483 research outputs found

    Optical properties and composition of viscous organic particles found in the Southern Great Plains

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    Atmospheric high-viscosity organic particles (HVOPs) were observed in samples of ambient aerosols collected in April and May 2016 in the Southern Great Plains of the United States. These particles were apportioned as either airborne soil organic particles (ASOPs) or tar balls (TBs) from biomass burning based on spetro-microscopic imaging and assessments of meteorological records of smoke and precipitation data. Regardless of their apportionment, the number fractions of HVOPs were positively correlated (R2=0.85) with increased values of absorption Ångström exponent (AAE) measured in situ for ambient aerosol at the site. Extending this correlation to 100 % HVOPs yields an AAE of 2.6, similar to previous literature reports of the class of light-absorbing organic particles known as brown carbon (BrC). One out of the three samples investigated had a significant number of ASOPs, while the other two samples contained TBs. Although there are chemical similarities between ASOPs and TBs, they can be distinguished based on composition inferred from near-edge absorption X-ray fine structure (NEXAFS) spectroscopy. ASOPs were distinguished from TBs based on their average − COOH/C = C and − COOH/COH peak ratios, with ASOPs having lower ratios. NEXAFS spectra of filtered soil organic brine particles nebulized from field samples of standing water deposited after rain were consistent with ASOPs when laboratory particles were generated by bubble bursting at the air–organic brine interface. However, particles generated by nebulizing the bulk volume of soil organic brine had a particle composition different from ASOPs. These observations are consistent with the raindrop generation mechanism responsible for ASOP emissions in the area of study. In contrast, nebulized samples carry with them higher fractions of soil inorganics dissolved in the bulk volume of soil brine, which are not aerosolized by the raindrop mechanism. Our results support the bubble bursting mechanism of particle generation during rainfall resulting in the ejection of soil organics into the atmosphere. In addition, our results show that ASOPs may only be atmospherically relevant during times when suitable emission conditions are met

    Brain transplantation of genetically corrected Sanfilippo type B neural stem cells induces partial cross-correction of the disease

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    Sanfilippo syndrome type B (mucopolysaccharidosis type IIIB) is a recessive genetic disorder that severely affects the brain due to a deficiency in the enzyme α

    Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15

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    Two complementary techniques, Scanning Transmission X-ray Microscopy/Near Edge Fine Structure spectroscopy (STXM/NEXAFS) and Scanning Electron Microscopy/Energy Dispersive X-ray spectroscopy (SEM/EDX), have been quantitatively combined to characterize individual atmospheric particles. This pair of techniques was applied to particle samples at three sampling sites (ATTO, ZF2, and T3) in the Amazon basin as part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) field campaign during the dry season of 2014. The combined data was subjected to k-means clustering using mass fractions of the following elements: C, N, O, Na, Mg, P, S, Cl, K, Ca, Mn, Fe, Ni, and Zn. Cluster analysis identified 12 particle types across different sampling sites and particle sizes. Samples from the remote Amazon Tall Tower Observatory (ATTO, also T0a) exhibited less cluster variety and fewer anthropogenic clusters than samples collected at the sites nearer to the Manaus metropolitan region, ZF2 (also T0t) or T3. Samples from the ZF2 site contained aged/anthropogenic clusters not readily explained by transport from ATTO or Manaus, possibly suggesting the effects of long range atmospheric transport or other local aerosol sources present during sampling. In addition, this data set allowed for recently established diversity parameters to be calculated. All sample periods had high mixing state indices (χ) that were \u3e0.8. Two individual particle diversity (Di) populations were observed, with particles \u3c0.5 µm having a Di of ~2.4 and \u3e0.5 µm particles having a Di of ~3.6, which likely correspond to fresh and aged aerosols, respectively. The diversity parameters determined by the quantitative method presented here will serve to aid in the accurate representation of aerosol mixing state, source apportionment, and aging in both less polluted and more developed environments in the Amazon Basin

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger

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    The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the newMultichip Modules along with the improvements to the signal processing achieved.ANPCyTYerPhI, ArmeniaAustralian Research CouncilBMWFW, AustriaAustrian Science Fund (FWF)Azerbaijan National Academy of Sciences (ANAS)SSTC, BelarusNational Council for Scientific and Technological Development (CNPq)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Natural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationNational Natural Science Foundation of China (NSFC)Departamento Administrativo de Ciencia, Tecnología e Innovación ColcienciasMinistry of Education, Youth & Sports - Czech Republic Czech Republic GovernmentCzech Republic GovernmentDNRF, DenmarkDanish Natural Science Research CouncilCentre National de la Recherche Scientifique (CNRS)CEA-DRF/IRFU, FranceFederal Ministry of Education & Research (BMBF)Max Planck SocietyGreek Ministry of Development-GSRTRGC and Hong Kong SAR, ChinaIsrael Science FoundationBenoziyo Center, IsraelIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of ScienceCNRST, MoroccoRCN, NorwayPortuguese Foundation for Science and TechnologyMNE/IFA, RomaniaMES of RussiaMESTD, SerbiaMSSR, SlovakiaSlovenian Research Agency - SloveniaMIZS, SloveniaSpanish GovernmentSRC, SwedenWallenberg Foundation, SwedenSNSF Geneva, SwitzerlandMinistry of Science and Technology, TaiwanMinistry of Energy & Natural Resources - TurkeyScience & Technology Facilities Council (STFC)United States Department of Energy (DOE)National Science Foundation (NSF)BCKDF, CanadaCANARIE, CanadaCRC, CanadaEuropean Research Council (ERC)European Union (EU)French National Research Agency (ANR)German Research Foundation (DFG)Alexander von Humboldt FoundationGreek NSRF, GreeceBSF-NSF, IsraelGerman-Israeli Foundation for Scientific Research and DevelopmentLa Caixa Banking Foundation, SpainCERCA Programme Generalitat de Catalunya, SpainPROMETEO, SpainGenT Programmes Generalitat Valenciana, SpainGoran Gustafssons Stiftelse, SwedenRoyal Society of LondonLeverhulme TrustNRC, CanadaCERNANID, ChileChinese Academy of SciencesMinistry of Science and Technology, ChinaSRNSFG, GeorgiaHGF, GermanyNetherlands Organization for Scientific Research (NWO) Netherlands GovernmentMinistry of Science and Higher Education, PolandNCN, PolandNRCKI, Russia FederationJINRDST/NRF, South AfricaSERI, Geneva, SwitzerlandCantons of Bern and Geneva, SwitzerlandCompute Canada, CanadaHorizon 2020Marie Sklodowska-Curie ActionsEuropean Cooperation in Science and Technology (COST)EU-ESF, Greec

