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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
Embodied carbon tracking in the construction supply chain: phenomenological insights into challenges and strategies
No full textPurposeEffective tracking of embodied carbon (EC) across construction supply chains is critical for decarbonisation but remains challenged by fragmented data, regulatory gaps and limited digital integration. This study aims to identify key EC tracking challenges and essential implementation strategies and evaluates the role of digital technologies in facilitating comprehensive EC tracking.Design/methodology/approachA phenomenological research design was used, involving semi-structured interviews with eight UK-based construction professionals experienced in EC management.FindingsFindings revealed that barriers like data inconsistency and low awareness can be overcome through strategies such as automation, collaboration and early planning. Digital technologies were revealed to be pivotal enablers, enhancing transparency and real-time monitoring.Originality/valueThis study advances EC scholarship by providing phenomenological evidence from UK practitioners on supply-chain EC tracking, yielding a consolidated typology of challenges, implementation strategies and adoption levers. It bridges the gap between theoretical frameworks and practical implementation by empirically identifying the specific strategies that practitioners perceive as essential for overcoming EC tracking challenges within the construction supply chain. Furthermore, it provides empirical evidence on the pivotal role of digital technologies in enhancing data transparency and real-time monitoring, thereby contributing actionable insights for industry stakeholders striving for a low-carbon built environment. This study offers an actionable framework for industry practitioners, policymakers and technology developers to advance EC tracking
Immersive HCI for Intangible Cultural Heritage in Tourism Contexts: A Narrative Review of Design and Evaluation
No full textImmersive technologies such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and multisensory interaction are increasingly deployed to support the transmission and presentation of intangible cultural heritage (ICH), particularly within tourism and heritage interpretation contexts. In cultural tourism, ICH is often encountered through museums, heritage sites, festivals, and digitally mediated experiences rather than through sustained community-based transmission, raising important challenges for interaction design, accessibility, and cultural representation. This study presents a narrative review of immersive human–computer interaction (HCI) research in the context ICH, with a particular focus on tourism-facing applications. An initial dataset of 145 records was identified through a structured search of major academic databases from their inception to 2024. Following staged screening based on relevance, publication type, and temporal criteria, 97 empirical or technical studies published after 2020 were included in the final analysis. The review synthesises how immersive technologies are applied across seven ICH domains and examines their deployment in key tourism-related settings, including museum interpretation, heritage sites, and sustainable cultural tourism experiences. The findings reveal persistent tensions between technological innovation, cultural authenticity, and user engagement, challenges that are especially pronounced in tourism context. The review also maps the dominant methodological approaches, including user-centred design, participatory frameworks, and mixed-method strategies. By integrating structured screening with narrative synthesis, the review highlights fragmentation in the field, uneven methodological rigour, and gaps in both cultural adaptability and long-term sustainability, and outlines future directions for culturally responsive and inclusive immersive HCI research in ICH tourism
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
Digital twin frameworks for polio and post-polio neurodegeneration: Toward predictive, personalised lifelong neuro-rehabilitation
No full textPoliomyelitis is a neuroinvasive viral disease that, despite near-global eradication, has left millions of survivors worldwide with lifelong motor-system injury. Many develop delayed neurological decline decades later in the form of Post-polio syndrome, characterised by progressive weakness, fatigue, pain, and respiratory compromise. Disease trajectories are highly heterogeneous, unpredictable, and shaped by complex interactions between residual motor-neuron pools, muscle adaptation, ageing, metabolism, and immune tone. Conventional care relies on episodic clinical review and reactive rehabilitation, with limited capacity for long-term personalised forecasting. Digital-twin technology, defined as an adaptive computational model that continuously mirrors an individual's biological and functional state, offers a transformative framework for predictive and precision-guided lifelong polio care. By integrating neuromuscular physiology, biomechanics, metabolic status, wearable sensor data, and rehabilitation responses, digital twins could enable real-time modelling of motor-unit decline, functional reserve, respiratory vulnerability, and fatigue dynamics. This article outlines a focused conceptual framework for polio digital twins, emphasising model architecture, feedback loops, and translational applications, rather than virological biology. The proposed framework positions digital twins as a missing precision-medicine layer for a neglected global survivor population
Beyond the Hodge theorem: Curl and asymmetric pseudodifferential projections
