6 resultados para external validation

em WestminsterResearch - UK


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Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

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Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). This report provides estimates of the total external costs of LGV and HGV operations in London. In 2006, total LGV and HGV activity imposed external costs of approximately £1.75-£1.8 billion using low, medium and high emission cost values. About 27 per cent of these costs were internalised by duties and taxes paid by LGV operators, compared with 26% in the case of HGVs. If congestion costs are excluded, taxes and duties paid by LGV operators are estimated to be 155% of LGVs' allocated infrastructural and environmental costs, compared with 85% in the case of HGVs. When using the medium emission cost values, LGVs accounted for 56% of these external costs in London and HGVs for 44%.

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This report provides estimates of the total external costs of LGV and HGV operations in London. In 2006, total LGV and HGV activity imposed external costs of approximately £1.75-£1.8 billion using low, medium and high emission cost values. About 27 per cent of these costs were internalised by duties and taxes paid by LGV operators, compared with 26% in the case of HGVs. If congestion costs are excluded, taxes and duties paid by LGV operators are estimated to be 155% of LGVs' allocated infrastructural and environmental costs, compared with 85% in the case of HGVs. When using the medium emission cost values, LGVs accounted for 56% of these external costs in London and HGVs for 44%.

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To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

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Multi-parametric magnetic resonance imaging (mp-MRI) has become an increasingly important method for detecting and treating prostate cancer. Transrectal ultrasound (TRUS) is the most commonly used method for guiding prostate needle biopsy and remains the gold standard for diagnosis of prostate cancer. MRI-to-TRUS image reg- istration is an important technology for enabling computer-assisted targeting of the majority of prostate lesions that are visible in MRI but not independently distinguishable in TRUS images. The aim of this study was to estimate the needle placement accuracy of an image guidance system (SmartTargetÒ), developed by our research group, using a surgical training phantom.

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Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.