Modelling the economics of farm-based anaerobic digestion in a UK whole-farm context

Anaerobic digestion (AD) technologies convert organic wastes and crops into methane-rich biogas for heating, electricity generation and vehicle fuel. Farm-based AD has proliferated in some EU countries, driven by favourable policies promoting sustainable energy generation and GHG mitigation. Despite increased state support there are still few AD plants on UK farms leading to a lack of normative data on viability of AD in the whole-farm context. Farmers and lenders are therefore reluctant to fund AD projects and policy makers are hampered in their attempts to design policies that adequately support the industry. Existing AD studies and modelling tools do not adequately capture the farm context within which AD interacts. This paper demonstrates a whole-farm, optimisation modelling approach to assess the viability of AD in a more holistic way, accounting for such issues as: AD scale, synergies and conflicts with other farm enterprises, choice of feedstocks, digestate use and impact on farm Net Margin. This modelling approach demonstrates, for example, that: AD is complementary to dairy enterprises, but competes with arable enterprises for farm resources. Reduced nutrient purchases significantly improve Net Margin on arable farms, but AD scale is constrained by the capacity of farmland to absorb nutrients in AD digestate.

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations.

The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

A logic-based agent that plans for extended reachability goals

Planning to reach a goal is an essential capability for rational agents. In general, a goal specifies a condition to be achieved at the end of the plan execution. In this article, we introduce nondeterministic planning for extended reachability goals (i.e., goals that also specify a condition to be preserved during the plan execution). We show that, when this kind of goal is considered, the temporal logic CTL turns out to be inadequate to formalize plan synthesis and plan validation algorithms. This is mainly due to the fact that the CTL`s semantics cannot discern among the various actions that produce state transitions. To overcome this limitation, we propose a new temporal logic called alpha-CTL. Then, based on this new logic, we implement a planner capable of synthesizing reliable plans for extended reachability goals, as a side effect of model checking.

Knowledge based crime scenario modelling

A crucial concern in the evaluation of evidence related to a major crime is the formulation of sufficient alternative plausible scenarios that can explain the available evidence. However, software aimed at assisting human crime investigators by automatically constructing crime scenarios from evidence is difficult to develop because of the almost infinite variation of plausible crime scenarios. This paper introduces a novel knowledge driven methodology for crime scenario construction and it presents a decision support system based on it. The approach works by storing the component events of the scenarios instead of entire scenarios and by providing an algorithm that can instantiate and compose these component events into useful scenarios. The scenario composition approach is highly adaptable to unanticipated cases because it allows component events to match the case under investigation in many different ways. Given a description of the available evidence, it generates a network of plausible scenarios that can then be analysed to devise effective evidence collection strategies. The applicability of the ideas presented here are demonstrated by means of a realistic example and prototype decision support software.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity

Oil spills cause great damage to coastal habitats, especially when rapid and suitable response measures are not taken. Establishing high priority areas is fundamental for the operation of response teams. Under this context and considering the need for keeping all geographical information up-to-date for emergencial use, the present study proposes employing a decision tree coupled with a knowledge-based approach using GIS to assign oil sensitivity indices to Brazilian coastal habitats. The modelled system works based on rules set by the official standards of Brazilian Federal Environment Organ. We tested it on one of the littoral regions of Brazil where transportation of petroleum is most intense: the coast of the municipalities of Sao Sebastiao and Caraguatatuba in the northern littoral of São Paulo state, Brazil. The system automatically ranked the littoral sensitivity index of the study area habitats according to geographical conditions during summer and winter; since index ranks of some habitats varied between these seasons because of sediment alterations. The obtained results illustrate the great potential of the proposed system in generating ESI maps and in aiding response teams during emergency operations. (C) 2009 Elsevier Ltd. All rights reserved.

Structural modelling of Eu3+-based siloxane-poly( oxyethylene) nanohybrids

The modelling of the local structure of sol-gel derived Eu3+-based organic/inorganic hybrids is reported, based on Small-Angle X-ray Scattering (SAXS), photoluminescence and mid-infrared spectroscopy. The hybrid matrix of these organically modified silicates, classed as di-ureasils and termed U(2000) and U(600), is formed by poly( oxyethylene) (POE) chains of variable length grafted to siloxane domains by means of urea cross-linkages. Europium triflate, Eu(CF3SO3)(3), was incorporated in the two di-ureasil matrices with compositions 400 greater than or equal ton greater than or equal to 10, n is the molar ratio of ether oxygens per Eu3+. The SAXS data for undoped hybrids (n=infinity) show the presence of a well-defined peak attributed to the existence of a liquid-like spatial correlation of siloxane rich domains embedded in the polymer matrix and located at the ends of the organic segments. The obtained siloxane particle gyration radius Rg(1) is around 5 Angstrom (error within 10%), whereas the interparticle distance d is 25 +/-2 Angstrom and 40 +/-2 Angstrom, for U(600) and U(2000), respectively. For the Eu3+-based nanocomposites the formation of a two-level hierarchical local structure is discerned. The primary level is constituted by strongly spatially correlated siloxane particles of gyration radius Rg(1) (4-6 and 3-8 Angstrom, errors within 5%, for U(600())n Eu(CF3SO3)(3), 200 greater than or equal ton greater than or equal to 40, and U(2000)(n)Eu(CF3SO3)(3), 400 greater than or equal ton greater than or equal to 40, respectively) forming large clusters of gyration radius Rg(2) (approximate to 75 +/- 10 Angstrom). The local coordination of Eu3+ in both di-ureasil series is described combining the SAXS, photoluminescence and mid-infrared results. In the di-ureasils containing long polymer chains, U(2000)(n)Eu(CF3SO3)(3), the cations interact exclusively with the carbonyl oxygens atoms of the urea bridges at the siloxane-POE interface. In the hybrids containing shorter chains, U(600)(n)Eu(CF3SO3)(3) with n ranging from 200 to 60, the Eu3+ ions interact solely with the ether-type oxygens of the polymer chains. Nevertheless, in this latter family of hybrids a distinct Eu3+ local site environment involving the urea cross-linkages is detected when the europium content is increased up to n=40.