1. |
- Ahdida, C., et al.
(author)
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Measurement of the muon flux from 400 GeV/c protons interacting in a thick molybdenum/tungsten target
- 2020
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In: European Physical Journal C. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 80:3
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Journal article (peer-reviewed)abstract
- The SHiP experiment is proposed to search for very weakly interacting particles beyond the Standard Model which are produced in a 400 GeV/c proton beam dump at the CERN SPS. About 1011muons per spill will be produced in the dump. To design the experiment such that the muon-induced background is minimized, a precise knowledge of the muon spectrum is required. To validate the muon flux generated by our Pythia and GEANT4 based Monte Carlo simulation (FairShip), we have measured the muon flux emanating from a SHiP-like target at the SPS. This target, consisting of 13 interaction lengths of slabs of molybdenum and tungsten, followed by a 2.4 m iron hadron absorber was placed in the H4 400 GeV/c proton beam line. To identify muons and to measure the momentum spectrum, a spectrometer instrumented with drift tubes and a muon tagger were used. During a 3-week period a dataset for analysis corresponding to (3.27 +/- 0.07)x1011protons on target was recorded. This amounts to approximatively 1% of a SHiP spill.
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2. |
- Ahdida, C., et al.
(author)
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The magnet of the scattering and neutrino detector for the SHiP experiment at CERN
- 2020
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In: Journal of Instrumentation. - 1748-0221. ; 15:01
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Journal article (peer-reviewed)abstract
- The Search for Hidden Particles (SHiP) experiment proposal at CERN demands a dedicated dipole magnet for its scattering and neutrino detector. This requires a very large volume to be uniformly magnetized at B > 1.2 T, with constraints regarding the inner instrumented volume as well as the external region, where no massive structures are allowed and only an extremely low stray field is admitted. In this paper we report the main technical challenges and the relevant design options providing a comprehensive design for the magnet of the SHiP Scattering and Neutrino Detector.
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3. |
- Nagao-Kitamoto, H., et al.
(author)
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Interleukin-22-mediated host glycosylation prevents Clostridioides difficile infection by modulating the metabolic activity of the gut microbiota
- 2020
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In: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26, s. 608-617
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Journal article (peer-reviewed)abstract
- In germ-free mice colonized with human microbiota, mucosal IL-22 signaling promotes the growth of succinate-consuming commensal bacteria via host mucus glycosylation, and transplantation of these bacteria limits Clostridioides difficile infection. The involvement of host immunity in the gut microbiota-mediated colonization resistance to Clostridioides difficile infection (CDI) is incompletely understood. Here, we show that interleukin (IL)-22, induced by colonization of the gut microbiota, is crucial for the prevention of CDI in human microbiota-associated (HMA) mice. IL-22 signaling in HMA mice regulated host glycosylation, which enabled the growth of succinate-consuming bacteria Phascolarctobacterium spp. within the gut microbiome. Phascolarctobacterium reduced the availability of luminal succinate, a crucial metabolite for the growth of C. difficile, and therefore prevented the growth of C. difficile. IL-22-mediated host N-glycosylation is likely impaired in patients with ulcerative colitis (UC) and renders UC-HMA mice more susceptible to CDI. Transplantation of healthy human-derived microbiota or Phascolarctobacterium reduced luminal succinate levels and restored colonization resistance in UC-HMA mice. IL-22-mediated host glycosylation thus fosters the growth of commensal bacteria that compete with C. difficile for the nutritional niche.
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4. |
- Haugg, Amelie, et al.
(author)
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Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?
- 2020
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 41:14, s. 3839-3854
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Journal article (peer-reviewed)abstract
- Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
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