903 resultados para Comparative historical analysis


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We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

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This paper uses the large-scale Cranet data to explore the extent of non-standard working time (NSWT) across Europe and to highlight the contrasts and similarities between two different varieties of capitalism (coordinated market economies and liberal market economies). We explore variations in the extent of different forms of NSWT (overtime, shift working and weekend working) within these two different forms of capitalism, controlling for firm size, sector and the extent of employee voice. Overall, there was no strong link between the variety of capitalism and the use of overtime and weekend working though shift working showed a clear distinction between the two varieties of capitalism. Usage of NSWT in some service sectors was particularly high under both forms of capitalism and service sector activities had a particularly marked influence on the use of overtime in liberal market economies. Surprisingly, strong employee voice was associated with greater use of NSWT.

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To fully appreciate the environmental impact of a workplace the transport-related carbon dioxide (CO2) emissions resulting from its location should be considered in addition to the emissions that result from the occupation of the building itself. Since the first one was built in the early 1980s, business parks have become a significant workplace location for service-sector workers; a sector of the economy that grew rapidly at that time as the UK manufacturing output declined and the employment base shifted to retail services and de-regulated financial services. This paper examines the transport-related CO2 emissions associated with these workplace locations in comparison to town and city centre locations. Using 2001 Census Special Workplace Statistics which record people’s residence, usual workplace and mode of transport between them, distance travelled and mode of travel were calculated for a sample of city centre and out-of-town office locations. The results reveal the extent of the difference between transport-related CO2 emitted by commuters to out-of-town and city centre locations. The implications that these findings have for monitoring the environmental performance of workplaces are discussed.

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Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

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The UK Department for Environment, Food and Rural Affairs (Defra) identified practices to reduce the risk of animal disease outbreaks. We report on the response of sheep and pig farmers in England to promotion of these practices. A conceptual framework was established from research on factors influencing adoption of animal health practices, linking knowledge, attitudes, social influences and perceived constraints to the implementation of specific practices. Qualitative data were collected from nine sheep and six pig enterprises in 2011. Thematic analysis explored attitudes and responses to the proposed practices, and factors influencing the likelihood of implementation. Most feel they are doing all they can reasonably do to minimise disease risk and that practices not being implemented are either not relevant or ineffective. There is little awareness and concern about risk from unseen threats. Pig farmers place more emphasis than sheep farmers on controlling wildlife, staff and visitor management and staff training. The main factors that influence livestock farmers’ decision on whether or not to implement a specific disease risk measure are: attitudes to, and perceptions of, disease risk; attitudes towards the specific measure and its efficacy; characteristics of the enterprise which they perceive as making a measure impractical; previous experience of a disease or of the measure; and the credibility of information and advice. Great importance is placed on access to authoritative information with most seeing vets as the prime source to interpret generic advice from national bodies in the local context. Uptake of disease risk measures could be increased by: improved risk communication through the farming press and vets to encourage farmers to recognise hidden threats; dissemination of credible early warning information to sharpen farmers’ assessment of risk; and targeted information through training events, farming press, vets and other advisers, and farmer groups, tailored to the different categories of livestock farmer.

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In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

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Objective: To investigate the sociodemographic determinants of diet quality of the elderly in four EU countries. Design: Cross-sectional study. For each country, a regression was performed of a multidimensional index of dietary quality v. sociodemographic variables. Setting In Finland, Finnish Household Budget Survey (1998 and 2006); in Sweden, SNAC-K (2001–2004); in the UK, Expenditure & Food Survey (2006–07); in Italy, Multi-purpose Survey of Daily Life (2009). Subjects: One- and two-person households of over-50s (Finland, n 2994; UK, n 4749); over-50 s living alone or in two-person households (Italy, n 7564); over-60 s (Sweden, n 2023). Results: Diet quality among the EU elderly is both low on average and heterogeneous across individuals. The regression models explained a small but significant part of the observed heterogeneity in diet quality. Resource availability was associated with diet quality either negatively (Finland and UK) or in a non-linear or non-statistically significant manner (Italy and Sweden), as was the preference for food parameter. Education, not living alone and female gender were characteristics positively associated with diet quality with consistency across the four countries, unlike socio-professional status, age and seasonality. Regional differences within countries persisted even after controlling for the other sociodemographic variables. Conclusions: Poor dietary choices among the EU elderly were not caused by insufficient resources and informational measures could be successful in promoting healthy eating for healthy ageing. On the other hand, food habits appeared largely set in the latter part of life, with age and retirement having little influence on the healthiness of dietary choices.

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The putative virulence and antimicrobial resistance gene contents of extended spectrum β-lactamase (ESBL)-positive E. coli (n=629) isolated between 2005 and 2009 from humans, animals and animal food products in Germany, The Netherlands and the UK were compared using a microarray approach to test the suitability of this approach with regard to determining their similarities. A selection of isolates (n=313) were also analysed by multilocus sequence typing (MLST). Isolates harbouring blaCTX-M-group-1 dominated (66%, n=418) and originated from both animals and cases of human infections in all three countries; 23% (n=144) of all isolates contained both blaCTX-M-group-1 and blaOXA-1-like genes, predominantly from humans (n=127) and UK cattle (n=15). The antimicrobial resistance and virulence gene profiles of this collection of isolates were highly diverse. A substantial number of human isolates (32%, n=87) did not share more than 40% similarity (based on the Jaccard coefficient) with animal isolates. A further 43% of human isolates from the three countries (n=117) were at least 40% similar to each other and to five isolates from UK cattle and one each from Dutch chicken meat and a German dog; the members of this group usually harboured genes such as mph(A), mrx, aac(6’)-Ib, catB3, blaOXA-1-like and blaCTX-M-group-1. forty-four per cent of the MLST-typed isolates in this group belonged to ST131 (n=18) and 22% to ST405 (n=9), all from humans. Among animal isolates subjected to MLST (n=258), only 1.2% (n=3) were more than 70% similar to human isolates in gene profiles and shared the same MLST clonal complex with the corresponding human isolates. The results suggest that minimising human-to-human transmission is essential to control the spread of ESBL-positive E. coli in humans.

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We compare and contrast the accuracy and uncertainty in forecasts of rents with those for a variety of macroeconomic series. The results show that in general forecasters tend to be marginally more accurate in the case of macro-economic series than with rents. In common across all of the series, forecasts tend to be smoothed with forecasters under-estimating performance during economic booms, and vice-versa in recessions We find that property forecasts are affected by economic uncertainty, as measured by disagreement across the macro-forecasters. Increased uncertainty leads to increased dispersion in the rental forecasts and a reduction in forecast accuracy.

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The human gut is a complex ecosystem occupied by a diverse microbial community. Modulation of this microbiota impacts health and disease. The definitive way to investigate the impact of dietary intervention on the gut microbiota is a human trial. However, human trials are expensive and can be difficult to control; thus, initial screening is desirable. Utilization of a range of in vitro and in vivo models means that useful information can be gathered prior to the necessity for human intervention. This review discusses the benefits and limitations of these approaches.