90 resultados para Domestic chicken


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The transition to a low-carbon economy urgently demands better information on the drivers of energy consumption. UK government policy has prioritized energy efficiency in the built stock as a means of carbon reduction, but the sector is historically information poor, particularly the non-domestic building stock. This paper presents the results of a pilot study that investigated whether and how property and energy consumption data might be combined for non-domestic energy analysis. These data were combined in a ‘Non-Domestic Energy Efficiency Database’ to describe the location and physical attributes of each property and its energy consumption. The aim was to support the generation of a range of energy-efficiency statistics for the industrial, commercial and institutional sectors of the non-domestic building stock, and to provide robust evidence for national energy-efficiency and carbon-reduction policy development and monitoring. The work has brought together non-domestic energy data, property data and mapping in a ‘data framework’ for the first time. The results show what is possible when these data are integrated and the associated difficulties. A data framework offers the potential to inform energy-efficiency policy formation and to support its monitoring at a level of detail not previously possible.

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Domestic gardens provide a significant component of urban green infrastructure but their relative contribution to eco-system service provision remains largely un-quantified. ‘Green infrastructure’ itself is often ill-defined, posing problems for planners to ascertain what types of green infrastructure provide greatest benefit and under what circumstances. Within this context the relative merits of gardens are unclear; however, at a time of greater urbanization where private gardens are increasingly seen as a ‘luxury’, it is important to define their role precisely. Hence, the nature of this review is to interpret existing information pertaining to gardens /gardening per se, identify where they may have a unique role to play and to highlight where further research is warranted. The review suggests that there are significant differences in both form and management of domestic gardens which radically influence the benefits. Nevertheless, gardens can play a strong role in improving the environmental impact of the domestic curtilage, e.g. by insulating houses against temperature extremes they can reduce domestic energy use. Gardens also improve localized air cooling, help mitigate flooding and provide a haven for wildlife. Less favourable aspects include contributions of gardens and gardening to greenhouse gas emissions, misuse of fertilizers and pesticides, and introduction of alien plant species. Due to the close proximity to the home and hence accessibility for many, possibly the greatest benefit of the domestic garden is on human health and well-being, but further work is required to define this clearly within the wider context of green infrastructure.

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There is currently an increased interest of Government and Industry in the UK, as well as at the European Community level and International Agencies (i.e. Department of Energy, American International Energy Agency), to improve the performance and uptake of Ground Coupled Heat Pumps (GCHP), in order to meet the 2020 renewable energy target. A sound knowledge base is required to help inform the Government Agencies and advisory bodies; detailed site studies providing reliable data for model verification have an important role to play in this. In this study we summarise the effect of heat extraction by a horizontal ground heat exchanger (installed at 1 m depth) on the soil physical environment (between 0 and 1 m depth) for a site in the south of the UK. Our results show that the slinky influences the surrounding soil by significantly decreasing soil temperatures. Furthermore, soil moisture contents were lower for the GCHP soil profile, most likely due to temperature-gradient related soil moisture migration effects and a decreased hydraulic conductivity, the latter as a result of increased viscosity (caused by the lower temperatures for the GCHP soil profile). The effects also caused considerable differences in soil thermal properties. This is the first detailed mechanistic study conducted in the UK with the aim to understand the interactions between the soil, horizontal heat exchangers and the aboveground environment. An increased understanding of these interactions will help to achieve an optimum and sustainable use of the soil heat resources in the future. The results of this study will help to calibrate and verify a simulation model that will provide UK-wide recommendations to improve future GCHP uptake and performance, while safeguarding the soil physical resources.

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There are varieties of physical and behavioral factors to determine energy demand load profile. The attainment of the optimum mix of measures and renewable energy system deployment requires a simple method suitable for using at the early design stage. A simple method of formulating load profile (SMLP) for UK domestic buildings has been presented in this paper. Domestic space heating load profile for different types of houses have been produced using thermal dynamic model which has been developed using thermal resistant network method. The daily breakdown energy demand load profile of appliance, domestic hot water and space heating can be predicted using this method. The method can produce daily load profile from individual house to urban community. It is suitable to be used at Renewable energy system strategic design stage.

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The development of an Artificial Neural Network model of UK domestic appliance energy consumption is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 households during the summer of 2010. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with backpropagation training and has a12:10:24architecture.Model outputs include appliance load profiles which can be applied to the fields of energy planning (micro renewables and smart grids), building simulation tools and energy policy.

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Government targets for CO2 reductions are being progressively tightened, the Climate Change Act set the UK target as an 80% reduction by 2050 on 1990 figures. The residential sector accounts for about 30% of emissions. This paper discusses current modelling techniques in the residential sector: principally top-down and bottom-up. Top-down models work on a macro-economic basis and can be used to consider large scale economic changes; bottom-up models are detail rich to model technological changes. Bottom-up models demonstrate what is technically possible. However, there are differences between the technical potential and what is likely given the limited economic rationality of the typical householder. This paper recommends research to better understand individuals’ behaviour. Such research needs to include actual choices, stated preferences and opinion research to allow a detailed understanding of the individual end user. This increased understanding can then be used in an agent based model (ABM). In an ABM, agents are used to model real world actors and can be given a rule set intended to emulate the actions and behaviours of real people. This can help in understanding how new technologies diffuse. In this way a degree of micro-economic realism can be added to domestic carbon modelling. Such a model should then be of use for both forward projections of CO2 and to analyse the cost effectiveness of various policy measures.

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The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

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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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A number of poultry probiotics contain bacterial spores. In this study, orally administered spores of Bacillus subtilis germinated in the gastrointestinal (GI) tracts of chicks. Furthermore, 20 h after spores were administered, vegetative cells outnumbered spores throughout the GI tract. This demonstrates that spore-based probiotics may function in this host through metabolically active mechanisms.

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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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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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A semi-quantitative cloacal-swab method was used as an indirect measure of caecal colonisation of one-day old and five-day old chicks after oral dosing with wild-type Salmonella enterica serovar Enteritidis PT4 and,genetically defined isogenic derivatives lacking the ability to elaborate flagella or fimbriae. Birds of both ages were readily and persistently colonised by all strains although there war a decline in shedding by the older birds after about 21 days. There were no significant differences in shedding of wild-type or mutants in single-dose experiments. In competition experiments, in which five-day old birds were dosed orally with wild-type and mutants together, shedding of non-motile derivatives was significantly lower than wild-type, At 35 days post infection, birds were sacrificed and direct counts of mutants and wild-type from each caecum were determined. Whilst there appeared to be poor correlation between direct counts and the indirect swab method, the overall trends shown by these methods of assessment indicated that flagella and not fimbriae were important in caecal colonisation in these models. Crown Copyright (C) 1999 Published by Elsevier Science B.V.