Wind‐driven strain extends seasonal stratification

The onset and breakdown of stratification are key physical drivers of phytoplankton growth in shelf seas and the open ocean. We show how in the Celtic Sea, where seasonality in stratification is generally viewed as controlled by heat input, a cross‐shelf salinity gradient horizontally strained by the wind prolonged the stratified period by 5‐6 days in autumn prior to full winter mixing, whilst in spring caused seasonal stratification to begin 7 days early. Salinity straining has important implications for setting light conditions during the start of the spring bloom and for the timing of bottom water ventilation in winter. Analysis of winds around the time of likely onset of spring stratification between 1979 and 2016 showed that in 60% of the years wind conditions were favourable for salinity straining. Accurate knowledge of the horizontal salinity field and wind stress are required to correctly determine the onset and breakdown of stratification

Correcting surface wave bias in structure function estimates of turbulent kinetic energy dissipation rate

The combination of acoustic Doppler current profilers and the structure function methodology provides an attractive approach to making extended time series measurements of oceanic turbulence (the rate of turbulent kinetic energy dissipation ε) from moorings. However, this study shows that for deployments in the upper part of the water column, estimates of ε will be biased by the vertical gradient in wave orbital velocities. To remove this bias, a modified structure function methodology is developed that exploits the differing length scale dependencies of the contributions to the structure function resulting from turbulent and wave orbital motions. The success of the modified method is demonstrated through a comparison of ε estimates based on data from instruments at three depths over a 3-month period under a wide range of conditions, with appropriate scalings for wind stress and convective forcing

Seasonality in the cross-shelf physical structure of a temperate shelf sea and the implications for nitrate supply

We address a long-standing problem of how nutrients are transported from the shelf edge and from rivers to support regular, seasonal primary production in the interior of a wide, temperate, shelf sea. Cross-shelf sections of hydrography and nutrients, from a series of cruises between March 2014 and August 2015, along with time series of river discharge and river nutrient load are used to assess the seasonality of cross-shelf transports. Riverine nitrogen inputs are estimated to account for 30% of the nitrate available for the spring bloom on the inner shelf, and 10% in the mid- to outer-shelf. In the bottom layer in summer, high salinity, nutrient-rich waters are transported on-shelf as a result of wind-driven Ekman transport, cross-shelf pressure gradients and/or internal tidal wave Stoke’s drift. In the centre of the shelf this advection is responsible for 25% of the increase in bottom water nitrate seen between April and November 2014. The remaining nitrate increase suggests that about 50–62% of the nitrogen fixed into organic material during spring, summer and autumn phytoplankton growth is recycled in the bottom water over the 12 months between March 2014 and March 2015. In winter, when the water column is vertically mixed, there is a weak net off-shelf transport of about 1 m2 s−1, possibly driven by a reversal of the horizontal density gradient caused by excess cooling of shallower shelf waters. Overall, shelf nitrate concentrations are maintained by a combination of riverine supply, recycling of organic material, and summer on-shelf transports. We suggest that the main driver of inter-annual variability in pre-spring nitrate concentrations is variability in the depth of the winter mixed layer over the shelf slope

Long-term oral antibiotic use in people with acne vulgaris in UK primary care: a drug utilization study

