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Paper microfluidic sentinel sensors enable rapid and on-site wastewater surveillance in community settings
Get PDFTracking genomic sequences as microbial biomarkers in wastewater has been used to determine community prevalence of infectious diseases, contributing to public health surveillance programs worldwide. Here, we report upon a low-cost, rapid, and user-friendly paper microfluidic platform for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza detection, using loop-mediated isothermal amplification, with signal read using a mobile phone camera. Sample-to-answer results were collected in less than 1.5 h, providing rapid multiplexed detection of viruses in wastewater, with a detection limit of <20 copies mL−1. The device was subsequently used for on-site testing of SARS-CoV-2 in wastewater samples from four quarantine hotels at London Heathrow Airport, showing comparable results to those obtained using polymerase chain reaction. This sensing platform, which enables rapid and localized testing without requiring samples to be sent to centralized laboratories, provides a potentially important public health tool for pandemic preparedness, with a variety of future wastewater surveillance applications in community settings.Royal Academy of Engineering, Natural Environment Research Council, Leverhulme TrustCell Reports Physical Scienc
Operating itself safely: merging the concepts of ‘safe to operate’ and ‘operate safely’ for lethal autonomous weapons systems containing artificial intelligence
Get PDFThe Ministry of Defence, specifically the Royal Navy, uses the ‘Duty Holder Structure’ to manage how it complies with deviations to maritime laws and health and safety regulations where military necessity requires it. The output statements ensuring compliance are ‘safe to operate’ certification for all platforms and equipment, and the ‘operate safely’ declaration for people who are suitably trained within the organisation. Together this forms the Safety Case. Consider a handgun; the weapon has calibration, design and maintenance certification to prove it is safe to operate, and the soldier is trained to be qualified competent to make predictable judgement calls on how and when to pull the trigger (operate safely). Picture those statements as separate circles drawn on a Venn diagram. As levels of autonomy and complexity are dialled up the two circles converge. Should autonomy increase to the point that the decision to fire be under the control of an Artificial Intelligence within the weapon’s software then the two circles will overlap. This paper details research conclusions within the overlap, and proposes a new methodology able to certify that an AI based autonomous weapons system is “safe to operate itself safely” when in an autonomous state.Defence Studie
Exploring nanobubble technology for enhanced anaerobic digestion of thermal-hydrolysis pre-treated sewage sludge
Get PDFNanobubble technology was used to enhance anaerobic digestion (AD) of thermal-hydrolysis pre-treated sewage sludge for bioenergy recovery. The prepared air, CO2, and H2 nanobubble solutions, with concentrations of 9.88–10.2 × 107 bubbles/mL, remained stable for at least 7 days. After adding them into AD reactors, significantly higher CH4 production (37.1 %) was observed for the CO2 nanobubble treatment, followed by air (25.6 %) and H2 (14.5 %) nanobubble treatments, compared to the control group. CO2 nanobubble treatment performed the best in improving acidogenesis/acetogenesis, resulting in significantly higher volatile fatty acid generation during the initial 3–4 days. A comparison of reactors supersaturated and non-saturated with oxygen has demonstrated most of the biogas uplift observed to result from the nanobubbles rather than from initial oxygen soluble levels, demonstrating the crucial role of nanobubbles in upgrading AD. This study demonstrates, for the first time, that nanobubbles can provide additional benefits when combined with stablished sludge pre-treatment technologies.Bioresource Technology Report
Effect of embedded shape memory alloy (SMA) on the low-velocity impact behaviour of stringer stiffened composite plates
Get PDFThis study presents an analytical model of low-velocity impact on composite plates, possessing either flat or cylindrical shapes. The overall plate`s stiffness properties are varied with an additionally assembled Ω-stringer and embedded shape memory alloy wires in the composite material, using only the shape memory effect. This analytical approach enables a low-effort but sufficiently accurate design of low-energy-impacted structures. Comprehensive analytical equations are developed based on the inclusion of the stringer effect on the curved panels. For both stringer-stiffened and non-stiffened plate models, parameter variations regarding the impact and shape memory alloy (SMA) wire integration are conducted. The effects can be classified as changes in essential and acquired stiffness. Our results indicate that SMAs improve the energy absorption capability of stiffened composite panels.Applied Composite Material
