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Search: WFRF:(Yun SH)

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  • Abel, I, et al. (author)
  • Overview of the JET results with the ITER-like wall
  • 2013
  • In: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 53:10, s. 104002-
  • Journal article (peer-reviewed)abstract
    • Following the completion in May 2011 of the shutdown for the installation of the beryllium wall and the tungsten divertor, the first set of JET campaigns have addressed the investigation of the retention properties and the development of operational scenarios with the new plasma-facing materials. The large reduction in the carbon content (more than a factor ten) led to a much lower Z(eff) (1.2-1.4) during L- and H-mode plasmas, and radiation during the burn-through phase of the plasma initiation with the consequence that breakdown failures are almost absent. Gas balance experiments have shown that the fuel retention rate with the new wall is substantially reduced with respect to the C wall. The re-establishment of the baseline H-mode and hybrid scenarios compatible with the new wall has required an optimization of the control of metallic impurity sources and heat loads. Stable type-I ELMy H-mode regimes with H-98,H-y2 close to 1 and beta(N) similar to 1.6 have been achieved using gas injection. ELM frequency is a key factor for the control of the metallic impurity accumulation. Pedestal temperatures tend to be lower with the new wall, leading to reduced confinement, but nitrogen seeding restores high pedestal temperatures and confinement. Compared with the carbon wall, major disruptions with the new wall show a lower radiated power and a slower current quench. The higher heat loads on Be wall plasma-facing components due to lower radiation made the routine use of massive gas injection for disruption mitigation essential.
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  • Bruin, WB, et al. (author)
  • Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters
  • 2020
  • In: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 342-
  • Journal article (peer-reviewed)abstract
    • No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
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