103 research outputs found

    On the behavior of the robust bayesian combination operator and the significance of discounting

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    Abstract We study the combination problem for credal sets via the robust Bayesian combination operator. We extend Walley's notion of degree of imprecision and introduce a measure for degree of conflict between two credal sets. Several examples are presented in order to explore the behavior of the robust Bayesian combination operator in terms of imprecision and conflict. We further propose a discounting operator that suppresses a source given an interval of reliability weights, and highlight the importance of using such weights whenever additional information about the reliability of a source is available

    Prevalences of primary headache symptoms at school-entry: a population-based epidemiological survey of preschool children in Germany

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    Primary headache and functional abdominal pain prevalences in an unselected populationbased sample of German preschool children and their parents (n=885) were collected in relation to health-related quality of life and sociodemographic variables. The pain symptoms were assessed according to IHS classification (2004) and Rome-II criteria (1999) during the 2004 data census. The participation rate was 62.7%, with an equal gender distribution. The focus of this paper lies on the symptom-oriented point prevalences for primary headaches of preschool children: 3.6% headache, 33.2% abdominal pain, 48.8% headache+abdominal pain and 14.4% without pain. High comorbidities for pain-affected children have been found. Pain intensities differ significantly only for abdominal pain (one-way ANOVA F=3,339, df=4/445, p=0.010*), not for headaches. However, recurrent headaches show a striking ratio in favour of boys (10:1). Children at preschool age have high quality-of-life measures, already influenced negatively by paediatric pain experiences (one-way ANOVA: F=9,193, df=4/546, p=0.000**). Headache and abdominal pain are relevant for children’s everyday life; hence, simultaneous and prospective assessment is an essential issue in public health research

    Gene probing reveals the widespread distribution, diversity and abundance of isoprene-degrading bacteria in the environment

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    Background: Approximately 500 Tg of isoprene are emitted to the atmosphere annually, an amount similar to that of methane, and despite its significant effects on the climate, very little is known about the biological degradation of isoprene in the environment. Isolation and characterisation of isoprene degraders at the molecular level has allowed the development of probes targeting isoA encoding the α-subunit of the isoprene monooxygenase. This enzyme belongs to the soluble diiron centre monooxygenase family and catalyses the first step in the isoprene degradation pathway. The use of probes targeting key metabolic genes is a successful approach in molecular ecology to study specific groups of bacteria in complex environments. Here, we developed and tested a novel isoA PCR primer set to study the distribution, abundance, and diversity of isoprene degraders in a wide range of environments. Results: The new isoA probes specifically amplified isoA genes from taxonomically diverse isoprene-degrading bacteria including members of the genera Rhodococcus, Variovorax, and Sphingopyxis. There was no cross-reactivity with genes encoding related oxygenases from non-isoprene degraders. Sequencing of isoA amplicons from DNA extracted from environmental samples enriched with isoprene revealed that most environments tested harboured a considerable variety of isoA sequences, with poplar leaf enrichments containing more phylogenetically diverse isoA genes. Quantification by qPCR using these isoA probes revealed that isoprene degraders are widespread in the phyllosphere, terrestrial, freshwater and marine environments. Specifically, soils in the vicinity of high isoprene-emitting trees contained the highest number of isoprene-degrading bacteria. Conclusion: This study provides the molecular ecology tools to broaden our knowledge of the distribution, abundance and diversity of isoprene degraders in the environment, which is a fundamental step necessary to assess the impact that microbes have in mitigating the effects of this important climate-active gas

    RTiS 2005 Proceedings of Real Time in Sweden

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    The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels : An experimental study

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    We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity. “System för brĂ€nslebesparing pĂ„ stora fartyg”, 2013-00301, Vinnova Forska & VĂ€x 201
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