    Measurement of hadronic event shapes in high-p T multijet final states at √s = 13 TeV with the ATLAS detector

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    A measurement of event-shape variables in proton-proton collisions at large momentum transfer is presented using data collected at s = 13 TeV with the ATLAS detector at the Large Hadron Collider. Six event-shape variables calculated using hadronic jets are studied in inclusive multijet events using data corresponding to an integrated luminosity of 139 fb−1. Measurements are performed in bins of jet multiplicity and in different ranges of the scalar sum of the transverse momenta of the two leading jets, reaching scales beyond 2 TeV. These measurements are compared with predictions from Monte Carlo event generators containing leading-order or next-to-leading order matrix elements matched to parton showers simulated to leading-logarithm accuracy. At low jet multiplicities, shape discrepancies between the measurements and the Monte Carlo predictions are observed. At high jet multiplicities, the shapes are better described but discrepancies in the normalisation are observed. [Figure not available: see fulltext.

    Measurement of the azimuthal anisotropy of charged-particle production in Xe+Xe collisions at sNN =5.44 TeV with the ATLAS detector

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    This paper describes the measurements of flow harmonics v2-v6 in 3μb-1 of Xe+Xe collisions at sNN=5.44 TeV performed using the ATLAS detector at the Large Hadron Collider (LHC). Measurements of the centrality, multiplicity, and pT dependence of the vn obtained using two-particle correlations and the scalar product technique are presented. The measurements are also performed using a template-fit procedure, which was developed to remove nonflow correlations in small collision systems. This nonflow removal is shown to have a significant influence on the measured vn at high pT, especially in peripheral events. Comparisons of the measured vn with measurements in Pb+Pb collisions and p+Pb collisions at sNN=5.02 TeV are also presented. The vn values in Xe+Xe collisions are observed to be larger than those in Pb+Pb collisions for n=2, 3, and 4 in the most central events. However, with decreasing centrality or increasing harmonic order n, the vn values in Xe+Xe collisions become smaller than those in Pb+Pb collisions. The vn in Xe+Xe and Pb+Pb collisions are also compared as a function of the mean number of participating nucleons, (Npart), and the measured charged-particle multiplicity in the detector. The v3 values in Xe+Xe and Pb+Pb collisions are observed to be similar at the same (Npart) or multiplicity, but the other harmonics are significantly different. The ratios of the measured vn in Xe+Xe and Pb+Pb collisions, as a function of centrality, are also compared to theoretical calculations

    Alignment of the ATLAS Inner Detector in Run 2

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    The performance of the ATLAS Inner Detector alignment has been studied using pp collision data at v s = 13 TeV collected by the ATLAS experiment during Run 2 (2015-2018) of the Large Hadron Collider (LHC). The goal of the detector alignment is to determine the detector geometry as accurately as possible and correct for time-dependent movements. The Inner Detector alignment is based on the minimization of track-hit residuals in a sequence of hierarchical levels, from global mechanical assembly structures to local sensors. Subsequent levels have increasing numbers of degrees of freedom; in total there are almost 750,000. The alignment determines detector geometry on both short and long timescales, where short timescales describe movementswithin anLHCfill. The performance and possible track parameter biases originating from systematic detector deformations are evaluated. Momentum biases are studied using resonances decaying to muons or to electrons. The residual sagitta bias and momentum scale bias after alignment are reduced to less than similar to 0.1 TeV-1 and 0.9 x 10(-3), respectively. Impact parameter biases are also evaluated using tracks within jets

    Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector

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    This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A → BC, for mA ∼ OðTeVÞ, mB; mC ∼ Oð100 GeVÞ and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 ffiffi s p ¼ 13 TeV pp collision dataset of 139 fb−1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA ¼ 3 TeV and mB ≳ 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model boson

    Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at \sqrt{s}=13 TeV

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    This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 \hbox {fb}^{-1} of pp collision data at \sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z\rightarrow \mu \mu and J/\psi \rightarrow \mu \mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |\eta |<2.7
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