C. Simpson

The SCUBA-2 Cosmology Legacy Survey: 850 μm maps, catalogues and number counts

We present a catalogue of similar to 3000 submillimetre sources detected (>= 3.5 sigma) at 850 mu m over similar to 5 deg(2) surveyed as part of the James Clerk Maxwell Telescope (JCMT) SCUBA-2 Cosmology Legacy Survey (S2CLS). This is the largest survey of its kind at 850 mu m, increasing the sample size of 850 mu m selected submillimetre galaxies by an order of magnitude. The wide 850 mu m survey component of S2CLS covers the extragalactic fields: UKIDSS-UDS, COSMOS, Akari-NEP, Extended Groth Strip, Lockman Hole North, SSA22 and GOODS-North. The average 1s depth of S2CLS is 1.2 mJy beam(-1), approaching the SCUBA-2 850 mu m confusion limit, which we determine to be sigma(c) approximate to 0.8 mJy beam(-1). We measure the 850 mu m number counts, reducing the Poisson errors on the differential counts to approximately 4 per cent at S-850 approximate to 3 mJy. With several independent fields, we investigate field-to-field variance, finding that the number counts on 0.5 degrees-1 degrees scales are generally within 50 per cent of the S2CLS mean for S-850 > 3 mJy, with scatter consistent with the Poisson and estimated cosmic variance uncertainties, although there is a marginal (2 sigma) density enhancement in GOODS-North. The observed counts are in reasonable agreement with recent phenomenological and semi-analytic models, although determining the shape of the faint-end slope (S-850 10 mJy there are approximately 10 sources per square degree, and we detect the distinctive up-turn in the number counts indicative of the detection of local sources of 850 mu m emission

Preventing falls among older people with mental health problems: A systematic review

BackgroundFalls are a leading cause of mortality and morbidity in older people and the risk of falling is exacerbated by mental health conditions. Existing reviews have focused on people with dementia and cognitive impairment, but not those with other mental health conditions or in mental health settings. The objective of this review is to evaluate the effectiveness of fall prevention interventions for older people with mental health problems being cared for across all settings.MethodsA systematic review of fall prevention interventions for older people with mental health conditions. We undertook electronic database and lateral searches to identify studies reporting data on falls or fall related injuries. Searches were initially conducted in February 2011 and updated in November 2012 and October 2013; no date restrictions were applied. Studies were assessed for risk of bias. Due to heterogeneity results were not pooled but are reported narratively.ResultsSeventeen RCTs and four uncontrolled studies met the inclusion criteria; 11 involved single interventions and ten multifactorial. Evidence relating to fall reduction was inconsistent. Eight of 14 studies found a reduction in fallers (statistically significant in five), and nine of 14 reported a significant reduction in rate or number of falls. Four studies found a non-significant increase in falls. Multifactorial, multi-disciplinary interventions and those involving exercise, medication review and increasing staff awareness appear to reduce the risk of falls but evidence is mixed and study quality varied. Changes to the environment such as increased supervision or sensory stimulation to reduce agitation may be promising for people with dementia but further evaluation is needed. Most of the studies were undertaken in nursing and residential homes, and none in mental health hospital settings.ConclusionsThere is a dearth of falls research in mental health settings or which focus on patients with mental health problems despite the high number of falls experienced by this population group. This review highlights the lack of robust evidence to support practitioners to implement practices that prevent people with mental health problems from falling.

Evolution of cosmic star formation in the SCUBA-2 Cosmology Legacy Survey

We present a new exploration of the cosmic star formation history and dust obscuration in massive galaxies at redshifts 0.5 10(10) M-O galaxies at 0.5 10. One third of this is accounted for by 450 mu m-detected sources, while one-fifth is attributed to UV-luminous sources (brighter than L-UV(*)), although even these are largely obscured. By extrapolating our results to include all stellar masses, we estimate a total SFRD that is in good agreement with previous results from IR and UV data at z <= 3, and from UV-only data at z similar to 5. The cosmic star formation history undergoes a transition at z similar to 3-4, as predominantly unobscured growth in the early Universe is overtaken by obscured star formation, driven by the build-up of the most massive galaxies during the peak of cosmic assembly.

