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Use design thinking and storytelling to help international students find their voices
No full textWe’ve been experimenting with design thinking, a human-centred approach to innovation based on deep empathy with the intended audiences, co-creating ideas and generating solutions, to help students like these. In doing so, we created the Warwick Secret Challenge methodology, a problem-solving workshop that uses design thinking to tackle innovation challenges through authentic student-staff co-creation. Here are some activities that have worked well
Practice Guides : guides to ESD in practice
No full textThis set of ESD practice guides are intended to offer examples of activity already being undertaken in the UK higher and further education sectors to embed Education for Sustainable Development (ESD) into teaching, learning and assessment. The guides complement guides published in 2021 by Advance HE and QAA
Epidemiological and health economic implications of symptom propagation in respiratory pathogens : a mathematical modelling investigation
Get PDFBackground: Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied. Methods and findings: We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens—seasonal influenza, pandemic influenza and SARS-CoV-2—we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation. Conclusions: Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis
Pandemic narratives in stories about hospice palliative care : the impact of Covid-19 upon ideals of timely, holistic care and quality of life
Get PDFBackground
Hospice palliative care aims to provide timely interventions and holistic care that focusses on quality of life for people who are terminally ill. In the first two years of the Covid-19 pandemic the national political and healthcare contexts changed significantly. Throughout this time hospices had to repeatedly adjust their approach to supporting terminally ill people, many of whom were especially vulnerable to Covid-19.
Aim
The aim of this paper was to explore hospice patients, carers, staff and senior managers stories to identify how changing pandemic narratives affected their understanding of hospice palliative care as timely, holistic and supporting quality of life.
Methods
Narrative analysis of in-depth interviews with patients, carers, staff and senior managers (n = 70) recruited from hospices across the West-Midlands, UK, in 2020–22.
Findings
We identified four ‘pandemic narratives’ (reaction; revision; resilience; (re)normalisation) in the participants' accounts of hospice palliative care support in the first two years of the pandemic. In each narrative we explore how Covid-19 and the associated pandemic guidance affected what quality of life was understood to be; how what was considered to be timely care could change during the palliative care journey; and, how different ideas of holistic care were emphasised as the hospice and wider healthcare context changed.
Conclusion
This is the first-time stories about the first two-years of the Covid-19 pandemic from hospice patients, carers, staff and senior managers have been analysed together. We identified how the pandemic brought an existential challenge to ideas of what hospice palliative care is and could be. Our findings suggest that ‘living with covid’ will continue to affect hospice palliative care's ideals of timeliness of care, holistic support, and quality of life left
What range of motion (ROM) does a hip arthroplasty actually need? A CT-based method to predict an individual's hip rom preoperatively
No full textIdeally the hip arthroplasty should not be subject to bony or prosthetic impingement, in order to minimise complications and optimise outcomes. Modern 3d planning permits pre-operative simulation of the movements of the planned hip arthroplasty to check for such impingement. For this to be meaningful, however, it is necessary to know the range of movement (ROM) that should be simulated. Arbitrary “normal” values for hip ROM are of limited value in such simulations: it is well known that hip ROM is individualised for each patient. We have therefore developed a method to determine this individualised ROM using CT scans.
CT scans were performed on 14 cadaveric hips, and the images were segmented to create 3d virtual models. Using Matlab software, each virtual hip was moved in all potential directions to the point of bony impingement, thus defining an individualised impingement-free 3d ROM envelope. This was then compared with the actual ROM as directly measured from each cadaver using a high-resolution motion capture system.
For each hip, the ROM envelope free of bony impingement could be described from the CT and represented as a 3d shape. As expected, the directly measured ROM from the cadaver study for each hip was smaller than the CT-based prediction, owing to the presence of constraining soft tissues. However, for movements associated with hip dislocation (such as flexion with internal rotation), the cadaver measurements matched the CT prediction, to within 10°.
It is possible to determine an individual's range of clinically important hip movements from a CT scan. This method could therefore be used to create truly personalised movement simulation as part of pre-operative 3d surgical planning
Accreditation of analogue quantum simulators
Get PDFWe present an accreditation protocol for analogue, i.e., continuous-time, quantum simulators. For a given simulation task, it provides an upper bound on the variation distance between the probability distributions at the output of an erroneous and error-free analogue quantum simulator. As its overheads are independent of the size and nature of the simulation, the protocol is ready for immediate usage and practical for the long term. It builds on the recent theoretical advances of strongly universal Hamiltonians and quantum accreditation as well as experimental progress toward the realization of programmable hybrid analogue–digital quantum simulators
Spectrogram-based approach with convolutional neural network for human activity classification
No full textHuman activity recognition (HAR) is an expanding research field for analyzing holistic wellbeing trajectory, frailty detection and prevention of critical situations. With the increased availability of wearables and novel machine learning methods, the automatic recognition of human activities is exploited by real-time signals via Deep Learning techniques. This is due to their capability of learning contextual and localized patterns which give them a significant edge over traditional machine learning approaches. However, most of the state-of-the-art deep learning techniques have limitations due to limited number of features present in temporal dimension. In this regard, we propose Spectrogram-driven multilayer 2D-Convolutional Neural Network (2D-CNN) to classify among different types of human activities using triaxial accelerometer data obtained under MEDICON Scientific Challenge. The spectrogram has significant advantage over 1D time domain signals due to their capability to extract power spectrum in time as well as in frequency domain. The dataset consists of twelve activities of daily living and three types of simulated falls performed by subjects wearing a single accelerometer. In total, the dataset was composed by 468 instances. The spectrograms were determined by Short Time Fourier Transform (STFT) from the continuous signal obtained from X-, Y-, and Z-axis of the accelerometer signals. Experimental results show that our spectrogram driven 2D-CNN model reach an overall accuracy of 86.02% and an overall
-score of 81.09% in classifying all the activity classes; significantly outperforming the deep learning architecture based on 1D time domain signal
The diversity of the antimicrobial resistome of lake Tanganyika increases with the water depth
No full textThe presence of antimicrobial resistance genes (ARGs) in the microbiome of freshwater communities is a consequence of thousands of years of evolution but also of the pressure exerted by anthropogenic activities, with potential negative impact on environmental and human health. In this study, we investigated the distribution of ARGs in Lake Tanganyika (LT)'s water column to define the resistome of this ancient lake. Additionally, we compared the resistome of LT with that of Lake Baikal (LB), the oldest known lake with different environmental characteristics and a lower anthropogenic pollution than LT. We found that richness and abundance of several antimicrobial resistance classes were higher in the deep water layers in both lakes. LT Kigoma region, known for its higher anthropogenic pollution, showed a greater richness and number of ARG positive MAGs compared to Mahale. Our results provide a comprehensive understanding of the antimicrobial resistome of LT and underscore its importance as reservoir of antimicrobial resistance. In particular, the deepest water layers of LT are the main repository of diverse ARGs, mirroring what was observed in LB and in other aquatic ecosystems. These findings suggest that the deep waters might play a crucial role in the preservation of ARGs in aquatic ecosystems