563 research outputs found

    A review of unmanned aerial vehicles usage, as an environmental survey tool, within tidal stream environments

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    Funding Information: This work was funded by the Bryden Centre project, supported by the European Union’s INTERREG VA Programme and managed by the Special EU Programmes Body (SEUPB). The views and opinions expressed in this paper do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB). Aspects of this research were also funded by a Royal Society Research Grant (RSG\R1\180430), the NERC VertIBase project (NE/N01765X/1), the UK Department for Business, Energy, and Industrial Strategy’s offshore energy Strategic Environmental Assessment programme and EPSRC Supergen ORE Hub (EP/S000747/1).Peer reviewe

    Using Unmanned Aerial Vehicle (UAV) Imagery to Characterise Pursuit-Diving Seabird Association With Tidal Stream Hydrodynamic Habitat Features

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    Acknowledgments We gratefully acknowledge the support of colleagues at Marine Scotland Science, the crew and scientists of the MRV Scotia 2018 cruise (particularly Chief Scientist Adrian Tait) and ERI interns: Gael Gelis and Martin Forestier. We gratefully acknowledge the constructive comments from reviewers. Finally, we also want to thank Ella Benninghaus for providing the auk illustrations used within the paper. Funding This work was funded by the Bryden Centre project, supported by the European Union’s INTERREG VA Programme, and managed by the Special EU Programmes Body (SEUPB). The views and opinions expressed in this paper do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB). Aspects of this research were also funded by a Royal Society Research Grant [RSG\R1\180430], the NERC VertIBase project [NE/N01765X/1], the UK Department for Business, Energy, and Industrial Strategy’s offshore energy Strategic Environmental Assessment programme and EPSRC Supergen ORE Hub [EP/S000747/1].Peer reviewedPublisher PD

    Predicting postoperative systolic dysfunction in mitral regurgitation: CT vs. echocardiography

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    IntroductionVolume overload from mitral regurgitation can result in left ventricular systolic dysfunction. To prevent this, it is essential to operate before irreversible dysfunction occurs, but the optimal timing of intervention remains unclear. Current echocardiographic guidelines are based on 2D linear measurement thresholds only. We compared volumetric CT-based and 2D echocardiographic indices of LV size and function as predictors of post-operative systolic dysfunction following mitral repair.MethodsWe retrospectively identified patients with primary mitral valve regurgitation who underwent repair between 2005 and 2021. Several indices of LV size and function measured on preoperative cardiac CT were compared with 2D echocardiography in predicting post-operative LV systolic dysfunction (LVEFecho <50%). Area under the curve (AUC) was the primary metric of predictive performance.ResultsA total of 243 patients were included (mean age 57 ± 12 years; 65 females). The most effective CT-based predictors of post-operative LV systolic dysfunction were ejection fraction [LVEFCT; AUC 0.84 (95% CI: 0.77–0.92)] and LV end systolic volume indexed to body surface area [LVESViCT; AUC 0.88 (0.82–0.95)]. The best echocardiographic predictors were LVEFecho [AUC 0.70 (0.58–0.82)] and LVESDecho [AUC 0.79 (0.70–0.89)]. LVEFCT was a significantly better predictor of post-operative LV systolic dysfunction than LVEFecho (p = 0.02) and LVESViCT was a significantly better predictor than LVESDecho (p = 0.03). Ejection fraction measured by CT demonstrated significantly greater reproducibility than echocardiography.DiscussionCT-based volumetric measurements may be superior to established 2D echocardiographic parameters for predicting LV systolic dysfunction following mitral valve repair. Validation with prospective study is warranted

    Revisiting Lynam's notion of the "fledgling psychopath": are HIA-CP children truly psychopathic-like?

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    <p>Abstract</p> <p>Background</p> <p>In his developmental model of emerging psychopathy, Lynam proposed that the "fledgling psychopath" is most likely to be located within a subgroup of children elevated in both hyperactivity/inattention/impulsivity (HIA) and conduct problems (CP). This approach has garnered some empirical support. However, the extent to which Lynam's model captures children who resemble psychopathy with regard to the core affective and interpersonal features remains unclear.</p> <p>Methods</p> <p>In the present study, we investigated this issue within a large community sample of youth (<it>N </it>= 617). Four groups (non-HIA-CP, HIA-only, CP-only, and HIA-CP), defined on the basis of teacher reports of the Strengths and Difficulties Questionnaire (SDQ), were compared with respect to parent-reported psychopathic-like traits and subjective emotional reactivity in response to unpleasant, emotionally-laden pictures from the International Affective Pictures System (IAPS).</p> <p>Results</p> <p>Results did not support Lynam's model. HIA-CP children did not appear most psychopathic-like on dimensions of callous-unemotional and narcissistic personality, nor did they report reduced emotional reactivity to the IAPS relative to the other children. Post-hoc regression analyses revealed a significant moderation such that elevated HIA weakened the association between CP and emotional underarousal.</p> <p>Conclusions</p> <p>Implications of these findings with regard to the development of psychopathy are discussed.</p

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

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    A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

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    Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

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