Open Research Exeter - University of Exeter
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Towards a Cultural Geography of Queer Storytelling through Collective Biography
No full textThis research project explores the power and value of queer storytelling through queer collective biographies – illustrated books containing collections of short biographies of LGBTQ+ people, telling the stories of queer lives from across the world, past and present, the famous and the everyday. This interdisciplinary research project brings together cultural geography, literary studies, and sexuality studies to establish a cultural geography of queer storytelling through collective biography which uncovers how these texts communicate knowledge, shape identities, create meaning and impact, and articulate cultural values.
Calling for literary geographies to pay attention to the genre of biography, this project uses a relational literary geographies approach, drawing on the conceptual frameworks of ‘text-as-spatial-event’ (Hones, 2008) and ‘book-as-assemblage’ (Anderson, 2015) to present a holistic understanding of ‘queer collective biography-as-assemblage’. This thesis asserts that the meaning and impact of queer collective biographies emerge out of an entangled network encompassing the interactions between an author-text-reader nexus, their relationships with external actors, and their intersections with spaces, and socio-political, cultural, and historical contexts. Methodologically, this thesis brings into conversation textual and visual analysis of eight queer collective biographies and semi-structured interviews with creators (authors, illustrators, editors, and publishers), circulators (teachers, queer bookshop owners, and librarians), and readers.
This project uncovers the complexities of writing queer lives, asking whose stories are told and by whom, through conceptualising ‘the queer publishing network’, shaped by concurrent personal motivations and commercial considerations. This thesis explores how queer lives are written, highlighting the challenges of navigating language and labels of queerness, privacy, and absence, when writing and illustrating queer lives, as well as uncovering the shortcomings of collective biography as a genre for telling queer stories. Moreover, this project draws attention to the narratives used to describe queer lives. Findings show that labels of heroes and icons perpetuate homonormativity; there must be critical engagement with the politics of visibility; and there is a need to platform queer joy whilst still attending to the difficult realities of LGBTQ+ life.
This thesis attends to the impact and meanings generated through readers’ encounters with books about queer lives through exploring the social, cultural and political possibilities (and limitations) of queer storytelling. It asserts that queer collective biography shapes understandings of identity and queerness in the world; provides affirmative, joyful, and empowering representation; creates a sense of community and belonging; promotes resistance and resilience; and provides an educational resource. Overall, this thesis argues that queer storytelling through collective biography is a powerful and valuable tool in times of crisis, fear, and hostility in the face of uncertain futures created by the anti-LGBTQ+ discourse that permeates UK society today.</p
Classification of Fundus Images for Early Diabetic Retinopathy Detection Using Evolutionary Algorithms
No full textObjective: This study explores the classification of diabetic retinopathy using fundus images and evaluates the effectiveness of evolutionary computation techniques, with the goal of improving the accuracy and efficiency of diagnosis in ophthalmology. Method: This study utilized a recently collected open-source dataset of fundus images from India. The images were acquired using Eidon equipment, which features confocal wide-field Scanning Laser Ophthalmoscopy (SLO) for non- mydriatic fundus imaging. Each image was manually classified by two expert specialists, who identified all cases of Non-Proliferative Diabetic Retinopathy (NPDR) and determined the disease stage at the time of capture, categorizing them into three classes: No DR, Mild DR, and Moderate NPDR. Result: The results for diabetic retinopathy grading using evolutionary algorithms showed that, after training the model over 400 generations, the algorithm stabilized at an accuracy of approximately 62.5% with a lowest achieved cost of 0.3. This training was conducted using a balanced dataset consisting of 20 positive and 20 negative DR images, divided into two classes. To further evaluate performance trends, the training process was repeated, this time over 7 generations, to monitor changes in cost and accuracy during the early stages of evolution. Conclusion: Diabetic retinopathy (DR) is one of the leading causes of vision impairment globally, highlighting the critical need for early detection and effective management strategies. Recent advancements in evolutionary algorithms (EAs) have demonstrated considerable potential in enhancing the accuracy and efficiency of DR diagnosis and treatment. In particular, neuro-evolution algorithms—which combine the strengths of neural networks and evolutionary computation—offer promising avenues for improving automated diagnostic systems.</p
Early detection of diabetic foot complications by analysis of plantar pressure with machine learning
No full textObjective: Diabetic foot complications, such as ulcers and amputations, remain a major challenge in diabetes care, largely due to peripheral neuropathy. These conditions significantly reduce quality of life and contribute to rising healthcare costs. Current monitoring approaches often fail to detect early internal changes in foot health, limiting opportunities for timely intervention. Plantar pressure measurement is a promising tool, providing insight into stress distribution across the foot and offering early warning signs of ulcer risk. This project aims to explore how machine learning (ML) can be applied to plantar pressure data to identify patterns associated with increased ulcer risk. The ultimate goal is to support personalised, preventive care for individuals with diabetes. Method: This study will design a protocol to collect plantar pressure data using pressure-sensing insoles from both healthy individuals and people with diabetes. Various ML models will be developed to analyse this data and identify features predictive of high-risk pressure patterns. Data preprocessing, feature selection, model training, and validation will be conducted using Python based ML frameworks. Additionally, interpretability techniques will be integrated to ensure model transparency and support clinical decision-making. Result: Results are currently in progress in the early-stage of development. Expected outcomes include a prototype ML model capable of detecting high-risk plantar pressure patterns and insights into how ML can enhance diabetic foot monitoring by identifying pressure patterns. Conclusion: This project is developing an innovative, novel data-driven approach to diabetic foot care by applying ML to plantar pressure analysis. If successful, it could enable more proactive and personalised prevention strategies, helping to reduce the risk of severe complications in people with diabetes</p
Building a professional imaginary of writing pedagogy: working with teacher knowledge and beliefs about writing
No full textIn various settings internationally, and in England in particular, writing pedagogy and associated practice is reported as being enacted in contexts of high-stakes accountability. These contexts contribute to a prevailing social imaginary for literacy education that can frame and constrain the possibilities for teachers and learners, meaning that opportunities to develop writing pedagogy and practice that are inclusive, expansive, responsive to change and socially just are restricted.
In this paper, in the light of contextual information, the social imaginary for literacy education is described and conceptualised in relation to teacher knowledge and beliefs about writing. Next, a scoping style review of relevant research and theoretical literature from the last twenty years, that reports insights into teacher knowledge and beliefs about writing and writing pedagogy is presented. Nine themes and associated claims are constructed as a result of the insights derived and are presented collectively to provoke research-informed critical reflection about the nature of teacher knowledge and beliefs about writing and writing pedagogy in relation to the social imaginary and its effects.
To conclude, an alternate imaginary is presented as an ideal: The Professional Imaginary for Writing Pedagogy. This imaginary brings teacher knowledge about the social imaginary for literacy education into relation with teacher professional knowledge, to promote pedagogies and practices for writing that are inclusive, expansive, responsive and socially just.</p
Explaining and exploiting the radial memory effect in multimode optical fibres
No full textLight propagation through a multimode optical fibre results in a seemingly random speckle pattern at the output. This makes it difficult to harness the full information capacity such fibres are theoretically capable of supporting. Yet, propagation through a fibre is fully deterministic, which leads to correlations in the apparently random output. In this work we explain and characterize the so-called ``radial memory effect", which manifests as an output ring of excess energy at the same radius as an input focussed spot. We show that this effect is robust against the bending of the fibre, we discuss its connections with other known correlations, and develop a scheme for its use for spatial multiplexing.</p
Links between central visual field loss and movement processing during walking
No full textBackgroundCentral visual field loss (CFL) is the most common irreversible visual impairment in aging and is associated with higher fall risk and concerns about falling. This study explored the links between CFL severity, functional balance, and walking-related attentional processing implicated in reduced gait performance.MethodsIn Study 1, 29 individuals with CFL and 29 age-matched controls completed the Timed Up and Go (TUG) test. In Study 2, 10 CFL participants and 10 controls performed the TUG while acceleration data were collected from head and trunk IMUs. For both studies, we assessed visual impairment severity (contrast sensitivity) and participants’ attentional processing during walking (Gait-Specific Attentional Profile, G-SAP).ResultsBoth groups showed positive correlations between TUG duration and G-SAP subscales. G-SAP scores were lower in CFL participants with worse contrast sensitivity indicating reduced cognitive processing during walking. Worse contrast sensitivity was also associated with greater head and trunk acceleration and acceleration variability during walking, suggesting reduced gait stability. Higher rumination and conscious movement processing scores also correlated with improved segmental control in CFL.SignificanceIncreased cognitive processing of gait is associated with impaired functional balance. This association appears to be reversed in CFL, with severe visual deficit diverting cognitive resources from movement control. This altered strategy may prioritise the acquisition and processing of visuospatial information in CFL. The observed postural instability with increasing CFL severity and a lack of excessive cognitive involvement in movement control suggest heightened gait-specific attention could be leveraged for balance and gait training in CFL.</p
Phosphorus and base cations drive contrasting root dynamics in a central Amazon forest
No full textBackground and aims In highly weathered soils of central Amazonia, where nutrients such as phosphorus (P) and base cations are scarce, fertilization experiments have demonstrated above- and belowground effects on total net primary productivity (NPP). This study examined how fine root stocks and turnover responded to added nutrients over a two-year period. We predicted that adding a limiting nutrient would decrease fine root stocks and increase turnover, with the strongest effects from P, followed by base cations, and no response to N. Methods Fine roots (< 2 mm diameter) were sampled from the 0–30 cm soil layer in a low-fertility primary forest in central Amazon subjected to a large-scale factorial experiment adding P, base cations, and N over two years. Fine root turnover was calculated as the ratio between fine root productivity, measured with in-growth cores, and fine root stock. Results Fine root stocks remained unchanged with nutrient addition. However, P increased root turnover by 23% and 48% in the first and second years, respectively, while base cations addition reduced turnover by 24% in year two. N had no significant effect, though a trend toward reduced turnover was observed in the second year. Conclusion The results of this study show that fine root standing stock and turnover in the central Amazon are regulated by soil nutrient availability, especially P and base cations. The contrasting responses observed suggest distinct belowground resource-use strategies for different nutrients, shaped by the nutrient specific mobility in the soil and physiological role in the plant.</p
Feasibility of the MAINTAIN intervention to support independence after a fall for people with dementia: a pilot cluster randomised controlled trial in participants’ own homes
No full textObjectives
To evaluate the feasibility of conducting a full-scale randomised controlled trial to assess the clinical and cost-effectiveness of the MAINTAIN intervention, designed to support recovery and independence following a fall among people living with dementia.
