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The Rapid ASKAP Continuum Survey (RACS) is the first large-area survey to be conducted with the full 36-antenna Australian Square Kilometre Array Pathfinder (ASKAP) telescope. RACS will provide a shallow model of the ASKAP sky that will aid the calibration of future deep ASKAP surveys. RACS will cover the whole sky visible from the ASKAP site in Western Australia and will cover the full ASKAP band of 700–1800 MHz. The RACS images are generally deeper than the existing NRAO VLA Sky Survey and Sydney University Molonglo Sky Survey radio surveys and have better spatial resolution. All RACS survey products will be public, including radio images (with
15 arcsec resolution) and catalogues of about three million source components with spectral index and polarisation information. In this paper, we present a description of the RACS survey and the first data release of 903 images covering the sky south of declination
made over a 288-MHz band centred at 887.5 MHz.
We evaluated the impact of reflex urine culture screen results on antibiotic initiation. More patients with positive urine screen but negative culture received antibiotics than those with a negative screen (30.5 vs 7.1%). Urine screen results may inappropriately influence antibiotic initiation in patients with a low likelihood of infection.
Breakthrough Listen is a 10-yr initiative to search for signatures of technologies created by extraterrestrial civilisations at radio and optical wavelengths. Here, we detail the digital data recording system deployed for Breakthrough Listen observations at the 64-m aperture CSIRO Parkes Telescope in New South Wales, Australia. The recording system currently implements two modes: a dual-polarisation, 1.125-GHz bandwidth mode for single-beam observations, and a 26-input, 308-MHz bandwidth mode for the 21-cm multibeam receiver. The system is also designed to support a 3-GHz single-beam mode for the forthcoming Parkes ultra-wideband feed. In this paper, we present details of the system architecture, provide an overview of hardware and software, and present initial performance results.
To determine the effect of mandatory and nonmandatory influenza vaccination policies on vaccination rates and symptomatic absenteeism among healthcare personnel (HCP).
Retrospective observational cohort study.
This study took place at 3 university medical centers with mandatory influenza vaccination policies and 4 Veterans Affairs (VA) healthcare systems with nonmandatory influenza vaccination policies.
The study included 2,304 outpatient HCP at mandatory vaccination sites and 1,759 outpatient HCP at nonmandatory vaccination sites.
To determine the incidence and duration of absenteeism in outpatient settings, HCP participating in the Respiratory Protection Effectiveness Clinical Trial at both mandatory and nonmandatory vaccination sites over 3 viral respiratory illness (VRI) seasons (2012–2015) reported their influenza vaccination status and symptomatic days absent from work weekly throughout a 12-week period during the peak VRI season each year. The adjusted effects of vaccination and other modulating factors on absenteeism rates were estimated using multivariable regression models.
The proportion of participants who received influenza vaccination was lower each year at nonmandatory than at mandatory vaccination sites (odds ratio [OR], 0.09; 95% confidence interval [CI], 0.07–0.11). Among HCP who reported at least 1 sick day, vaccinated HCP had lower symptomatic days absent compared to unvaccinated HCP (OR for 2012–2013 and 2013–2014, 0.82; 95% CI, 0.72–0.93; OR for 2014–2015, 0.81; 95% CI, 0.69–0.95).
These data suggest that mandatory HCP influenza vaccination policies increase influenza vaccination rates and that HCP symptomatic absenteeism diminishes as rates of influenza vaccination increase. These findings should be considered in formulating HCP influenza vaccination policies.
We describe a versatile infrared camera/spectrograph, IRIS, designed and constructed at the Anglo-Australian Observatory for use on the Anglo-Australian Telescope. A variety of optical configurations can be selected under remote control to provide several direct image scales and a few low-resolution spectroscopic formats. Two cross-dispersed transmission echelles are of novel design, as is the use of a modified Bowen-Burch system to provide a fast f/ratio in the widest-field option. The drive electronics includes a choice of readout schemes for versatility, and continuous display when the array is not taking data, to facilitate field acquisition and focusing.
The linearity of the detector has been studied in detail. Although outwardly good, slight nonlinearities prevent removal of fixed-pattern noise from the data without application of a cubic linearising function.
Specific control and data-reduction software has been written. We describe also a scanning mode developed for spectroscopic imaging.
Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue.
To investigate whether higher BMI increases the risk of major depression.
Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case–control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI.
Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient −0.03, 95% CI −0.18 to 0.13, P = 0.73; GRS: coefficient −0.02, 95% CI −0.11 to 0.07, P = 0.62).
Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.