62 resultados para disinfectant agent


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Increased penetration of generation and decentralised control are considered to be feasible and effective solution for reducing cost and emissions and hence efficiency associated with power generation and distribution. Distributed generation in combination with the multi-agent technology are perfect candidates for this solution. Pro-active and autonomous nature of multi-agent systems can provide an effective platform for decentralised control whilst improving reliability and flexibility of the grid.

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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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Objectives: The aims of this study were to determine whether strains of Salmonella enterica serovar Typhimurium which had acquired low-level multiple antibiotic resistance (MAR) through repeated exposure to farm disinfectants were able to colonize and transmit between chicks as easily as the parent strain and, if such strains were less susceptible to fluoroquinolones, would high-level resistance be selected after fluoroquinolone treatment. Methods: Two mutants were compared with the isogenic parent. In the first experiment, day-old chicks were co-infected with both the parent and a mutant to determine their relative fitness. In the second experiment, parent and mutant strains (in separate groups of chicks) were assessed for their ability to transmit from infected (contact) to non-infected (naive) birds and with respect to their susceptibility to fluoroquinolone treatment. Birds were regularly monitored for the presence of Salmonella in caecal contents. Replica plating was used to monitor for the selection of antibiotic-resistant strains. Results: The parent strain was shown to be significantly fitter than the two mutants and was more rapidly disseminated to naive birds. Antibiotic treatment did not preferentially select for the two mutants or for resistant strains. Conclusions: The disinfectant-exposed strains, although MAR, were less fit, less able to disseminate than the parent strain and were not preferentially selected by therapeutic antibiotic treatment. As such, these strains are unlikely to present a greater problem than other salmonellae in chickens.

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This study examines differences in net selling price for residential real estate across male and female agents. A sample of 2,020 home sales transactions from Fulton County, Georgia are analyzed in a two-stage least squares, geospatial autoregressive corrected, semi-log hedonic model to test for gender and gender selection effects. Although agent gender seems to play a role in naïve models, its role becomes inconclusive as variables controlling for possible price and time on market expectations of the buyers and sellers are introduced to the models. Clear differences in real estate sales prices, time on market, and agent incomes across genders are unlikely due to differences in negotiation performance between genders or the mix of genders in a two-agent negotiation. The evidence suggests an interesting alternative to agent performance: that buyers and sellers with different reservation price and time on market expectations, such as those selling foreclosure homes, tend to select agents along gender lines.

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Aims: To test the efficacy of Lactobacillus johnsonii FI9785 in reducing the colonization and shedding of Salmonella enterica serotype Enteritidis, Escherichia coli O78:K80 and Clostridium perfringens in poultry. Methods and Results: Specific pathogen-free chicks (1 day old) were dosed with a single oral inoculum of 1 x 10(9) CFU. Lactobacillus johnsonii FI9785 and 24 h later were challenged in separate experiments with S. Enteritidis (S1400, nal(r)) and E. coli O78:K80 (EC34195, nal(r)). There were no significant effects against S. Enteritidis whereas colonization of the small intestine by E. coli O78:K80 was reduced significantly. Both S. Enteritidis and E. coli colonized the caeca and colon to levels equivalent to control birds and there was no reduction in shedding as assessed by a semi-quantitative cloacal swabbing technique. Specific pathogen-free chicks (20 day old) were dosed with a single oral inoculum of 1 x 10(9) CFU L. johnsonii FI9785 and 24 h later were challenged with C. perfringens. A single oral dose of L. johnsonii FI9785 was sufficient to suppress all aspects of colonization and persistence of C. perfringens. Conclusions: Lactobacillus johnsonii FI9785 may be given to poultry for use as a competitive exclusion agent to control C. perfringens. Significance and Impact of the Study: Lactobacillus johnsonii FI9785 may be a valuable tool to control the endemic disease of necrotic enteritis, thereby reducing economic losses associated with reduced use of antimicrobials in the poultry industry.

