151398 research outputs found
Sort by
Implementing education for sustainable development in teaching and learning practice
No full textEmbedding sustainability in the curriculum is morally and ethically imperative, but also increasingly stakeholders are demanding that sustainability feature so graduates can tackle sustainability issues faced in employment. Graduates need an understanding of the UN Sustainable Development Goals, and to develop abilities across the eight ESD competencies, therefore holding sustainability at the core of their professional and personal practice to make changes locally and globally for sustainable and equitable world (Giangrande et al., 2019). Education for Sustainable Development (ESD) presents a viable pedagogical orientation for achieving this, but educators face difficulty operationalising it (Higgins, 2022). Previous SoTL work regarding ESD has been highly theoretical (Hallinger & Nyugen, 2020), or small-scale case reports focused on singular courses or programmes (Loorback & Wittmayer, 2024). This workshop bridges theory and practice, using the Co-Designing Reflective Approaches for the Teaching of Sustainability (C.R.A.F.T.S) model created by the presenters to embed ESD into courses across disciplines, levels of study, and at a course or programme level (Higgins & Calvert, 2024). Participants will complete this workshop with an understanding of ESD and its core competencies, as well as how to engage learners in sustainability through co-creation, transformative pedagogy, active learning, and authentic assessment. Participants should bring an existing course, or one currently in development, to be worked on through our interactive and tactile approach supported by dialogical coaching practices. Participants in previous iterations of this workshop have stated that it contains “great strategies...to reflect on our practice” and enabled for them “broader thinking...methods and design using a clear path”
Joining the Educational Development Conversation through Blogging
No full textIn this post we (the SEDA Blog editors) reflect on the merits of blogging as discussed in our recent webinar. Many colleagues begin blogging to promote a recently published paper, research project, or institutional initiative. This often makes for our most popular and cited blogs and is an excellent starting point for authors new to blogging! However, a blog offers more than a condensed version of a journal article—it provides a unique opportunity to extend the conversation
Inclusion of under-served groups in trials: an audit at a UK primary care clinical trials unit
No full textBackgroundClinical trials need to include patients who are representative of the population who may receive the tested interventions in the future. The importance of inclusivity is recognised by ethical and funding bodies and has public support. Appropriate inclusion is required to provide equitable evidence-based healthcare and to comply with ethical principles for research. However, there is little information about the inclusivity of most under-served groups in UK clinical trials.MethodsThis audit assesses the inclusion of under-served groups in trials run by the Oxford Primary Care Clinical Trials Unit (PC-CTU). We included trials with ethical approval between 2017 and 2023. We checked protocols, patient-facing information and selected data collection tools for information on the under-served groups in the INCLUDE guidance and protected characteristics in the UK Equality Act 2010, to identify explicit exclusions and data collection.ResultsWe included 19 trials. They were in a variety of clinical conditions, testing different types of interventions, both Clinical Trial of an Investigational Medicinal Product (CTIMP) and non-CTIMP. Most were non-commercially funded. We reviewed 21 protocols, 29 Patient Information Sheets/Leaflets and 40 data collection tools.Common exclusions were based on age (19), sex or gender (11), language (8), capacity to consent (14), pregnancy (11), multiple health conditions (10) and severity of illness (17).Trials most often collected data on age (19), sex or gender (15), ethnicity (16), education (11), address (13), mental health conditions (6), who gave consent (19), addiction (6), multiple health conditions (10), severity of illness (17), smoking status (12) and obesity (13).ConclusionsOften, exclusions were due to the focusing of the trial for a specific group, such as older people, women, or people being treated for a specific severity of condition. However, many explicit exclusions may not have been essential, may have reduced the inclusivity of the trials and might limit the applicability of the trial’s findings to people to whom the tested interventions might be relevant. These include the exclusion of people aged under 18, people without English language fluency and people without capacity to consent. All trials could have collected more informative data on under-served group status.<br/
Stage at diagnosis and breast cancer-specific mortality in breast cancer patients treated with antidepressants, anxiolytics, and antipsychotics: a population-based cohort study from Northern Ireland
