922017 research outputs found
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Analysing single cell secretions by ‘shadow imaging’
No full textHere, we describe a method, which we term ‘shadow imaging’, to analyse the secretions of individual cells at immune synapses, or other cell contacts. Following immune synapse formation and cellular activation on ligand-rich slides the position of each cell is recorded using a pulsed immunofluorescence stain against the proteins on the ligand-rich slide surface. The pulsed stain does not penetrate the synaptic cleft, resulting in an unlabelled region or ‘shadow’ beneath cells that is retained following cellular detachment. The secreted components, such as perforin, exosomes or other types of extracellular vesicles are retained on the slide and can be analysed on a single-cell basis using immunofluorescence. The ability to identify single cells secreting different combinations of particles, proteins and vesicles, enables us to better understand the heterogeneity in immune cell secretions, and can be used as a novel approach for phenotyping cell populations
Measuring Risk of Re-identification in Microdata: State-of-the Art and New Directions
No full textWe review the influential research carried out by Chris Skinner in the area of statistical disclosure control, and in particular quantifying the risk of re-identification in sample microdata from a random survey drawn from a finite population. We use the sample microdata to infer population parameters when the population is unknown, and estimate the risk of re-identification based on the notion of population uniqueness using probabilistic modelling. We also introduce a new approach to measure the risk of re-identification for a subpopulation in a register that is not representative of the general population, for example a register of cancer patients. In addition, we can use the additional information from the register to measure the risk of re-identification for the sample microdata. This new approach was developed by the two authors and is published here for the first time. We demonstrate this approach in an application study based on UK census data where we can compare the estimated risk measures to the known truth. <br/
“My life isn't my life, it's the system’s”: A qualitative exploration of women’s experiences of day-to-day restrictive practices as inpatients
No full textIntroductionInpatient care often involves restrictive interventions such as seclusion and restraint and restrictive practices that limit the person’s freedom, rights, and daily activities. Restrictive practice has not been the explicit focus in previous research however, it often appears as an important theme, with participants identifying it can have a detrimental effect on their wellbeing. More research specifically on this topic in an inpatient setting is therefore needed. Women might be particularly vulnerable to adverse effects of restrictive practices compared to men as women generally occupy less powerful positions in society and more often experience abuse. AimsThe study aimed to explore women’s experiences of routine restrictive practices in mental health inpatient settings. MethodsTwenty-two women who were currently inpatients on mental health wards were interviewed about their experiences of restrictive practices in hospital. Interviews were analysed using thematic analysis. ResultsAn overarching theme emerged of powerlessness. Four key subthemes were also identified: restrictions perceived as punitive, having no voice, impact of restrictions on relationships, and restrictions providing safety and support. DiscussionAlthough restrictive practices were found to provide the women with a sense of safety, they were also found to impact upon the women’s well-being, leading to increases in self-harm and over-reliance on restrictions. Implications for practiceThis research highlights the importance of gender-informed inpatient services for women that foster independence, empowerment and allow women to have their voices heard. Safewards interventions such as clear mutual expectations and soft words could contribute to mitigating the impact of restrictive practices
Applications of Immersive Technologies for Occupational Safety and Health Management in the Construction Industry: A Systematic Review
No full textThe construction industry contributes significantly to workplace fatalities and injuries despite multiple interventions implemented by governments and construction companies. Recently, immersive technologies as part of a suite of industry 4.0 technologies have also strongly emerged as a viable pathway to help address poor construction occupational safety and health (OSH) performance. A review of literature on the application of immersive technologies for construction OSH management is conducted with the aim of gaining a broader view of different construction OSH areas using the preferred reporting items for systematic reviews and meta-analysis (PRISMA) approach. The evaluation of 79 relevant articles were carried out, selected from Scopus database. The review revealed that literature have focused on the application of various immersive technologies for hazard identification and visualisation, safety training, design for safety, risk perception and assessment in various construction works. This review identified several limitations regarding the use of immersive technologies, which include the low level of adoption of developed immersive technologies for OSH management, very limited research works on the application of immersive technologies for health hazards and limited focus on the effectiveness of various immersive technologies for construction OSH management. Future research should identify possible reasons for the low level knowledge transfer from research to practice and proffer ways of addressing the identified reasons. The effectiveness of the use of immersive technologies for addressing health hazards should also be investigated
Bounds for the chi-square approximation of Friedman’s statistic by Stein’s method
No full textFriedman’s chi-square test is a non-parametric statistical test for r treatments across n trials to assess the null hypothesis that there is no treatment effect. We use Stein’s method with an exchangeable pair coupling to derive a bound on the distance between the distribution of Friedman’s statistic and its limiting chi-square distribution, measured using smooth test functions. Our bound is of the optimal order n−1, and also has an optimal dependence on the parameter r, in that the bound tends to zero if and only if r/n→0. From this bound, we deduce a Kolmogorov distance bound that decays to zero under the weaker condition r1/2/n→0
IDENTIFYING VULNERABLE LINES CONSIDERING UNCERTAIN HEAT ELECTRIFICATION IN INTEGRATED GAS AND ELECTRICITY NETWORKS
