128 resultados para Domestic productivity


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Enterohaemorrhagic Escherichia coli O157:H7 was first implicated in human disease in the early 1980s, with ruminants cited as the primary reservoirs. Preliminary studies indicated cattle to be the sole source of E. coli O157:H7 outbreaks in humans; however, further epidemiological studies soon demonstrated that E. coli O157:H7 was widespread in other food sources and that a number of transmission routes existed. More recently, small domestic ruminants (sheep and goats) have emerged as important sources of E. coli O157:H7 human infection, particularly with the widespread popularity of petting farms and the increased use of sheep and goat food products, including unpasteurized cheeses. Although the colonization and persistence characteristics of E. coli O157:H7 in the bovine host have been studied intensively, this is not the case for small ruminants. Despite many similarities to the bovine host, the pathobiology of E. coli O157:H7 in small domestic ruminants does appear to differ significantly from that described in cattle. This review aims to critically review the current knowledge regarding colonization and persistence of E. coli O157:H7 in small domestic ruminants, including comparisons with the bovine host where appropriate.

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The terrestrial biosphere is subjected to a wide range of natural climatic oscillations. Best known is the El Niño–southern oscillation (ENSO) that exerts globally extensive impacts on crops and natural vegetation. A 50-year time series of ENSO events has been analysed to determine those geographical areas that are reliably impacted by ENSO events. Most areas are impacted by changes in precipitation; however, the Pacific Northwest is warmed by El Niño events. Vegetation gross primary production (GPP) has been simulated for these areas, and tests well against independent satellite observations of the normalized difference vegetation index. Analyses of selected geographical areas indicate that changes in GPP often lead to significant changes in ecosystem structure and dynamics. The Pacific decadal oscillation (PDO) is another climatic oscillation that originates from the Pacific and exerts global impacts that are rather similar to ENSO events. However, the longer period of the PDO provided two phases in the time series with a cool phase from 1951 to 1976 and a warm phase from 1977 to 2002. It was notable that the cool phase of the PDO acted additively with cool ENSO phases to exacerbate drought in the earlier period for the southwest USA. By contrast in India, the cool phase of the PDO appears to reduce the negative impacts of warm ENSO events on crop production.

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This paper examines the impact of regulatory reform on productivity growth and its components for Indian banks in 1992-2009. We estimate parametric and non-parametric efficiency frontiers, followed by Divisia and Malmquist indexes of Total Factor Productivity respectively. To account for technology heterogeneity among ownership types we utilise a metafrontier approach. Results are consistent across methodologies and show sustained productivity growth, driven mainly by technological progress. Furthermore, results indicate that different ownership types react differently to changes in the operating environment. The position of foreign banks becomes increasingly dominant and their production technology becomes the best practice in the industry.

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The agricultural sector which contributes between 20-50% of gross domestic product in Africa and employs about 60% of the population is greatly affected by climate change impacts. Agricultural productivity and food prices are expected to rise due to this impact thereby worsening the food insecurity and poor nutritional health conditions in the continent. Incidentally, the capacity in the continent to adapt is very low. Addressing these challenges will therefore require a holistic and integrated adaptation framework hence this study. A total of 360 respondents selected through a multi-stage random sampling technique participated in the study that took place in Southern Nigeria from 2008-2011. Results showed that majority of respondents (84%) were aware that some climate change characteristics such as uncertainties at the onset of farming season, extreme weather events including flooding and droughts, pests, diseases, weed infestation, and land degradation have all been on the increase. The most significant effects of climate change that manifested in the area were declining soil fertility and weed infestation. Some of the adaptation strategies adopted by farmers include increased weeding, changing the timing of farm operations, and processing of crops to reduce post-harvest losses. Although majority of respondents were aware of government policies aimed at protecting the environment, most of them agreed that these policies were not being effectively implemented. A mutually inclusive framework comprising of both indigenous and modern techniques, processes, practices and technologies was then developed from the study in order to guide farmers in adapting to climate change effects/impacts.

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Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

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Climate change is a serious threat to crop productivity in regions that are already food insecure. We assessed the projected impacts of climate change on the yield of eight major crops in Africa and South Asia using a systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies. Here we show that the projected mean change in yield of all crops is − 8% by the 2050s in both regions. Across Africa, mean yield changes of − 17% (wheat), − 5% (maize), − 15% (sorghum) and − 10% (millet) and across South Asia of − 16% (maize) and − 11% (sorghum) were estimated. No mean change in yield was detected for rice. The limited number of studies identified for cassava, sugarcane and yams precluded any opportunity to conduct a meta-analysis for these crops. Variation about the projected mean yield change for all crops was smaller in studies that used an ensemble of > 3 climate (GCM) models. Conversely, complex simulation studies that used biophysical crop models showed the greatest variation in mean yield changes. Evidence of crop yield impact in Africa and South Asia is robust for wheat, maize, sorghum and millet, and either inconclusive, absent or contradictory for rice, cassava and sugarcane.

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Common approaches to the simulation of borehole heat exchangers (BHEs) assume heat transfer in circulating fluid and grout to be in a quasi-steady state and ignore fluctuations in fluid temperature due to transport of the fluid around the loop. However, in domestic ground source heat pump (GSHP) systems, the heat pump and circulating pumps switch on and off during a given hour; therefore, the effect of the thermal mass of the circulating fluid and the dynamics of fluid transport through the loop has important implications for system design. This may also be important in commercial systems that are used intermittently. This article presents transient simulation of a domestic GSHP system with a single BHE using a dynamic three-dimensional (3D) numerical BHE model. The results show that delayed response associated with the transit of fluid along the pipe loop is of some significance in moderating swings in temperature during heat pump operation. In addition, when 3D effects are considered, a lower heat transfer rate is predicted during steady operations. These effects could be important when considering heat exchanger design and system control. The results will be used to develop refined two-dimensional models.

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The purpose of the study is to seek a better understanding of the investment allocation behaviour of the real estate mutual funds by focusing on asset allocation at the country level. Analysing the country allocation of 553 real estate mutual funds domiciled in 20 countries, we attempt to trace how investment bias exists across countries and affects their country allocations. Our results evidence the existence of disproportionate country allocation to their domestic markets (domestic bias) and to each foreign market (foreign bias). We also find each bias is influenced by different sets of variables: real estate market influences for domestic bias and familiarity influences for foreign bias. This difference in factors influential for each bias in part explains the conflated relationship between the two biases.

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The type and thickness of insulation on the topside horizontal of cold pitched roofs has a significant role in controlling air movement, energy conservation and moisture transfer reduction through the ceiling to the loft (roof void) space. To investigate its importance, a numerical model using a HAM software package on a Matlab platform with a Simulink simulation tool has been developed using insitu measurements of airflows from the dwelling space through the ceiling to the loft of three houses of different configurations and loft space. Considering typical UK roof underlay (i.e. bituminous felt and a vapour permeable underlay), insitu measurements of the 3 houses were tested using a calibrated passive sampling technique. Using the measured airflows, the effect of air movement on three types of roof insulation (i.e. fibreglass, cellulose and foam) was modelled to investigate associated energy losses and moisture transport. The thickness of the insulation materials were varied but the ceiling airtightness and eaves gap size were kept constant. These instances were considered in order to visualize the effects of the changing parameters. In addition, two different roof underlays of varying resistances were considered and compared to access the influence of the underlay, if any, on energy conservation. The comparison of these insulation materials in relation to the other parameters showed that the type of insulation material and thickness, contributes significantly to energy conservation and moisture transfer reduction through the roof and hence of the building as a whole.

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In today's global economic conditions, improving the productivity of the construction industry is becoming more pressing than ever. Several factors impact the efficiency of construction operatives, but motivation is among the most important. Since low productivity is one of the significant challenges facing the construction industry in the State of Kuwait, the objective of this case study is to identify, explore, and rank the relative importance of the factors perceived to impact the motivational level of master craftsmen involved in primary construction trades. To achieve this objective, a structured questionnaire survey comprising 23 factors, which were shortlisted based on relevant previous research on motivation, the input of local industry experts, and numerous interviews with skilled operatives, was distributed to a large number of master craftsmen. Using the “Relative Importance Index” technique, the following prominent factors are identified: (1) payment delay; (2) rework; (3) lack of a financial incentive scheme; (4) the extent of change orders during execution; (5) incompetent supervisors; (6) delays in responding to Requests For Information (RFI); (7) overcrowding and operatives interface; (8) unrealistic scheduling and performance expectation; (9) shortage of materials on site; and (10) drawings quality level. The findings can be used to provide industry practitioners with guidance for focusing, acting upon, and controlling the critical factors influencing the performance of master craftsmen, hence, assist in achieving an efficient utilization of the workforce, and a reasonable level of competitiveness and cost effective operation.

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Urban domestic cat (Felis catus) populations can attain exceedingly high densities and are not limited by natural prey availability. This has generated concerns that they may negatively affect prey populations, leading to calls for management. We enlisted cat-owners to record prey returned home to estimate patterns of predation by free-roaming pets in different localities within the town of Reading, UK and questionnaire surveys were used to quantify attitudes to different possible management strategies. Prey return rates were highly variable: only 20% of cats returned ≥4 dead prey annually. Consequently, approximately 65% of owners received no prey in a given season, but this declined to 22% after eight seasons. The estimated mean predation rate was 18.3 prey cat−1 year−1 but this varied markedly both spatially and temporally: per capita predation rates declined with increasing cat density. Comparisons with estimates of the density of six common bird prey species indicated that cats killed numbers equivalent to adult density on c. 39% of occasions. Population modeling studies suggest that such predation rates could significantly reduce the size of local bird populations for common urban species. Conversely, most urban residents did not consider cat predation to be a significant problem. Collar-mounted anti-predation devices were the only management action acceptable to the majority of urban residents (65%), but were less acceptable to cat-owners because of perceived risks to their pets; only 24% of cats were fitted with such devices. Overall, cat predation did appear to be of sufficient magnitude to affect some prey populations, although further investigation of some key aspects of cat predation is warranted. Management of the predation behavior of urban cat populations in the UK is likely to be challenging and achieving this would require considerable engagement with cat owners.

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The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures.

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The different associations of Borrelia burgdorferi sensu lato spirochaetes with their natural reservoir hosts and tick vectors are slowly being unravelled. This review discusses the interactions of different genospecies of Lyme borreliosis spirochaetes and their differing tick vectors, vertebrate reservoirs and 'accidental hosts'. Particular reference is made to spirochaete-host interactions and occurrence of pathological consequences. Attention is focused on the unique prevalence of enzoonotic cycles in operation within the UK. Risk factors for acquiring Lyme borreliosis in man are discussed. (C) 2001 Lippincott Williams & Wilkins.

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A total of 1527 serum samples from pigs, goats, sheep, cattle and dogs in Greece were examined by the microscopic agglutination test and 11.8 per cent of them had antibodies against one or more Leptospira serovars at titres of 1/100 or more. The predominant serovar affecting farm animal species was Bratislava, and Copenhageni was common among dogs and the second most important serovar when all animals were considered together. Another prevalent serovar was Australis, but antibodies to Pomona were detected only in goats and cattle.