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Träfflista för sökning "WFRF:(Pearson JF) "

Sökning: WFRF:(Pearson JF)

  • Resultat 1-10 av 22
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1.
  • Kanai, M, et al. (författare)
  • 2023
  • swepub:Mat__t
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2.
  • Schael, S, et al. (författare)
  • Precision electroweak measurements on the Z resonance
  • 2006
  • Ingår i: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 427:5-6, s. 257-454
  • Forskningsöversikt (refereegranskat)abstract
    • We report on the final electroweak measurements performed with data taken at the Z resonance by the experiments operating at the electron-positron colliders SLC and LEP. The data consist of 17 million Z decays accumulated by the ALEPH, DELPHI, L3 and OPAL experiments at LEP, and 600 thousand Z decays by the SLID experiment using a polarised beam at SLC. The measurements include cross-sections, forward-backward asymmetries and polarised asymmetries. The mass and width of the Z boson, m(Z) and Gamma(Z), and its couplings to fermions, for example the p parameter and the effective electroweak mixing angle for leptons, are precisely measured: m(Z) = 91.1875 +/- 0.0021 GeV, Gamma(Z) = 2.4952 +/- 0.0023 GeV, rho(l) = 1.0050 +/- 0.0010, sin(2)theta(eff)(lept) = 0.23153 +/- 0.00016. The number of light neutrino species is determined to be 2.9840 +/- 0.0082, in agreement with the three observed generations of fundamental fermions. The results are compared to the predictions of the Standard Model (SM). At the Z-pole, electroweak radiative corrections beyond the running of the QED and QCD coupling constants are observed with a significance of five standard deviations, and in agreement with the Standard Model. Of the many Z-pole measurements, the forward-backward asymmetry in b-quark production shows the largest difference with respect to its SM expectation, at the level of 2.8 standard deviations. Through radiative corrections evaluated in the framework of the Standard Model, the Z-pole data are also used to predict the mass of the top quark, m(t) = 173(+10)(+13) GeV, and the mass of the W boson, m(W) = 80.363 +/- 0.032 GeV. These indirect constraints are compared to the direct measurements, providing a stringent test of the SM. Using in addition the direct measurements of m(t) and m(W), the mass of the as yet unobserved SM Higgs boson is predicted with a relative uncertainty of about 50% and found to be less than 285 GeV at 95% confidence level. (c) 2006 Elsevier B.V. All rights reserved.
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3.
  • Niemi, MEK, et al. (författare)
  • 2021
  • swepub:Mat__t
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  • Abel, I, et al. (författare)
  • Overview of the JET results with the ITER-like wall
  • 2013
  • Ingår i: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 53:10, s. 104002-
  • Tidskriftsartikel (refereegranskat)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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  • Romagnoni, A, et al. (författare)
  • Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
  • 2019
  • Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
  • Tidskriftsartikel (refereegranskat)abstract
    • Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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