1,288 research outputs found

    Refining fast simulation using machine learning

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    At the CMS experiment, a growing reliance on the fast Monte Carlo application (FastSim) will accompany the high luminosity and detector granularity expected in Phase 2. The FastSim chain is roughly 10 times faster than the application based on the GEANT4 detector simulation and full reconstruction referred to as FullSim. However, this advantage comes at the price of decreased accuracy in some of the final analysis observables. In this contribution, a machine learning-based technique to refine those observables is presented. We employ a regression neural network trained with a sophisticated combination of multiple loss functions to provide post-hoc corrections to samples produced by the FastSim chain. The results show considerably improved agreement with the FullSim output and an improvement in correlations among output observables and external parameters. This technique is a promising replacement for existing correction factors, providing higher accuracy and thus contributing to the wider usage of FastSim.Comment: 8 pages, 4 figures, CHEP2023 proceedings, submitted to EPJ Web of Conference

    The impact of tourism arrivals, tourism receipts and renewable energy consumption on quality of life : A panel study of Southern African region

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    Improving wellbeing and livelihoods exemplify the third Sustainable Development Goal. Literature related to the tourism-renewable energy-quality of life nexus is limited and lacks consensus. This study contributes to the debate and examines the influence of international tourism arrival (TA), real international tourism receipts (TR), and renewable energy consumption (REC) on quality of life (QoL) by using a panel of 8 Southern African countries spanning 1995–2017. The results found a significant positive and long-run relationship between TA, TR, and QoL. A significant negative effect was found between REC, trade openness (TO), and QoL while urbanization (Urb) had an insignificant negative impact on QoL. A unidirectional causal relationship was found running from QoL to TR and bidirectional causality between QoL and REC. Feedback causality was found between QoL and Urb and unidirectional causality from QoL to TO. The results imply that tourism is an effective economic tool for improving human development in Southern Africa.publishedVersio

    Progressive myoclonus epilepsies-Residual unsolved cases have marked genetic heterogeneity including dolichol-dependent protein glycosylation pathway genes

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    Progressive myoclonus epilepsies (PMEs) comprise a group of clinically and genetically heterogeneous rare diseases. Over 70% of PME cases can now be molecularly solved. Known PME genes encode a variety of proteins, many involved in lysosomal and endosomal function. We performed whole-exome sequencing (WES) in 84 (78 unrelated) unsolved PME-affected individuals, with or without additional family members, to discover novel causes. We identified likely disease-causing variants in 24 out of 78 (31%) unrelated individuals, despite previous genetic analyses. The diagnostic yield was significantly higher for individuals studied as trios or families (14/28) versus singletons (10/50) (OR = 3.9, p value = 0.01, Fisher's exact test). The 24 likely solved cases of PME involved 18 genes. First, we found and functionally validated five heterozygous variants in NUS1 and DHDDS and a homozygous variant in ALG10, with no previous disease associations. All three genes are involved in dolichol-dependent protein glycosylation, a pathway not previously implicated in PME. Second, we independently validate SEMA6B as a dominant PME gene in two unrelated individuals. Third, in five families, we identified variants in established PME genes; three with intronic or copy-number changes (CLN6, GBA, NEU1) and two very rare causes (ASAH1, CERS1). Fourth, we found a group of genes usually associated with developmental and epileptic encephalopathies, but here, remarkably, presenting as PME, with or without prior developmental delay. Our systematic analysis of these cases suggests that the small residuum of unsolved cases will most likely be a collection of very rare, genetically heterogeneous etiologies.Peer reviewe

    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