The Variables and Slow Transients Survey (VAST) on the Australian Square Kilometre Array Pathfinder (ASKAP) is designed to detect highly variable and transient radio sources on timescales from 5 s to $\sim\!5$ yr. In this paper, we present the survey description, observation strategy and initial results from the VAST Phase I Pilot Survey. This pilot survey consists of $\sim\!162$ h of observations conducted at a central frequency of 888 MHz between 2019 August and 2020 August, with a typical rms sensitivity of $0.24\ \mathrm{mJy\ beam}^{-1}$ and angular resolution of $12-20$ arcseconds. There are 113 fields, each of which was observed for 12 min integration time, with between 5 and 13 repeats, with cadences between 1 day and 8 months. The total area of the pilot survey footprint is 5 131 square degrees, covering six distinct regions of the sky. An initial search of two of these regions, totalling 1 646 square degrees, revealed 28 highly variable and/or transient sources. Seven of these are known pulsars, including the millisecond pulsar J2039–5617. Another seven are stars, four of which have no previously reported radio detection (SCR J0533–4257, LEHPM 2-783, UCAC3 89–412162 and 2MASS J22414436–6119311). Of the remaining 14 sources, two are active galactic nuclei, six are associated with galaxies and the other six have no multi-wavelength counterparts and are yet to be identified.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.

We describe the frequency of pediatric healthcare-associated infections (HAIs) identified through prospective surveillance in community hospitals participating in an infection control network. Over a 6-year period, 84 HAIs were identified. Of these 51 (61%) were pediatric central-line–associated bloodstream infections, and they often occurred in children <1 year of age.

Background: Surgical site infections (SSIs) among cardiothoracic (CT) patients are associated with high rates of morbidity and mortality. Data are limited regarding SSI incidence among pediatric patients undergoing primary reparative procedures for congenital cardiac disease. Published evidence on targeted interventions to prevent pediatric CT-surgery SSI is lacking. We aimed to establish standard metrics for measuring CT-surgery SSI incidence and to implement bundled interventions for SSI prevention. Methods: A dedicated CT-surgery SSI prevention workgroup was established, consisting of hospital leadership, CT surgeons, cardiac critical care unit staff, anesthesia, perfusion, environmental services, instrument sterile processing, risk management, infection prevention and antibiotic stewardship. We created a standard definition for CT-surgery SSI and calculated retrospective SSI rates over a 24-month period (2017–2019). The outcome measured was incidence of CT-surgery SSI per 100 primary cardiac procedures with delayed ( 3 days after primary surgery) or non-delayed chest closure. The difference in proportion of SSI was reported separately for delayed closure and non-delayed closure; statistical significance was tested using a Fisher’s Exact test. We identified many potential improvement opportunities, including gaps in SSI surveillance, poor compliance with daily bathing, inconsistent perioperative antimicrobial prophylaxis, lack of controlled environment for bedside chest closures, and lapses in environmental cleaning. These issues informed the enhanced SSI prevention bundle, which included education on sterility with the operating room (OR) staff. Protocols for care of cardiac patients with delayed chest closures focused on universal daily and preoperative chlorhexidine baths. In addition, the bundle incorporated stringent environmental cleaning interventions including scheduled decluttering of patient rooms and clinical spaces, terminal cleaning of patient rooms prior to returning from the OR, and use of adjunctive ultraviolet light for the daily cleaning of operating rooms and patient rooms at discharge. Results: Surveillance definition of microbiological growth from a clinical sample obtained within 30 days of primary cardiac procedure sufficiently captured all CT-surgery SSIs. Of 551 CT-surgery procedures prior to intervention, 91 (17%) had delayed final operative closures. Prior to the intervention, 16 SSIs were identified from July 2017 – May 2019 for a rate of 2.90 per /100 procedures, and was higher among patients with delayed chest closure 6.59 per /100 procedures (6 SSIs/91 procedures) versus those with primary chest closure 2.17 per /100 procedures (10 SSIs/460 procedures; P = 0.034). Gram-positive organisms, including coagulase coagulase-negative Staphylococci, were most frequently identified as the causative organisms for SSIs. Compliance with bundled intervention, rolled out over a 2-month period, was associated with an immediate decrease in the number of SSIs for primary and delayed chest closures 6SSIs /185 procedures in the initial quarters (August – December 2019) of the post-intervention period. However, this decrease was not reflected in the overall rate (3.24 per /100 procedures) due to fewer procedures performed. Data collection to measure sustainability is ongoing. Conclusions: Bundled interventions targeting skin antisepsis and environmental cleaning may be associated with a decrease in SSIs among pediatric CT-surgery patients. Ongoing surveillance is required to determine sustainability of these interventions.

Funding: None

Disclosures: None

We implemented universal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing of patients undergoing surgical procedures as a means to conserve personal protective equipment (PPE). The rate of asymptomatic coronavirus disease 2019 (COVID-19) was <0.5%, which suggests that early local public health interventions were successful. Although our protocol was resource intensive, it prevented exposures to healthcare team members.

Hobby metal detecting is a controversial subject. Legal and policy approaches differ widely across national and regional contexts, and the attitudes of archaeologists and heritage professionals towards detectorists are often polarized and based on ethical or emotive arguments. We, the European Public Finds Recording Network (EPFRN), have implemented collaborative approaches towards detectorist communities in our respective contexts (Denmark, England and Wales, Finland, Flanders, and the Netherlands). Although our motivations are affected by our national circumstances, we base our work on an agreed set of goals, practices, and visions. This article presents the EPFRN's vision statement and provides insight into its underlying thoughts. We hope to create a debate on how to develop best practice approaches that acknowledge the inherent challenges of hobby metal detecting while realizing its potential.

The surprising election of Donald Trump to the presidency calls for a comprehensive assessment of what motivated voters to opt for a controversial political novice rather than a provocative but experienced political veteran. Our study provides a novel exploration of the Trump victory through the prism of the defeated candidate—Hillary Rodham Clinton (HRC). Losing candidates’ perceptions are usually not subject to academic analyses. Nevertheless, these people often hold substantial sway in their parties and thus understanding their views on the loss is essential, especially as a party regroups after defeat. Using HRC’s memoir What Happened, we devise the Hillary Hypotheses, her rationale for her electoral defeat. Using the 2016 American National Election Study (ANES), we provide the first systematic test of a losing candidate’s rationale for their defeat. We show that more often than not, HRC’s assumptions are supported. However, we find little evidence to support HRC’s most crucial assertion, namely that the e-mail scandal and specifically James Comey’s intervention ten days before Election Day cost her the presidency. Our findings have implications for understanding why Donald Trump won, but more broadly the contribution explores an understudied aspect of elections—a defeated candidate’s impression of their loss.

Are ordinary citizens better at predicting election results than conventional voter intention polls? The authors address this question by comparing eight forecasting models for British general elections: one based on voters' expectations of who will win and seven based on who voters themselves intend to vote for (including ‘uniform national swing model’ and ‘cube rule’ models). The data come from ComRes and Gallup polls as well as the Essex Continuous Monitoring Surveys, 1950–2017, yielding 449 months with both expectation and intention polls. The large sample size permits comparisons of the models' prediction accuracy not just in the months prior to the election, but in the years leading up to it. Vote expectation models outperform vote intention models in predicting both the winning party and parties' seat shares.