Racism as a determinant of health: a systematic review and meta-analysis

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants.<br /

A search for pair-produced resonances in four-jet final states at root s=13 TeV with the ATLAS detector

A search for massive coloured resonances which are pair-produced and decay into two jets is presented. The analysis uses 36.7 fb−1 − 1 of √ s = 13 TeV pp collision data recorded by the ATLAS experiment at the LHC in 2015 and 2016. No significant deviation from the background prediction is observed. Results are interpreted in a SUSY simplified model where the lightest supersymmetric particle is the top squark, ̃ t ~ , which decays promptly into two quarks through R-parity-violating couplings. Top squarks with masses in the range 100 GeV<̃<410 100 GeV < m t ~ < 410 GeV GeV are excluded at 95% confidence level. If the decay is into a b-quark and a light quark, a dedicated selection requiring two b-tags is used to exclude masses in the ranges 100 GeV<̃<470 100 GeV < m t ~ < 470 GeV GeV and 480 GeV<̃<610 480 GeV < m t ~ < 610 GeV GeV . Additional limits are set on the pair-production of massive colour-octet resonances

Identification and rejection of pile-up jets at high pseudorapidity with the ATLAS detector

The rejection of forward jets originating from additional proton–proton interactions (pile-up) is crucial for a variety of physics analyses at the LHC, including Standard Model measurements and searches for physics beyond the Standard Model. The identification of such jets is challenging due to the lack of track and vertex information in the pseudorapidity range |η| &gt; 2.5. This paper presents a novel strategy for forward pile-up jet tagging that exploits jet shapes and topological jet correlations in pile-up interactions. Measurements of the per-jet tagging efficiency are presented using a data set of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of 13 TeV collected with the ATLAS detector. The fraction of pile-up jets rejected in the range 2.5 &lt; |η| &lt; 4.5 is estimated in simulated events with an average of 22 interactions per bunch-crossing. It increases with jet transverse momentum and, for jets with transverse momentum between 20 and 50 GeV, it ranges between 49% and 67% with an efficiency of 85% for selecting hard-scatter jets. A case study is performed in Higgs boson production via the vector-boson fusion process, showing that these techniques mitigate the background growth due to additional proton–proton interactions, thus enhancing the reach for such signatures

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of highenergy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb(-1) of data collected by the ATLAS experiment and simulation of protonproton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of chargedparticle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, datadriven, method. The method uses the energy loss, dE/ dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, themeasured fraction that fail to be reconstructed is 0.061 +/- 0.006 (stat.) +/- 0.014 (syst.) and 0.093 +/- 0.017 (stat.) +/- 0.021 (syst.) for jet transverse momenta of 200-400GeV and 1400-1600GeV, respectively

Identification and rejection of pile-up jets at high pseudorapidity with the ATLAS detector (vol 77, 580, 2017)

SCOAP