Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

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.

Community-based climate change adaptation strategies for integrated prawn-fish-rice farming in Bangladesh to promote social-ecological resilience

Farming freshwater prawns with fish in rice fields is widespread in coastal regions of southwest Bangladesh because of favourable resources and ecological conditions. This article provides an overview of an ecosystem-based approach to integrated prawn-fish-rice farming in southwest Bangladesh. The practice of prawn and fish farming in rice fields is a form of integrated aquaculture-agriculture, which provides a wide range of social, economic and environmental benefits. Integrated prawn-fish-rice farming plays an important role in the economy of Bangladesh, earning foreign exchange and increasing food production. However, this unique farming system in coastal Bangladesh is particularly vulnerable to climatechange. We suggest that community-based adaptation strategies must be developed to cope with the challenges. We propose that integrated prawn-fish-rice farming could be relocated from the coastal region to less vulnerable upland areas, but caution that this will require appropriate adaptation strategies and an enabling institutional environment.

Artefact-oriented business process modelling: an ontological dependency approach

Business process modelling can help an organisation better understand and improve its business processes. Most business process modelling methods adopt a task- or activity-based approach to identifying business processes. Within our work, we use activity theory to categorise elements within organisations as being either human beings, activities or artefacts. Due to the direct relationship between these three elements, an artefact-oriented approach to organisation analysis emerges. Organisational semiotics highlights the ontological dependency between affordances within an organisation. We analyse the ontological dependency between organisational elements, and therefore produce the ontology chart for artefact-oriented business process modelling in order to clarify the relationship between the elements of an organisation. Furthermore, we adopt the techniques from semantic analysis and norm analysis, of organisational semiotics, to develop the artefact-oriented method for business process modelling. The proposed method provides a novel perspective for identifying and analysing business processes, as well as agents and artefacts, as the artefact-oriented perspective demonstrates the fundamental flow of an organisation. The modelling results enable an organisation to understand and model its processes from an artefact perspective, viewing an organisation as a network of artefacts. The information and practice captured and stored in artefact can also be shared and reused between organisations that produce similar artefacts.

A niche-based framework to assess current monitoring of European forest birds and guide indicator species' selection

Concern that European forest biodiversity is depleted and declining has provoked widespread efforts to improve management practices. To gauge the success of these actions, appropriate monitoring of forest ecosystems is paramount. Multi-species indicators are frequently used to assess the state of biodiversity and its response to implemented management, but generally applicable and objective methodologies for species' selection are lacking. Here we use a niche-based approach, underpinned by coarse quantification of species' resource use, to objectively select species for inclusion in a pan-European forest bird indicator. We identify both the minimum number of species required to deliver full resource coverage and the most sensitive species' combination, and explore the trade-off between two key characteristics, sensitivity and redundancy, associated with indicators comprising different numbers of species. We compare our indicator to an existing forest bird indicator selected on the basis of expert opinion and show it is more representative of the wider community. We also present alternative indicators for regional and forest type specific monitoring and show that species' choice can have a significant impact on the indicator and consequent projections about the state of the biodiversity it represents. Furthermore, by comparing indicator sets drawn from currently monitored species and the full forest bird community, we identify gaps in the coverage of the current monitoring scheme. We believe that adopting this niche-based framework for species' selection supports the objective development of multi-species indicators and that it has good potential to be extended to a range of habitats and taxa.

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.

Earthworm distribution and abundance predicted by a process-based model

Earthworms are significant ecosystem engineers and are an important component of the diet of many vertebrates and invertebrates, so the ability to predict their distribution and abundance would have wide application in ecology, conservation and land management. Earthworm viability is known to be affected by the availability and quality of food resources, soil water conditions and temperature, but has not yet been modelled mechanistically to link effects on individuals to field population responses. Here we present a novel model capable of predicting the effects of land management and environmental conditions on the distribution and abundance of Aporrectodea caliginosa, the dominant earthworm species in agroecosystems. Our process-based approach uses individual based modelling (IBM), in which each individual has its own energy budget. Individual earthworm energy budgets follow established principles of physiological ecology and are parameterised for A. caliginosa from experimental measurements under optimal conditions. Under suboptimal conditions (e.g. food limitation, low soil temperatures and water contents) reproduction is prioritised over growth. Good model agreement to independent laboratory data on individual cocoon production and growth of body mass, under variable feeding and temperature conditions support our representation of A. caliginosa physiology through energy budgets. Our mechanistic model is able to accurately predict A. caliginosa distribution and abundance in spatially heterogeneous soil profiles representative of field study conditions. Essential here is the explicit modelling of earthworm behaviour in the soil profile. Local earthworm movement responds to a trade-off between food availability and soil water conditions, and this determines the spatiotemporal distribution of the population in the soil profile. Importantly, multiple environmental variables can be manipulated simultaneously in the model to explore earthworm population exposure and effects to combinations of stressors. Potential applications include prediction of the population-level effects of pesticides and changes in soil management e.g. conservation tillage and climate change.

