Identification of RR Lyrae stars in multiband, sparsely-sampled data from the Dark Energy Survey using template fitting and Random Forest classification

Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ~ 23.5 mag) in a single exposure; over 5000 deg2) provides a rich opportunity to search for substructures out to the edge of the Milky Way halo. However, the sparse and unevenly sampled multiband light curves from the DES wide-field survey (median 4 observations in each of grizY over the first three years) pose a challenge for traditional techniques used to detect RRL. We present an empirically motivated and computationally efficient template fitting method to identify these variable stars using three years of DES data. When tested on DES light curves of previously classified objects in SDSS stripe 82, our algorithm recovers 89% of RRL periods to within 1% of their true value with 85% purity and 76% completeness. Using this method, we identify 5783 RRL candidates, ~31% of which are previously undiscovered. This method will be useful for identifying RRL in other sparse multiband data sets

Clinical and cost-effectiveness of the Managing Agitation and Raising Quality of Life (MARQUE) intervention for agitation in people with dementia in care homes: a single-blind, cluster-randomised controlled trial

BACKGROUND: Many people with dementia living in care homes have distressing and costly agitation symptoms. Interventions should be efficacious, scalable, and feasible. METHODS: We did a parallel-group, cluster-randomised controlled trial in 20 care homes across England. Care homes were eligible if they had 17 residents or more with dementia, agreed to mandatory training for all eligible staff and the implementation of plans, and more than 60% of eligible staff agreed to participate. Staff were eligible if they worked during the day providing face-to-face care for residents with dementia. Residents were eligible if they had a known dementia diagnosis or scored positive on screening with the Noticeable Problems Checklist. A statistician independent of the study randomised care homes (1:1) to the Managing Agitation and Raising Quality of Life (MARQUE) intervention or treatment as usual (TAU) using computer-generated randomisation in blocks of two, stratified by type of home (residential or nursing). Care home staff were not masked to the intervention but were asked not to inform assessors. Residents with dementia, family carers, outcome assessors, statisticians, and health economists were masked to allocation until the data were analysed. MARQUE is an evidence-based manualised intervention, delivered by supervised graduate psychologists to staff in six interactive sessions. The primary outcome was agitation score at 8 months, measured using the Cohen-Mansfield Agitation Inventory (CMAI). Analysis of the primary outcome was done in the modified intention-to-treat population, which included all randomly assigned residents for whom CMAI data was available at 8 months. Mortality was assessed in all randomly assigned residents. This study is registered with the ISRCTN registry, number ISRCTN96745365. FINDINGS: Between June 14, 2016, and July 4, 2017, we randomised ten care homes (189 residents) to the MARQUE intervention and ten care homes (215 residents) to TAU. At 8 months, primary outcome data were available for 155 residents in the MARQUE group and 163 residents in the TAU group. At 8 months, no significant differences in mean CMAI scores were identified between the MARQUE and TAU groups (adjusted difference -0·40 [95% CI -3·89 to 3·09; p=0·8226]). In the intervention care homes, 84% of all eligible staff completed all sessions. The mean difference in cost between the MARQUE and TAU groups was £204 (-215 to 623; p=0·320) and mean difference in quality-adjusted life-years was 0·015 (95% CI -0·004 to 0·034; p=0·127). At 8 months, 27 (14%) of 189 residents in the MARQUE group and 41 (19%) of 215 residents in the TAU group had died. The prescription of antipsychotic drugs was not significantly different between the MARQUE group and the TAU group (odds ratio 0·66; 95% CI 0·26 to 1·69, p=0·3880). INTERPRETATION: The MARQUE intervention was not efficacious for agitation although feasible and cost-effective in terms of quality of life. Addressing agitation in care homes might require resourcing for delivery by professional staff of a more intensive intervention, implementing social and activity times, and a longer time to implement change. FUNDING: UK Economic and Social Research Council and the National Institute of Health Research

Identifying RR lyrae variable stars in six years of the dark energy survey

We present a search for RR Lyrae stars using the full six-year data set from the Dark Energy Survey covering ∼5000 deg2 of the southern sky. Using a multistage multivariate classification and light-curve template-fitting scheme, we identify RR Lyrae candidates with a median of 35 observations per candidate. We detect 6971 RR Lyrae candidates out to ∼335 kpc, and we estimate that our sample is >70% complete at ∼150 kpc. We find excellent agreement with other wide-area RR Lyrae catalogs and RR Lyrae studies targeting the Magellanic Clouds and other Milky Way satellite galaxies. We fit the smooth stellar halo density profile using a broken-power-law model with fixed halo flattening (q = 0.7), and we find strong evidence for a break at = - R 32.1+ kpc 0 0.9 1.1 with an inner slope of = - - n 2.54+ 1 0.09 0.09 and an outer slope of = - - n 5.42+ 2 0.14 0.13. We use our catalog to perform a search for Milky Way satellite galaxies with large sizes and low luminosities. Using a set of simulated satellite galaxies, we find that our RR Lyrae-based search is more sensitive than those using resolved stellar populations in the regime of large (rh 500 pc), low-surface-brightness dwarf galaxies. A blind search for large, diffuse satellites yields three candidate substructures. The first can be confidently associated with the dwarf galaxy Eridanus II. The second has a distance and proper motion similar to the ultrafaint dwarf galaxy Tucana II but is separated by ∼5 deg. The third is close in projection to the globular cluster NGC 1851 but is ∼10 kpc more distant and appears to differ in proper motion. © 2021 Institute of Physics Publishing. All rights reserved

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

Peer reviewe

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

A conceptual model for action and design research

Organizational research has a pattern of special characteristics which make a clear distinction from other research paradigms. When using these approaches – based on Action and Design – the Interpretivist, Constructivist, and Participatory perspectives dominate. They have already proven to have strong foundations, which turn these paradigmatic approaches into effective ways for getting knowledge, doing things, and promoting change within organizational settings. It combines the traditional scientific, engineering, and organization development approaches, depicting how an organization can, simultaneously, solve multidimensional problems and produce actionable knowledge, effective change and useful artifacts. It has been developed using a Design Science Research approach, tested in a major organizational change program (Henriques, 2015; Henriques & ONeill, 2014), and successfully used to teach research methods essentials to Master and DBA students.info:eu-repo/semantics/publishedVersio

Providing Universal Access While Avoiding Antiretroviral Resistance: Ethical Tensions in HIV Treatment

The provision of effective antiretroviral therapy is an ethical imperative, and global access to antiretroviral drugs is an important aspect of this. The other less recognised aspect of effective HIV management is in ensuring that HIV does not become resistant to the drugs used in treatment (and increasingly also in prevention), as multi-drug resistant HIV poses a major threat to the sustainability of current responses to HIV control. In resource-constrained environments, the rapid scale up of access to life-saving anti-HIV treatment was achieved using a public health approach that standardised antiretroviral regimens, minimised laboratory monitoring, and devolved responsibilities from clinicians where necessary. In recent years demand for antiretroviral treatment has increased due to new understandings of the clinical importance of early treatment, but global investment has declined. Exponential growth of the population using antiretrovirals without careful monitoring increases the risk of significant antiretroviral drug resistance. In this chapter, I consider the example of single-drug interventions to prevent parent-to-child HIV transmission, and how the implementation of that strategy increased health risks for mothers. I argue that while global antiretroviral scale up must continue, laboratory monitoring at individual and national levels needs to improve to maintain treatment effectiveness, and protocols for moving people from failing regimens need to be strengthened

How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?

Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition