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- 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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- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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- Bravo, L, et al.
(author)
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- 2021
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swepub:Mat__t
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- Tabiri, S, et al.
(author)
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- 2021
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swepub:Mat__t
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| 29. |
- Graetz, N, et al.
(author)
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Mapping disparities in education across low- and middle-income countries
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 577:77907789, s. 235-238
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Journal article (peer-reviewed)abstract
- Educational attainment is an important social determinant of maternal, newborn, and child health1–3. As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting4–6. The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness7,8; however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health9–11. Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but—to our knowledge—no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries12–14. By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations.
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| 31. |
- Hayden, JA, et al.
(author)
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Exercise treatment effect modifiers in persistent low back pain: an individual participant data meta-analysis of 3514 participants from 27 randomised controlled trials
- 2020
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In: British journal of sports medicine. - : BMJ. - 1473-0480 .- 0306-3674. ; 54:21, s. 1277-
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Journal article (peer-reviewed)abstract
- Low back pain is one of the leading causes of disability worldwide. Exercise therapy is widely recommended to treat persistent non-specific low back pain. While evidence suggests exercise is, on average, moderately effective, there remains uncertainty about which individuals might benefit the most from exercise.MethodsIn parallel with a Cochrane review update, we requested individual participant data (IPD) from high-quality randomised clinical trials of adults with our two primary outcomes of interest, pain and functional limitations, and calculated global recovery. We compiled a master data set including baseline participant characteristics, exercise and comparison characteristics, and outcomes at short-term, moderate-term and long-term follow-up. We conducted descriptive analyses and one-stage IPD meta-analysis using multilevel mixed-effects regression of the overall treatment effect and prespecified potential treatment effect modifiers.ResultsWe received IPD for 27 trials (3514 participants). For studies included in this analysis, compared with no treatment/usual care, exercise therapy on average reduced pain (mean effect/100 (95% CI) −10.7 (−14.1 to –7.4)), a result compatible with a clinically important 20% smallest worthwhile effect. Exercise therapy reduced functional limitations with a clinically important 23% improvement (mean effect/100 (95% CI) −10.2 (−13.2 to –7.3)) at short-term follow-up. Not having heavy physical demands at work and medication use for low back pain were potential treatment effect modifiers—these were associated with superior exercise outcomes relative to non-exercise comparisons. Lower body mass index was also associated with better outcomes in exercise compared with no treatment/usual care. This study was limited by inconsistent availability and measurement of participant characteristics.ConclusionsThis study provides potentially useful information to help treat patients and design future studies of exercise interventions that are better matched to specific subgroups.Protocol publicationhttps://doi.org/10.1186/2046-4053-1-64
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- 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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| 46. |
- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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