98 research outputs found

    The role of left ventricular deformation in the assessment of microvascular obstruction and intramyocardial haemorrhage

    Get PDF
    In the setting of acute ST-elevation myocardial infarction (STEMI), it remains unclear which strain parameter most strongly correlates with microvascular obstruction (MVO) or intramyocardial haemorrhage (IMH). We aimed to investigate the association of MVO, IMH and convalescent left ventricular (LV) remodelling with strain parameters measured with cardiovascular magnetic resonance (CMR). Forty-three patients with reperfused STEMI and 10 age and gender matched healthy controls underwent CMR within 3-days and at 3-months following reperfused STEMI. Cine, T2-weighted, T2*-imaging and late gadolinium enhancement (LGE) imaging were performed. Infarct size, MVO and IMH were quantified. Peak global longitudinal strain (GLS), global radial strain (GRS), global circumferential strain (GCS) and their strain rates were derived by feature tracking analysis of LV short-axis, 4-chamber and 2-chamber cines. All 43 patients and ten controls completed the baseline scan and 34 patients completed 3-month scans. In multivariate regression, GLS demonstrated the strongest association with MVO or IMH (beta = 0.53, p 20%). Baseline GLS also demonstrated the strongest diagnostic performance in predicting adverse LV remodelling (AUC = 0.79; 95% CI 0.60–0.98; p = 0.03). Post-reperfused STEMI, baseline GLS was most closely associated with the presence of MVO or IMH. Baseline GLS was more strongly associated with adverse LV remodelling than other CMR parameters

    Modern MT: A New Open-Source Machine Translation Platform for the Translation Industry

    Get PDF
    Modern MT (www.modernmt.eu) is a three-year Horizon 2020 innovation action (2015–2017) to develop new open-source machine translation technology for use in translation production environments, both fully automatic and as a back-end in interactive post-editing scenarios. Led by Translated srl, the project consortium also includes the Fondazione Bruno Kessler (FBK), the University of Edinburgh, and TAUS B.V. Modern MT has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 645487 (call ICT-17-2014)

    Complexities of learning with computer-based tools: A case of inquiry about sound and music in elementary school

    Full text link
    Computer-based technology is increasingly becoming available for students at all grade levels in schools, and its promise and power as a learning tool is being extolled by many. From a constructive perspective, if individuals actively construct meaning from their experiences, then simply having particular tools to work with via a computer doesn't ensure that desired learning will result. Thus, it is important to examine how students construct meaning while using such tools. This study examined what fourth grade students learned from the use of two computer-based tools intended to help them understand sound and music: software that emulated an oscilloscope and allowed students to view sound waves from audio input; and software that turned the computer into an electronic keyboard, which provided students with standard pitches for comparison purposes. Principles of selective attention and pior knowledge and experiences —foundational ideas of a constructivist epistemology—were useful in understanding learning outcomes from inquiry with these tools. Our findings provide critical information for future instruction with the goal of supporting learning about sound and music from such tools. They also indicate the need for more studies examining learning from computer-based tools in specific contexts, to advance our understanding of how teachers can mediate student activity with computer-based tools to support the development of conceptual understanding.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45183/1/10956_2005_Article_BF01677126.pd

    Quantile regression for overdispersed count data: a hierarchical method

    Get PDF
    Abstract Generalized Poisson regression is commonly applied to overdispersed count data, and focused on modelling the conditional mean of the response. However, conditional mean regression models may be sensitive to response outliers and provide no information on other conditional distribution features of the response. We consider instead a hierarchical approach to quantile regression of overdispersed count data. This approach has the benefits of effective outlier detection and robust estimation in the presence of outliers, and in health applications, that quantile estimates can reflect risk factors. The technique is first illustrated with simulated overdispersed counts subject to contamination, such that estimates from conditional mean regression are adversely affected. A real application involves ambulatory care sensitive emergency admissions across 7518 English patient general practitioner (GP) practices. Predictors are GP practice deprivation, patient satisfaction with care and opening hours, and region. Impacts of deprivation are particularly important in policy terms as indicating effectiveness of efforts to reduce inequalities in care sensitive admissions. Hierarchical quantile count regression is used to develop profiles of central and extreme quantiles according to specified predictor combinations

    Distributed Multimedia Learning Environments: Why and How?

    Full text link

    Bulletin No. 10

    No full text
    corecore