1,796 research outputs found

    Investigation on the Loss of Taste and Smell and Consequent Psychological Effects: A Cross-Sectional Study on Healthcare Workers Who Contracted the COVID-19 Infection

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    The aim of this study was to investigate the correlation between psychological distress and taste and sense of smell dysfunctions on healthcare workers (HCW) who contracted the COVID-19 infection in the midst of the disease outbreak. Reports of sudden loss of taste and smell which persist even after recovery from COVID-19 infection are increasingly recognized as critical symptoms for COVID-19 infections. Therefore, we conducted a cross-sectional study on COVID-19 HCW (N = 104) who adhered to respond to a phone semistructured interview addressing the virus symptoms and associated psychological distress. Data were collected from June to September 2020. Findings confirm the association between experienced taste/olfactory loss and emotional distress and suggest that dysfunctions of taste and smell correlate positively with anxiety and depression. Furthermore, their psychological impact tends to persist even after the recovery from the disease, suggesting the need for appropriate psychological interventions to prevent people from developing more serious or long-lasting psychological disorders and, as far as HCW, to reduce the risk of work-related distress

    SARS-CoV-2 Breakthrough Infections: Incidence and Risk Factors in a Large European Multicentric Cohort of Health Workers

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    The research aimed to investigate the incidence of SARS-CoV-2 breakthrough infections and their determinants in a large European cohort of more than 60,000 health workers

    b-tagging in DELPHI at LEP

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    Abstract: The standard method used for tagging b-hadrons in the DELPHI experiment at the CERN LEP Collider is discussed in detail. The main ingredient of b-tagging is the impact parameters of tracks, which relies mostly on the vertex detector. Additional information, such as the mass of particles associated to a secondary vertex, significantly improves the selection efficiency and the background suppression. The paper describes various discriminating variables used for the tagging and the procedure of their combination. In addition, applications of b-tagging to some physics analyses, which depend crucially on the performance and reliability of b-tagging, are described briefly

    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 √į√į¬•with constraints√į √į √į¬• ¬• √įand√į¬ī√į¬• = √į. 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

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