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| 2. |
- Sherratt, K., et al.
(författare)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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| 3. |
- Terracciano, A, et al.
(författare)
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National character does not reflect mean personality trait levels in 49 cultures
- 2005
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 310:5745, s. 96-100
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Tidskriftsartikel (refereegranskat)abstract
- Most people hold beliefs about personality characteristics typical of members of their own and others' cultures. These perceptions of national character may be generalizations from personal experience, stereotypes with a "kernel of truth," or inaccurate stereotypes. We obtained national character ratings of 3989 people from 49 cultures and compared them with the average personality scores of culture members assessed by observer ratings and self-reports. National character ratings were reliable but did not converge with assessed traits. Perceptions of national character thus appear to be unfounded stereotypes that may serve the function of maintaining a national identity.
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| 4. |
- Yamaguchi, H., et al.
(författare)
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History of NAMRI and NAMRC
- 2019
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Ingår i: Procedia Manufacturing. - : Elsevier B.V.. - 2351-9789. ; 34, s. 3-5
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Tidskriftsartikel (refereegranskat)
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| 5. |
- Rostkowski, Pawel, et al.
(författare)
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The strength in numbers : comprehensive characterization of house dust using complementary mass spectrometric techniques
- 2019
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Ingår i: Analytical and Bioanalytical Chemistry. - : Springer Science and Business Media LLC. - 1618-2642 .- 1618-2650. ; 411:10, s. 1957-1977
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Tidskriftsartikel (refereegranskat)abstract
- Untargeted analysis of a composite house dust sample has been performed as part of a collaborative effort to evaluate the progress in the field of suspect and nontarget screening and build an extensive database of organic indoor environment contaminants. Twenty-one participants reported results that were curated by the organizers of the collaborative trial. In total, nearly 2350 compounds were identified (18%) or tentatively identified (25% at confidence level 2 and 58% at confidence level 3), making the collaborative trial a success. However, a relatively small share (37%) of all compounds were reported by more than one participant, which shows that there is plenty of room for improvement in the field of suspect and nontarget screening. An even a smaller share (5%) of the total number of compounds were detected using both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Thus, the two MS techniques are highly complementary. Most of the compounds were detected using LC with electrospray ionization (ESI) MS and comprehensive 2D GC (GCxGC) with atmospheric pressure chemical ionization (APCI) and electron ionization (EI), respectively. Collectively, the three techniques accounted for more than 75% of the reported compounds. Glycols, pharmaceuticals, pesticides, and various biogenic compounds dominated among the compounds reported by LC-MS participants, while hydrocarbons, hydrocarbon derivatives, and chlorinated paraffins and chlorinated biphenyls were primarily reported by GC-MS participants. Plastics additives, flavor and fragrances, and personal care products were reported by both LC-MS and GC-MS participants. It was concluded that the use of multiple analytical techniques was required for a comprehensive characterization of house dust contaminants. Further, several recommendations are given for improved suspect and nontarget screening of house dust and other indoor environment samples, including the use of open-source data processing tools. One of the tools allowed provisional identification of almost 500 compounds that had not been reported by participants.
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| 6. |
- Turja, R., et al.
(författare)
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A multibiomarker approach to the assessment of pollution impacts in two Baltic Sea coastal areas in Sweden using caged mussels (Mytilus trossulus)
- 2014
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 473, s. 398-409
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Tidskriftsartikel (refereegranskat)abstract
- Blue mussels (Mytilus trossulus) were transplanted in cages for three months in two Swedish coastal areas in the Bothnian Sea (northern Baltic Sea) to investigate the interactions between analysed environmental chemicals and biological responses. A wide array of biological parameters (biomarkers) including antioxidant and biotransformation activity, geno-, cyto- and neurotoxic effects, phagocytosis, bioenergetic status and heart rate were measured to detect the possible effects of contaminants. Integrated Biomarker Response index and Principal Component Analysis performed on the individual biological response data were able to discriminate between the two study areas as well as the contaminated sites from their respective local reference sites. The two contaminated sites outside the cities of Sundsvall (station 51) and Gavle (station G1) were characterised by different biomarker response patterns. Mussels at station S1 showed a low condition index, increased heart rate recovery time and phagocytosis activity coinciding with the highest tissue concentrations of some trace metals, polycyclic aromatic hydrocarbons and organotins. At station G1 the highest organochlorine pesticide concentration was recorded as well as elevations in glutathione S-transferase activity, thiamine content and low lysosomal membrane stability. Significant variability in the geno- and cytotoxic responses and bioenergetic status was also observed at the different caging stations. The results obtained suggest that different chemical mixtures present in the study areas cause variable biological response patterns in organisms.
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