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Mobile sensors for hydraulic calibration of pipe network models
No full textThis paper is the first to explore the potential use of mobile sensors in the hydraulic calibration of water distribution system and sewer system network models. Novel simulation and optimisation functionality is developed to simulate, utilise and analyse the data that would be collected from mobile hydraulic sensors. Comparable functionality is obtained for static sensors to demonstrate the benefits for a mobile sensor approach. Real world case studies are used to show and compare the accuracy of resulting model calibration, with pipe roughness used to independently assess the calibration quality achieved. Mobile sensors achieved substantially lower pipe roughness error values, around 50% lower in the water supply network and around 25% lower in the sewer network. This level of relative predictive performance was demonstrated for 24 hours of data collection from a single mobile sensor, in comparison to nearly 97% nodal coverage of the water supply network and 66% coverage of combined sewer network by static sensors – all sensors sampled at the same frequency. The evidence generated shows the significant potential of mobile sensors, deployed on robotic platforms, to transform the accuracy of water supply and sewer network model calibration. Such improvements are essential to enable, and as part of, digital twin paradigms and to confidently inform proactive management driven from accurate and comprehensive assessment of system performance
Low-cost hybrid copper–carbon nanotube coating with antimicrobial properties in ambient conditions
No full textBackground
The development of bactericidal surfaces using nanotechnology has gained traction in high-tech sectors due to their effectiveness against pathogens. However, widespread adoption in low-income regions remains limited by the high cost of materials such as copper nanoparticles and the need for specialized application personnel. This study aims to develop a cost-effective bactericidal coating that minimizes nano-copper usage while maintaining strong antimicrobial performance and practical applicability in resource-limited environments.
Results
A polymer-based coating incorporating ≤3 wt% nano-copper and carbon nanotubes was formulated to enhance conductivity and mechanical stability. The fabrication process was optimized for on-site application under ambient conditions. Scanning Electron Microscopy (SEM) revealed a uniform surface distribution of nano-copper particles. Bactericidal activity tests confirmed efficacy against Escherichia coli, Listeria monocytogenes, and Salmonella spp. Techno-economic analysis indicated that the coating could be integrated into existing surface finishing systems at an incremental cost of 2.6–3.5 USD per gallon.
Conclusions
This work demonstrates the feasibility of producing and applying affordable nano-based bactericidal coatings under real-world conditions. The approach provides a practical pathway for implementing antimicrobial surface technologies in low-resource settings. Although the present study focused on wood substrates, future research should assess performance on diverse materials to broaden applicability. The combination of cost-effectiveness, efficacy, and scalability underscores the potential for both commercial adoption and significant public health benefits
A synthesis of explanations for spatial inequalities in gambling harm: integrating social and material dimensions of place
No full textPlace matters for understanding patterns of gambling harm as shown by the spatial clustering of both ‘vulnerable’ people and gambling outlets. Harms are experienced at a community level (and never restricted to individuals) and are spread unequally across communities of place. Following the liberalisation of gambling laws in the UK in the 1990s, gambling outlets and advertising have proliferated in many economically disadvantaged places, with the gambling industries in some cases appearing to target these areas. Despite growing recognition of place-based inequalities in the harms caused by gambling, there have been limited efforts to understand gambling as a spatial practice that reflects and produces inequalities in health. This paper presents a synthesis of theories and explanations in the social science and public health literature about the unequal harms from gambling experienced by people in different places. We draw on a socio-material approach in our synthesis to show how different assemblages of gambling products, venues, marketing materials and collective histories form in different localities to influence different gambling practices with varying consequences for health. The synthesis foregrounds how different levels of power and influence in the production, regulation and experience of space across communities shape i) the meanings of gambling as a social practice and ii) the collective resources of communities to protect themselves from gambling harms. The analysis thus points to socio-material spaces as sites for interventions to reduce inequalities in harm
Understanding novel biocomposites comprising of short cellulose fibres in a hybrid cellulose/silk fibroin matrix
No full textBiopolymer blends offer a promising route to tunable, high-performance biomaterials, yet their potential in reinforced composites remains underexplored. This study investigates biocomposites produced by reinforcing a
hybrid biopolymer matrix (90:10 cellulose:silk fibroin) with randomly oriented short cotton fibres and varying
the reinforcement weight percentage. A pure cellulose matrix was tested for comparison. The composites were
characterised using X-ray diffraction (XRD), density analysis, tensile testing, optical microscopy, scanning
electron microscopy (SEM), and acoustic insulation analysis. Optimal hybrid composites with 50 vol%
reinforcement exhibited superior performance to pure cellulose, achieving a Young’s modulus of 3.3 ± 0.3
GPa, strain at failure of 1.4 ± 0.2%, and maximum tensile strength of 42 ± 6 MPa. These enhancements
were attributed to the hybrid matrix’s reduced viscosity and improved solvation capacity allowing higher fibre
loading and stronger interfacial adhesion. In addition, the hybrid matrix’s greater extensibility enabled more efficient stress transfer to the fibres, maximising mechanical performance. Fibre content was identified as the
primary driver of material modulus, underscoring the critical role of reinforcement. Flock content was then
