in the study. Most isolates were Salmonella Typhimurium and harboured SGI1. Salmonella isolated from livestock was shown to harbour antimicrobial resistance genes although no or little resistance to third-generation cephalosporins or ciprofloxacin, respectively, was detected. The preponderance in pigs of multidrug-resistant Salmonella Typhimurium makes it important to introduce control measures such as improved biosecurity to ensure that they do not pass through the food chain and limit human therapeutic options.

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The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

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Mode of access: Internet.

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Mode of access: Internet.