Incorporating implicit condensation into data-driven reduced-order models for nonlinear structures
No full textThe global climate effort is increasingly dependent on lightweight, flexible designs to provide engineering solutions capable of meeting ambitious emissions targets. Examples of these designs include high-aspect-ratio wings, which are capable of achieving extended flight times using significantly less energy, but their complexity introduces geometric nonlinearity to the system, leading to a substantial increase in complexity. Although these nonlinear dynamics can be accurately modelled using finite element (FE) software, the required magnitude of such models is extremely computationally expensive, preventing their use in real-time applications or extensive modelling procedures. Non-intrusive reduced-order models (NIROMs) for nonlinear behaviour are of great interest to the mechanical engineering community, as they are capable of capturing the full system dynamics using a significantly reduced coordinate system (typically a subset of the vibration modes). However, the generation of reliable NIROMs remains an active challenge. This chapter combines the projection-based strategy adopted by the implicit condensation method with recent results from the field of machine learning to create a novel NIROM generation technique based on time series data. Specifically, a variational recurrent autoencoder is applied to the system dynamics on a reduced modal basis. To complement the ability of VRAEs to reproduce time series and create statistically consistent synthetic data, a second decoder is added to recreate the true parameterization of the nonlinear system of equations.42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024Nonlinear Structures & Systems, Vol.
Parametric analysis of rotary VTOL aerobot design configurations to fly on Titan
Get PDFThe exploration of Titan, Saturn’s largest moon, presents significant aerodynamic challenges due to its dense atmosphere and low gravity, necessitating specialised rotorcraft designs. This study conducts a parametric analysis of multiple rotary Vertical Takeoff and Landing (VTOL) aerobot configurations, including conventional helicopters, coaxial systems, tandem rotorcraft, quadcopters, and hexacopters, with a focus on performance in Titan's environment. Using simplified momentum theory, the power consumption and operational efficiency of these rotorcraft are evaluated across key flight phases such as vertical climb, hover, and forward flight. The analysis highlights that hexacopter configurations are the most power-efficient during vertical ascent and hover for smaller rotor diameters, whereas conventional helicopter designs excel in forward flight for larger rotor sizes. The study also utilises Battery Mass Fraction (BMF) calculations to assess the energy requirements for various flight segments, offering valuable insights into the energy-efficient design of rotorcraft for Titan exploration. This research establishes a foundational framework for optimising rotorcraft design in extraterrestrial environments, providing critical data for future missions aimed at exploring Titan’s surface and atmosphere.75th International Astronautical Congress IAC-202
Bistatic multi‐polarimetric synthetic aperture radar coherence investigation using spatially variant incoherence trimming
Get PDFSynthetic Aperture Radar (SAR) Coherent Change Detection allows for the detection of very small scene changes. This is particularly useful for Intelligence, Surveillance and Reconnaissance as small changes such as vehicle tracks can be identified. Rapidly collecting repeat pass SAR imagery is important in these applications. For space‐borne platforms, such repeat passes may however have significant differences, or baselines. Coherent Change Detection products are reliant on high coherence for good interpretability. This work investigates the sources and levels of incoherence associated with bistatic SAR imagery for a variety of baselines using simulations and measured laboratory data for two ground types. Additionally, spatially variant incoherence trimming is implemented. The paper shows the importance of angle‐dependant backscatter on the coherence of sub‐resolution cell scatterers.This research was produced as a part of a PhD funded by Defence Science and Technology Laboratory.IET Radar, Sonar & Navigatio
Early detection of dementia through retinal imaging and trustworthy AI
