Open Research Exeter - University of Exeter
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Not all roads are created equal: network science shows some highways matter more for Brazil’s connectivity
No full textRoad infrastructure is essential for the moving goods and people. Given its logistical importance around the world, a deeper understanding of its network structure can improve connectivity, efficiency, and safety. When viewed through the lens of network science, this system reveals patterns and structural properties that can justify improvements and changes. It also strengthens the ability to plan for control, disaster recovery, and future investments. Brazil is highly dependent on road mobility, with approximately 75,000 kilometers of federal roads that serve as the main national and regional corridors. This paper provides an in-depth analysis of these road networks by modeling the federal system as weighted networks using road segments at both national and regional levels. First, we examine connectivity and topology using the distance between nodes as the primary weight. Next, we incorporate additional metrics: number of incidents, vehicle flow, incidents per kilometer, and flow per road lane. We then focus on community detection to identify clusters of road segments that form cohesive groups within both the national and regional networks. Additionally, we simulate resilience and vulnerability by removing selected nodes and edges to assess the impact of natural disasters on the network. Our findings aim to improve understanding of Brazil’s segmented federal road structure, enabling comparison with other models and providing actionable insights for assessing impacts and improving infrastructure.</p
Maternal and fetal genetic predispositions to insulin deficiency and resistance affect fetal growth through distinct pathways.
No full textAIMS/HYPOTHESIS: We aimed to investigate whether maternal and fetal genetic predispositions to insulin deficiency and resistance affect offspring fetal growth through distinct pathways in multi-ethnic populations. METHODS: In 5065 multi-ethnic mother-infant pairs, we examined the conditional associations of maternal and fetal partitioned polygenic risk scores (pPRSs) for type 2 diabetes-related pathways with fetal growth outcomes, including birthweight, sum of skinfold thicknesses (SSF), large-for-gestational-age (LGA) births and small-for-gestational-age (SGA) births. Two-sample Mendelian randomisation (2SMR) in Europeans was performed for triangulation. Exposures were eight type 2 diabetes-related pathways (n=1,812,017), eight beta cell function indices (n=26,356) and two insulin sensitivity indices (n=53,657). Outcomes were maternal and fetal genetically determined birthweight (n=406,063). Mediation analysis was used to assess the mediation effects of maternal glucose levels and BMI on maternal genetic effects and of cord blood C-peptide on fetal genetic effects. Co-localisation analyses were performed to test for shared causal variants. RESULTS: Fetal type 2 diabetes polygenic risk score (PRS) and pPRSs for lipodystrophy-related insulin resistance and impaired fasting glucose (IFG)-related insulin deficiency were associated with lower birthweight and SSF, while maternal type 2 diabetes PRS and pPRSs for IFG-related insulin deficiency and obesity-related insulin resistance were associated with higher offspring birthweight, SSF and LGA. These associations were consistent across five ethnic groups. Maternal post-load hyperglycaemia mediated 44.2% and 34.2% of the effects of type 2 diabetes PRS and IFG pPRS, respectively, while maternal BMI mediated 43.4% of the effect of Obesity pPRS. 2SMR found consistent results in Europeans and further revealed that fetal insulin sensitivity index and corrected insulin response were associated with higher birthweight. Some loci with shared causal variants acted through multiple pathways, including CDKAL1, TCF7L2, ADCY5 and MACF1. CONCLUSIONS/INTERPRETATION: Reduced fetal growth may be driven by lipodystrophy-related insulin resistance and IFG-related insulin deficiency pathways. Targeting pregnant women with high type 2 diabetes PRS/pPRS and prescribing interventions to reduce their post-load hyperglycaemia and BMI may help reduce offspring risk of LGA.</p
Autistic narrative agency
No full textIn this paper, we develop a view of autistic agency, autistic narrative agency, that emphasizes the connection between agency as revealing autistic subjectivity and agency as a form of resistance to injustice as it affects autistic people. Two interwoven strands in autism studies help us shed light on the relationship between the individual and political aspects of autistic agency: work on epistemic injustice experienced by autistic people and work on autistic autobiography. We supplement these approaches with a view of agency that underscores the importance of tracking back and forth between the particularity of autistic life experience and the systematic harms suffered by autistic people as a marginalised group. On our view, appearance before another as a unique self, which we call ontological agency, is a precondition for any kind of meaning making, and meaning making, in turn, is a precondition for meaningful resistance to neuro-normative systems of power, which we call political agency. Drawing on two autistic autobiographies—Anand Prahlad’s The Secret Life of a Black Aspie (2017) and Joanne Limburg’s Letters to My Weird Sisters (2021)—we argue that autistic narrative agency can enhance epistemic and autobiographical accounts of autistic agency by grounding them in uniqueness.</p
