Cost function for sub-agent elements in multi-agent energy management system

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.

Biology as an agent of chemical and mineralogical change in soil

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.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

nor-Mevaldic acid surrogates as selective antifungal agent leads against Botrytis cinerea. Enantioselective preparation of 4-hydroxy-6-(1-phenylethoxy)tetrahydro-2H-pyran-2-one

Solvent-free desymmetrisation of meso-dialdehyde 1 with chiral 1-phenylethan-1-ol, led to preparation of 4-silyloxy-6-alkyloxytetrahydro-2H-pyran-2-one (+)-3a with a 96:4 d.r. Deprotected lactone (+)-19a and the related racemic lactones 16a-18a present a lactone moiety resembling the natural substrate of HMG-CoA reductase and their antifungal properties have been evaluated against the phytopathogenic fungi Botrytis cinerea and Colletotrichum gloeosporioides. These compounds were selectively active against B. cinerea, while inactive against C. gloeosporioides.