BACKGROUND: The inappropriate use of antibiotics is understood to contribute to antimicrobial resistance. Oral antibiotics are regularly used to treat moderate-to-severe acne vulgaris. In practice, we do not know the typical length of oral antibiotic treatment courses for acne in routine primary care and what proportion of people receive more than one course of treatment following a new acne diagnosis. OBJECTIVES: To describe how oral antibiotics are prescribed for acne over time in UK primary care. METHODS: We conducted a descriptive longitudinal drug utilization study using routinely collected primary care data from the Clinical Practice Research Datalink GOLD (2004-2019). We included individuals (8-50 years) with a new acne diagnosis recorded between 1 January 2004 and 31 July 2019. RESULTS: We identified 217 410 people with a new acne diagnosis. The median age was 17 years [interquartile range (IQR) 15-25] and median follow-up was 4.3 years (IQR 1.9-7.6). Among people with a new acne diagnosis, 96 703 (44.5%) received 248 560 prescriptions for long-term oral antibiotics during a median follow-up of 5.3 years (IQR 2.8-8.5). The median number of continuous courses of antibiotic therapy (≥ 28 days) per person was four (IQR 2-6). The majority (n = 59 010, 61.0%) of first oral antibiotic prescriptions in those with a recorded acne diagnosis were between the ages of 12 and 18. Most (n = 71 544, 74.0%) first courses for oral antibiotics were for between 28 and 90 days. The median duration of the first course of treatment was 56 days (IQR 50-93 days) and 18 127 (18.7%) of prescriptions of ≥ 28 days were for < 6 weeks. Among people who received a first course of oral antibiotic for ≥ 28 days, 56 261 (58.2%) received a second course after a treatment gap of ≥ 28 days. The median time between first and second courses was 135 days (IQR 67-302). The cumulative duration of exposure to oral antibiotics during follow-up was 255 days (8.5 months). CONCLUSIONS: Further work is needed to understand the consequences of using antibiotics for shorter periods than recommended. Suboptimal treatment duration may result in reduced clinical effectiveness or repeated exposures, potentially contributing to antimicrobial resistance

The Color Variability of Quasars

We quantify quasar color-variability using an unprecedented variability database - ugriz photometry of 9093 quasars from SDSS Stripe 82, observed over 8 years at ~60 epochs each. We confirm previous reports that quasars become bluer when brightening. We find a redshift dependence of this blueing in a given set of bands (e.g. g and r), but show that it is the result of the flux contribution from less-variable or delayed emission lines in the different SDSS bands at different redshifts. After correcting for this effect, quasar color-variability is remarkably uniform, and independent not only of redshift, but also of quasar luminosity and black hole mass. The color variations of individual quasars, as they vary in brightness on year timescales, are much more pronounced than the ranges in color seen in samples of quasars across many orders of magnitude in luminosity. This indicates distinct physical mechanisms behind quasar variability and the observed range of quasar luminosities at a given black hole mass - quasar variations cannot be explained by changes in the mean accretion rate. We do find some dependence of the color variability on the characteristics of the flux variations themselves, with fast, low-amplitude, brightness variations producing more color variability. The observed behavior could arise if quasar variability results from flares or ephemeral hot spots in an accretion disc.Comment: Accepted for publication in ApJ - in press, 17 pages, 14 figures - v2: abstract typo corrected & reference clean-u

Think Outside the Color Box: Probabilistic Target Selection and the SDSS-XDQSO Quasar Targeting Catalog

We present the SDSS-XDQSO quasar targeting catalog for efficient flux-based quasar target selection down to the faint limit of the Sloan Digital Sky Survey (SDSS) catalog, even at medium redshifts (2.5 <~ z <~ 3) where the stellar contamination is significant. We build models of the distributions of stars and quasars in flux space down to the flux limit by applying the extreme-deconvolution method to estimate the underlying density. We convolve this density with the flux uncertainties when evaluating the probability that an object is a quasar. This approach results in a targeting algorithm that is more principled, more efficient, and faster than other similar methods. We apply the algorithm to derive low-redshift (z < 2.2), medium-redshift (2.2 <= z 3.5) quasar probabilities for all 160,904,060 point sources with dereddened i-band magnitude between 17.75 and 22.45 mag in the 14,555 deg^2 of imaging from SDSS Data Release 8. The catalog can be used to define a uniformly selected and efficient low- or medium-redshift quasar survey, such as that needed for the SDSS-III's Baryon Oscillation Spectroscopic Survey project. We show that the XDQSO technique performs as well as the current best photometric quasar-selection technique at low redshift, and outperforms all other flux-based methods for selecting the medium-redshift quasars of our primary interest. We make code to reproduce the XDQSO quasar target selection publicly available

Photometric redshifts and quasar probabilities from a single, data-driven generative model

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift one can obtain quasar flux-densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques---which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data---and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar--star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84 and 97 percent of the objects with GALEX UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available