No full textPurposeWe examined the stage at diagnosis and breast cancer-specific mortality in a cohort of breast cancer patients prescribed medications used for mental health conditions before diagnosis.MethodsWomen newly diagnosed with breast cancer from 2011 to 2021 were identified from the Northern Ireland Cancer Registry. The primary outcome was time to breast cancer-specific mortality up to March 2023. The secondary outcomes included stage at diagnosis. We identified anxiolytic, antidepressant, and antipsychotic prescriptions dispensed in the year before breast cancer diagnosis from the Northern Ireland Enhanced Prescribing Database. Cox regression models were used to calculate adjusted hazard ratios (aHR) and 95% confidence intervals (95%CIs) for cancer-specific mortality by use of medications.ResultsWe included 13,846 women with breast cancer. In the year before breast cancer diagnosis, 31.5% were dispensed antidepressants, 12.7% anxiolytics, and 3.5% antipsychotics. The odds of late-stage disease presentation in breast cancer patients dispensed medications for mental health conditions was similar to breast cancer patients not dispensed these medications, but patients dispensed antipsychotics had higher odds of unknown stage. We found no difference in the hazard rate of breast cancer-specific mortality in patients dispensed, versus not dispensed, anxiolytics (aHR = 1.06 95%CI 0.93–1.20), a small increase in patients dispensed, versus not dispensed, antidepressants (aHR = 1.11 95%CI 1.01–1.23) and a moderate increase in patients dispensed, versus not dispensed, antipsychotics (aHR = 1.45 95%CI 1.17–1.81).ConclusionsBreast cancer patients dispensed medications for mental health conditions were not at higher odds of presenting with late-stage disease, but patients dispensed antidepressants, and especially antipsychotics, had worse breast cancer-specific mortality.<br/
Use of a priority lane to increase voluntary visits to a milking robot in dairy cows
No full textVoluntary visits to the milking robot are the basis of automatic milking system functionality. Therefore, problems arise when cows are undermotivated to visit the robot. Cows with reduced competitive abilities, specifically those that are lame or low-ranking (or both), are at risk of lower visit frequencies. These cows typically have reduced autonomy as they must conform to the schedules of more dominant herd-mates. Solutions seeking to ameliorate these access issues may thus improve welfare and productivity. We evaluated the effects of providing lame or low-ranking cows with increased access to the milking robot via a priority lane, which provided an additional entrance to the robot for this group only. We aimed to understand the effects of the priority lane upon training duration, milking robot visit behavior, lying behavior, and hair cortisol. We further aimed to understand how losing and gaining access to the priority lane would affect milking robot visit behavior. We hypothesized that priority access would increase total milking robot visits and lying time, decrease milking interval variability and hair cortisol concentrations, and would not affect training duration. Twenty-four lame (mobility score ≥2) or low-ranking (lowest third of herd) cows were matched into 12 pairs of equal mobility, social ranking, or both. Each pair was split over treatments (i.e., priority lane and control). An additional 18 cows were included in the herd to increase competition but could not access the priority lane. Data were collected in 4 phases (pretreatment phase, training phase, treatment phase 1, and treatment phase 2) over a 15-wk period. New priority and control groups were created for treatment phase 2. Training time and hair cortisol concentrations were compared using linear regression, and generalized linear mixed models were used to analyze milking and lying behavior during treatment phase 1. Wilcoxon signed-rank tests were used to compare values between pre- and postregrouping in treatment phase 2. During the training phase and treatment phase 1, priority cows had more lying bouts, and successful, unsuccessful, and total robot visits. No treatment differences in training time, hair cortisol concentrations, lying time, or milking interval variability were observed. During treatment phase 2, cows granted access to the priority lane increased their successful milking visits, whereas cows removed from the priority lane did not decrease their visits. In conclusion, priority access had no effect on welfare indicators or training time. However, it did increase milking robot visit frequency. We suggest that the productivity and welfare benefits of a priority lane may be greater under conditions of greater competition.<br/
TDSRL: time series dual self-supervised representation learning for anomaly detection from different perspectives
No full textAnomaly detection in time series is crucial for applications ranging from finance to industrial monitoring. Effective models need to capture both the inherent characteristics of time series data and the distinct patterns of anomalies. While traditional forecasting-based and reconstruction-based approaches have been successful, they tend to struggle with complex and evolving anomalies. For instance, stock market data exhibits ever-changing fluctuation patterns that defy straightforward modelling. In this paper, we propose a novel method called TDSRL (Time Series Dual Self-Supervised Representation Learning) for robust anomaly detection. TDSRL attach great importance to the frequency domain information throughout the anomaly modelling process. We introduce a data degradation method that simulates real-world anomalies more naturally by operating in both time and frequency domains. Additionally, the key innovations also lie in dual self-supervised pretext tasks: one task characterises anomalies in relation to the entire time series, and the other focuses on local anomaly boundaries using contrastive learning. This significantly improves the network’s discrimination between anomaly and adjacent normal intervals. Consequently, TDSRL is expected to achieve a faster and stronger response to the anomalies, with the potential for early detection. Experimental results show that TDSRL outperforms state-of-the-art methods, making it a promising new direction for time series anomaly detection. The code of our paper is available here: https://github.com/ys-Dai/TDSRL/tree/main
