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Adaptive human–robot collaboration in wind turbine manufacturing using digital twins
No full textThe push for higher wind turbine-rated capacity has spurred the development of larger generators, extended blade lengths, and taller towers. Wind turbines with capacities of up to 16 megawatts are available in the market, reflecting an almost 60% surge in design capacity over the past five years. However, due to frequent design changes and the diverse range of tasks involved, conventional automation methods are less practical, leading to a labor-intensive process. Handling and assembling these large components pose challenges to human capabilities. To address these challenges, this study proposes integrating collaborative robots (cobots) to develop a hybrid approach to automating wind turbine manufacturing. Employing cobots can reduce manufacturing costs, increase production speed, and improve working conditions. The article details the development of a mobile robotic assistant designed to collaborate with human operators during wind turbine assembly, based on a case study from a leading global wind turbine manufacturer. Besides highlighting the areas attractive for collaborative automation, the article’s key contributions are to introduce a framework based on digital twin technology for the design, commissioning, and operation of robots. It also presents a human-robot interface using smartwatches to enable fluid interaction between humans and robots on production floors. The developed system can be scaled to other large-size component manufacturing involving intensive manual effort
Evaluating school-based obesity prevention interventions in 6- to 12-year-old children : a scoping review of all reported outcomes and expert consultation
Get PDFIntroduction: This scoping review aims to identify all outcomes reported in school‐based obesity prevention interventions in childhood. It serves as an essential first step towards developing an internationally agreed‐upon Core Outcome Set (COS), which defines what should be measured in all school‐based childhood obesity prevention studies, thereby reducing research waste and enhancing the comparability and relevance of future research. Methods: Four databases (PubMed, Embase, Cochrane Database of Systematic Reviews, and PsycINFO) were searched for published studies on controlled trials of school‐based overweight/obesity prevention interventions in 6‐ to 12‐year‐olds, from inception until June 2024. Two researchers independently searched for relevant articles, extracted study/intervention characteristics, and reported outcomes. Through multiple meetings and feedback rounds, an international expert panel, including researchers (n = 5), healthcare providers (n = 4; i.e., pediatrician, youth health physician, dietician, psychologist), and a health educator identified unique outcomes underlying all reported outcomes, by reflecting on what was measured irrespective of how outcomes were defined and measured. Results: In total, 262 published studies that evaluated 242 interventions were included in this review. From these studies, we extracted 642 different reported outcomes. BMI (kg/m2) was the most frequently reported outcome (128 studies), then BMI‐z (108 studies) and BMI categories (100 studies). Experts identified 69 unique outcomes from all reported outcomes. Conclusion: There is substantial heterogeneity in outcomes reported in studies evaluating school‐based overweight/obesity prevention interventions in 6‐ to 12‐year‐olds, limiting a synthesis of evidence in meta‐analyses. This highlights the need for a consensus‐based COS to improve the comparability and relevance of evidence of childhood obesity prevention trials
Synthetic varroacides in honey bee colonies : A comprehensive monitoring program across the European Union
Get PDFManaging Varroa destructor in honey bee colonies remains a constant challenge for beekeepers, requiring a balance between maintaining mite levels low whilst minimizing the negative impacts of miticide treatments on bee health. Synthetic varroacides such as coumaphos, tau-fluvalinate, and amitraz are widely used due to their convenience, but they can have negative impacts on the colony and persist in hive materials, with residues detectable long after application. To investigate the presence and dynamics of these synthetic varroacides, the INSIGNIA-EU initiative conducted a large-scale monitoring program, covering 312 bee hive sites across the European Union. The study employed the APIStrip—a novel, non-invasive passive sampler based on TENAX® sorbent—which, when placed inside the hive, passively adsorbs chemical residues from the internal hive environment. This approach has demonstrated its effectiveness eliminating the need to sample bees, wax, honey, or pollen, while still providing representative contamination data from a single, standardized analytical matrix. This study reports results from APIStrip analyses deployed across all EU countries for residues of amitraz, tau-fluvalinate, and coumaphos, using a harmonized and validated analytical protocol. Additionally, thymol, regarded as an environmentally friendly alternative, was also included in the evaluation as a reference. Sampling was carried out over nine consecutive two-week periods from May to August 2023, ensuring synchronized data collection and enabling direct comparability of results across sites and time points. The study found these miticides to be pervasive across most EU regions, appearing in more than 85% of samples and greatly outnumbering detections of the natural alternative, thymol. In most cases, notable miticide residue concentrations persisted throughout the entire sampling period
