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

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

How to promote, improve and test adherence to scientific evidence in clinical practice

BACKGROUND: Negative variation in the management of patients with the same clinical condition is frequent, and affects quality of care. Recent studies indicate that single interventions are not an effective solution. We aim to demonstrate that a multifaceted strategy can favor the introduction of research into practice, and to assess its long-term effects on a set of common medical conditions exhibiting significant negative variation at our institution. METHODS: The strategy, devised and agreed upon by a multidisciplinary group, was first applied to one relevant medical condition – cerebral ischemic stroke. To test its effectiveness a quasi-experimental study was conducted, comparing an intervention group with historical controls. After validation the strategy was extended to other pathologies, and its long-term effect measured using evidence-based quality indicators. Adherence to each indicator was determined prospectively on a six-month basis for a period of at least two consecutive years. Measures are expressed as proportions with 95% confidence intervals. RESULTS: Validation findings demonstrated that the strategy improved compliance with scientific evidence: the percentage of patients who received a CT scan within 24 hours of hospital presentation rose from 56% to 75%, (χ(2 )= 7.43 p < 0.01); admissions to selected wards increased from 45% to 64%, (χ(2 )= 7.81 p < 0.01); the number of physical medicine visits within 24 hours of the request grew from 59% to 91% (χ(2 )= 14,40 p < 0.001). Over a four-year period the program was gradually applied to 14 medical conditions. Except for 3 cases, compliance with the pathway, i.e. number of eligible patients for whom data on the care process is collected, was above the minimum requirement of 75%. Indicator adherence generally exhibited a positive trend, though variability was observed both among different conditions and between different semesters for the same pathology. CONCLUSION: According to our experience, incorporation of research into practice can be favored by systematically applying a shared, multifaceted strategy, involving multidisciplinary teams supported by central coordination. Institutions should device a tailor-made approach, should train personnel on implementation strategies, and create cultural acceptance of change. Just like for experimental trials, human and economic resources should be allocated within health care services to allow the achievement of this objective

Genes left behind: Climate change threatens cryptic genetic diversity in the canopy-forming seaweed bifurcaria bifurcata

The global redistribution of biodiversity will intensify in the coming decades of climate change, making projections of species range shifts and of associated genetic losses important components of conservation planning. Highly-structured marine species, notably brown seaweeds, often harbor unique genetic variation at warmer low-latitude rear edges and thus are of particular concern. Here, a combination of Ecological Niche Models (ENMs) and molecular data is used to forecast the potential near-future impacts of climate change for a warm-temperate, canopy forming seaweed, Bifurcaria bifurcata. ENMs for B. bifurcata were developed using marine and terrestrial climatic variables, and its range projected for 2040-50 and 2090-2100 under two greenhouse emission scenarios. Geographical patterns of genetic diversity were assessed by screening 18 populations spawning the entire distribution for two organelle genes and 6 microsatellite markers. The southern limit of B. bifurcata was predicted to shift northwards to central Morocco by the mid-century. By 2090-2100, depending on the emission scenario, it could either retreat further north to western Iberia or be relocated back to Western Sahara. At the opposing margin, B. bifurcata was predicted to expand its range to Scotland or even Norway. Microsatellite diversity and endemism were highest in Morocco, where a unique and very restricted lineage was also identified. Our results imply that B. bifurcata will maintain a relatively broad latitudinal distribution. Although its persistence is not threatened, the predicted extirpation of a unique southern lineage or even the entire Moroccan diversity hotspot will erase a rich evolutionary legacy and shrink global diversity to current (low) European levels. NW Africa and similarly understudied southern regions should receive added attention if expected range changes and diversity loss of warm-temperate species is not to occur unnoticed.Portuguese FCT (Fundacao para a Ciencia e a Tecnologia) [PTDC/AAC-CLI/109108/2008, EXPL/BIA-BIC/1471/2012, EXCL/AAG-GLO/0661/2012]; [SFRH/BPD/88935/2012]info:eu-repo/semantics/publishedVersio

Search for heavy neutral Higgs bosons produced in association with b-quarks and decaying into b-quarks at root s=13 TeV with the ATLAS detector

A search for heavy neutral Higgs bosons produced in association with one or two b -quarks and decaying to b -quark pairs is presented using 27.8  fb − 1 of √ s = 13  TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider during 2015 and 2016. No evidence of a signal is found. Upper limits on the heavy neutral Higgs boson production cross section times its branching ratio to b ¯ b are set, ranging from 4.0 to 0.6 pb at 95% confidence level over a Higgs boson mass range of 450 to 1400 GeV. Results are interpreted within the two-Higgs-doublet model and the minimal supersymmetric Standard Model

Measurement of single top-quark production in association with a W boson in the single-lepton channel at \sqrt{s} = 8\,\text {TeV} with the ATLAS detector

The production cross-section of a top quark in association with a W boson is measured using proton–proton collisions at \sqrt{s} = 8\,\text {TeV}. The dataset corresponds to an integrated luminosity of 20.2\,\text {fb}^{-1}, and was collected in 2012 by the ATLAS detector at the Large Hadron Collider at CERN. The analysis is performed in the single-lepton channel. Events are selected by requiring one isolated lepton (electron or muon) and at least three jets. A neural network is trained to separate the tW signal from the dominant t{\bar{t}} background. The cross-section is extracted from a binned profile maximum-likelihood fit to a two-dimensional discriminant built from the neural-network output and the invariant mass of the hadronically decaying W boson. The measured cross-section is \sigma _{tW} = 26 \pm 7\,\text {pb}, in good agreement with the Standard Model expectation

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

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

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

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

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

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