14,972 research outputs found

    Nurturing the young shoots of talent: Using action research for exploration and theory building

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    This is an Author's Accepted Manuscript of an article published in European Early Childhood Education Research Journal, 19(4), 433-450, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/1350293X.2011.623515.This paper reports the outcomes of a set of action research projects carried out by teacher researchers in 14 local education authorities in England, working collaboratively with university tutors, over a period of three years. The common aim of all the projects was to explore practical ways of nurturing the gifts and talents of children aged four–seven years. The project was funded by the Department of Education and Skills in England as part of the government's gifted and talented programme. The project teachers felt that their understanding of issues relating to nurturing the gifts and talents of younger children was enhanced through their engagement in the project. It was possible to map the findings of the projects to the English government's National Quality Standards for gifted and talented education which include: (1) identification; (2) effective provision in the classroom; (3) enabling curriculum entitlement and choice; (4) assessment for learning; (5) engaging with community, families and beyond. The findings are also analysed within the framework of good practice in educating children in the first years of schooling. Participating practitioners felt that action research offered them a suitable methodology to explore the complexity of the topic of giftedness through cycles of planning, action and reflection and personal theory building

    No Spare Parts: Sharing Part Detectors for Image Categorization

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    This work aims for image categorization using a representation of distinctive parts. Different from existing part-based work, we argue that parts are naturally shared between image categories and should be modeled as such. We motivate our approach with a quantitative and qualitative analysis by backtracking where selected parts come from. Our analysis shows that in addition to the category parts defining the class, the parts coming from the background context and parts from other image categories improve categorization performance. Part selection should not be done separately for each category, but instead be shared and optimized over all categories. To incorporate part sharing between categories, we present an algorithm based on AdaBoost to jointly optimize part sharing and selection, as well as fusion with the global image representation. We achieve results competitive to the state-of-the-art on object, scene, and action categories, further improving over deep convolutional neural networks

    Efficacy of new-generation antidepressants assessed with the Montgomery-Asberg depression rating scale, the gold standard clinician rating scale : a meta-analysis of randomised placebo-controlled trials

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    It has been claimed that efficacy estimates based on the Hamilton Depression Rating-Scale (HDRS) underestimate antidepressants true treatment effects due to the instrument's poor psychometric properties. The aim of this study is to compare efficacy estimates based on the HDRS with the gold standard procedure, the Montgomery-Asberg Depression Rating-Scale (MADRS)

    Determining species tree topologies from clade probabilities under the coalescent

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    One approach to estimating a species tree from a collection of gene trees is to first estimate probabilities of clades from the gene trees, and then to construct the species tree from the estimated clade probabilities. While a greedy consensus algorithm, which consecutively accepts the most probable clades compatible with previously accepted clades, can be used for this second stage, this method is known to be statistically inconsistent under the multispecies coalescent model. This raises the question of whether it is theoretically possible to reconstruct the species tree from known probabilities of clades on gene trees. We investigate clade probabilities arising from the multispecies coalescent model, with an eye toward identifying features of the species tree. Clades on gene trees with probability greater than 1/3 are shown to reflect clades on the species tree, while those with smaller probabilities may not. Linear invariants of clade probabilities are studied both computationally and theoretically, with certain linear invariants giving insight into the clade structure of the species tree. For species trees with generic edge lengths, these invariants can be used to identify the species tree topology. These theoretical results both confirm that clade probabilities contain full information on the species tree topology and suggest future directions of study for developing statistically consistent inference methods from clade frequencies on gene trees.Comment: 25 pages, 2 figure
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