Functional identity and diversity of animals predict ecosystem functioning better than species-based indices

Drastic biodiversity declines have raised concerns about the deterioration of ecosystem functions and have motivated much recent research on the relationship between species diversity and ecosystem functioning. A functional trait framework has been proposed to improve the mechanistic understanding of this relationship, but this has rarely been tested for organisms other than plants. We analysed eight datasets, including five animal groups, to examine how well a trait-based approach, compared with a more traditional taxonomic approach, predicts seven ecosystem functions below- and above-ground. Trait-based indices consistently provided greater explanatory power than species richness or abundance. The frequency distributions of single or multiple traits in the community were the best predictors of ecosystem functioning. This implies that the ecosystem functions we investigated were underpinned by the combination of trait identities (i.e. single-trait indices) and trait complementarity (i.e. multi-trait indices) in the communities. Our study provides new insights into the general mechanisms that link biodiversity to ecosystem functioning in natural animal communities and suggests that the observed responses were due to the identity and dominance patterns of the trait composition rather than the number or abundance of species per se.

Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TR alpha and TR beta. Several pharmacological effects mediated by TR beta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TR beta activation may elicit these effects while maintaining an acceptable safety profile, To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

Use Multilevel Graph Partitioning Scheme to solve traveling salesman problem

The traveling salesman problem is although looking very simple problem but it is an important combinatorial problem. In this thesis I have tried to find the shortest distance tour in which each city is visited exactly one time and return to the starting city. I have tried to solve traveling salesman problem using multilevel graph partitioning approach.Although traveling salesman problem itself very difficult as this problem is belong to the NP-Complete problems but I have tried my best to solve this problem using multilevel graph partitioning it also belong to the NP-Complete problems. I have solved this thesis by using the k-mean partitioning algorithm which divides the problem into multiple partitions and solving each partition separately and its solution is used to improve the overall tour by applying Lin Kernighan algorithm on it. Through all this I got optimal solution which proofs that solving traveling salesman problem through graph partition scheme is good for this NP-Problem and through this we can solved this intractable problem within few minutes.Keywords: Graph Partitioning Scheme, Traveling Salesman Problem.

Modeling and illustrating requirement prioritization in public e-service development from a value-based perspective

A major problem in e-service development is the prioritization of the requirements of different stakeholders. The main stakeholders are governments and their citizens, all of whom have different and sometimes conflicting requirements. In this paper, the prioritization problem is addressed by combining a value-based approach with an illustration technique. This paper examines the following research question: How can multiple stakeholder requirements be illustrated from a value-based perspective in order to be prioritizable? We used an e-service development case taken from a Swedish municipality to elaborate on our approach. Our contributions are: 1) a model of the relevant domains for requirement prioritization for government, citizens, technology, finances and laws and regulations; and 2) a requirement fulfillment analysis tool (RFA) that consists of a requirement-goal-value matrix (RGV), and a calculation and illustration module (CIM). The model reduces cognitive load, helps developers to focus on value fulfillment in e-service development and supports them in the formulation of requirements. It also offers an input to public policy makers, should they aim to target values in the design of e-services.

Personalised Grid Service Discovery

The authors take a broad view that ultimately Grid- or Web-services must be located via personalised, semantic-rich discovery processes. They argue that such processes must rely on the storage of arbitrary metadata about services that originates from both service providers and service users. Examples of such metadata are reliability metrics, quality of service data, or semantic service description markup. This paper presents UDDI-MT, an extension to the standard UDDI service directory approach that supports the storage of such metadata via a tunnelling technique that ties the metadata store to the original UDDI directory. They also discuss the use of a rich, graph-based RDF query language for syntactic queries on this data. Finally, they analyse the performance of each of these contributions in our implementation.

Personalised Grid Service Discovery

We take a broad view that ultimately Grid- or Web-services must be located via personalised, semantic-rich discovery processes. We argue that such processes must rely on the storage of arbitrary metadata about services that originates from both service providers and service users. Examples of such metadata are reliability metrics, quality of service data, or semantic service description markup. This paper presents UDDI-MT, an extension to the standard UDDI service directory approach that supports the storage of such metadata via a tunnelling technique that ties the metadata store to the original UDDI directory. We also discuss the use of a rich, graph-based RDF query language for syntactic queries on this data. Finally, we analyse the performance of each of these contributions in our implementation.

Improved Fault Location on Distribution Feeders Based on Matching During-Fault Voltage Sags

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Anchor Areas to Improve Conservation and Increase Connectivity within the Brazilian "Mesopotamia of Biodiversity"

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Measurement of Spin Correlation in t(t)over-bar Production Using a Matrix Element Approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)