The SCUBA-2 Cosmology Legacy Survey: Multiwavelength Counterparts to 103 Submillimeter Galaxies in the UKIDSS-UDS Field

We present multiwavelength identifications for the counterparts of 1088 submillimeter sources detected at 850 μm in the SCUBA-2 Cosmology Legacy Survey study of the UKIRT Infrared Deep Sky Survey-Ultra-Deep Survey (UDS) field. By utilizing an Atacama Large Millimeter Array (ALMA) pilot study on a subset of our bright SCUBA-2 sample as a training set, along with the deep optical–near-infrared (OIR) data available in this field, we develop a novel technique, Optical–IR Triple Color (OIRTC), using z − K, K − [3.6], [3.6] − [4.5] colors to select the candidate submillimeter galaxy (SMG) counterparts. By combining radio identification and the OIRTC technique, we find counterpart candidates for 80% of the Class = 1 ≥ 4σ SCUBA-2 sample, defined as those that are covered by both radio and OIR imaging and the base sample for our scientific analyses. Based on the ALMA training set, we expect the accuracy of these identifications to be 82% ± 20%, with a completeness of 69% ± 16%, essentially as accurate as the traditional p-value technique but with higher completeness. We find that the fraction of SCUBA-2 sources having candidate counterparts is lower for fainter 850 μm sources, and we argue that for follow-up observations sensitive to SMGs with S850 gsim 1 mJy across the whole ALMA beam, the fraction with multiple counterparts is likely to be >40% for SCUBA-2 sources at S850 gsim 4 mJy. We find that the photometric redshift distribution for the SMGs is well fit by a lognormal distribution, with a median redshift of z = 2.3 ± 0.1. After accounting for the sources without any radio and/or OIRTC counterpart, we estimate the median redshift to be z = 2.6 ± 0.1 for SMGs with S850 > 1 mJy. We also use this new large sample to study the clustering of SMGs and the far-infrared properties of the unidentified submillimeter sources by stacking their Herschel SPIRE far-infrared emission.

The MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey

The MIGHTEE large survey project will survey four of the most well-studied extragalactic deep fields, totalling 20 square degrees to

A direct calibration of the IRX-β relation in Lyman-break Galaxies at z=3-5

\mu

Falling in Acute Mental Health Settings for Older People : Who falls, where, when and why?

Jy sensitivity at Giga-Hertz frequencies, as well as an ultra-deep image of a single ~1 square degree MeerKAT pointing. The observations will provide radio continuum, spectral line and polarisation information. As such, MIGHTEE, along with the excellent multi-wavelength data already available in these deep fields, will allow a range of science to be achieved. Specifically, MIGHTEE is designed to significantly enhance our understanding of, (i) the evolution of AGN and star-formation activity over cosmic time, as a function of stellar mass and environment, free of dust obscuration; (ii) the evolution of neutral hydrogen in the Universe and how this neutral gas eventually turns into stars after moving through the molecular phase, and how efficiently this can fuel AGN activity; (iii) the properties of cosmic magnetic fields and how they evolve in clusters, filaments and galaxies. MIGHTEE will reach similar depth to the planned SKA all-sky survey, and thus will provide a pilot to the cosmology experiments that will be carried out by the SKA over a much larger survey volume.

A Machine-learning Method for Identifying Multiwavelength Counterparts of Submillimeter Galaxies: Training and Testing Using AS2UDS and ALESS