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Objective: To determine the effect of growth of five strains of Salmonella enterica and their isogenic multiply antibiotic-resistant (MAR) derivatives with a phenolic farm disinfectant or triclosan (biocides) upon the frequency of mutation to resistance to antibiotics or cyclohexane. Methods: Strains were grown in broth with or without the biocides and then spread on to agar containing ampicillin, ciprofloxacin or tetracycline each at 4x MIC or agar overlaid with cyclohexane. Incubation was for 24 and 48 h and the frequency of mutation to resistance was calculated for strains with and without prior growth with the biocides. MICs were determined and the presence of mutations in the acrR and marR regions was determined by sequencing and the presence of mutations in gyrA by light-cycler analysis, for a selection of the mutants that arose. Results: The mean frequency of mutation to antibiotic or cyclohexane resistance was increased similar to10- to 100-fold by prior growth with the phenolic disinfectant or triclosan. The increases were statistically significant for all antibiotics and cyclohexane following exposure to the phenolic disinfectant (P less than or equal to 0.013), and for ampicillin and cyclohexane following exposure to triclosan (P less than or equal to 0.009). Mutants inhibited by >1 mg/L ciprofloxacin arose only from strains that were MAR. Reduced susceptibility to ciprofloxacin (at 4x MIC for parent strains) alone was associated with mutations in gyrA. MAR mutants did not contain mutations in the acrR or marR region. Conclusions: These data renew fears that the use of biocides may lead to an increased selective pressure towards antibiotic resistance.

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Summary 1. Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. 2. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. 3. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. 4. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. 5. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. Keywords: bioenergetics; energy budget; individual-based models; population dynamics.

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Wireless technology based pervasive healthcare has been proposed in many applications such as disease management and accident prevention for cost saving and promoting citizen’s wellbeing. However, the emphasis so far is on the artefacts with limited attentions to guiding the development of an effective and efficient solution for pervasive healthcare. Therefore, this paper aims to propose a framework of multi-agent systems design for pervasive healthcare by adopting the concept of pervasive informatics and using the methods of organisational semiotics. The proposed multi-agent system for pervasive healthcare utilises sensory information to support healthcare professionals for providing appropriate care. The key contributions contain theoretical aspect and practical aspect. In theory, this paper articulates the information interactions between the pervasive healthcare environment and stakeholders by using the methods of organisational semiotics; in practice, the proposed framework improves the healthcare quality by providing appropriate medical attentions when and as needed. In this paper, both systems and functional architecture of the multi-agent system are elaborated with the use of wireless technologies such as RFID and wireless sensor networks. The future study will focus on the implementation of the proposed framework.

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This study puts forward a method to model and simulate the complex system of hospital on the basis of multi-agent technology. The formation of the agents of hospitals with intelligent and coordinative characteristics was designed, the message object was defined, and the model operating mechanism of autonomous activities and coordination mechanism was also designed. In addition, the Ontology library and Norm library etc. were introduced using semiotic method and theory, to enlarge the method of system modelling. Swarm was used to develop the multi-agent based simulation system, which is favorable for making guidelines for hospital's improving it's organization and management, optimizing the working procedure, improving the quality of medical care as well as reducing medical charge costs.

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Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.

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This paper aims to examine the perception of key actors regarding the costs and benefits that result from adopting International Financial Reporting Standards (IFRS) in Ukraine. Authors showed that IFRS implementation impacts on internal reporting quality, the relationship with customers, creditors and shareholders, the access to international markets and external financing. They also indicated that financial managers have serious concerns about implementation costs related to the introduction of IFRS. These costs relate to training, instruction on IFRS adoption and translation of current IFRS, changes in software systems, double purpose accounting and deadlines for IFRS adoption and consulting services.

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The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

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This paper introduces a new agent-based model, which incorporates the actions of individual homeowners in a long-term domestic stock model, and details how it was applied in energy policy analysis. The results indicate that current policies are likely to fall significantly short of the 80% target and suggest that current subsidy levels need re-examining. In the model, current subsidy levels appear to offer too much support to some technologies, which in turn leads to the suppression of other technologies that have a greater energy saving potential. The model can be used by policy makers to develop further scenarios to find alternative, more effective, sets of policy measures. The model is currently limited to the owner-occupied stock in England, although it can be expanded, subject to the availability of data.

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Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

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Earthworms have a significant impact on the functioning of soils and the processes that occur within them. Here we review our work on the impact of earthworms on soil mineralogy and chemistry, in particular focusing on the contribution of earthworms to mineral weathering and calcium carbonate in soils and the impact that earthworms have on metal mobility at contaminated sites.