No full textWe develop a new approach to the study of spectral asymmetry. Working with the operator curl : = * d on a connected oriented closed Riemannian 3-manifold, we construct, by means of microlocal analysis, the asymmetry operator — a scalar pseudodifferential operator of order -3. The latter is completely determined by the Riemannian manifold and its orientation, and encodes information about spectral asymmetry. The asymmetry operator generalises and contains the classical eta invariant traditionally associated with the asymmetry of the spectrum, which can be recovered by computing its regularised operator trace. Remarkably, the whole construction is direct and explicit
Large Eddy Simulation of Optimized Air Curtain Separation via Secondary Co-Flowing Jets
No full textUnconditioned air infiltration through frequently used entrance doors can degrade building energy performance, indoor air quality, and thermal comfort. Air curtains mitigate these effects and are also critical in smoke and dust control, cleanrooms, and cold rooms. Their performance is commonly expressed as separation efficiency, which depends on jet dynamics and entrainment. While most studies consider single-jet air curtains, this work investigates secondary co-flowing jets as a design strategy to reduce entrainment and enhance separation efficiency. Large eddy simulations (LES), validated against a dedicated particle image velocimetry (PIV) dataset of plane turbulent impinging co-flowing jets, assess the influence of key jet parameters: velocity ratio (R), secondary-jet width (W s ), and inter-jet spacing (d). The results indicate that incorporating secondary jets under suitable discharge conditions increases infiltration-based separation efficiency by up to 5.4 % without compromising the combined infiltration–exfiltration metric; the latter can also improve by up to 3 %. Given baseline efficiencies of 86.2 % (infiltration) and 78.7 % (combined) for an optimized single-jet curtain, these gains are significant
PINN modeling for predicting the solute concentration distribution of COBC with case study on L-glutamic acid crystallization
No full textTo predict the solute concentration distribution (SCD) during continuous crystallization via a continuous oscillatory baffled crystallizer (COBC), a novel physics-informed neural network (PINN) based soft modelling method is proposed in this paper. By analyzing the sensitivity of solute concentration at the COBC outlet with respect to the main operating conditions (e.g., initial solution supersaturation ratio and liquid flow rate), a sensitivity analysis-based design of experiments (SA-DoE) is developed to generate informative data for model training, which can effectively reduce the number of experiments for implementation. Meanwhile, a pseudo two-dimensional (2D) fluid kinetic model is built to reflect the relationship between the crystal velocity and liquid flow velocity during the continuous crystallization process via COBC, which can be effectively used in the PINN-based model building for predicting SCD. Simulation studies and experiments on the continuous crystallization process of β form L-glutamic acid are conducted to demonstrate the effectiveness and advantage of the proposed modeling method
Explicit Non-Abelian Gerbes with Connections
No full textWe define the notion of adjustment for strict Lie 2-groups and provide the complete cocycle description for non-Abelian gerbes with connections whose structure 2-group is an adjusted 2-group. Most importantly, we depart from the common fake-flat connections and employ adjusted connections. This is an important generalisation that is needed for physical applications especially in the context of supergravity. We give a number of explicit examples; in particular, we lift the spin structure on S4, corresponding to an instanton–anti-instanton pair, to a string structure, a 2-group bundle with connection. We also outline how categorified forms of Bogomolny monopoles known as self-dual strings can be obtained via a Penrose–Ward transform of string bundles over twistor space
University–industry collaboration in post-Soviet states: A bibliometric study with implications for educational policy and practice
No full textUniversity–industry collaboration has become an essential mechanism not only for fostering innovation and economic development but also for shaping the educational missions of universities. In post-Soviet states, however, University–Industry Collaboration has evolved within a distinctive context marked by the legacies of centrally planned economies, state dominance, and systemic transition, creating both structural barriers and new opportunities for higher education reform. This study conducts a bibliometric review of University–Industry Collaboration research in post-Soviet states between 1991 and 2024, complemented by a thematic analysis of selected studies. Using a dataset of 223 publications drawn from the Web of Science and applying co-citation analysis, bibliographic coupling, and thematic mapping, the study identifies the intellectual foundations, collaborative networks, and key thematic clusters shaping the field. The findings reveal five persistent challenges—state dominance, weak industry demand, underdeveloped commercialization infrastructure, human capital constraints, and cultural barriers—alongside emerging opportunities for curriculum reform, work-based learning, and employability-focused teaching models. Beyond mapping the research landscape, the study shows how University–Industry Collaboration intersects with higher education by reshaping curricula, influencing academic roles, and expanding student engagement with industry. These insights extend current debates by situating the post-Soviet experience within broader discussions of educational change, institutional reform, and the pedagogical implications of university–industry partnerships
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