227 research outputs found

    Building a Community-Academic Partnership to Improve Screening for Intimate Partner Violence: Integrating Advocates in Healthcare Clinic Settings

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    Aims To develop an innovative community-academic partnership to advance, test and promote intimate partner violence screening and referral protocols by comparing the effect of integrating intimate partner violence advocates versus enhancing medical training in medical clinic settings serving women from vulnerable populations. Detecting intimate partner violence in healthcare settings allows for survivors to connect to safety and referral resources prior to violence escalating. Screening for intimate partner violence and connecting patients to referral resources requires creating a safe and trusting relationship between healthcare providers and patients. Developing screening and referral protocols responsive to survivors\u27 needs requires involvement of clinic staff, survivors and community agencies that support survivors. Design Three phases of the project include Discovery, Implementation and Dissemination. Mixed-methodology will help in understanding current practices and effects of interventions. Methods Actions included in each phase: Discovery: 1) nurse-led focus groups of clinic staff, providers and survivors to understand current clinic practices; 2) retrospective chart review of the number of screens performed, positive screens detected and interventions performed. Implementation: 1) randomization of patients to be interviewed by a trained advocate or by healthcare provider with enhanced training; and 2) assess the number of screenings and referrals performed in each arm and 3) evaluate outcomes of intervention. Dissemination through: presentations, manuscripts and policy recommendations at the institutional and regional level. This IRB-approved proposal was funded in July 2021 by an Advancing a Healthier Wisconsin grant. Discussion The partnership has improved channels of communication and understanding between diverse clinical care providers, survivors and community agency staff as they navigate the complex challenges to the development and integration of screening and referral protocols. Impact This project will provide evidence of the most effective intimate partner violence screening and referral methodology that can be utilized in a wide variety of medical settings

    Weak Lensing with SDSS Commissioning Data: The Galaxy-Mass Correlation Function To 1/h Mpc

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    (abridged) We present measurements of galaxy-galaxy lensing from early commissioning imaging data from the Sloan Digital Sky Survey (SDSS). We measure a mean tangential shear around a stacked sample of foreground galaxies in three bandpasses out to angular radii of 600'', detecting the shear signal at very high statistical significance. The shear profile is well described by a power-law. A variety of rigorous tests demonstrate the reality of the gravitational lensing signal and confirm the uncertainty estimates. We interpret our results by modeling the mass distributions of the foreground galaxies as approximately isothermal spheres characterized by a velocity dispersion and a truncation radius. The velocity dispersion is constrained to be 150-190 km/s at 95% confidence (145-195 km/s including systematic uncertainties), consistent with previous determinations but with smaller error bars. Our detection of shear at large angular radii sets a 95% confidence lower limit s>140s>140^{\prime\prime}, corresponding to a physical radius of 260h1260h^{-1} kpc, implying that galaxy halos extend to very large radii. However, it is likely that this is being biased high by diffuse matter in the halos of groups and clusters. We also present a preliminary determination of the galaxy-mass correlation function finding a correlation length similar to the galaxy autocorrelation function and consistency with a low matter density universe with modest bias. The full SDSS will cover an area 44 times larger and provide spectroscopic redshifts for the foreground galaxies, making it possible to greatly improve the precision of these constraints, measure additional parameters such as halo shape, and measure the properties of dark matter halos separately for many different classes of galaxies.Comment: 28 pages, 11 figures, submitted to A

    Finding Common Ground When Experts Disagree: Robust Portfolio Decision Analysis

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    The Seventh Data Release of the Sloan Digital Sky Survey

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    This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11663 deg^2 of imaging data, with most of the roughly 2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry over 250 deg^2 along the Celestial Equator in the Southern Galactic Cap. A coaddition of these data goes roughly two magnitudes fainter than the main survey. The spectroscopy is now complete over a contiguous area of 7500 deg^2 in the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog (UCAC-2), reducing the rms statistical errors at the bright end to 45 milli-arcseconds per coordinate. A systematic error in bright galaxy photometr is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat-fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities. (Abridged)Comment: 20 pages, 10 embedded figures. Accepted to ApJS after minor correction

