320 research outputs found

    Mental Disorder Symptoms during the COVID-19 Pandemic in Latin America – A Systematic Review and Meta-analysis

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    Aims There is a lack of evidence related to the prevalence of mental health symptoms as well as their heterogeneities during the coronavirus disease 2019 (COVID-19) pandemic in Latin America, a large area spanning the equator. The current study aims to provide meta-analytical evidence on mental health symptoms during COVID-19 among frontline healthcare workers, general healthcare workers, the general population and university students in Latin America. Methods Bibliographical databases, such as PubMed, Embase, Web of Science, PsycINFO and medRxiv, were systematically searched to identify pertinent studies up to August 13, 2021. Two coders performed the screening using predefined eligibility criteria. Studies were assigned quality scores using the Mixed Methods Appraisal Tool. The double data extraction method was used to minimise data entry errors. Results A total of 62 studies with 196 950 participants in Latin America were identified. The pooled prevalence of anxiety, depression, distress and insomnia was 35%, 35%, 32% and 35%, respectively. There was a higher prevalence of mental health symptoms in South America compared to Central America (36% v. 28%, p \u3c 0.001), in countries speaking Portuguese (40%) v. Spanish (30%). The pooled prevalence of mental health symptoms in the general population, general healthcare workers, frontline healthcare workers and students in Latin America was 37%, 34%, 33% and 45%, respectively. Conclusions The high yet heterogenous level of prevalence of mental health symptoms emphasises the need for appropriate identification of psychological interventions in Latin America

    Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

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    Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a ZZ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 <pT<100< p_{\textrm{T}} < 100 GeV and in the pseudorapidity range 2.5<η<42.5 < \eta < 4. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb−1^{-1}. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

    Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

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    The decay B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} is studied in proton-proton collisions at a center-of-mass energy of s=13\sqrt{s}=13 TeV using data corresponding to an integrated luminosity of 5 fb−1\mathrm{fb}^{-1} collected by the LHCb experiment. In the Λc+K−\Lambda_{c}^+ K^{-} system, the Ξc(2930)0\Xi_{c}(2930)^{0} state observed at the BaBar and Belle experiments is resolved into two narrower states, Ξc(2923)0\Xi_{c}(2923)^{0} and Ξc(2939)0\Xi_{c}(2939)^{0}, whose masses and widths are measured to be m(Ξc(2923)0)=2924.5±0.4±1.1 MeV,m(Ξc(2939)0)=2938.5±0.9±2.3 MeV,Γ(Ξc(2923)0)=0004.8±0.9±1.5 MeV,Γ(Ξc(2939)0)=0011.0±1.9±7.5 MeV, m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV}, where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt Λc+K−\Lambda_{c}^{+} K^{-} sample. Evidence of a new Ξc(2880)0\Xi_{c}(2880)^{0} state is found with a local significance of 3.8 σ3.8\,\sigma, whose mass and width are measured to be 2881.8±3.1±8.5 MeV2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV} and 12.4±5.3±5.8 MeV12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}, respectively. In addition, evidence of a new decay mode Ξc(2790)0→Λc+K−\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-} is found with a significance of 3.7 σ3.7\,\sigma. The relative branching fraction of B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} with respect to the B−→D+D−K−B^{-} \to D^{+} D^{-} K^{-} decay is measured to be 2.36±0.11±0.22±0.252.36 \pm 0.11 \pm 0.22 \pm 0.25, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

    Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

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    The ratios of branching fractions R(D∗)≡B(Bˉ→D∗τ−Μˉτ)/B(Bˉ→D∗Ό−ΜˉΌ)\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu}) and R(D0)≡B(B−→D0τ−Μˉτ)/B(B−→D0Ό−ΜˉΌ)\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu}) are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb−1{ }^{-1} of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode τ−→Ό−ΜτΜˉΌ\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}. The measured values are R(D∗)=0.281±0.018±0.024\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024 and R(D0)=0.441±0.060±0.066\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is ρ=−0.43\rho=-0.43. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

    Greening south Asia: Investing in sustainability and innovation to preserve natural resources and combat environmental pollution

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    Over the past few years, South Asian economies have witnessed consistent growth. Despite the region's vast wealth in natural resources, the impacts of climate change are evident across its diverse climatic zones. The integration of Green Finance (GIFN), Environmentally Friendly Investments (EFI), and Green Technology Innovation (GTI) can significantly alter the trajectory for South Asian nations. These mechanisms not only support economic growth targets but also mitigate the escalating environmental pollution in the region. Consequently, this study was undertaken to assess the potential of NTR, GIFN, EFI, and GTI in addressing CO2 emissions within the South Asian economic framework. Utilizing the Method of Moments of Quantile Regression (MMQR) on the dataset revealed that NTR has a positive impact on CO2 emissions. Conversely, GIFN, EFI, and GTI demonstrated negative impacts on CO2 emissions. Based on these findings, there's a pressing need for robust governance and policy enforcement by regional institutions to enhance environmental well-being

    Evaluating the impacts of education and digitalization on renewable energy demand behaviour: new evidence from Japan

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    AbstractIncreasing renewable energy consumption is considered the panacea to tackle the issue of global warming and energy security. The digitalization of society can provide smart solutions for energy and environmental-related issues. Similarly, education can bring environmental awareness and encourage individuals and firms to rely more on renewable energy sources. We have tried to investigate the impact of education and digitalization on the renewable energy demand in Japan by applying the Quantile ARDL model. In the short and long run, the estimates attached to education are significantly positive almost all quantiles, which confirms that the higher the level of education in Japan, the higher the renewable energy demand. Likewise, the estimated coefficients of ICT, in both the short and long run, are positive and significant, confirming that increased digitalization help facilitate the renewable energy demand in Japan. Moreover, when we observe the Wald test, the asymmetric impact of education and digitalization are confirmed on the renewable energy demand in the short and long run

    Preference between Individual Products and Bundles: Effects of Complementary, Price, and Discount Level in Portugal

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    This paper aims to (1) compare consumers’ preferences between individual products and bundles as well as (2) investigate some of the factors involved in bundle characteristics that may affect consumer’s preferences. Those factors are complementarity, price level, and discount level. An online survey developed by means of questionnaires were collected from the Portuguese population. Student’s t-tests were used to test the hypothesis formulated and to analyze the consumers’ preferences. The findings corroborate that in a scenario where the bundle does not offer any discounts, preference of individual products is higher. When a 20% discount is assigned to bundles, the overall preference for individual products is still superior. By offering a discount level of 45%, the overall preference for bundles becomes higher. The positive effect of complementarity bundles valuation is confirmed. This is the first approach to evaluate the preferences between bundles and individual products in the Portuguese market. The findings contribute to clarify the customer map within a Business Model Canvas. Furthermore, this paper analyzes the bundle complementarity and discount level effects simultaneously

    Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers

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    Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592

    Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers

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    Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592

    Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers

    Get PDF
    Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592
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