941 resultados para Job demand-resources model


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Development research has responded to a number of charges over the past few decades. For example, when traditional research was accused of being 'top-down', the response was participatory research, linking the 'receptors' to the generators of research. As participatory processes were recognised as producing limited outcomes, the demand-led agenda was born. In response to the alleged failure of research to deliver its products, the 'joined-up' model, which links research with the private sector, has become popular. However, using examples from animal-health research, this article demonstrates that all the aforementioned approaches are seriously limited in their attempts to generate outputs to address the multi-faceted problems facing the poor. The article outlines a new approach to research: the Mosaic Model. By combining different knowledge forms, and focusing on existing gaps, the model aims to bridge basic and applied findings to enhance the efficiency and value of research, past, present, and future.

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Restocking is a favoured option in supporting livelihoods after a disaster. With the depletion of local livestock populations, the introduction of new species and breeds will clearly affect biodiversity. Nevertheless, the impact of restocking on Animal Genetic Resources has been largely ignored. The aim of this paper, therefore, is to examine the consequences of restocking on biodiversity via a simple model. Utilising a hypothetical project based on cattle, the model demonstrates that more than one-third of the population was related to the original restocked animals after three generations. Under conditions of random breed selection, the figure declined to 20 per cent. The tool was then applied to a donor-led restocking project implemented in Bosnia-Herzegovina. By restocking primarily with Simmental cattle, the model demonstrated that the implementation of a single restocking project is likely to have accelerated the decline of the indigenous Busa breed by a further nine per cent. Thus, greater awareness of the long-term implications of restocking on biodiversity is required.

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Restocking is a favoured option in supporting livelihoods after a disaster. With the depletion of local livestock populations, the introduction of new species and breeds will clearly affect biodiversity. Nevertheless, the impact of restocking on Animal Genetic Resources has been largely ignored. The aim of this paper, therefore, is to examine the consequences of restocking on biodiversity via a simple model. Utilising a hypothetical project based on cattle, the model demonstrates that more than one-third of the population was related to the original restocked animals after three generations. Under conditions of random breed selection, the figure declined to 20 per cent. The tool was then applied to a donor-led restocking project implemented in Bosnia-Herzegovina. By restocking primarily with Simmental cattle, the model demonstrated that the implementation of a single restocking project is likely to have accelerated the decline of the indigenous Buşa breed by a further nine per cent. Thus, greater awareness of the long-term implications of restocking on biodiversity is required.

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A two-sector Ramsey-type model of growth is developed to investigate the relationship between agricultural productivity and economy-wide growth. The framework takes into account the peculiarities of agriculture both in production ( reliance on a fixed natural resource base) and in consumption (life-sustaining role and low income elasticity of food demand). The transitional dynamics of the model establish that when preferences respect Engel's law, the level and growth rate of agricultural productivity influence the speed of capital accumulation. A calibration exercise shows that a small difference in agricultural productivity has drastic implications for the rate and pattern of growth of the economy. Hence, low agricultural productivity can form a bottleneck limiting growth, because high food prices result in a low saving rate.

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This paper provides a generalisation of the structural time series version of the Almost Ideal Demand System (AIDS) that allows for time-varying coefficients (TVC/AIDS) in the presence of cross-equation constraints. An empirical appraisal of the TVC/AIDS is made using a dynamic AIDS with trending intercept as the baseline model with a data set from the Italian Household Budget Survey (1986-2001). The assessment is based on four criteria: adherence to theoretical constraints, statistical diagnostics on residuals, forecasting performance and economic meaningfulness. No clear evidence is found for superior performance of the TVC/AIDS, apart from improved short-term forecasts.

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Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

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1. The habitat components determining the structure of bee communities are well known when considering foraging resources; however, there is little data with respect to the role of nesting resources. 2. As a model system this study uses 21 diverse bee communities in a Mediterranean landscape comprising a variety of habitats regenerating after fire. The findings clearly demonstrate that a variety of nesting substrates and nest building materials have key roles in organising the composition of bee communities. 3. The availability of bare ground and potential nesting cavities were the two primary factors influencing the structure of the entire bee community, the composition of guilds, and also the relative abundance of the dominant species. Other nesting resources shown to be important include availability of steep and sloping ground, abundance of plant species providing pithy stems, and the occurrence of pre-existing burrows. 4. Nesting resource availability and guild structure varied markedly across habitats in different stages of post-fire regeneration; however, in all cases, nest sites and nesting resources were important determinants of bee community structure.