Stability and stabilization using discrete-time feedback control for hybrid stochastic delay systems with general delay
No full textThis paper develops stability and stabilization for hybrid stochastic differential delay equations (SDDEs) with general time-variable delays using the Halanay-type inequalities. First, a right-continuous version of the Halanay inequality is proved using methods different from the usual approach of proof by contradiction method. Because the Halanay inequality does not require much on the delay, boundedness and stability in mean square of hybrid SDDEs with general time delays are obtained. For stability not focusing on the equilibrium points, asymptotic stability in distribution is an appropriate criterion and has been studied extensively. For this type of stability, it is crucial to use time-homogeneous Markov processes. In this work, the problem is examined by treating delays that behave periodically. The proof is conducted using probabilistic argument, segment processes, and weaker conditions than that of the moment conditions. For a given hybrid SDDE being unstable in distribution, a feedback control based on discrete-time observations is constructed to stabilize the underlying system. For the controlled systems (hybrid SDDEs with non-constant delays), time homogeneous Markov processes are also identified. The use of Halanay inequality enables us to obtain the upper bound of observation duration using linear equations rather than the cumbersome exponential equations. Finally, two examples are given to demonstrate the effectiveness of our theory. It is shown that a better bound on observation duration can be achieved compared with the existing results
An analysis of the motivations of long-distance walkers : segmenting walkers on the West Highland Way
Get PDFLong-distance recreational walking has surged in popularity post-COVID, with trails facilitating nature-based tourism experiences. Understanding walker motivations is important for effective trail management, especially given the increasing numbers and the need to develop strategies to conserve these destinations. This study examines the motivations of 238 walkers undertaking a long-distance trail, specifically the West Highland Way in Scotland. A survey was conducted using social media and QR codes along the trail. Factor-cluster analysis is used to identify walker segments and consider their motivations for undertaking the trail. Five motivational constructs emerged: spiritual motivations, sites and education, new people and places, outdoor experience, and fulfilment of promise or tradition. Notably, the route lacked religious associations, contrasting with other studies on long-distance trails. Differences between segments were minor; however, domestic walkers exhibited higher motivations to fulfil promises and traditions, likely aligned with psychological and sociological factors
Adaptive compensation for in-process ultrasonic cladding inspection
Get PDFThroughout the early 21st century, the rise in manufacturing costs has led to economic and industrial drivers to develop novel solutions to tackle the increasing costs of high-integrity manufacturing. A key driver to reduce costs is to implement product quality conformance inspections, such as Non-Destructive Testing (NDT) at the point of manufacture, rather than at the end of the process, reducing manufacturing rework, improving schedule certainty, and increasing manufacturing throughput within industrial facilities. Welding is a highly utilised process deployed in the manufacture of high-value components such as nuclear pressure vessels, which are then clad with a corrosion-resistant alloy, with preferential attributes onto a cheaper base material to reduce the cost of manufacture. Traditional code-compliant ultrasonic inspection methodology commonly requires the machining of any non-planar surfaces prior to inspection, preventing the inspection of cladding methods during manufacture. Until now, in-process inspection has not been applied to weld cladding applications with non-planar surface profiles. This paper presents a novel approach to optimising ultrasonic imaging through the as-clad surface, consisting of multiple angled transmission and reception beams. Representative cladding trials, with artificial ultrasonic reflectors representing typical cladding defects, were introduced to assess the sensitivity of the ultrasonic inspection to defects under various non-planar surfaces. The approach demonstrated a reduction in variability of defect amplitude due to surface profile compensation alone, from 9.42dB to 1.37dB, demonstrating the methodology that can be applied agnostically of complex ray-tracing methods