shown to correlate with improved acoustic insulation performance which led to a maximum average acoustic
transmission loss of 47 ± 7 dB in hybrid samples compared to 29 ± 4 dB in cellulose samples. This work
demonstrates the viability of hybrid biopolymer blends for creating low-density, high-performance materials
from short-fibre textile waste with sustainable applications in insulative structural engineering
Structural Causal World Models for Safety Assurance of AI-based Autonomy
No full textWe propose a formal world model, grounded in structural causal models, which we call Structural Causal World Models (SCWMs): interpretable, structured, and machine-verifiable representations of environmental, contextual, and system-internal conditions that define the circumstances under which a system can operate safely. Unlike existing domain-specific approaches, our methodology is domain-agnostic and applicable across diverse safety-critical contexts. By unifying symbolic constraints, probabilistic uncertainty, and causal dependencies, our proposed methodology enables traceable hazard analysis, systematic requirement propagation, and context-aware refinement of safety constraints. We illustrate the methodology through autonomous driving examples, focusing on hazard analysis and safety requirement derivation. More broadly, this work contributes to reducing uncertainty in the safety assurance of AI-based autonomous systems by providing a means of closing the semantic gap in the definition of the system safety requirements associated within complex environments and functions, providing a basis for causal hazard and risk analysis, verification of probabilistic guarantees and run-time monitoring to counteract residual AI model insufficiencies
Investigating the effects of energy export options and policies on consumers’ electric vehicle preferences in a low-uptake country
No full textElectric vehicles (EVs) are pivotal for decarbonising the transport sector, yet adoption rates in many countries fall short of what is needed to meet climate targets. Existing research on consumer preferences for EVs predominantly examines high-adoption regions, focusing on established EV attributes and policies. However, as EV technologies evolve and the policy landscape shifts, understanding their impact on shaping consumer preferences in low-adoption markets is critical. This study investigates the influence of advanced energy export capabilities – Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) – and emerging policies on consumers’ EV preferences in a low-adoption market. We use stated preference data collected from a nationally representative sample in Australia. Notably, this is also the first study to quantify the impact of EV-specific road user charges on consumer preferences. The findings reveal that V2G and V2H capabilities significantly enhance consumer appeal, increasing willingness to pay by up to AUD 8991. This is comparable to the willingness to pay increase of AUD 10,006 associated with a purchase subsidy of AUD 5000. Moreover, favourable monetary incentives deliver greater perceived value to consumers. Conversely, non-favourable policies, such as EV-exclusive road user charges, diminish consumer interest, with a 1 cent per km charge reducing willingness to pay by AUD 5415. These findings underscore the transformative potential of EV energy export features to drive adoption, comparable to the effect of financial incentives, while highlighting the necessity of balanced, consumer-focused policy frameworks to accelerate EV adoption in low-adoption markets
The Digital Campaign
No full textIn January 2024 Facebook users were invited to request a personalised video from Prime Minister Rishi Sunak. ‘Hi [insert name]’, it went, ‘I just wanted to take a moment to wish you a very happy New Year. Now, like you, I think immigration levels are too high. So, I hope you know that today, and every day throughout 2024, whether I’m working in my office in Downing Street or at home in Yorkshire, I will deliver for you.’ Within hours, videos addressing Nigel (Farage) or with photoshopped backgrounds offering pro-Labour messages began to appear. The tool was removed soon afterwards. Initially rumoured to have been generated by Artificial Intelligence (AI), it was quickly reported that Sunak had in fact spent hours recording thousands of names, revealing a surprisingly low-tech infrastructure behind the flashy new tool
Design and optimization of miniaturized co-planar Vivaldi antennas for enhanced microwave imaging in brain hemorrhage detection
No full textWe designed and optimized a miniaturized coplanar Vivaldi antenna specifically for microwave imaging in cerebral hemorrhage detection. The antenna measures 80 mm × 80 mm × 1 mm and features an arc-shaped radiating arm, a 3 mm × 3 mm optimized pad layout, and an improved metallized via structure with nine vias, each 0.5 mm in diameter. These enhancements significantly improve the antenna's directivity, impedance matching, and signal penetration capability. Experimental results demonstrate that the antenna operates stably within the ultra-wide frequency band of 1.6-8 GHz, achieving a reflection coefficient as low as -45 dB at 4 GHz, a voltage standing wave ratio (VSWR) consistently below 1.5, and a peak gain of 9.5 dB at 6.5 GHz. These characteristics fully meet the sensitivity and penetration depth requirements for medical imaging. In addition to presenting a novel antenna design, this study validates its effectiveness under realistic biological conditions. Comparative analysis between 18- and 36-element antenna arrays demonstrates that the 36-element configuration improves image resolution and signal uniformity, while the 18-element array offers faster acquisition and better suitability for emergency or point-of-care screening scenarios. Additionally, in realistic skull model experiments, we employed rotating antenna technology (with a 20° step size) and multi-angle signal acquisition, further optimizing imaging uniformity and detection accuracy in hemorrhagic regions. By integrating real-time differential imaging technology and beamforming algorithms such as Delayed Sum (DAS) and Delayed Multiplication and Sum (DMAS), the experimental results indicate substantial progress in the identification of brain hemorrhage areas. This research provides critical technical support for the development of portable and non-invasive cerebral hemorrhage detection systems. Overall, by integrating miniaturization, performance optimization, and targeted enhancements, this study provides a robust technical basis for the development of early stroke detection systems