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Globalisation and Network Resilience: A Special Issue Introduction
No full textThis special issue examines globalisation and resilience, variously conceived, from a network perspective. In an era that moved from hyperglobalisation to disruption—pandemics, geopolitical tensions, climate risks—we argue that a key orienting question should be how globalisation is being reconfigured across multiplex economic, social and industrial networks. With this special issue, we hope to motivate new bodies of literature deploying social network analysis to diagnose and analyse the resilience of global economic networks to exogenous shocks. Where are such shocks likely to occur? Do they get contained in network subgraphs? Or are they absorbed more equally throughout the network? In any given network, which actors and ties, or types of actors and ties, underpin systemic robustness? The four papers in the issue span a bibliometric synthesis of ‘network resilience’ across domains; an industry‐level measure of supply‐chain disruption linking logistics reliability to US output; a country‐level study connecting embeddedness in the global FDI network to democratic resilience in less‐developed countries; and a firm‐level reconstruction of the EV corporate ownership network. We conclude by highlighting the substantive contributions of these papers, by calling for conceptual clarity on network resilience, and by suggesting a number of fruitful directions for future research
Digital Twin Modeling for Acanthamoeba Keratitis: From Empirical Therapy to Predictive Ophthalmology
No full textAcanthamoeba keratitis is a rare, vision-threatening corneal infection that remains difficult to diagnose and treat, with therapy often extending for many months. Despite recent advances, the management of Acanthamoeba keratitis still depends largely on empirical regimens combining biguanides, diamidines, and azoles. Outcomes vary widely, reflecting differences in pathogen virulence, drug penetration, host response, and timing of diagnosis. It is proposed that digital-twin technology offers a powerful new framework for studying and managing this disease. Digital twin is a data-driven computational approach that creates continuously updating virtual replicas of biological systems. By integrating multimodal clinical, imaging, and molecular data, digital twins could simulate corneal infection dynamics, drug diffusion, and cyst reactivation, providing clinicians with predictive insight rather than retrospective interpretation. Here, it is discussed how digital-twin models could be constructed for Acanthamoeba keratitis, challenges to implementation, and implications for precision ophthalmology
CFD investigation of indoor airflow and heat removal during night cooling with ceiling and attic ventilation in a residential building
No full textThis paper investigates the cooling potential of a perforated ceiling as part of a night-time ventilation technique for residential buildings in tropical climates. 3D steady Reynolds-averaged Navier-Stokes computational fluid dynamics simulations were carried out under non-isothermal conditions (wind and buoyancy-driven ventilation) for an isolated realistic single-story residential building with internal partitions and a pitched roof. Three different building ventilation configurations were assessed, i.e. cross-ventilation through window openings on the windward and leeward walls (C1), configuration C1 but with a perforated ceiling and attic ventilation (C2), single-sided ventilation through the windward window opening combined with a perforated ceiling and attic ventilation (C3). The results show that C2 performs better than C1 and C3, as it allows the most efficient heat removal from the occupied zone, resulting in a reduction of the volume-average mean air temperature within the rooms. Configuration C2 resulted in a 98% higher heat removal effectiveness (HRE) and a 20% higher air exchange rate (ACH) than the reference case (C1). Decreasing the porosity of the perforated ceiling for C2, from φ = 40% to φ = 33%, resulted in a reduction of HRE and ACH of 32% and 7%, respectively. Furthermore, different approach-flow angles (i.e. α = -60°; α = -30°; α = 0°; α = 30°; α = 60°) did not significantly affect HRE and ACH within the unpartitioned side of the building (Room 1 (R1)), while a substantial effect was found for the partitioned side (R2/R3). Overall, C2 outperforms C1 and C3 with respect to heat removal
Driving systems transition through learning:a case study for net zero school transport in rural Scotland
No full textThe school run is a persistent local transport issue in most urban areas. Private automobiles remain the dominant transport mode for school journeys, supported by infrastructure and vehicles designed for traffic flow, safety, comfort and convenience. While the car journey offers perceived benefits to carers, it also generates well-documented externalities, including traffic congestion, air pollution, reduced physical activity and increased risks for pedestrians and cyclists. The School Strike for Climate added the ground-up pressure from students to take action. This study explores a transdisciplinary systems approach to tackling the wicked problem of the car drop-off at primary schools. The transition engineering methodology was carried out to design a novel education programme that empowers students to understand global warming and the role of petrol car trips, communicate their needs to carers and contribute to achieving net-zero transport goals through equitable and inclusive changes. The programme was implemented in a participatory action research process involving over 300 students, educators and local stakeholders. Participants reflected that the programme catalysed a cultural shift within the school community, fostering ownership of sustainable school transport and aligning with broader community-level transport strategies. This article presents the design methodology, implementation of outcomes, prototyping experiences and stakeholder feedback. The article contributes a novel programme for sustainable school transport that supports the development of competencies among students to become change makers.</p
Improving biocide evaluation using propidium monoazide (PMA) viability staining technique