Get PDFAlzheimer's disease (AD) is a global healthcare challenge lacking a simple and affordable detection method. We propose a novel deep learning framework, Eye-AD, to detect Early-onset Alzheimer's Disease (EOAD) and Mild Cognitive Impairment (MCI) using OCTA images of retinal microvasculature and choriocapillaris. Eye-AD employs a multilevel graph representation to analyze intra- and inter-instance relationships in retinal layers. Using 5751 OCTA images from 1671 participants in a multi-center study, our model demonstrated superior performance in EOAD (internal data: AUC = 0.9355, external data: AUC = 0.9007) and MCI detection (internal data: AUC = 0.8630, external data: AUC = 0.8037). Furthermore, we explored the associations between retinal structural biomarkers in OCTA images and EOAD/MCI, and the results align well with the conclusions drawn from our deep learning interpretability analysis. Our findings provide further evidence that retinal OCTA imaging, coupled with artificial intelligence, will serve as a rapid, noninvasive, and affordable dementia detection.Engineering and Physical Sciences Research Council (EPSRC)This work was supported in part by the National Science Foundation Program of China (62422122, 62272444, 62371442, 62302488), in part by the Youth Innovation Promotion Association CAS (2021298), in part by the Zhejiang Provincial Natural Science Foundation of China (LR22F020008, LQ23F010007, LR24F010002, LZ23F010002), in part by Key research and development program of Zhejiang Province (2024C03101, 2024C03204) and Key Project of Ningbo Public Welfare Science and Technology (2023S012). AFF acknowledges the support of the Royal Academy of Engineering Chair INSILEX (CiET1819\9), the UKRI Frontier Research Guarantee INSILICO (EP\Y030494\1). The research of AFF was carried out at the National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre (BRC) (NIHR203308).npj Digital Medicin
Digital technology and innovation: the impact of blockchain application on enterprise innovation
Get PDFBlockchain as a frontier digital technology provides new opportunities for innovation. This paper builds a theoretical framework utilizing the Resource-Based View (RBV), and empirically examines the impact of blockchain application on enterprise innovation, based on panel data from Chinese listed companies spanning from 2007 to 2020. This paper finds that the adoption of blockchain applications significantly promotes enterprise innovation, through mechanisms of improving operational efficiency and expanding operational scope. With regard to contextuality, the positive effect of blockchain applications on innovation is more pronounced in enterprises with higher levels of technological and capital accumulation. With regard to temporality, innovation at faster paces can better realise the benefits of blockchain applications. This paper provides robust empirical evidence derived from a large sample, thereby enhancing our understanding of this dynamic relationship and suggesting directions for future research.This work is supported by two CASS fundings: Youth Development Program (2024QQJH128) and CASS Laboratory for Economic Big Data and Policy Evaluation (2024SYZH004).Technovatio
The impact of weather patterns on inter-annual crop yield variability
Get PDFInter-annual variations in crop production have significant implications for global food security, economic stability, and environmental sustainability. Existing crop yield prediction models primarily using meteorological variables may not adequately encapsulate the full breadth of weather influences on crop development processes, such as compound or extreme events. Incorporating weather patterns into crop models could provide a more comprehensive understanding of the environmental conditions affecting growth, enabling more accurate and earlier yield predictions. Our study examines 30 distinct UK Met Office weather patterns (MO30) based on mean sea level pressure. We investigate their association with weather conditions that limit winter wheat yield in the UK (1990-2020). Blocked, negative North Atlantic Oscillation (NAO) patterns create the highest risk of temperatures that are below optimal for crop yield. However, the connection between weather patterns and yield is complex, with differing effects at a regional scale and even at which point in the growth cycle they appear. It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling. The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. This is due to increased cyclonic weather patterns, which bring warmer, wetter conditions during the wheat's vernalisation stage, followed by warmer, drier conditions during the anthesis and grain-filling phases.Natural Environment Research CouncilThis research was funded by the UK Natural Environment Research Council through the CENTA2 Doctoral Training Partnership [NERC Ref: NE/S007350/1].Science of The Total Environmen