254 research outputs found

    Is the Sun Embedded in a Typical Interstellar Cloud?

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    The physical properties and kinematics of the partially ionized interstellar material near the Sun are typical of warm diffuse clouds in the solar vicinity. The interstellar magnetic field at the heliosphere and the kinematics of nearby clouds are naturally explained in terms of the S1 superbubble shell. The interstellar radiation field at the Sun appears to be harder than the field ionizing ambient diffuse gas, which may be a consequence of the low opacity of the tiny cloud surrounding the heliosphere. The spatial context of the Local Bubble is consistent with our location in the Orion spur.Comment: "From the Outer Heliosphere to the Local Bubble", held at International Space Sciences Institute, October 200

    What Physical Processes Drive the Interstellar Medium in the Local Bubble?

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    Recent 3D high-resolution simulations of the interstellar medium in a star form- ing galaxy like the Milky Way show that supernova explosions are the main driver of the structure and evolution of the gas. Its physical state is largely controlled by turbulence due to the high Reynolds numbers of the average flows. For a constant supernova rate a dynam- ical equilibrium is established within 200 Myr of simulation as a consequence of the setup of a galactic fountain. The resulting interstellar medium reveals a typical density/pressure pattern, i.e. distribution of so-called gas phases, on scales of 500–700 pc, with interstellar bubbles being a common phenomenon just like the Local Bubble and the Loop I superbub- ble, which are assumed to be interacting. However, modeling the Local Bubble is special, because it is driven by a moving group, passing through its volume, as it is inferred from the analysis of Hipparcos data. A detailed analysis reveals that between 14 and 19 super- novae have exploded during the last 15 Myr. The age of the Local Bubble is derived from comparison with HI and UV absorption line data to be 14.5±0.7 Myr. We further predict the 0.4merging of the two bubbles in about 3 Myr from now, when the interaction shell starts to fragment. The Local Cloud and its companion HI clouds are the consequence of a dynamical instability in the interaction shell between the Local and the Loop I bubble

    Psychology and aggression

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

    National identity predicts public health support during a global pandemic

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    Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.publishedVersio

    The genetic architecture of the human cerebral cortex

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    INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

    The performance of the jet trigger for the ATLAS detector during 2011 data taking

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    The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction

    Measurement of the branching ratio Γ(Λb⁰ → ψ(2S)Λ0)/Γ(Λb⁰ → J/ψΛ0) with the ATLAS detector

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    An observation of the Λb0ψ(2S)Λ0\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0 decay and a comparison of its branching fraction with that of the Λb0J/ψΛ0\Lambda_b^0 \rightarrow J/\psi \Lambda^0 decay has been made with the ATLAS detector in proton--proton collisions at s=8\sqrt{s}=8\,TeV at the LHC using an integrated luminosity of 20.620.6\,fb1^{-1}. The J/ψJ/\psi and ψ(2S)\psi(2S) mesons are reconstructed in their decays to a muon pair, while the Λ0pπ\Lambda^0\rightarrow p\pi^- decay is exploited for the Λ0\Lambda^0 baryon reconstruction. The Λb0\Lambda_b^0 baryons are reconstructed with transverse momentum pT>10p_{\rm T}>10\,GeV and pseudorapidity η<2.1|\eta|<2.1. The measured branching ratio of the Λb0ψ(2S)Λ0\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0 and Λb0J/ψΛ0\Lambda_b^0 \rightarrow J/\psi \Lambda^0 decays is Γ(Λb0ψ(2S)Λ0)/Γ(Λb0J/ψΛ0)=0.501±0.033(stat)±0.019(syst)\Gamma(\Lambda_b^0 \rightarrow \psi(2S)\Lambda^0)/\Gamma(\Lambda_b^0 \rightarrow J/\psi\Lambda^0) = 0.501\pm 0.033 ({\rm stat})\pm 0.019({\rm syst}), lower than the expectation from the covariant quark model.Comment: 12 pages plus author list (28 pages total), 5 figures, 1 table, published on Physics Letters B 751 (2015) 63-80. All figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/BPHY-2013-08

    Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

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    This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

    Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at sqrt [ s ] = 13TeV

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    A search for physics beyond the Standard Model, in final states with at least one high transverse momentum charged lepton (electron or muon) and two additional high transverse momentum leptons or jets, is performed using 3.2 fb−1 of proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015 at √s = 13 TeV. The upper end of the distribution of the scalar sum of the transverse momenta of leptons and jets is sensitive to the production of high-mass objects. No excess of events beyond Standard Model predictions is observed. Exclusion limits are set for models of microscopic black holes with two to six extra dimensions
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