No full textChemical biocides are commonly employed to manage problems caused by microbial processes. In the energy sector, for example, engineered systems are often treated with biocides to control microbiologically influenced corrosion (MIC), biofouling, and the biological generation of hydrogen sulfide. Standard DNA-based methods that are widely used to assess biocide effectiveness often cannot distinguish between live and dead microorganisms, potentially leading to inflated estimates of living cell populations. Incorporating propidium monoazide (PMA) viability staining technique offers a promising solution to this limitation. In this study, we explored the application of PMA within a standard DNA-based workflow to evaluate biocide performance more accurately. A model sulfate-reducing microbial consortium, derived from oilfield produced water, was exposed to widely used biocides including glutaraldehyde (Glut) and tetrakis(hydroxymethyl)phosphonium sulfate (THPS). PMA was applied prior to standard DNA extraction and subsequent qPCR and amplicon sequencing procedures. We observed PMA-derived microbial abundance at least an order of magnitude lower compared to that without PMA. The reduced PMA-derived microbial abundance correlated with the lower ability of the model microbial communities to produce hydrogen sulfide - an association that was absent based on the usual approach without PMA. Biocide-treated communities, in comparison to untreated controls, displayed significant alterations in their microbial ecological properties, such as alpha diversity, beta diversity, and taxonomic composition, as determined through 16S rRNA gene sequencing - differences that were only apparent when PMA was applied. These results confirm that incorporating PMA into standard DNA-based biocide assessment protocols is both feasible and beneficial. Since PMA implementation requires minimal additional effort, we advocate for its adoption in future biocide performance studies, in particular for engineered systems in the energy industry
A mixed methods systematic review of the psychosocial and rehabilitative impact of prison technology with recommendations for practice
No full textExtant research suggests the use of technology in prisons can improve their safety, legitimacy, environment, and efficiency. Recently, mechanisms have also been described throughwhich technology may contribute to rehabilitation. However, less is known about the psychologicalprocesses that explain this outcome. Here we present a systematic review addressing this lacuna.The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method wasapplied to search six databases (Scopus, PsycINFO, LISTA, Criminal Justice Abstracts, Web of Scienceand Academic Search) and grey literature in October 2020. Studies were included if participantswere people living in prison, the intervention was a technological innovation to support arehabilitative environment, and outcomes were psychological or behavioural. Fourteen reports ofthirteen studies met the criteria, and quality assessment checks were performed. Analysis usingmeta-aggregation identified five integrated findings. A broad range of technologies have beenintroduced to prisons. Technologies were found to positively influence the emotions, thinking,behaviour, and relationships of those living in prisons. However, technology failures weredetrimental experiences for prisoners. The findings are used to shape recommendations for howtechnology might contribute to the psychosocial and rehabilitative environment of prisons. <br/
Temporal, spectral, and modal analysis of a thin-slab Tm:LuLF hybrid stable-unstable laser
No full textTemporal instabilities observed in a thin-slab Tm:LuLF hybrid stable-unstable resonator are studied both experimentally and with numerical modelling. Near-field beam profiles and intra-cavity modes are investigated under different alignment conditions, and a two-dimensional Fox and Li model is developed and applied to verify the results. Laser rate equations for the gain medium can be integrated into the model to understand how Thulium’s complex energy structure may be influencing the resonator dynamics. The laser was scaled to ~30 W of high-brightness output power
3D crop reconstruction: A review of hyperspectral and multispectral approaches
No full textHyperspectral imaging (HSI) has emerged as a powerful tool for precision agriculture, enabling the non-destructive monitoring of crop biochemical and physiological traits. However, HSI alone lacks structural context, which limits its ability to accurately capture complex canopy architectures and organ-level traits. Integrating HSI with depth-sensing modalities such as Light Detection and Ranging (LiDAR), Red, Green, Blue, and Depth (RGB-D) cameras, and computational reconstruction technique such as photogrammetry enables the generation of three-dimensional hyperspectral point clouds, combining spectral richness with geometric fidelity. This multi-modal fusion enhances crop trait estimation, including biomass, leaf chlorophyll content, canopy height, leaf area, and stress indicators, while improving the robustness of phenotyping under occlusions, shadows, and varying illumination. Dimensionality reduction, feature selection, and machine learning approaches, including deep learning and explainable AI, are useful for handling high-dimensional hyperspectral data and extracting actionable agronomic insights. Moreover, the integration of thermal, radar, and Global Navigation Satellite System (GNSS) data further expands the capabilities of multi-modal sensing, enabling continuous, all-weather crop monitoring and accurate spatial referencing. Despite these advances, most studies to date focus on controlled environments, highlighting the need for field-based validation to ensure the reliability and scalability of HSI-depth fusion techniques. This review consolidates current knowledge on multi-modal hyperspectral and 3D crop reconstruction, highlighting methods, applications, and challenges, and outlines future directions for implementing high-throughput, real-time phenotyping and precision agriculture solutions
Isofrequency spin-wave imaging using color center magnetometry for magnon spintronics
No full textMagnon spintronics aims to harness spin waves in magnetic films for information technologies. Color center magnetometry is a promising tool for imaging spin waves, using electronic spins associated with atomic defects in solid-state materials as sensors. However, two main limitations persist: the magnetic fields required for spin-wave control detune the sensor-spin detection frequency, and this frequency is further restricted by the color center nature. Here, we overcome these limitations by decoupling the sensor spins from the spin-wave control fields -selecting color centers with intrinsic anisotropy axes orthogonal to the film magnetization- and by using color centers in diamond and hexagonal boron nitride to operate at complementary frequencies. We demonstrate isofrequency imaging of field-controlled spin waves in a magnetic half-plane and show how intrinsic magnetic anisotropies trigger bistable spin textures that govern spin-wave transport at device edges. Our results establish color center magnetometry as a versatile tool for advancing spin-wave technologies. [Abstract copyright: © 2025. The Author(s).
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