1. |
- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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2. |
- Schael, S, et al.
(author)
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Precision electroweak measurements on the Z resonance
- 2006
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In: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 427:5-6, s. 257-454
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Research review (peer-reviewed)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. |
- Schael, S., et al.
(author)
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Electroweak measurements in electron positron collisions at W-boson-pair energies at LEP
- 2013
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In: Physics Reports. - : Elsevier BV. - 0370-1573 .- 1873-6270. ; 532:4, s. 119-244
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Research review (peer-reviewed)abstract
- Electroweak measurements performed with data taken at the electron positron collider LEP at CERN from 1995 to 2000 are reported. The combined data set considered in this report corresponds to a total luminosity of about 3 fb(-1) collected by the four LEP experiments ALEPH, DELPHI, 13 and OPAL, at centre-of-mass energies ranging from 130 GeV to 209 GeV. Combining the published results of the four LEP experiments, the measurements include total and differential cross-sections in photon-pair, fermion-pair and four-fermion production, the latter resulting from both double-resonant WW and ZZ production as well as singly resonant production. Total and differential cross-sections are measured precisely, providing a stringent test of the Standard Model at centre-of-mass energies never explored before in electron positron collisions. Final-state interaction effects in four-fermion production, such as those arising from colour reconnection and Bose Einstein correlations between the two W decay systems arising in WW production, are searched for and upper limits on the strength of possible effects are obtained. The data are used to determine fundamental properties of the W boson and the electroweak theory. Among others, the mass and width of the W boson, m(w) and Gamma(w), the branching fraction of W decays to hadrons, B(W -> had), and the trilinear gauge-boson self-couplings g(1)(Z), K-gamma and lambda(gamma), are determined to be: m(w) = 80.376 +/- 0.033 GeV Gamma(w) = 2.195 +/- 0.083 GeV B(W -> had) = 67.41 +/- 0.27% g(1)(Z) = 0.984(-0.020)(+0.018) K-gamma - 0.982 +/- 0.042 lambda(gamma) = 0.022 +/- 0.019. (C) 2013 Elsevier B.V. All rights reserved.
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5. |
- Ramdas, S., et al.
(author)
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A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
- 2022
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
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Journal article (peer-reviewed)abstract
- A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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6. |
- Abate, E., et al.
(author)
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Combined performance tests before installation of the ATLAS Semiconductor and Transition Radiation Tracking Detectors
- 2008
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In: Journal of Instrumentation. - 1748-0221. ; 3
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Journal article (peer-reviewed)abstract
- The ATLAS (A Toroidal LHC ApparatuS) Inner Detector provides charged particle tracking in the centre of the ATLAS experiment at the Large Hadron Collider (LHC). The Inner Detector consists of three subdetectors: the Pixel Detector, the Semiconductor Tracker (SCT), and the Transition Radiation Tracker (TRT). This paper summarizes the tests that were carried out at the final stage of SCT+TRT integration prior to their installation in ATLAS. The combined operation and performance of the SCT and TRT barrel and endcap detectors was investigated through a series of noise tests, and by recording the tracks of cosmic rays. This was a crucial test of hardware and software of the combined tracker detector systems. The results of noise and cross-talk tests on the SCT and TRT in their final assembled configuration, using final readout and supply hardware and software, are reported. The reconstruction and analysis of the recorded cosmic tracks allowed testing of the offline analysis chain and verification of basic tracker performance parameters, such as efficiency and spatial resolution, in combined operation before installation.
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7. |
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9. |
- Adcox, K, et al.
(author)
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PHENIX detector overview
- 2003
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In: Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment. - 0167-5087. ; 499:2-3, s. 469-479
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Journal article (peer-reviewed)abstract
- The PHENIX detector is designed to perform a broad study of A-A, p-A, and p-p collisions to investigate nuclear matter under extreme conditions. A wide variety of probes, sensitive to all timescales, are used to study systematic variations with species and energy as well as to measure the spin structure of the nucleon. Designing for the needs of the heavy-ion and polarized-proton programs has produced a detector with unparalleled capabilities. PHENIX measures electron and muon pairs, photons, and hadrons with excellent energy and momentum resolution. The detector consists of a large number of subsystems that are discussed in other papers in this volume. The overall design parameters of the detector are presented. (C) 2002 Elsevier Science B.V. All rights reserved.
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10. |
- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)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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