| 1. |
- Bécoulet, A., et al.
(författare)
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Science and technology research and development in support to ITER and the Broader Approach at CEA
- 2013
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Ingår i: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 53:10
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Tidskriftsartikel (refereegranskat)abstract
- In parallel to the direct contribution to the procurement phase of ITER and Broader Approach, CEA has initiated research & development programmes, accompanied by experiments together with a significant modelling effort, aimed at ensuring robust operation, plasma performance, as well as mitigating the risks of the procurement phase. This overview reports the latest progress in both fusion science and technology including many areas, namely the mitigation of superconducting magnet quenches, disruption-generated runaway electrons, edge-localized modes (ELMs), the development of imaging surveillance, and heating and current drive systems for steady-state operation. The WEST (W Environment for Steady-state Tokamaks) project, turning Tore Supra into an actively cooled W-divertor platform open to the ITER partners and industries, is presented.
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| 2. |
- Gerkin, RC, et al.
(författare)
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The best COVID-19 predictor is recent smell loss: a cross-sectional study
- 2020
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Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundCOVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19.MethodsThis preregistered, cross-sectional study used a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified singular and cumulative predictors of COVID-19 status and post-COVID-19 olfactory recovery.ResultsBoth C19+ and C19-groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both single and cumulative feature models (ROC AUC=0.72), with additional features providing negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ∼50% of participants and was best predicted by time since illness onset.ConclusionsAs smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<OR<10), which can be deployed when viral lab tests are impractical or unavailable.
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