55,078 research outputs found

    ‘Other spaces’ for lesbian, gay, bisexual, transgendered and questioning (LGBTQ) students: positioning LGBTQ-affirming schools as sites of resistance within inclusive education

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    This article explores the growing interest in schools which are aimed at children and young people who are lesbian, gay, bisexual, transgendered and questioning (LGBTQ), schools described as LGBTQ-affirming. Schools which target specific groups of students are sometimes viewed as being anti-inclusive because they assign labels to students and separate them from one another. This is based on a notion of inclusive education as a single ‘school for all’; a comprehensive, common school which is suitable for all children in a particular locality. Using academic literature alongside original data from an in-depth qualitative case study of an LGBTQ-affirming school in Atlanta, this article addresses the question of whether there is a place for LGBTQ-affirming schools within inclusive education systems. It argues that the word ‘segregated’ is not an accurate description of these schools, positing that segregated spaces are not the same as separate spaces. It argues that the separateness of LGBTQ-affirming schools is important to their role in inclusive education, specifically when they are positioned as examples of Foucault’s heterotopias. Viewing them through this theoretical lens enables them to be seen as ‘other spaces’, as a form of ‘resistance’ and ‘protest’ which may ‘unstitch’ the utopian vision of inclusive education

    Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East

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    This article presents the latest generation of ground-motion models for the prediction of elastic response (pseudo-) spectral accelerations, as well as peak ground acceleration and velocity, derived using pan-European databases. The models present a number of novelties with respect to previous generations of models (Ambraseys et al. in Earthq Eng Struct Dyn 25:371–400, 1996, Bull Earthq Eng 3:1–53, 2005; Bommer et al. in Bull Earthq Eng 1:171–203, 2003; Akkar and Bommer in Seismol Res Lett 81:195–206, 2010), namely: inclusion of a nonlinear site amplification function that is a function of V S30 and reference peak ground acceleration on rock; extension of the magnitude range of applicability of the model down to M w 4; extension of the distance range of applicability out to 200 km; extension to shorter and longer periods (down to 0.01 s and up to 4 s); and consistent models for both point-source (epicentral, R epi, and hypocentral distance, R hyp) and finite-fault (distance to the surface projection of the rupture, R JB) distance metrics. In addition, data from more than 1.5 times as many earthquakes, compared to previous pan-European models, have been used, leading to regressions based on approximately twice as many records in total. The metadata of these records have been carefully compiled and reappraised in recent European projects. These improvements lead to more robust ground-motion prediction equations than have previously been published for shallow (focal depths less than 30 km) crustal earthquakes in Europe and the Middle East. We conclude with suggestions for the application of the equations to seismic hazard assessments in Europe and the Middle East within a logic-tree framework to capture epistemic uncertainty

    Dermatological Manifestations of Down Syndrome

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    Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

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    Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a query image their corresponding 3D world coordinates in the scene. The final pose is then solved via a RANSAC-based optimization scheme using the predicted coordinates. Usually, the CNN is trained with ground truth scene coordinates, but it has also been shown that the network can discover 3D scene geometry automatically by minimizing single-view reprojection loss. However, due to the deficiencies of the reprojection loss, the network needs to be carefully initialized. In this paper, we present a new angle-based reprojection loss, which resolves the issues of the original reprojection loss. With this new loss function, the network can be trained without careful initialization, and the system achieves more accurate results. The new loss also enables us to utilize available multi-view constraints, which further improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning

    Waking up the gut in critically ill patients

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    Multiorgan failure frequently develops in critically ill patients. While therapeutic efforts in such patients are often focused on the lungs, on the cardiovascular system as well as on the kidneys, it is important to also consider the functional alterations in gut motility and hormone secretion. Given the central regulatory functions of many gut hormones, such as glucagon-like peptide 1, glucagon-like peptide 2, ghrelin and others, exogenous supplementation of some of these factors may be beneficial under conditions of critical illness. From a pragmatic point of view, the most feasible way towards a restoration of gut hormone secretion in critically ill patients is to provide enteral nutritional supply as soon as possible
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