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This paper presents a new method for the inclusion of nonlinear demand and supply relationships within a linear programming model. An existing method for this purpose is described first and its shortcomings are pointed out before showing how the new approach overcomes those difficulties and how it provides a more accurate and 'smooth' (rather than a kinked) approximation of the nonlinear functions as well as dealing with equilibrium under perfect competition instead of handling just the monopolistic situation. The workings of the proposed method are illustrated by extending a previously available sectoral model for the UK agriculture.

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The presumption that the synthesis of 'defence' compounds in plants must incur some 'trade-off' or penalty in terms of annual crop yields has been used to explain observed inverse correlations between resistance to herbivores and rates of growth or photosynthesis. An analysis of the cost of making secondary compounds suggests that this accounts for only a small part of the overall carbon budget of annual crop plants. Even the highest reported amounts of secondary metabolites found in different crop species (flavonoids, allylisothiocyanates, hydroxamic acids, 2-tridecanone) represent a carbon demand that can be satisfied by less than an hour's photosynthesis. Similar considerations apply to secondary compounds containing nitrogen or sulphur, which are unlikely to represent a major investment compared to the cost of making proteins, the major demand for these elements. Decreases in growth and photosynthesis in response to stress are more likely the result of programmed down-regulation. Observed correlations between yield and low contents of unpalatable or toxic compounds may be the result of parallel selection during the refinement of crop species by humans.

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In this paper, we list some new orthogonal main effects plans for three-level designs for 4, 5 and 6 factors in IS runs and compare them with designs obtained from the existing L-18 orthogonal array. We show that these new designs have better projection properties and can provide better parameter estimates for a range of possible models. Additionally, we study designs in other smaller run-sizes when there are insufficient resources to perform an 18-run experiment. Plans for three-level designs for 4, 5 and 6 factors in 13 to 17 runs axe given. We show that the best designs here are efficient and deserve strong consideration in many practical situations.

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Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.

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A model for comparing the inventory costs of purchasing under the economic order quantity (EOQ) system and the just-in-time (JIT) order purchasing system in existing literature concluded that JIT purchasing was virtually always the preferable inventory ordering system especially at high level of annual demand. By expanding the classical EOQ model, this paper shows that it is possible for the EOQ system to be more cost effective than the JIT system once the inventory demand approaches the EOQ-JIT cost indifference point. The case study conducted in the ready-mixed concrete industry in Singapore supported this proposition.

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In order to organize distributed educational resources efficiently, to provide active learners an integrated, extendible and cohesive interface to share the dynamically growing multimedia learning materials on the Internet, this paper proposes a generic resource organization model with semantic structures to improve expressiveness, scalability and cohesiveness. We developed an active learning system with semantic support for learners to access and navigate through efficient and flexible manner. We learning resources in an efficient and flexible manner. We provide facilities for instructors to manipulate the structured educational resources via a convenient visual interface. We also developed a resource discovering and gathering engine based on complex semantic associations for several specific topics.

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The Danish Eulerian Model (DEM) is a powerful air pollution model, designed to calculate the concentrations of various dangerous species over a large geographical region (e.g. Europe). It takes into account the main physical and chemical processes between these species, the actual meteorological conditions, emissions, etc.. This is a huge computational task and requires significant resources of storage and CPU time. Parallel computing is essential for the efficient practical use of the model. Some efficient parallel versions of the model were created over the past several years. A suitable parallel version of DEM by using the Message Passing Interface library (AIPI) was implemented on two powerful supercomputers of the EPCC - Edinburgh, available via the HPC-Europa programme for transnational access to research infrastructures in EC: a Sun Fire E15K and an IBM HPCx cluster. Although the implementation is in principal, the same for both supercomputers, few modifications had to be done for successful porting of the code on the IBM HPCx cluster. Performance analysis and parallel optimization was done next. Results from bench marking experiments will be presented in this paper. Another set of experiments was carried out in order to investigate the sensitivity of the model to variation of some chemical rate constants in the chemical submodel. Certain modifications of the code were necessary to be done in accordance with this task. The obtained results will be used for further sensitivity analysis Studies by using Monte Carlo simulation.

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Large scientific applications are usually developed, tested and used by a group of geographically dispersed scientists. The problems associated with the remote development and data sharing could be tackled by using collaborative working environments. There are various tools and software to create collaborative working environments. Some software frameworks, currently available, use these tools and software to enable remote job submission and file transfer on top of existing grid infrastructures. However, for many large scientific applications, further efforts need to be put to prepare a framework which offers application-centric facilities. Unified Air Pollution Model (UNI-DEM), developed by Danish Environmental Research Institute, is an example of a large scientific application which is in a continuous development and experimenting process by different institutes in Europe. This paper intends to design a collaborative distributed computing environment for UNI-DEM in particular but the framework proposed may also fit to many large scientific applications as well.