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Belonging, desistance and corrections
Full text linkhis short paper explains the development and importance of the concept of tertiary (or relational)
desistance, which relates to securing acceptance and belonging in a community after criminalisation
and punishment. The paper presents evidence from a range of recent studies that have studied
tertiary desistance empirically, before going on to discuss the implications for correctional policy and
practice
Housing Quality and Health – an Economic Analysis
No full textThis report aims to assess the economic impact of poor-quality housing on health outcomes in Scotland. Ultimately, it seeks to inform the ongoing critical discussion regarding housing as a determinant of health and driver of health inequalities, particularly concerning the impacts of good quality housing and the economic costs of poor-quality housing in the Scottish context to inform and influence the future policy and national health and housing strategies.
Report findings shows the substantial financial implications of poor housing in Scotland. However, it also stresses the necessity for increased investment in research, including ongoing monitoring and evaluation, to enable more precise quantification of the costs associated with inadequate housing in Scotland
Estimating intra-urban traffic CO2 emissions and assessing environmental justice using smart data
Full text linkSmart data, defined as digital traces that people leave behind during their daily activities, has an underexplored potential to estimate intra-urban traffic emissions and their implications for environmental justice. Here, we incorporate fine-grained mobility flows from the App (Huq) into the Spatial Weight Matrix (SWM) to predict traffic CO 2 in Glasgow City, UK. The results demonstrate that models based on customized SWM with real mobility better predict traffic CO 2 than traditional distance-based models. According to model results, income and car ownership rates are dominant factors associated with traffic CO 2 . Noticeably, traffic CO emissions are closely related to incoming mobility flows from neighborhoods with high income and car ownership rates. Moreover, the top 20% areas by income and car ownership account for 37.21% and 49.52% of total traffic CO 2 , respectively, indicating that disadvantaged groups bear the costs of emissions disproportionately generated by residents of wealthier areas. Finally, urban planners should not only consider reducing traffic emissions but also ensure that disadvantaged residents will not be affected by affluent communities to mitigate emission inequality. This study provides insightful solutions for urban planning policies to reduce traffic emissions and to reveal environmental injustices, thereby achieving just urban transitions in global cities
Talking all things SoTL with Nick Quinn
No full text"[H]uge merit in finding like minded colleagues and working with them".
Tune in to hear more from Nick Quinn who talks all things SoTL with podcast editors Eilidh Soussi and Alison McCandlish
A simple prudential-effort foundation for the financial trilemma
No full textThe “financial trilemma” asserts that deep financial integration, purely national financial policies and financial stability cannot simultaneously be achieved. Existing formalisations employing ex post burden-sharing games imply the trilemma result hinges on equilibrium selection. We develop a minimal ex ante prudential-effort model where financial integration amplifies cross-border crisis risk and national regulators internalise only part of global losses. The unique symmetric Nash equilibrium underprovides prudential effort and cannot deliver first-best stability when both integration and national policy autonomy are high. That provides a unique-equilibrium foundation for the financial trilemma and clarifies when supranational prudential arrangements are needed
Three-dimensional time series building reconstruction framework in Global South based on openly available satellite data
No full textRapid urbanization necessitates accurate 3D building data for effective urban planning and analysis. Building height provides critical vertical information reflecting urban morphology, land use intensity, and energy demand. However, high-resolution large-scale 3D datasets remain limited, particularly in the Global South, due to the high cost and complexity of traditional methods. Although machine learning approaches have been widely explored, they often underperform in dense urban areas and tend to underestimate tall buildings due to limited training data and generalizability. In this study, we propose a novel framework for large-scale building height estimation using only free remote sensing data. Leveraging 0.5 m resolution open-access satellite imagery and ICESat-2 photons, we construct an accurate parallel projection model for each image. It enables the generation of dense height points via triangulation across image pairs without additional geometric parameters. The height points are then integrated with 2D building footprints to reconstruct building height maps. Validation results of the full urban area in Nairobi, achieving a root mean square error (RMSE) of 3.338 m, demonstrated the feasibility of our framework. The method also exhibits strong temporal consistency, with a maximum mean deviation of only 1.93 m across multi-temporal height maps. Experiment results in the three additional Global South cities (Medellín, Salvador and Jakarta), achieving mean absolute errors (MAE) of 3.867 m, 3.642 m, and 2.484 m, respectively, further confirmed the transferability of our framework. These results highlight our framework’s capability to deliver low-cost, accurate, and high-resolution 3D urban reconstruction, particularly in resource-constrained cities, providing a scalable tool for urban analysis, planning, and policy support
Morphospatial profiling of cancer-associated fibroblasts reveals architectural subtypes of pancreatic ductal adenocarcinoma