Design
Pilot cluster randomised controlled trial (c-RCT).
Setting
Community-based healthcare services across six UK sites representing primary and secondary care settings.
Participants
31 participant-carer dyads were recruited. Eligibility criteria included a diagnosis of dementia and a recent fall. Exclusion criteria included severe comorbidity precluding participation. The consent rate was 84%, and retention at follow-up was 81%.
Interventions
The MAINTAIN intervention comprised tailored, home-based therapy sessions delivered by trained professionals, focusing on functional recovery, confidence and re-engagement in daily activities, compared with usual care. The intervention was delivered over 12 weeks with booster sessions up to week 24, with the full trial period lasting 28 weeks.
Primary and secondary outcome measures
Feasibility outcomes included recruitment and retention rates, intervention adherence and data completeness for outcome and economic measures. Exploratory outcomes assessed functional performance and quality of life. Feasibility outcomes were assessed at baseline, 12 weeks and 28 weeks.
Results
Recruitment occurred over an 8-month period (September 2023–April 2024) across six UK sites. Most intervention participants (89%) attended at least 60% of planned sessions. Completion rates for outcome and economic data were high, indicating strong acceptability and feasibility of both the intervention and trial procedures.
Conclusions
The pilot c-RCT demonstrated that recruitment, retention and intervention delivery were feasible and well accepted. Findings support progression to a definitive trial to evaluate the effectiveness and cost-effectiveness of the MAINTAIN intervention.
Trial registration number
ISRCTN16413728
(International Standard Randomised Controlled Trial Number registry).</p
The signals we give: Performance feedback, gender, and competition
No full textFeedback is vital for growth and learning, yet anecdotal evidence suggests people often hesitate to provide it, and its provision may be shaped by asymmetries and gender-related biases. We study feedback provision across variations in the nature of performance signals, their instrumental value, and the recipient’s gender. We find that a surprising degree of both positive and negative feedback is withheld, with a follow-up experiment suggesting that advisors’ feedback decisions are driven mainly by transparency- and duty-related considerations, or, to a lesser extent, are motivated by self-serving reasons. Additionally, when initial performance signals are vague, advisors are more likely to withhold non-instrumental negative than positive feedback—an effect we conjecture may be stemming from the lower psychological cost of lying (by omission) under uncertainty. Suggestive evidence shows the difference is more pronounced for female recipients, and exploratory analysis traces this to stronger ego-protective concern by advisors for women than for men.</p
Vector fields as a framework for modelling the mobility of commodities
No full textCommodities flow through trade networks across the world, with trajectories that can be effectively modelled using approaches similar to those used in human mobility studies. Yet, documenting these movements comprehensively is challenging due to data sparsity, cost, and privacy constraints. Origin-destination (OD) matrices provide a widely used framework for representing mobility, although they inherently omit locations not directly observed as either origins or destinations. This incompleteness creates gaps across different geographical scales, constraining our ability to characterise movement patterns in underrepresented areas. In this study, we introduce a vector-field-based method to address these persistent data challenges. By transforming OD data into continuous vector fields, we capture spatial flow patterns more comprehensively than traditional network approaches, while also enabling robust analysis of mobility directions. Our approach incorporates interpolation techniques that handle incomplete and sparse datasets effectively; when approximately 500 out of 853 areas are removed, 189 areas (36%) maintain degree deviations of less than 15 degrees, showing that the general direction of flow is preserved for over one-third of the impacted areas and enabling continuous spatial analysis. We apply this framework to cattle trade data from Minas Gerais, Brazil. Cattle movements are particularly significant as they directly impact disease transmission, including foot-and-mouth disease. Accurately modelling these flows supports effective disease surveillance and preparedness, with benefits for both animal health and economic stability. Our analysis reveals distinct spatial clusters of trade behaviour, temporal patterns in flow directions, and seasonally varying critical points likely associated with known periodicities in cattle trade driven by breeding cycles, slaughter schedules, and fluctuations in global demand. While previous vector-field studies focused on human mobility, our framework addresses the distinct challenges of commodity flows, where aggregated OD data, sparse observations, and lack of data are the norm. It enables inference in unobserved areas which is a critical capability for modelling scenarios such as disease spread. This approach enhances our capacity to infer flow patterns from incomplete datasets and advances understanding of large-scale commodity trade dynamics.</p