Despite sustained investment in gender-equity initiatives, hierarchies of authority, legitimacy and reward remain entrenched in higher education. This paper synthesises two staff surveys conducted in Athena Swan-accredited institutions in the United Kingdom and SAGE Athena Swan-accredited institutions in Australia. We develop a processual account of how gendered advantage is accumulated and defended within institutions recognised for equity progress. Across the studies, encouragement, sponsorship, workload protection and recognition operated as informal judgements of deservingness that shaped who entered formal evaluation with credibility and institutional momentum. Resistance became more visible when equity initiatives rendered these arrangements contestable, appearing through appeals to merit, reverse-discrimination claims and institutional withdrawal. We theorise these mechanisms as operating at different organisational speeds: deservingness is slow, cumulative and ordinarily obscured, whereas backlash is faster, reactive and more visible. Backlash is therefore treated as diagnostic evidence of the status, resources and authority being defended. This framework explains how accreditation can generate substantial activity while leaving informal distributions of legitimacy comparatively intact.
Introduction Mobility-as-a-Service underpins sustainable urban mobility strategies and promises to reduce car dependency through seamless integration of transport modes within a single digital platform. However, as cities increasingly digitise access to mobility services, concerns are growing that older adults may be disproportionately excluded from these benefits, creating a new form of transport disadvantage. Despite the importance of inclusive mobility for ageing populations, behavioural mechanisms underpinning older adults’ adoption of mobility-as-a-service remain unknown. This study addresses this critical gap by examining how technology perceptions and innovation attributes jointly shape mobility-as-a-service adoption intentions amongst older adults. Method We develop and test a new integrated theoretical framework combining the Technology Acceptance Model and Diffusion of Innovation theory to explain digital mobility adoption in later life. The framework proposes that innovation attributes influence adoption indirectly through usability perceptions, revealing how established travel behaviours interact with emerging digital mobility services. Survey data were collected from 603 adults aged 60 years and above in Nottinghamshire, UK. Partial least squares-structural equation modelling is employed to evaluate the proposed relationships and identify the principal drivers of mobility-as-a-service adoption intentions. Results The findings demonstrate that behavioural intention is primarily driven by attitude towards mobility-as-a-service use, which is positively influenced by perceived usefulness and perceived ease of use. Innovation attributes exert their effects largely through these usability perceptions. Relative advantage and compatibility significantly enhance perceived usefulness, whilst complexity reduces perceived usefulness and perceived ease of use. Trialability and observability strengthen perceived ease of use, highlighting the importance of direct engagement and experiential learning in facilitating adoption. Age is negatively associated with behavioural intention, indicating that barriers to digital mobility adoption increase across later life. Conclusions This study advances understanding of digital mobility adoption by demonstrating that older adults evaluate mobility-as-a-service not solely as a technology but as an innovation embedded within established travel practices. By revealing how innovation attributes influence adoption through usability perceptions, the study extends existing adoption theory and provides a more nuanced explanation of technology uptake in later life. The findings have significant implications for sustainable transport policy, suggesting that the success of mobility-as-a-service will depend not only on technological functionality but also on reducing digital complexity, enhancing compatibility with existing travel routines, and creating opportunities for experiential engagement. As transport systems become increasingly digitalised, these insights are essential for ensuring that sustainable mobility transitions remain inclusive of ageing populations.
Challenges related to the teaching and learning of formal notation in school mathematics are widely documented, and specifically in relation to the underlying mathematical structures that the notation is intended to convey. In this article, we draw on embodied cognition to examine the interactions among three students working with the software Grid Algebra. Embodied cognition emphasises the role of gesture and movement in learning and understanding mathematics. Grid Algebra uses movement to direct students' attention to mathematical operations on numbers and numerical expressions within the grid and the structure of these operations, while the software takes care of the formal notation of the numerical expressions that describe these sequences of operations. We analyse how different modes of communication work together to scaffold students' fluency with operations and the formal notation representing these operations and the order in which they are performed. The dynamic between notation, speech, movement and position allows students to educate their interpretation of mathematical notation through the movements and positions that they are very familiar with.
Solar photovoltaic (PV) cells are used to power satellites in space, and incorporate ultra-thin (∼150 μm), radiation-tolerant coverglass sheets to provide protection and mechanical support. Optical coatings can be applied to this coverglass surface, such as anti-reflection coatings to reduce reflection losses, typically a single layer of MgF2, which has limitations such as poor durability and lack of thermal management. Optical coatings can also contribute to passive cooling, reducing cell operating temperatures in the space environment where large temperature swings are present. This work details the design, deposition and characterisation of a multilayer, multifunctional coating comprising metal-oxide dielectrics (SiO2, HfO2, Nb2O5), to provide anti-reflection for a single-junction III-V solar cell such as GaAs or InP, increasing power output, with UV and IR reflection as well as high emissivity to provide passive cooling. The multifunctional coating reduces weighted average reflectance (WAR) by 2.48% across 400 - 870 nm, with IR reflection peaking at over 60%, and UV reflectance peaking at over 80%. A temperature reduction of approximately 13 K under one sun AM0 is predicted, and a total relative increase in efficiency of 4.4% for a single-junction GaAs device, compared to uncoated coverglass. Durability testing shows the coating is resistant to UV and damp heat, mechanical abrasion, and proton irradiation. Displacement Damage Dose modelling predicts significant improvement in shielding against proton damage across LEO (Starlink), Molniya, and GEO orbits. The multifunctional coating can be adapted to all PV technologies for space applications, to provide improved power output and increased mission lifetime.
Predicting pedestrian activity across unmonitored urban space from sparse sensor data remains a fundamental challenge for evidence-based policy and decision-making. Effective urban regeneration depends on understanding mobility patterns that shape accessibility, vitality, and social equity, yet limited monitoring infrastructure creates spatial blind spots that undermine investment decisions, risking misallocation toward low-activity areas while neglecting underserved neighbourhoods. This paper introduces the Geospatial Pedestrian Activity Engine (GPAE), a GeoAI framework that bridges human activity patterns, emerging sensing technologies, and urban planning by learning non-linear relationships between the built environment and pedestrian activity. Applied to Loughborough, UK, GPAE fuses WiFi sensor data and computer vision-derived video counts (29 monitoring points) with engineered spatial context features, deploying LightGBM gradient boosting to predict city-wide, high-resolution pedestrian activity data. Model performance was validated using Leave-One-Out Cross-Validation against raw observation points (R2 = 0.89, MAE = 400 pedestrians/day). Feature importance analysis reveals that pedestrian activity is associated with the combined contribution of social amenities, daily necessities, and residential density rather than transit infrastructure alone, directly informing active travel and public realm policy. The resulting intelligence, when combined with infrastructure provision data, supports a Policy Decision Framework which is designed to classify urban areas into four actionable intervention typologies: overburdened, underutilised, neglected, and effectively supported, enabling planners to target infrastructure upgrades, active travel investment, and equity-informed regeneration based on predicted activity rather than reactive observation. Beyond prediction accuracy, GPAE shows how existing pedestrian data can be transformed into decision-ready evidence for sustainable mobility and pedestrian-focused urban planning supporting modal shift to walking and contributing to sustainable urban mobility goals.
