Changing places: some practical outcomes from a reclassification project using DDC22

Abstract: Want to know about the practical steps involved in reclassifying an area of stock? What about some recommnedations before undertaking such a task? This is the article for you as it provides answers developed from lessons learned during a real experience, in 2005, when the author completed a reclassification project during a six-month temporary contract at the Surrey Institute of Art and Design

Managing an arts institutional repository

The article describes the background to UCA Research Online which originated from the Kultur project of 2007-2009 and then goes onto detail the management of the institutional repository at UCA

Raising the profile of research data management: the UCA story

During the course of this project there were three key achievements: contribution to the Environmental Assessment Report, the composition of a discussion paper 'Towards a Research Data Management Policy for UCA' and as a result of this the creation of a Research Data Management (RDM) policy. The areas of communication, dissemination, collaboration and an increased understanding of research data management are four key areas which have emerged as a result of this project. Underpinning these areas has been the development of relationships with key stake-holders within UCA and also the participation in external events and training. The following case study will outline the background, challenges, approach and lessons learned from the experience of working on the Kaptur project

JISC funded Kaptur project environmental assessment report

The overall objective of the JISC funded Kaptur project (October 2011 - March 2013) is to discover, create and pilot a sectoral model of best practice in the management of research data in the visual arts. This report outlines findings from the first workpackage, environmental assessment, based on the following research question: What is the nature of visual arts research data? Appendix A provides detail on the methodology; data was gathered from a literature review and 16 face-to-face interviews with visual arts researchers; four at each partner institution: Glasgow School of Art; Goldsmiths, University of London; University for the Creative Arts; and University of the Arts London

Exploring research data management in the visual arts

This workshop will enable participants to explore the nature of research data in the visual arts and the essential elements of its appropriate management. For researchers, the effective management of research data helps validate and contextualise the outputs of artistic research, while at the same time supports the research method by enabling researchers to work more effectively and to mitigate against the risk of data lost. In addition, many funders now require data management plans to be submitted as part of the funding process. Funded by the Arts and Humanities Research Council (AHRC), and led by the Centre for Digital Scholarship (formerly VADS), at the University for the Creative Arts, and working in partnership with Falmouth University and the Glasgow School of Art, the VADS4R project is developing a series of tailored skills development workshops and materials on research data management in the visual arts. These are focused on the needs of early careers researchers and postgraduate students in the visual arts and will be piloted over the course of the academic year 2013-14

UCARIS: Developing a research information system for a specialist arts institution

In response to the Higher Education Funding Council of England (HEFCE) research quality assurance assessment exercise, the Research Excellence Framework in 2014 (REF), the University for the Creative Arts (UCA) identified a need to establish a centralised information system to gather, manage and maintain relevant data relating to its research and researchers in order to effectively prepare for the university’s REF submission. In 2010 internal funds were secured to develop UCA Research Information System (UCARIS). The project proposed the development of a comprehensive, university wide research information system using the EPrints repository platform. As well as being seen as critical for the REF submission, the overarching approach of the implementation of UCARIS was that there should be ‘one input, many outputs’, in order to minimise the burden on academics and administrators in producing publications lists and reports for other internal and external purposes

Correction to: Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

In the original publication of the article, consortium author lists were missing in the articl

Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

In the original publication of the article, consortium author list was missing in the article

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe