155 research outputs found

    A New Mechanism for Interpreting the Motion of Auroral Arcs in the Nightside Ionosphere

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    Abstract. A new mechanism is proposed for predicting and interpreting the motion of auroral arcs observed in the nightside ionosphere during the expansion phase of a substorm. This mechanism is centred on the idea that such arcs act as visible manifestations of the arrival of earthwardpropagating shock waves in the near-Earth magnetosphere. These shock waves are generated at a near-Earth X-line, and propagate at the local Alfv6n speed. Because of the non-uniform nature of the magnetised plasma in the magnetotail, dispersion results in a change in the shape of the wave fronts as the shocks propagate towards the ionosphere. Theoretical analysis shows that a variety of arc motions can occur as a result of this dispersion, depending on factors such as the reconnection rate, the location of the reconnection site, and gradients in the magnetic field strength and plasma density

    OrChem - An open source chemistry search engine for Oracle®

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    <p>Abstract</p> <p>Background</p> <p>Registration, indexing and searching of chemical structures in relational databases is one of the core areas of cheminformatics. However, little detail has been published on the inner workings of search engines and their development has been mostly closed-source. We decided to develop an open source chemistry extension for Oracle, the de facto database platform in the commercial world.</p> <p>Results</p> <p>Here we present OrChem, an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today's powerful database servers to provide fast response times in equally large data sets.</p> <p>Availability</p> <p>OrChem is free software and can be redistributed and/or modified under the terms of the GNU Lesser General Public License as published by the Free Software Foundation. All software is available via <url>http://orchem.sourceforge.net</url>.</p

    Finding a short and accurate decision rule in disjunctive normal form by exhaustive search

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    Greedy approaches suffer from a restricted search space which could lead to suboptimal classifiers in terms of performance and classifier size. This study discusses exhaustive search as an alternative to greedy search for learning short and accurate decision rules. The Exhaustive Procedure for LOgic-Rule Extraction (EXPLORE) algorithm is presented, to induce decision rules in disjunctive normal form (DNF) in a systematic and efficient manner. We propose a method based on subsumption to reduce the number of values considered for instantiation in the literals, by taking into account the relational operator without loss of performance. Furthermore, we describe a branch-and-bound approach that makes optimal use of user-defined performance constraints. To improve the generalizability we use a validation set to determine the optimal length of the DNF rule. The performance and size of the DNF rules induced by EXPLORE are compared to those of eight well-known rule learners. Our results show that an exhaustive approach to rule learning in DNF results in significantly smaller classifiers than those of the other rule learners, while securing comparable or even better performance. Clearly, exhaustive search is computer-intensive and may not always be feasible. Nevertheless, based on this study, we believe that exhaustive search should be considered an alternative for greedy search in many problems

    Dependency of magnetocardiographically determined fetal cardiac time intervals on gestational age, gender and postnatal biometrics in healthy pregnancies

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    BACKGROUND: Magnetocardiography enables the precise determination of fetal cardiac time intervals (CTI) as early as the second trimester of pregnancy. It has been shown that fetal CTI change in course of gestation. The aim of this work was to investigate the dependency of fetal CTI on gestational age, gender and postnatal biometric data in a substantial sample of subjects during normal pregnancy. METHODS: A total of 230 fetal magnetocardiograms were obtained in 47 healthy fetuses between the 15(th )and 42(nd )week of gestation. In each recording, after subtraction of the maternal cardiac artifact and the identification of fetal beats, fetal PQRST courses were signal averaged. On the basis of therein detected wave onsets and ends, the following CTI were determined: P wave, PR interval, PQ interval, QRS complex, ST segment, T wave, QT and QTc interval. Using regression analysis, the dependency of the CTI were examined with respect to gestational age, gender and postnatal biometric data. RESULTS: Atrioventricular conduction and ventricular depolarization times could be determined dependably whereas the T wave was often difficult to detect. Linear and nonlinear regression analysis established strong dependency on age for the P wave and QRS complex (r(2 )= 0.67, p < 0.001 and r(2 )= 0.66, p < 0.001) as well as an identifiable trend for the PR and PQ intervals (r(2 )= 0.21, p < 0.001 and r(2 )= 0.13, p < 0.001). Gender differences were found only for the QRS complex from the 31(st )week onward (p < 0.05). The influence on the P wave or QRS complex of biometric data, collected in a subgroup in whom recordings were available within 1 week of birth, did not display statistical significance. CONCLUSION: We conclude that 1) from approximately the 18(th )week to term, fetal CTI which quantify depolarization times can be reliably determined using magnetocardiography, 2) the P wave and QRS complex duration show a high dependency on age which to a large part reflects fetal growth and 3) fetal gender plays a role in QRS complex duration in the third trimester. Fetal development is thus in part reflected in the CTI and may be useful in the identification of intrauterine growth retardation

    Common Problems, Common Data Model Solutions: Evidence Generation for Health Technology Assessment

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    There is growing interest in using observational data to assess the safety, effectiveness, and cost effectiveness of medical technologies, but operational, technical, and methodological challenges limit its more widespread use. Common data models and federated data networks offer a potential solution to many of these problems. The open-source Observational and Medical Outcomes Partnerships (OMOP) common data model standardises the structure, format, and terminologies of otherwise disparate datasets, enabling the execution of common analytical code across a federated data network in which only code and aggregate results are shared. While common data models are increasingly used in regulatory decision making, relatively little attention has been given to their use in health technology assessment (HTA). We show that the common data model has the potential to facilitate access to relevant data, enable multidatabase studies to enhance statistical power and transfer results across populations and settings to meet the needs of local HTA decision makers, and validate findings. The use of open-source and standardised analytics improves transparency and reduces coding errors, thereby increasing confidence in the results. Further engagement from the HTA community is required to inform the appropriate standards for mapping data to the common data model and to design tools that can support evidence generation and decision making

    Common Problems, Common Data Model Solutions: Evidence Generation for Health Technology Assessment

    Get PDF
    There is growing interest in using observational data to assess the safety, effectiveness, and cost effectiveness of medical technologies, but operational, technical, and methodological challenges limit its more widespread use. Common data models and federated data networks offer a potential solution to many of these problems. The open-source Observational and Medical Outcomes Partnerships (OMOP) common data model standardises the structure, format, and terminologies of otherwise disparate datasets, enabling the execution of common analytical code across a federated data network in which only code and aggregate results are shared. While common data models are increasingly used in regulatory decision making, relatively little attention has been given to their use in health technology assessment (HTA). We show that the common data model has the potential to facilitate access to relevant data, enable multidatabase studies to enhance statistical power and transfer results across populations and settings to meet the needs of local HTA decision makers, and validate findings. The use of open-source and standardised analytics improves transparency and reduces coding errors, thereby increasing confidence in the results. Further engagement from the HTA community is required to inform the appropriate standards for mapping data to the common data model and to design tools that can support evidence generation and decision making
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