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- Lindholm, Daniel, et al.
(author)
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Prediction Of Major Bleeding In Revascularized Patients With Acute Coronary Syndromes : Development Of A Novel Biomarker-Based Clinical Prediction Model
- 2016
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In: Journal of the American College of Cardiology. - Uppsala Univ, Dept Med Sci, Cardiol, Uppsala, Sweden. Uppsala Univ, Uppsala Clin Res Ctr, Uppsala, Sweden.. - 0735-1097 .- 1558-3597. ; 67:13, s. 493-493
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Journal article (other academic/artistic)
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- Pavlović, Tomislav, et al.
(author)
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Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
- 2022
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In: PNAS Nexus. - : Oxford University Press (OUP). - 2752-6542 .- 2752-6542. ; 1:3
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Journal article (other academic/artistic)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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- Sumaila, U. Rashid, et al.
(author)
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WTO must ban harmful fisheries subsidies
- 2021
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 374:6567, s. 544-544
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- Eilertsen, Gabriel, et al.
(author)
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Survey and Evaluation of Tone Mapping Operators for HDR-video
- 2013
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In: Siggraph 2013 Talks. - New York, NY, USA : ACM Press. - 9781450323444
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Conference paper (other academic/artistic)abstract
- This work presents a survey and a user evaluation of tone mapping operators (TMOs) for high dynamic range (HDR) video, i.e. TMOs that explicitly include a temporal model for processing of variations in the input HDR images in the time domain. The main motivations behind this work is that: robust tone mapping is one of the key aspects of HDR imaging [Reinhard et al. 2006]; recent developments in sensor and computing technologies have now made it possible to capture HDR-video, e.g. [Unger and Gustavson 2007; Tocci et al. 2011]; and, as shown by our survey, tone mapping for HDR video poses a set of completely new challenges compared to tone mapping for still HDR images. Furthermore, video tone mapping, though less studied, is highly important for a multitude of applications including gaming, cameras in mobile devices, adaptive display devices and movie post-processing. Our survey is meant to summarize the state-of-the-art in video tonemapping and, as exemplified in Figure 1 (right), analyze differences in their response to temporal variations. In contrast to other studies, we evaluate TMOs performance according to their actual intent, such as producing the image that best resembles the real world scene, that subjectively looks best to the viewer, or fulfills a certain artistic requirement. The unique strength of this work is that we use real high quality HDR video sequences, see Figure 1 (left), as opposed to synthetic images or footage generated from still HDR images.
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