No full textThe installation of heat pumps, powered from clean electricity sources, will play a key role in heat decarbonisation. However, the resulting surge in electricity demand will put the existing transmission lines under enormous strain, increasing the risk of line overloading, potential failure and even loss of load events. This paper presents a probabilistic method for assessing line overload in integrated gas and electricity networks with the consideration of heat electrification. The established model fully considers the uncertainties associated with intermittent generation and fluctuating loads. The effectiveness of the proposed method is verified via its application in an integrated 9-bus electricity and 8-node gas network. Numerical results show that the overload probability of power lines and gas pipelines increases as a result of heat electrification. The overload probability further rises when the correlations of renewable generation and loads are considered, confirming the significance of modelling correlation for an accurate estimation of power and gas flows. The overload probability of some power lines and gas pipelines soar as they become disproportionately loaded, when considering an uneven distribution of heat loads (i.e., clustering of lowcarbon technologies) in the electricity network.<br/
Obstetric Outcomes in Women with Rheumatic Disease and COVID-19 in the Context of Vaccination Status
No full textObjective:To describe obstetric outcomes based on COVID-19 vaccination status, in women with rheumatic and musculoskeletal diseases (RMDs) who developed COVID-19 during pregnancy. Methods:Data regarding pregnant women entered into the COVID-19 Global Rheumatology Alliance registry from 24 March 2020 to 25 February 2022 were analysed. Obstetric outcomes were stratified by number of COVID-19 vaccine doses received prior to COVID-19 infection in pregnancy. Descriptive differences between groups were tested using the chi -square or Fisher’s exact test. Results: There were 73 pregnancies in 73 women with RMD and COVID-19. Overall, 24.7% (18) of pregnancies were ongoing, while of the 55 completed pregnancies 90.9% (50) of pregnancies resulted in livebirths. At the time of COVID-19 diagnosis, 60.3% (n=44) of women were unvaccinated, 4.1% (n=3) had received one vaccine dose while 35.6% (n=26) had two or more doses. Although 83.6% (n=61) of women required no treatment for COVID-19, 20.5% (n=15) required hospital admission. COVID-19 resulted in delivery in 6.8% (n=3) of unvaccinated women and 3.8% (n=1) of fully vaccinated women. There was a greater number of preterm births (PTB) in unvaccinated women compared to fully vaccinated 29.5% (n=13) vs 18.2%(n=2). Conclusion:In this descriptive study, unvaccinated pregnant women with RMD and COVID-19 had a greater number of PTB compared with those fully vaccinated against COVID-19. Additionally, the need for COVID-19 pharmacological treatment was uncommon in pregnant women with RMD regardless of vaccination status. These results support active promotion of COVID-19 vaccination in women with RMD who are pregnant or planning a pregnancy.<br/
Comparison of biomedical relationship extraction methods and models for knowledge graph creation
No full textBiomedical research is growing at such an exponential pace that scientists, researchers, and practitioners are no more able to cope with the amount of published literature in the domain. The knowledge presented in the literature needs to be systematized in such a way that claims and hypotheses can be easily found, accessed, and validated. Knowledge graphs can provide such a framework for semantic knowledge representation from literature. However, in order to build a knowledge graph, it is necessary to extract knowledge as relationships between biomedical entities and normalize both entities and relationship types. In this paper, we present and compare a few rule-based and machine learning-based (Naive Bayes, Random Forests as examples of traditional machine learning methods and DistilBERT, PubMedBERT, T5, and SciFive-based models as examples of modern deep learning transformers) methods for scalable relationship extraction from biomedical literature, and for the integration into the knowledge graphs. We examine how resilient are these various methods to unbalanced and fairly small datasets. Our experiments show that transformer-based models handle well both small (due to pre-training on a large dataset) and unbalanced datasets. The best performing model was the PubMedBERT-based model fine-tuned on balanced data, with a reported F1-score of 0.92. The distilBERT-based model followed with an F1-score of 0.89, performing faster and with lower resource requirements. BERT-based models performed better than T5-based generative models
Governance choice misfit and firm performance in offshoring innovation: The role of institutional environment
No full textIn this paper, we analyse the effect of institutional factors on the relationship between governance choices and business outcomes when offshoring innovation. Grounded in an institutional theory perspective, we use survey data from the ORN database to estimate regression models and identify governance modes related to specific drivers of offshore innovation. We then analyse the effect on firm performance of choosing a governance mode not in line with the one predicted by the model. We find that choosing a fully owned offshoring operation when theory would predict selecting offshore outsourcing has a negative effect on performance, but not vice versa. We also find that institutional factors of rule of law and IPR protection strength in host countries negatively affect firm performance when offshoring innovation activities
Biographical accounts of the impact of fatigue in young people with sickle cell disease
No full textChildren and young people (CYP) with sickle cell disease (SCD) are a 'missing voice' in the debate on biography and sociology of chronic illness, meaning we know little about the social consequences of the illness for CYP. This paper examines the meaning of fatigue (a common symptom) for adolescents with SCD. Analysing 24 in-depth interviews with adolescents aged 12-17 years in Ghana, we draw on the distinction proposed by Bury (1988) between 'meanings as significance' and 'meanings as consequence' to examine biographical aspects of fatigue. We argue that concepts of 'biographical disruption' and 'normal illness' do not easily accommodate the experience of CYP with congenital chronic illnesses like SCD, as their sense of (un)disruption and normality/continuity is contextualised relative to normative expectations about what it is to be a young person. At biographical transition points, illness/symptoms present from birth may evolve, shift and become experienced as 'new', 'different', or 'non-normal'. They may become restrictive rather than continuous or disruptive. These experiences are influenced primarily by normative biographical expectations and the pursuit of identity affirmations. We propose that biographical restriction, biographical enactment, biographical abandonment and biographical reframing are more relevant concepts for understanding the experiences of CYP living with SCD