    LSST: from Science Drivers to Reference Design and Anticipated Data Products

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    (Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg2^2 field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5σ\sigma point-source depth in a single visit in rr will be 24.5\sim 24.5 (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg2^2 with δ<+34.5\delta<+34.5^\circ, and will be imaged multiple times in six bands, ugrizyugrizy, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg2^2 region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to r27.5r\sim27.5. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

    The Baryon Oscillation Spectroscopic Survey of SDSS-III

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    The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

    Pavlovian Reward Prediction and Receipt in Schizophrenia: Relationship to Anhedonia

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    Reward processing abnormalities have been implicated in the pathophysiology of negative symptoms such as anhedonia and avolition in schizophrenia. However, studies examining neural responses to reward anticipation and receipt have largely relied on instrumental tasks, which may confound reward processing abnormalities with deficits in response selection and execution. 25 chronic, medicated outpatients with schizophrenia and 20 healthy controls underwent functional magnetic resonance imaging using a Pavlovian reward prediction paradigm with no response requirements. Subjects passively viewed cues that predicted subsequent receipt of monetary reward or non-reward, and blood-oxygen-level-dependent signal was measured at the time of cue presentation and receipt. At the group level, neural responses to both reward anticipation and receipt were largely similar between groups. At the time of cue presentation, striatal anticipatory responses did not differ between patients and controls. Right anterior insula demonstrated greater activation for nonreward than reward cues in controls, and for reward than nonreward cues in patients. At the time of receipt, robust responses to receipt of reward vs. nonreward were seen in striatum, midbrain, and frontal cortex in both groups. Furthermore, both groups demonstrated responses to unexpected versus expected outcomes in cortical areas including bilateral dorsolateral prefrontal cortex. Individual difference analyses in patients revealed an association between physical anhedonia and activity in ventral striatum and ventromedial prefrontal cortex during anticipation of reward, in which greater anhedonia severity was associated with reduced activation to money versus no-money cues. In ventromedial prefrontal cortex, this relationship held among both controls and patients, suggesting a relationship between anticipatory activity and anhedonia irrespective of diagnosis. These findings suggest that in the absence of response requirements, brain responses to reward receipt are largely intact in medicated individuals with chronic schizophrenia, while reward anticipation responses in left ventral striatum are reduced in those patients with greater anhedonia severity

    Elite Suppressors Harbor Low Levels of Integrated HIV DNA and High Levels of 2-LTR Circular HIV DNA Compared to HIV+ Patients On and Off HAART

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    Elite suppressors (ES) are a rare population of HIV-infected individuals that are capable of naturally controlling the infection without the use of highly active anti-retroviral therapy (HAART). Patients on HAART often achieve viral control to similar (undetectable) levels. Accurate and sensitive methods to measure viral burden are needed to elucidate important differences between these two patient populations in order to better understand their mechanisms of control. Viral burden quantification in ES patients has been limited to measurements of total DNA in PBMC, and estimates of Infectious Units per Million cells (IUPM). There appears to be no significant difference in the level of total HIV DNA between cells from ES patients and patients on HAART. However, recovering infectious virus from ES patient samples is much more difficult, suggesting their reservoir size should be much smaller than that in patients on HAART. Here we find that there is a significant difference in the level of integrated HIV DNA in ES patients compared to patients on HAART, providing an explanation for the previous results. When comparing the level of total to integrated HIV DNA in these samples we find ES patients have large excesses of unintegrated HIV DNA. To determine the composition of unintegrated HIV DNA in these samples, we measured circular 2-LTR HIV DNA forms and found ES patients frequently have high levels of 2-LTR circles in PBMC. We further show that these high levels of 2-LTR circles are not the result of inefficient integration in ES cells, since HIV integrates with similar efficiency in ES and normal donor cells. Our findings suggest that measuring integration provides a better surrogate of viral burden than total HIV DNA in ES patients. Moreover, they add significantly to our understanding of the mechanisms that allow viral control and reservoir maintenance in this unique patient population

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment
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