From agnosis to accidental activism: Infinite regress and the Post Office Scandal
No full textThis paper explores the lived experiences of victims/survivors affected by the UK Post Office Scandal, drawing on 28 in-depth interviews and critical legal analysis. It introduces the concept of ‘accidental activism’ to explore how victims, initially isolated and disempowered, became central agents of justice reform. The authors examine how institutional agnosis and legality illusions—mechanisms of ignorance-making and legal manipulation—enabled systemic harm and prolonged injustice. Despite legal victories such as the Bates litigation and the Horizon IT Inquiry, the paper highlights the cyclical nature of legal processes and logics reasserting the system-norms the victims/survivors are resisting. This is experienced as an ‘infinite’ regress of revictimisation. In mapping the transformation of personal trauma into collective resistance, we see how survivor led activism can challenge state-corporate power and foster broader structural change but also how the system will work to protect itself.</p
Co-creation of an airflow and COVID-19 transmission risk model for humanitarian shelter design
No full textVentilation rates in overcrowded humanitarian shelters are often insufficient to prevent condensation, respiratory illness, and the transmission of airborne diseases. Enhancing ventilation is challenging due to security needs, protection from dust and insects, and a lack of design expertise among humanitarian teams without engineering backgrounds. This study presents the development, validation, and testing of a novel natural-ventilation and infection-risk assessment methodology co-designed with 42 practitioners from NGOs, humanitarian organisations, and academia through a six-phase participatory process. The new methodology requires approximately 20 inputs to characterise shelter conditions across more than 3100 global locations and performs natural-ventilation, indoor CO₂, and COVID-19 transmission-risk calculations without the need for prior airflow-modelling knowledge. Model performance was evaluated against established network models (EnergyPlus Airflow Network and CONTAM) using representative shelters in Ethiopia, Djibouti, and Nepal, demonstrating good agreement. Usability testing with 12 aid workers showed that first-time users could complete a full shelter assessment in about 30 min, with subsequent iterations requiring around 15 min. The method provides a rapid, accessible method for estimating ventilation adequacy and airborne-diseases risk in resource-constrained settings and has been adopted by several humanitarian agencies to support emergency shelter design and ventilation decision-making.</p
Revision knee replacement outcomes and implications for the organisation of care in the NHS: Can regional networks improve outcomes?
No full textIntroduction
Revision knee replacement (RevKR) is a complex and costly procedure with high rates of reoperations. Identifying better models of care delivery is a top research priority in RevKR. Regional networks were introduced in England to improve outcomes through multidisciplinary decision making and complex cases being done by fewer more experienced surgeons and hospitals. While higher procedure volumes are associated with improved outcomes in surgery, RevKR is still often performed by low volume surgeons and hospitals. The literature shows an inconsistent relationship between volume and outcomes in RevKR, highlighting the need to better understand this relationship, particularly as the National Health Service (NHS) considers reconfiguring care for low volume, high complexity orthopaedic procedures.
Methods
This work aimed to explore the association between procedural volume and outcomes following RevKR using data from the UK National Joint Registry (NJR), Hospital Episode Statistics (HES), and the Department of Health’s Patient Reported Outcome Measures (PROMs). Semi-structured interviews were also conducted with patients and carers who had experience or knowledge of RevKR.
Results
Multivariable fixed effects models with restricted cubic splines revealed that for first-time RevKR for non-infected causes, higher surgeon volume was associated with lower re-revision rates. For revisions due to prosthetic joint infection, the relationship between volume and outcome was more complex. Surgical units with the highest annual volumes (52) were associated with lower re-revision rates compared with the lowest volume units (<12), whereas no surgeon-level volume-outcome relationship was observed. Increased travel distance from specialist hospitals did not worsen emergency readmission or mortality rates. Patients and carers supported travelling further for specialist surgery, although many expressed concerns about the burden of travel for hospital visits before and after surgery.