Domain-adapted explainability for machine learning predictions of rotodynamic pump degradation in safety-critical industrial sectors
No full textIn safety-critical industries, it is essential to have clear and trustworthy predictive models to ensure reliability and build confidence. This paper presents a new framework to explain predictions made by Machine Learning (ML) and Artificial Intelligence (AI) models, specifically designed for experts who may not have technical knowledge of these technologies. The focus is on predicting potential issues in pumps that play a critical role in moving fluids within industrial systems. The framework uses real-world data and a tool called Shapley Additive exPlanations (SHAP) to explain how different factors influence the model’s predictions. These explanations are transformed into clear, easy-to-understand text and visuals, making them accessible to users without technical expertise. The framework was tested on predicting pump performance issues and demonstrated its ability to build trust by aligning explanations with existing expert knowledge. By offering accurate and reliable insights, this approach supports the adoption of ML tools in industries with strict regulations, fostering confidence in their use for critical decision-making
Measurement of ion acceleration and diffusion in a laser-driven magnetized plasma
No full textHere we present results from an experiment performed at the GSI Helmholtz Center for Heavy Ion Research. A mono-energetic beam of chromium ions with initial energies of ~ 450 MeV was fired through a magnetized interaction region formed by the collision of two counter-propagating laser-ablated plasma jets. While laser interferometry revealed the absence of strong fluid-scale turbulence, acceleration and diffusion of the beam ions was driven by wave-particle interactions. A possible mechanism is particle acceleration by electrostatic, short scale length kinetic turbulence, such as the lower-hybrid drift instability. [Abstract copyright: © 2026. The Author(s).
Prototype distance ratio sampling for generalised few shot object detection
No full textFew-Shot Learning has emerged as a topic that maximises DNN performance based on very few samples. In Generalised Few-Shot Learning, a model has to learn new few-shot classes while recalling earlier large-scale training classes. Learning the new classes leads to a drop in performance on the base ones. In this work, we identify and explore the parallels between Generalised Few-Shot Object Detection (G-FSOD) and Continual Learning (CL), focusing on two areas in particular: gradient manipulation methods and sampling strategies. Through extensive experimentation we demonstrate that gradient manipulation methods appear to be no better than existing techniques and do not improve performance, but actually harm performance unless the gradients are averaged. Our investigations into sampling strategies consider a number of aspects: the impact of removing the base limit and the effectiveness of different distance measures (with respect to a class prototype) for sample selection. Our experiments into these aspects reveal illuminating insights into their impact on Average Precision on the COCO and VOC datasets. Consequently, we suggest that G-FSOD research focus on the replay aspect and investigate other sampling strategies
Mental Health Support Service for Mathematics and Statistics students in Scotland
No full textMental health conditions are increasing among young people in Scotland, with universities experiencing rising demand for support services. Long waiting times and limited resources have highlighted the need for innovative approaches. This article presents a case study of a Mental Health Support Service (MHSS) embedded within the Mathematics and Statistics department at a Scottish university. Since its launch in 2021, the service has facilitated over 100 appointments, providing confidential listening and signposting support for students. Analysis of service usage reveals engagement across all year groups and demographics, with common issues including anxiety, low mood, and stress. Feedback indicates that students valued the subjectspecific understanding, accessibility, and responsiveness of the service. These findings suggest that departmental-level support can complement university-wide provision, enhance early intervention, and improve student well-being, offering a model for other faculties seeking to address mental health challenges in higher education
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