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Träfflista för sökning "WFRF:(Stoica B) srt2:(2020-2023)"

Sökning: WFRF:(Stoica B) > (2020-2023)

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  • 2021
  • swepub:Mat__t
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  • Azevedo, Flavio, et al. (författare)
  • Social and moral psychology of COVID-19 across 69 countries
  • 2023
  • Ingår i: Scientific Data. - : NATURE PORTFOLIO. - 2052-4463. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.
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6.
  • Obers, Niels A., et al. (författare)
  • Quantum gravity phenomenology at the dawn of the multi-messenger era—A review
  • 2022
  • Ingår i: Progress in Particle and Nuclear Physics. - : Elsevier BV. - 0146-6410 .- 1873-2224. ; 125
  • Forskningsöversikt (refereegranskat)abstract
    • The exploration of the universe has recently entered a new era thanks to the multi-messenger paradigm, characterized by a continuous increase in the quantity and quality of experimental data that is obtained by the detection of the various cosmic messengers (photons, neutrinos, cosmic rays and gravitational waves) from numerous origins. They give us information about their sources in the universe and the properties of the intergalactic medium. Moreover, multi-messenger astronomy opens up the possibility to search for phenomenological signatures of quantum gravity. On the one hand, the most energetic events allow us to test our physical theories at energy regimes which are not directly accessible in accelerators; on the other hand, tiny effects in the propagation of very high energy particles could be amplified by cosmological distances. After decades of merely theoretical investigations, the possibility of obtaining phenomenological indications of Planck-scale effects is a revolutionary step in the quest for a quantum theory of gravity, but it requires cooperation between different communities of physicists (both theoretical and experimental). This review, prepared within the COST Action CA18108 “Quantum gravity phenomenology in the multi-messenger approach”, is aimed at promoting this cooperation by giving a state-of-the art account of the interdisciplinary expertise that is needed in the effective search of quantum gravity footprints in the production, propagation and detection of cosmic messengers.
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7.
  • Van Bavel, Jay J., et al. (författare)
  • National identity predicts public health support during a global pandemic
  • 2022
  • Ingår i: Nature Communications. - : Nature Portfolio. - 2041-1723. ; 13:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic. Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.
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  • Pavlović, Tomislav, et al. (författare)
  • Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
  • 2022
  • Ingår i: PNAS Nexus. - : Oxford University Press (OUP). - 2752-6542 .- 2752-6542. ; 1:3
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (  = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.
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  • Leta, Tesfaye H., et al. (författare)
  • The use of antibiotic-loaded bone cement and systemic antibiotic prophylactic use in 2,971,357 primary total knee arthroplasties from 2010 to 2020: an international register-based observational study among countries in Africa, Europe, North America, and Oceania
  • 2023
  • Ingår i: Acta Orthopaedica. - 1745-3674 .- 1745-3682. ; 94, s. 416-425
  • Tidskriftsartikel (refereegranskat)abstract
    • Background and purpose — Antibiotic-loaded bone cement (ALBC) and systemic antibiotic prophylaxis (SAP) have been used to reduce periprosthetic joint infection (PJI) rates. We investigated the use of ALBC and SAP in primary total knee arthroplasty (TKA). Patients and methods — This observational study is based on 2,971,357 primary TKAs reported in 2010–2020 to national/regional joint arthroplasty registries in Australia, Den-mark, Finland, Germany, Italy, the Netherlands, New Zealand, Norway, Romania, South Africa, Sweden, Switzerland, the UK, and the USA. Aggregate-level data on trends and types of bone cement, antibiotic agents, and doses and duration of SAP used was extracted from participating registries. Results — ALBC was used in 77% of the TKAs with variation ranging from 100% in Norway to 31% in the USA. Palacos R+G was the most common (62%) ALBC type used. The primary antibiotic used in ALBC was gentamicin (94%). Use of ALBC in combination with SAP was common practice (77%). Cefazolin was the most common (32%) SAP agent. The doses and duration of SAP used varied from one single preoperative dosage as standard practice in Bolzano, Italy (98%) to 1-day 4 doses in Norway (83% of the 40,709 TKAs reported to the Norwegian arthroplasty register). Conclusion — The proportion of ALBC usage in primary TKA varies internationally, with gentamicin being the most common antibiotic. ALBC in combination with SAP was common practice, with cefazolin the most common SAP agent. The type of ALBC and type, dose, and duration of SAP varied among participating countries.
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10.
  • Osama, Muhammad, et al. (författare)
  • Online Learning for Prediction via Covariance Fitting : Computation, Performance and Robustness
  • 2023
  • Ingår i: Transactions on Machine Learning Research. - : Transactions on Machine Learning Research. - 2835-8856.
  • Tidskriftsartikel (refereegranskat)abstract
    • We consider the online learning of linear smoother predictors based on a covariance model of the outcomes. To control its degrees of freedom in an appropriate manner, the covariance model parameters are often learned using cross-validation or maximum-likelihood techniques. However, neither technique is suitable when training data arrives in a streaming fashion. Here we consider a covariance-fitting method to learn the model parameters, initially used  in spectral estimation. We show that this results in a computation efficient online learning method in which the resulting predictor can be updated sequentially. We prove that, with high probability, its out-of-sample error approaches the minimum achievable level at root-$n$ rate. Moreover, we show that the resulting predictor enjoys two different robustness properties. First, it minimizes the out-of-sample error with respect to the least favourable distribution within a given Wasserstein distance from the empirical distribution. Second, it is robust against errors in the covariate training data. We illustrate the performance of the proposed method in a numerical experiment.
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