422 research outputs found

    Parallels, prescience and the past: analogical reasoning and contemporary international politics

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    Analogical reasoning has held a perpetual appeal to policymakers who have often drafted in historical metaphor as a mode of informing decision-making. However, this article contends that since the beginning of the ‘War on Terror’ we have arguably seen the rise of a more potent form of analogy, namely ones that are selected because they fulfil an ideological function. Analogical reasoning as a tool of rational decision-making has increasingly become replaced by analogical reasoning as a tool of trenchant ideologically-informed policy justification. This article addresses three key areas which map out the importance of analogical reasoning to an understanding of developments in contemporary international politics: the relationship between history and politics, in intellectual and policy terms; a critical assessment of the appeal that analogical reasoning holds for policymakers; and the development of a rationale for a more effective use of history in international public policymaking

    Genetic analysis of Mendelian mutations in a large UK population-based Parkinson's disease study

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    Our objective was to define the prevalence and clinical features of genetic Parkinson's disease in a large UK population-based cohort, the largest multicentre prospective clinico-genetic incident study in the world. We collected demographic data, Movement Disorder Society Unified Parkinson's Disease Rating Scale scores, and Montreal Cognitive Assessment scores. We analysed mutations in PRKN (parkin), PINK1, LRRK2 and SNCA in relation to age at symptom onset, family history and clinical features. Of the 2262 participants recruited to the Tracking Parkinson's study, 424 had young-onset Parkinson's disease (age at onset ≤ 50) and 1799 had late onset Parkinson's disease. A range of methods were used to genotype 2005 patients: 302 young-onset patients were fully genotyped with multiplex ligation-dependent probe amplification and either Sanger and/or exome sequencing; and 1701 late-onset patients were genotyped with the LRRK2 'Kompetitive' allele-specific polymerase chain reaction assay and/or exome sequencing (two patients had missing age at onset). We identified 29 (1.4%) patients carrying pathogenic mutations. Eighteen patients carried the G2019S or R1441C mutations in LRRK2, and one patient carried a heterozygous duplication in SNCA. In PRKN, we identified patients carrying deletions of exons 1, 4 and 5, and P113Xfs, R275W, G430D and R33X. In PINK1, two patients carried deletions in exon 1 and 5, and the W90Xfs point mutation. Eighteen per cent of patients with age at onset ≤30 and 7.4% of patients from large dominant families carried pathogenic Mendelian gene mutations. Of all young-onset patients, 10 (3.3%) carried biallelic mutations in PRKN or PINK1. Across the whole cohort, 18 patients (0.9%) carried pathogenic LRRK2 mutations and one (0.05%) carried an SNCA duplication. There is a significant burden of LRRK2 G2019S in patients with both apparently sporadic and familial disease. In young-onset patients, dominant and recessive mutations were equally common. There were no differences in clinical features between LRRK2 carriers and non-carriers. However, we did find that PRKN and PINK1 mutation carriers have distinctive clinical features compared to young-onset non-carriers, with more postural symptoms at diagnosis and less cognitive impairment, after adjusting for age and disease duration. This supports the idea that there is a distinct clinical profile of PRKN and PINK1-related Parkinson's disease. We estimate that there are approaching 1000 patients with a known genetic aetiology in the UK Parkinson's disease population. A small but significant number of patients carry causal variants in LRRK2, SNCA, PRKN and PINK1 that could potentially be targeted by new therapies, such as LRRK2 inhibitors

    Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants

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    Background:Genomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients carrying de novo SVs are frequently unknown. Methods:We applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with multiple congenital abnormalities and/or intellectual disability harboring apparent de novo SVs, most with an inconclusive diagnosis after regular genetic testing. Results: In 7 of these cases (18%), whole-genome sequencing analysis revealed disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict the effects on genes directly affected by SVs and on genes indirectly affected likely due to the changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In 8 cases, evidence was found for the involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to two cohorts containing a total of 379 patients with previously detected and classified de novo SVs and identified candidate driver genes in 189 cases (50%), including 40 cases whose SVs were previously not classified as pathogenic. Pathogenic position effects were predicted in 28% of all studied cases with balanced SVs and in 11% of the cases with copy number variants. Conclusions:These results demonstrate an integrated computational and experimental approach to predict driver genes based on analyses of WGS data with phenotype association and chromatin organization datasets. These analyses nominate new pathogenic loci and have strong potential to improve the molecular diagnosis of patients with de novo SVs

    Serious mental illness and smoking cessation

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    Smoking rates among individuals with severe mental illness are significantly higher than in the general population. Contrary to common perception, individuals with severe mental illness have been shown to be motivated to quit smoking. This paper discusses and synthesises literature on smoking among individuals with severe mental illness and contributes to the debate about the significant role mental health professionals can play in targeting the effective cessation therapies towards smokers with severe mental illness. Severe mental illnesses include schizophrenia, paranoid and other psychotic disorders, psychotic depression, bipolar affective disorder, major depression