We use a sample of 4209 Lyman-break galaxies (LBGs) at z~ -3, 4, and 5 in the UKIRT Infrared Deep Sky Survey Ultra Deep Survey field to investigate the relationship between the observed slope of the stellar continuum emission in the ultraviolet, β , and the thermal dust emission, as quantified via the so-called ‘infrared excess’ (IRX≡LIR/LUV). Through a stacking analysis, we directly measure the 850-μm flux density of LBGs in our deep (0.9 mJy) James Clerk Maxwell Telescope SCUBA-2850-μm map as well as deep public Herschel/SPIRE 250-, 350-, and 500-μm imaging. We establish functional forms for the IRX–β relation to z∼5, confirming that there is no significant redshift evolution of the relation, and that the resulting average IRX–β curve is consistent with a Calzetti-like attenuation law. Comparing our results with recent works in the literature, we confirm that discrepancies in the slope of the IRX–β relation are driven by biases in the methodology used to determine the ultraviolet slopes. Consistent results are found when IRX–β is evaluated by stacking in bins of stellar mass, and we argue that the near-linear IRX–M* relationship is a better proxy for correcting observed ultraviolet luminosities to total star formation rates, provided an accurate handle on M* and also gives clues as to the physical driver of the role of dust-obscured star formation in high-redshift galaxies.

An analytical review of local and national fall policy and guidelines in England and Wales

Falls, slips and trips are a major patient safety concern in hospital settings accounting for 26 per cent of all reported patient safety incidents in England. Mental health conditions and their treatments add further to fall risk but we have little information regarding who falls, where and when within mental health settings. Methods: This paper presents an overview of the pattern of falls by older patients within an in-patient mental health setting in the South of England using routine records completed by staff when a fall occurs. 920 fall reports over three years were analysed, and 7 focus groups were undertaken with ward staff to explore how staff understood falls and their experiences of using the falls reporting system. Results: In terms of diagnosis 40% of fallers had a primary functional diagnosis, 46% an organic mental health diagnosis (14% non-specific diagnosis), average age was 81.7 years (range 59 to 99 years; SD 8.3) and 57% were female. Approximately one quarter, 27%, of falls were observed by staff. Falls were not evenly distributed across either day of week or time of day, with peak times for falls on Tuesday and Saturday and morning (7-8 and 9-10am) and subsidiary peaks between noon and 1pm and early evening (5-6pm). Almost half of falls occurred in private spaces in the ward such as bedrooms, and 42% in public spaces such as sitting rooms. However 60% of falls in public spaces were unseen. Reporting in these settings was problematic for staff and patients were sometimes described as placing themselves on the floor as a consequence of their mental health condition. The average time to first fall was 5 weeks. Conclusions: Routine mapping of falls could be undertaken at ward and organization level and contribute to better understanding of the local factors contributing to falls. Exploring incident report data in focus groups with staff helped us and them to interpret the data and to understand some of the decision making staffs engage in everyday when reporting falls.

AGN environments at z<1.5 in the UKIDSS Ultra-Deep Survey

We describe the application of supervised machine-learning algorithms to identify the likely multiwavelength counterparts to submillimeter sources detected in panoramic, single-dish submillimeter surveys. As a training set, we employ a sample of 695 (S 870μm gsim 1 mJy) submillimeter galaxies (SMGs) with precise identifications from the ALMA follow-up of the SCUBA-2 Cosmology Legacy Surveys UKIDSS-UDS field (AS2UDS). We show that radio emission, near-/mid-infrared colors, photometric redshift, and absolute H-band magnitude are effective predictors that can distinguish SMGs from submillimeter-faint field galaxies. Our combined radio + machine-learning method is able to successfully recover ~85% of ALMA-identified SMGs that are detected in at least three bands from the ultraviolet to radio. We confirm the robustness of our method by dividing our training set into independent subsets and using these for training and testing, respectively, as well as applying our method to an independent sample of ~100 ALMA-identified SMGs from the ALMA/LABOCA ECDF-South Survey (ALESS). To further test our methodology, we stack the 870 μm ALMA maps at the positions of those K-band galaxies that are classified as SMG counterparts by the machine learning but do not have a >4.3σ ALMA detection. The median peak flux density of these galaxies is S 870μm = (0.61 ± 0.03) mJy, demonstrating that our method can recover faint and/or diffuse SMGs even when they are below the detection threshold of our ALMA observations. In future, we will apply this method to samples drawn from panoramic single-dish submillimeter surveys that currently lack interferometric follow-up observations to address science questions that can only be tackled with large statistical samples of SMGs.