Full text linkPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with an urgent need for biomarkers to predict prognosis and guide treatment. Understanding the complex spatial biology of pancreatic cancer-associated fibroblasts (CAFs) and the broader architecture of the PDAC tumour microenvironment is central to this challenge. Using a multi-omics approach across multiple spatial resolutions in a large human PDAC cohort, we integrate geometry and shape to define discrete morphological CAF subtypes, expanding CAF phenotyping beyond conventional proteomics. We then reveal an architectural and molecular axis of PDAC at tissue level, suggestive of epithelial-stromal co-evolution, with translational implications and prioritisation of stromal targets. Finally, we recapitulate this axis by introducing four unique, internally validated architectural subtypes of PDAC, each characterised by a common microenvironment and CAF enrichment profile. These archetypes outperform conventional pathology in prognostication, and predict response to adjuvant chemotherapy. Collectively, this study establishes a novel morphological paradigm for spatial biology, illuminates the architectural landscape of PDAC, and provides a framework for spatial biomarker discovery to close the translational gap in this devastating disease.Competing Interest StatementThe authors have declared no competing interest.Beatson Cancer Charity, https://ror.org/02j37bn23, 22-23-067Mazumdar Shaw Chair Endowment, NACancer Research UK Scotland Institute, CTRQQR-2021\100006Pathological Society, 0422/04Annie McNab Bequest, NAChief Scientist Office, PCL/22/03Rosetrees Trust, PGS21/10084Tenovus Scotland, https://ror.org/037866t57, S21-06EU Horizon 2020, 10101685
Economic incentives for biodiversity conservation on farmland
No full textIn this paper, we review recent advances in the field of economic incentives for biodiversity conservation, focusing on incentives offered to private landowners to change how they manage land. Due to market failures, profit-maximizing land-use decisions are rarely consistent with optimal provision of biodiversity. As a result, it has been argued that additional financial incentives are needed to slow global biodiversity decline and aid biodiversity recovery. The paper organizes recent literature along four thematic lines: paying for results rather than actions, incentives for spatial coordination, collective participation schemes, and biodiversity offset markets
Performance Comparison of Statistical Emulators for Parameter Estimation in Complex Systems
Full text linkMathematical models allow us to simulate complex systems, whose behaviour depends significantly on their underlying parameters. However, direct parameter inference of these systems typically involves repeatedly computing numerical solutions. Consequently, reducing the computational burden associated with parameter estimation is crucial for enhancing the practicality of these models. Statistical emulators present a promising solution to this issue, as they approximate mathematical models and substantially reduce computational demands. Despite the potential benefits of emulators, selecting an appropriate emulation strategy remains challenging, primarily due to issues such as high dimensionality, sparse data and correlated outputs. In this study, we assess the effectiveness of various emulation strategies for parameter inference under different data scenarios. Our evaluation encompasses statistical models based on standard Gaussian Processes, variational Gaussian Processes, deep kernel learning, deep Gaussian Processes, and deep neural networks. We construct several simulated data sets and analyse the parameter estimation accuracy of these models under different conditions, including output independence, different input-output dimensionality ratios and data sparsity. Our results demonstrate that the multi-output Gaussian Process consistently achieves superior parameter estimation accuracy compared to other Gaussian Process variants and deep neural networks, particularly in high-dimensional complex systems with multiple dependent outputs, and maintains greater stability in scenarios with sparse data. These findings give insight into emulation strategies applicable to parameter estimation of high-dimensional complex systems and provide a foundation for the future development of real-time parameter estimation in practical applications
Eligibility of real-world patients for aspirin primary prevention trials in cardiovascular disease
No full textBackground: Evidence for the net benefit of aspirin for primary prevention of cardiovascular disease (CVD) is finely balanced, leading to variation in guideline recommendations internationally. External validity of randomised clinical trial (RCT) evidence may therefore be of particular importance. The aim of this study is to characterise real-world patients according to their eligibility for guideline-cited aspirin RCTs for primary CVD prevention. Methods: Eligibility criteria from 14 RCTs were applied to a linked primary care/hospital discharge dataset of people ≥ 40 years without CVD. Proportions eligible for each trial were calculated, and characteristics of eligible and ineligible patients compared for each trial, including Cox regression analysis of event rates for major adverse cardiovascular events (MACE), major bleeding events, and non-cardiovascular mortality. Results: Of 570,211 included patients (300,500 [52.7%] women, 336,877 [59%] < 60 years), the median proportion ineligible for 14 RCTs was 90.7% (range 42.5–99.4%) and 24.0% of patients were ineligible for all RCTs. On average, trial-ineligible populations were younger (median age trial-ineligible 57.8 vs trial-eligible 62.6 years, p = 0.008) and a lower proportion had hypertension (23.9% vs 50.9%, p = 0.004), diabetes (6.4% vs 11.5%, p = 0.015), or a regular statin prescription (11.8% vs 26.7%, p = 0.001). Trial-ineligible populations had a higher hazard of MACE compared to trial-eligible in four RCTs and lower in ten (hazard ratio [HR] range across all RCTs 0.45 [95%CI 0.40–0.51] to 2.78 [95%CI 2.61–2.96]). Hazards of bleeding events in the trial-ineligible were lower than the trial-eligible in eight RCTs and higher in four (HR range across all RCTs 0.63 [95%CI, 0.59–0.66] to 1.69 [95%CI, 1.53–1.86]), and time-varying hazards of non-CVD death were consistently lower in four RCTs and higher in five (HR range across all RCTs and time points 0.29 [95%CI 0.24–0.36] to 11.42 [95%CI 9.91–13.17]). Conclusions: Compared with trial-ineligible populations within the same age and sex strata, RCTs recruited people of varying CVD risk but often excluded people at high risk of bleeding or non-CVD death, highlighting that many trials may overestimate the net benefit of aspirin for primary prevention
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