    Measurement of the tt¯tt¯ production cross section in pp collisions at √s=13 TeV with the ATLAS detector

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    A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb

    Measurements of W+W−+ ≥ 1 jet production cross-sections in pp collisions at s \sqrt{s} = 13 TeV with the ATLAS detector

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    Fiducial and differential cross-section measurements of W+W− production in association with at least one hadronic jet are presented. These measurements are sensitive to the properties of electroweak-boson self-interactions and provide a test of perturbative quantum chromodynamics and the electroweak theory. The analysis is performed using proton-proton collision data collected at p s = 13TeV with the ATLAS experiment, corresponding to an integrated luminosity of 139 fb−1. Events are selected with exactly one oppositely charged electron-muon pair and at least one hadronic jet with a transverse momentum of pT > 30 GeV and a pseudorapidity of |�| < 4.5. After subtracting the background contributions and correcting for detector effects, the jet-inclusive W+W−+ � 1 jet fiducial cross-section and W+W−+ jets differential cross-sections with respect to several kinematic variables are measured. These measurements include leptonic quantities, such as the lepton transverse momenta and the transverse mass of the W+W− system, as well as jet-related observables such as the leading jet transverse momentum and the jet multiplicity. Limits on anomalous triple-gauge-boson couplings are obtained in a phase space where interference between the Standard Model amplitude and the anomalous amplitude is enhanced

    Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

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    Non-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010–2012) and Run 2 (2015–2018) of the Large Hadron Collider. The extracted fluence shows a much stronger |z|-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.publishedVersio

    Measurement of the energy asymmetry in t(t)over-barj production at 13 TeV with the ATLAS experiment and interpretation in the SMEFT framework

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    A measurement of the energy asymmetry in jet-associated top-quark pair production is presented using 139fb1139\,{\mathrm {fb}}^{-1} 139 fb - 1 of data collected by the ATLAS detector at the Large Hadron Collider during pp collisions at s=13TeV\sqrt{s}=13\,\text {TeV} s = 13 TeV . The observable measures the different probability of top and antitop quarks to have the higher energy as a function of the jet scattering angle with respect to the beam axis. The energy asymmetry is measured in the semileptonic ttˉt{\bar{t}} t t ¯ decay channel, and the hadronically decaying top quark must have transverse momentum above 350GeV350\,\text {GeV} 350 GeV . The results are corrected for detector effects to particle level in three bins of the scattering angle of the associated jet. The measurement agrees with the SM prediction at next-to-leading-order accuracy in quantum chromodynamics in all three bins. In the bin with the largest expected asymmetry, where the jet is emitted perpendicular to the beam, the energy asymmetry is measured to be 0.043±0.020-0.043\pm 0.020 - 0.043 ± 0.020 , in agreement with the SM prediction of 0.037±0.003-0.037\pm 0.003 - 0.037 ± 0.003 . Interpreting this result in the framework of the Standard Model effective field theory (SMEFT), it is shown that the energy asymmetry is sensitive to the top-quark chirality in four-quark operators and is therefore a valuable new observable in global SMEFT fits

    Determination of the parton distribution functions of the proton using diverse ATLAS data from pp collisions at √s = 7, 8 and 13 TeV

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    This paper presents an analysis at next-to-next-to-leading order in the theory of quantum chromodynamics for the determination of a new set of proton parton distribution functions using diverse measurements in pp collisions at \sqrt{s} = 7, 8 and 13 TeV, performed by the ATLAS experiment at the Large Hadron Collider, together with deep inelastic scattering data from ep collisions at the HERA collider. The ATLAS data sets considered are differential cross-section measurements of inclusive W^{±} and Z/gamma^{*} boson production, W^{±} and Z boson production in association with jets, t\bar{t} production, inclusive jet production and direct photon production. In the analysis, particular attention is paid to the correlation of systematic uncertainties within and between the various ATLAS data sets and to the impact of model, theoretical and parameterisation uncertainties. The resulting set of parton distribution functions is called ATLASpdf21

    Modelling and computational improvements to the simulation of single vector-boson plus jet processes for the ATLAS experiment

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    This paper presents updated Monte Carlo configurations used to model the production of single electroweak vector bosons (W, Z/gamma*) in association with jets in proton-proton collisions for the ATLAS experiment at the Large Hadron Collider. Improvements pertaining to the electroweak input scheme, parton-shower splitting kernels and scale-setting scheme are shown for multi-jet merged configurations accurate to next-to-leading order in the strong and electroweak couplings. The computational resources required for these set-ups are assessed, and approximations are introduced resulting in a factor three reduction of the per-event CPU time without affecting the physics modelling performance. Continuous statistical enhancement techniques are introduced by ATLAS in order to populate low cross-section regions of phase space and are shown to match or exceed the generated effective luminosity. This, together with the lower per-event CPU time, results in a 50% reduction in the required computing resources compared to a legacy set-up previously used by the ATLAS collaboration. The set-ups described in this paper will be used for future ATLAS analyses and lay the foundation for the next generation of Monte Carlo predictions for single vector-boson plus jets production
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