Conclusion
This work supports the setting of minimum activity levels for surgeons and units. It also advocates for early warning systems for outlier detection and emphasises the importance of incorporating patient perspectives in service redesign. While volume outcome relationships in RevKR may be complex, regional coordination is generally supported by patients. Local services and pathways should be examined to address the impact of travel on an older, less mobile patient group.</p
Enhancing healthcare outcome with scalable processing and predictive analytics via cloud healthcare API
No full textThis systematic literature review investigates the Google Cloud Healthcare API's role in transforming healthcare delivery through advanced analytics, machine learning, and cloud-based solutions. The study examines current features of cloud-based healthcare platforms in managing heterogeneous healthcare data formats, analyzes the effectiveness of cloud solutions in enhancing clinical outcomes, and compares Google Cloud Healthcare API with alternative platforms. The findings reveal that Google Cloud Healthcare API demonstrates notable advantages through its fully managed, serverless architecture, native support for healthcare standards (e.g., FHIR, HL7v2, DICOM), and seamless integration with advanced AI/ML services. Cloud-based predictive analytics platforms have proven effective in reducing hospital readmissions, addressing physician burnout, and enabling scalable telemedicine solutions. However, significant challenges persist including data privacy concerns, regulatory compliance complexities, infrastructure dependencies, and potential vendor lock-in risks. The research demonstrates that healthcare organizations implementing comprehensive cloud-based solutions achieve measurable improvements in patient outcomes, operational efficiency, and care delivery models. While technical challenges around latency in medical imaging and interoperability remain, the evidence strongly supports cloud adoption for healthcare transformation, provided organizations address security, compliance, and implementation challenges through strategic planning and comprehensive change management approaches.</p
From Ideology to Identity: Deconstructing Disabled Stereotypes in Video Games and Their Effects on Self-Identity
No full textVideo games represent disabled characters via long-standing stereotypes found within literature, film and theatre, reinforcing biases that continue to shape perceptions today. This thesis examines the impact of these stereotypes through ideologies of stigma, centre and periphery and the concept of the identity schema. Through semi-structured interviews, this thesis examines five prominent disability stereotypes within selected games. The data collected was analysed using thematic coding and NVivo, revealing that these stereotypes persist and act to reinforce established hegemonic ideologies pertaining to disability. Additionally, the findings highlight the significant impact these representations have on the identities of disabled players, influencing how they perceive themselves and others. This research contributes to a deeper understanding of how media, specifically video games, continues to perpetuate stereotypes and the ways in which these representations can affect disabled individuals and how disability is understood. Furthermore, this research demonstrates a need for disabled representation within media which is constructed from lived experience and identity. This will enable a more diverse range of disabled experience to be represented within characters, allowing for the subversion of stereotyping and for more disabled individuals to connect with disabled characters.</p
While The Sedum Is In Flower: A Biographical Novel of William Butler Yeats
No full textTo be added at a later date</p
HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Control
No full textAdaptive traffic signal control (ATSC) is essential for mitigating urban congestion in modern smart cities, where traffic infrastructure is evolving into interconnected Web-of-Things (WoT) environments with thousands of sensing-and-control nodes. However, existing methods face a critical scalability-coordination tradeoff: centralized approaches optimize global objectives but become computationally intractable at city scale, while decentralized multi-agent methods scale efficiently yet lack network-level coherence, resulting in sub-optimal performance. In this paper, we present HALO, a hierarchical reinforcement learning framework that addresses this tradeoff for large-scale ATSC. HALO decouples decision-making into two levels: a high-level global guidance policy employs Transformer-LSTM encoders to model spatio-temporal dependencies across the entire network and broadcast compact guidance signals, while low-level local intersection policies execute decentralized control conditioned on both local observations and global context. To ensure better alignment of global-local objectives, we introduce an adversarial goal-setting mechanism where the global policy proposes challenging-yet-feasible network-level targets that local policies are trained to surpass, fostering robust coordination. We evaluate HALO extensively on multiple standard benchmarks, and a newly constructed large-scale Manhattan-like network with 2,668 intersections under real-world traffic patterns, including peak transitions, adverse weather and holiday surges. Results demonstrate HALO shows competitive performance and becomes increasingly dominant as network complexity grows across small-scale benchmarks, while delivering the strongest performance in all large-scale regimes, offering up to 6.8% lower average travel time and 5.0% lower average delay than the best state-of-the-art.</p