4,181 research outputs found

    Challenges with Delivering Gender-Specific and Comprehensive Primary Care to Women Veterans

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    Background The growing presence of women veterans in Veterans Administration (VA) settings has prompted the need for greater attention to clinical proficiency related to women's health (WH) primary care needs. Instead of making appointments for multiple visits or referring patients to a WH clinic or alternate site for gender-specific care, a comprehensive primary care model now allows for women veteran patients be seen by primary care providers (PCPs) who have WH training/experience and can see patients for both primary and WH care in the context of a single visit. However, little is currently known about the barriers and facilitators WH-PCPs face in using this approach to incorporate gender-specific services into women veterans' primary care services. Methods We conducted qualitative in-depth interviews with 22 WH-PCPs at one Midwestern VA Medical Center. All participants were members of one of four outpatient primary care clinics within the main medical center, one off-site satellite clinic, or two off-site community-based outpatient clinics. Results Inductive thematic analysis identified six themes: 1) Time constraints, 2) importance of staff support, 3) necessity of sufficient space and equipment/supplies, 4) perceptions of discomfort among patients with trauma histories, 5) lack of education/training, and 6) challenges with scheduling/logistics. Conclusion Although adequate staff was a key facilitator, the findings suggest that there may be barriers that undermine the ability of VA WH-PCPs to provide high-quality, comprehensive primary and gender-specific care. The nature of these barriers is multifactorial and multilevel in nature, and may therefore require special policy and practice action

    Sort and Sift, Think and Shift: Let the Data Be Your Guide An Applied Approach to Working With, Learning From, and Privileging Qualitative Data

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    The Sort and Sift, Think and Shift qualitative data analysis approach is an iterative process where analysts dive into data to understand its content, dimensions, and properties, and then step back to assess what they have learned and to determine next steps. Researchers move from establishing an understanding of what is in the data (“Diving In”) to exploring their relationship to the data (“Stepping Back”). This process of “Diving In” and “Stepping Back” is repeated throughout analysis. To conclude, researchers arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge. To illustrate core tenets of Sort and Sift, Think and Shift, we analyzed three focus group transcripts from a study of postnatal care referral behavior by traditional birth attendants in Nigeria; these transcripts came from Syracuse University’s Qualitative Data Repository and were unfamiliar to the analytic team prior to this exercise. We focused on letting the data be our guide into not only the explicit purpose of the interviews, but also into the unexpected discoveries that arise when inquiring about people’s lived experiences. Situating our efforts within an Initial Learning Period, each member of the team closely read each transcript, and then identified powerful quotations that made us pause and take note. We documented what we learned from each transcript in an episode profile which contained diagrams and memos. Episode profiles were shared and discussed across the team to identify key points of interest, such as the role of faith in women’s decision-making processes related to their pregnancy and delivery preferences, and concepts of who bears what knowledge about reproductive health. Our engagement in this analytic exercise demonstrates the applicability of qualitative inquiry and Sort and Sift as flexible approaches for applied research

    Quantitative analysis of powder mixtures by raman spectrometry : the influence of particle size and its correction

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    Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness

    Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using √s=8 TeV proton-proton collision data

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    A search for squarks and gluinos in final states containing high-p T jets, missing transverse momentum and no electrons or muons is presented. The data were recorded in 2012 by the ATLAS experiment in s√=8 TeV proton-proton collisions at the Large Hadron Collider, with a total integrated luminosity of 20.3 fb−1. Results are interpreted in a variety of simplified and specific supersymmetry-breaking models assuming that R-parity is conserved and that the lightest neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1330 GeV for a simplified model incorporating only a gluino and the lightest neutralino. For a simplified model involving the strong production of first- and second-generation squarks, squark masses below 850 GeV (440 GeV) are excluded for a massless lightest neutralino, assuming mass degenerate (single light-flavour) squarks. In mSUGRA/CMSSM models with tan β = 30, A 0 = −2m 0 and μ > 0, squarks and gluinos of equal mass are excluded for masses below 1700 GeV. Additional limits are set for non-universal Higgs mass models with gaugino mediation and for simplified models involving the pair production of gluinos, each decaying to a top squark and a top quark, with the top squark decaying to a charm quark and a neutralino. These limits extend the region of supersymmetric parameter space excluded by previous searches with the ATLAS detector

    Measurement of the top quark-pair production cross section with ATLAS in pp collisions at \sqrt{s}=7\TeV

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    A measurement of the production cross-section for top quark pairs(\ttbar) in pppp collisions at \sqrt{s}=7 \TeV is presented using data recorded with the ATLAS detector at the Large Hadron Collider. Events are selected in two different topologies: single lepton (electron ee or muon μ\mu) with large missing transverse energy and at least four jets, and dilepton (eeee, μμ\mu\mu or eμe\mu) with large missing transverse energy and at least two jets. In a data sample of 2.9 pb-1, 37 candidate events are observed in the single-lepton topology and 9 events in the dilepton topology. The corresponding expected backgrounds from non-\ttbar Standard Model processes are estimated using data-driven methods and determined to be 12.2±3.912.2 \pm 3.9 events and 2.5±0.62.5 \pm 0.6 events, respectively. The kinematic properties of the selected events are consistent with SM \ttbar production. The inclusive top quark pair production cross-section is measured to be \sigmattbar=145 \pm 31 ^{+42}_{-27} pb where the first uncertainty is statistical and the second systematic. The measurement agrees with perturbative QCD calculations.Comment: 30 pages plus author list (50 pages total), 9 figures, 11 tables, CERN-PH number and final journal adde

    Inclusive search for same-sign dilepton signatures in pp collisions at root s=7 TeV with the ATLAS detector

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    An inclusive search is presented for new physics in events with two isolated leptons (e or mu) having the same electric charge. The data are selected from events collected from p p collisions at root s = 7 TeV by the ATLAS detector and correspond to an integrated luminosity of 34 pb(-1). The spectra in dilepton invariant mass, missing transverse momentum and jet multiplicity are presented and compared to Standard Model predictions. In this event sample, no evidence is found for contributions beyond those of the Standard Model. Limits are set on the cross-section in a fiducial region for new sources of same-sign high-mass dilepton events in the ee, e mu and mu mu channels. Four models predicting same-sign dilepton signals are constrained: two descriptions of Majorana neutrinos, a cascade topology similar to supersymmetry or universal extra dimensions, and fourth generation d-type quarks. Assuming a new physics scale of 1 TeV, Majorana neutrinos produced by an effective operator V with masses below 460 GeV are excluded at 95% confidence level. A lower limit of 290 GeV is set at 95% confidence level on the mass of fourth generation d-type quarks

    Measurement of the production of a W boson in association with a charm quark in pp collisions at √s = 7 TeV with the ATLAS detector

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    The production of a W boson in association with a single charm quark is studied using 4.6 fb−1 of pp collision data at s√ = 7 TeV collected with the ATLAS detector at the Large Hadron Collider. In events in which a W boson decays to an electron or muon, the charm quark is tagged either by its semileptonic decay to a muon or by the presence of a charmed meson. The integrated and differential cross sections as a function of the pseudorapidity of the lepton from the W-boson decay are measured. Results are compared to the predictions of next-to-leading-order QCD calculations obtained from various parton distribution function parameterisations. The ratio of the strange-to-down sea-quark distributions is determined to be 0.96+0.26−0.30 at Q 2 = 1.9 GeV2, which supports the hypothesis of an SU(3)-symmetric composition of the light-quark sea. Additionally, the cross-section ratio σ(W + +c¯¯)/σ(W − + c) is compared to the predictions obtained using parton distribution function parameterisations with different assumptions about the s−s¯¯¯ quark asymmetry

    Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

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    The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal
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