769 resultados para Glycemia (Index)


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The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

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Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TFP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953-2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector. (C) 2004 Elsevier B.V. All rights reserved.

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P>1. The development of sustainable, multi-functional agricultural systems involves reconciling the needs of agricultural production with the objectives for environmental protection, including biodiversity conservation. However, the definition of sustainability remains ambiguous and it has proven difficult to identify suitable indicators for monitoring progress towards, and the successful achievement of, sustainability. 2. In this study, we show that a trait-based approach can be used to assess the detrimental impacts of agricultural change to a broad range of taxonomic groupings and derive a standardised index of farmland biodiversity health, built around an objective of achieving stable or increasing populations in all species associated with agricultural landscapes. 3. To demonstrate its application, we assess the health of UK farmland biodiversity relative to this goal. Our results suggest that the populations of two-thirds of 333 plant and animal species assessed are unsustainable under current UK agricultural practices. 4. We then explore the potential benefits of an agri-environment scheme, Entry Level Stewardship (ELS), to farmland biodiversity in the UK under differing levels of risk mitigation delivery. We show that ELS has the potential to make a significant contribution to progress towards sustainability targets but that this potential is severely restricted by current patterns of scheme deployment. 5.Synthesis and applications: We have developed a cross-taxonomic sustainability index which can be used to assess both the current health of farmland biodiversity and the impacts of future agricultural changes relative to quantitative biodiversity targets. Although biodiversity conservation is just one of a number of factors that must be considered when defining sustainability, we believe our cross-taxonomic index has the potential to be a valuable tool for guiding the development of sustainable agricultural systems.

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The Agri-Environmental Footprint project is developing a common methodology for assessing the environmental impact of European agri-environment schemes. The Agri-Environmental Footprint Index (AFI) has been constructed as a customisable approach. It is a farm-level index that aggregates the measurement of agri-environmental indicators. Farm-level impact scores can be aggregated at a regional level to track temporal change and/or to provide comparisons of the success (or otherwise) of an agri-environment scheme.

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An aggregated farm-level index, the Agri-environmental Footprint Index (AFI), based on multiple criteria methods and representing a harmonised approach to evaluation of EU agri-environmental schemes is described. The index uses a common framework for the design and evaluation of policy that can be customised to locally relevant agri-environmental issues and circumstances. Evaluation can be strictly policy-focused, or broader and more holistic in that context-relevant assessment criteria that are not necessarily considered in the evaluated policy can nevertheless be incorporated. The Index structure is flexible, and can respond to diverse local needs. The process of Index construction is interactive, engaging farmers and other relevant stakeholders in a transparent decision-making process that can ensure acceptance of the outcome, help to forge an improved understanding of local agri-environmental priorities and potentially increase awareness of the critical role of farmers in environmental management. The structure of the AFI facilitates post-evaluation analysis of relative performance in different dimensions of the agri-environment, permitting identification of current strengths and weaknesses, and enabling future improvement in policy design. Quantification of the environmental impact of agriculture beyond the stated aims of policy using an 'unweighted' form of the AFI has potential as the basis of an ongoing system of environmental audit within a specified agricultural context. (C) 2009 Elsevier Ltd. All rights reserved.

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The paper considers meta-analysis of diagnostic studies that use a continuous Score for classification of study participants into healthy, or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between Studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might he confounded by a potentially unknown variation of the cut-off Value. To cope with this phenomena it is suggested to use, instead an overall estimate of the misclassification error previously suggested and used as Youden's index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel-Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden's index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.

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We have developed a model that allows players in the building and construction sector and the energy policy makers on energy strategies to be able to perceive the interest of investors in the kingdom of Bahrain in conducting Building Integrated Photovoltaic (BIPV) or Building integrated wind turbines (BIWT) projects, i.e. a partial sustainable or green buildings. The model allows the calculation of the Sustainable building index (SBI), which ranges from 0.1 (lowest) to 1.0 (highest); the higher figure the more chance for launching BIPV or BIWT. This model was tested in Bahrain and the calculated SBI was found 0.47. This means that an extensive effort must be made through policies on renewable energy, renewable energy education, and incentives to BIPV and BIWT projects, environmental awareness and promotion to clean and sustainable energy for building and construction projects. Our model can be used internationally to create a "Global SBI" database. The Sustainable building and construction initiative (SBCI), United Nation, can take the task for establishing such task using this model.

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This paper deals with the energy consumption and the evaluation of the performance of air supply systems for a ventilated room involving high- and low-level supplies. The energy performance assessment is based on the airflow rate, which is related to the fan power consumption by achieving the same environmental quality performance for each case. Four different ventilation systems are considered: wall displacement ventilation, confluent jets ventilation, impinging jet ventilation and a high level mixing ventilation system. The ventilation performance of these systems will be examined by means of achieving the same Air Distribution Index (ADI) for different cases. The widely used high-level supplies require much more fan power than those for low-level supplies for achieving the same value of ADI. In addition, the supply velocity, hence the supply dynamic pressure, for a high-level supply is much larger than for low-level supplies. This further increases the power consumption for high-level supply systems. The paper considers these factors and attempts to provide some guidelines on the difference in the energy consumption associated with high and low level air supply systems. This will be useful information for designers and to the authors' knowledge there is a lack of information available in the literature on this area of room air distribution. The energy performance of the above-mentioned ventilation systems has been evaluated on the basis of the fan power consumed which is related to the airflow rate required to provide equivalent indoor environment. The Air Distribution Index (ADI) is used to evaluate the indoor environment produced in the room by the ventilation strategy being used. The results reveal that mixing ventilation requires the highest fan power and the confluent jets ventilation needs the lowest fan power in order to achieve nearly the same value of ADI.

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One of the most common decisions we make is the one about where to move our eyes next. Here we examine the impact that processing the evidence supporting competing options has on saccade programming. Participants were asked to saccade to one of two possible visual targets indicated by a cloud of moving dots. We varied the evidence which supported saccade target choice by manipulating the proportion of dots moving towards one target or the other. The task was found to become easier as the evidence supporting target choice increased. This was reflected in an increase in percent correct and a decrease in saccade latency. The trajectory and landing position of saccades were found to deviate away from the non-selected target reflecting the choice of the target and the inhibition of the non-target. The extent of the deviation was found to increase with amount of sensory evidence supporting target choice. This shows that decision-making processes involved in saccade target choice have an impact on the spatial control of a saccade. This would seem to extend the notion of the processes involved in the control of saccade metrics beyond a competition between visual stimuli to one also reflecting a competition between options.

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Random number generation (RNG) is a functionally complex process that is highly controlled and therefore dependent on Baddeley's central executive. This study addresses this issue by investigating whether key predictions from this framework are compatible with empirical data. In Experiment 1, the effect of increasing task demands by increasing the rate of the paced generation was comprehensively examined. As expected, faster rates affected performance negatively because central resources were increasingly depleted. Next, the effects of participants' exposure were manipulated in Experiment 2 by providing increasing amounts of practice on the task. There was no improvement over 10 practice trials, suggesting that the high level of strategic control required by the task was constant and not amenable to any automatization gain with repeated exposure. Together, the results demonstrate that RNG performance is a highly controlled and demanding process sensitive to additional demands on central resources (Experiment 1) and is unaffected by repeated performance or practice (Experiment 2). These features render the easily administered RNG task an ideal and robust index of executive function that is highly suitable for repeated clinical use.

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