Beyond the cuff - characterising biofilm-forming microorganisms on endotracheal tubes in critically ill patients
No full textBackground/Aims: Mechanical ventilation, commonly used for acute respiratory failure in intensive care units (ICUs), usually involves tracheal intubation with an endotracheal tube (ETT). Microorganisms can attach to the ETT surface within hours, forming biofilms that may serve as infection reservoirs and enhance microbial tolerance to external factors, such as antimicrobials. This study aimed to characterise the diversity of biofilm-forming microorganisms on ETTs, examining differences in biofilm microbial communities from sections above and below the cuff.Methods: Critically ill adults requiring mechanical ventilation through an ETT who were admitted to two participating ICUs within the Belfast Health and Social Care Trust, Northern Ireland, were prospectively recruited between April 2023 and March 2024. Following extubation, pre-defined 1 cm2 sections directly above and below the cuff were excised and biofilms removed. The viable counts (density) of bacteria and fungi (colony-forming units per 1 cm2 section [CFU/cm2]) were determined by extended quantitative culture. Isolate identification was done by MALDI-ToF and/or 16S rRNA (bacteria) or ITS (fungi) marker gene sequencing. Routine microbiological investigations of respiratory samples (secretions, bronchoalveolar fluid, pleural fluid) during hospital admission were recorded, when available, for participants. The study was approved by the Social Care Research Ethics Committee (20/IEC08/0025).Results: Forty participants (mean age, 58 years; 15 female) were included. The median (range) intubation duration was 3 days (<24 hours to 14 days). Overall, 433/456 (95.0%) ETT isolates recovered were identified to the species- (or genus-) level with a median (range) richness of 2 (0-12) in biofilms above and 2 (0-17) below the cuff (p=0.5). No microorganisms were cultured in at least one section of five participant ETTs. There was no difference in the microbial density (geometric mean [95% confidence interval]: above cuff, 2.0 x103 [4.0 x102 – 7.9 x103] CFU/cm2; below cuff, 1.6 x103 [4.0 x102 – 5.0 x103] CFU/cm2; p=0.7) or in the microbial diversity between sections (Shannon-Wiener diversity, median: above cuff, 0.951; below cuff, 0.693; p=0.8). Microbial biofilm communities were more similar within than between patient ETTs. Among the taxa cultured, Candida albicans was the most prevalent (above cuff, 7/40 [17.5%] participants; below cuff, 11/40 [27.5%] participants). Fungal taxa were identified in 32 biofilms and usually co-cultured with bacterial taxa (84% of the time). Recognised respiratory pathogens including Staphylococcus aureus, Pseudomonas aeruginosa and Enterobacteriaceae were also identified in the ETT biofilms. Pathogens were found in 18 participants’ respiratory samples, of whom 9 had the same pathogen recovered from their ETT biofilm.Conclusion: Community profiling showed that microbial biofilms were similar regardless of their origin (above or below the cuff), with fungi frequently detected. Generally, viable microorganisms in most ETT biofilms were present in low density; nonetheless, recognised respiratory pathogens were commonly present. Further studies will investigate the microbial community composition and structure in ETT biofilms using next-generation sequencing.<br/
Crowdsourcing effectiveness at a problem level: a meta-synthesis
No full textCrowdsourcing is commonly portrayed as a tool to tap into the diverse expertise of large (often unknown) crowds to address various problems, a practice we metaphorically label as “fishing”. However, we empirically show that solver appropriateness, i.e. the proximity of solvers’ knowledge and/ or background to the problem requirements, is critical for the effectiveness of crowdsourcing. Through a meta-synthesis of 17 qualitative case studies , we identify different levels of targeting in solver identification for problems with heterogeneous attributes (generic, urgent, highly technical and complex problems). We demonstrate that generic and urgent problems typically benefit from “chance encounters”, as well as semi-targeted recruitment mechanisms. In contrast, adopting more informed approaches in solver identification or preselection increases the likelihood of success for complex or highly technical problems. Put differently, in cases where the alignment between problem attributes and solver appropriateness is blurred or non-existent, the results tend to be meagre and/or the screening costs and information overload for organizations are huge. Finally, we discuss the directions for future research to advance the literature on crowdsourcing at a problem level of analysis
Sonic haunting in Nigel Kneale's ghost stories
No full textThis chapter analyses the use of sound in Nigel Kneale's ghost stories. It specifically covers The Road, 'The Chopper', The Stone Tape, Beasts and The Woman in Black. Through a focus on the scripts, it argues that the use of sound in these productions is very much originated and directed by Kneale as the writer rather than being a decision elsewhere in the production process