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Semi-supervised tapping wear detection in nodular cast iron workpieces under real industrial conditions
No full textPublisher Copyright: © The Author(s) 2025.The tapping of metal components is a manufacturing task with great potential for automation, because the conditions affecting the industrial components are of limited variability. However, automation encounters two main problems: both the human- and the time-related costs associated with the manual classification of threads are excessive, and thread quality can vary greatly, due to tapping tool wear. In this study, the use of semi-supervised algorithms is proposed to improve the performance of machine learning–based models trained on real industrial datasets. The strategy was validated on a dataset of more than 7000 threads produced with 36 different tapping tools under the same working conditions involving nodular cast iron workpieces. Several algorithms were trained using datasets with different features and data processing. The best results were obtained with datasets using linear regression in which sinusoidal fluctuations in the raw signals were replaced by linear regressions and the slope of an 11-element rolling window was applied to extend the raw dataset. Algorithms were trained with different percentages of labeled datasets. The co-training-based algorithms almost systematically obtained the best results, yielding better results than the reference algorithms using a 100% labeled dataset. Besides, the proposed solution also achieved higher performance with 50% of labeled instances in the training dataset, drastically reducing the costs of manual labeling for that sort of industrial dataset.Peer reviewe
The Transition to Circular Economy in Transport Infrastructure - CERCOM and LIAISON Progression
Get PDFPublisher Copyright: © The Author(s) 2025.To achieve climate neutrality, synergies between circular economy (CE) and carbon reduction need to be established in the context of transport infrastructure. Implementation of the circular economy and resource efficiency (RE) policies have the potential to facilitate decarbonization targets, while using fewer natural resources, maintaining or enhancing biodiversity and providing regenerative design for generations to come. This paper presents the interpretation of RE and CE within transport infrastructure in the context of the CERCOM and LIAISON projects. As part of CERCOM, a strategic review of current practice was carried out to develop a definition of CE within transport infrastructure, and provide the successes and barriers for further transition from a linear to a circular economy. A Risk Based Assessment Framework (RBAF) and associated software tool were developed to provide a means to evaluate the impacts of certain measures and prioritize areas that require further research or investigation. LIAISON will provide further progression in this regard, and develop a methodology, support tools and close to market technological solutions to transform EU Transport Infrastructure into a more sustainable and low carbon economic activity.Peer reviewe
Prior use-dependent plasticity triggers different individual corticomotor responses during persistent musculoskeletal pain
No full textPublisher Copyright: © 2025 International Association for the Study of Pain.Movement repetition is crucial for pain interventions. It facilitates the rehabilitation of motor patterns, the acquisition of motor skills, and the genesis of adaptive use-dependent plasticity. However, the influence of prior motor experience and preexisting use-dependent plasticity on pain severity and progression remains poorly investigated. This study investigated the effects of preexisting use-dependent plasticity during the development of prolonged experimental musculoskeletal pain. Using transcranial magnetic stimulation, corticospinal excitability was assessed by measuring the Rest motor threshold (RMT), motor-evoked potential (MEP), representational area of the motor map, volume, and center of gravity of the first dorsal interosseous (FDI) muscle in musicians (n = 19), a well-known ecological model of use-dependent plasticity, and in nonmusicians (n = 20). All participants attended 3 sessions (day 1, day 3, day 8). Prolonged pain for several days was induced by intramuscular injection of nerve growth factor (NGF) into the right FDI muscle at the end of day 1. Compared to day 1, prolonged pain uniquely led to reduced motor map volume in nonmusicians on day 3 (P = 0.004), who also showed higher NGF-related pain intensity compared to musicians. The motor maps of musicians, which were already smaller in pain-free conditions (day 1) compared to nonmusicians (P = 0.021), remained nonsignificantly different across days. Notably, corticomotor responses (map volume, MEP amplitude, and RMT) were correlated to weekly and accumulated musical training. These findings demonstrate that preexisting use-dependent plasticity associated with motor training may counteract the effects of prolonged pain in the motor system. Moreover, it confirms that prior motor experience acts as a source of individual variability to pain.Peer reviewe
Comparative study of HD-EMG electrode setups for Smart Mechatronic Ankle-Foot Orthoses development
No full textSmart mechanized ankle-foot orthoses aim to enhance rehabilitation and mobility assistance by integrating advanced human-machine interfaces. This study evaluates different high-density electromyography (HD-EMG) electrode configurations to investigate signal quality for future designs, addressing challenges in sensor variability and noise. By analyzing dorsiflexion and plantarflexion movements with HD-EMG arrays placed over the tibialis anterior and gastrocnemius medial muscles of 4 healthy participants, the research identifies configurations that improve signal quality and enable better integration into future ankle-foot orthoses. The results demonstrate that the electrodes with smaller surface area of sensors provide higher signal-to-noise ratio and more stable signals compared to the larger electrodes with a higher interelectrode distance. Additionally, while printed electrodes tend to offer greater comfort, due to their flexible design, they performed worse in comparison to their conventional counterparts. The study highlights the need for further investigation of alternative printed interfaces and materials, which will allow for smaller and more densely placed electrode pads while retaining the overall malleability.Clinical relevance- The results of this study provide guidance for future HD-EMG system designs for integration into advanced ankle-foot orthoses, which are used in the rehabilitation of mobility problems.Peer reviewe
Evaluation of Imidazolium Ionenes: Solid–Solid Phase Change Materials as Heat Sinks
Get PDFPublisher Copyright: © 2025 by the authors.Overheating in miniaturized electronic devices can reduce their useful life, where conventional heat sinks are insufficient. The utilization of ionenes as solid–solid phase change materials is proposed to enhance thermal dissipation without the risk of leakage. In this work, a series of imidazolium ionenes with structural modifications in their aromatic core and aliphatic chain length were synthesized. The synthesis was carried out using the respective monomers diimidazole and alkyl dibromide, followed by counterion bromide exchange using lithium bis(trifluoromethanesulfonyl)imide, with yields over 90% in all cases. Thermal characterizations showed that all ionenes are heat-resistant, with degradation temperatures between 421 °C and 432 °C; moreover, they all presented only a solid–solid transition (Tg) as a phase change, between 59 °C and 28 °C, which varied depending on the aromatic core used and the length of the aliphatic chain. The obtained ionenes were introduced into an experimental device with an operating temperature of 40 °C, to be evaluated as solid–solid phase change materials in heat sinks. These demonstrated an average decrease in operating temperature of 9 °C compared to the device without ionenes. On the other hand, the stability of the ionenes was analyzed over 10 thermal cycles at 40 °C at a heating rate of 5 °C/min. This analysis demonstrated that the ionenes did not present changes or degradation during the evaluated cycles. These findings demonstrate that imidazolium ionenes are promising solid–solid phase change materials for use as efficient and self-repairing heat sinks in compact electronic devices.Peer reviewe
Carbon flow analysis: A novel approach for circularity evaluation of façade components
Get PDFPublisher Copyright: © 2025 The AuthorsThe transition towards a circular economy in the built environment requires robust methodologies to evaluate carbon and material flows at the component level. This paper introduces Carbon Flow Analysis (CFA), an innovative approach that integrates Material Flow Analysis and Life Cycle Assessment to facilitate environmental decision- making for façade renovations. CFA systematically maps embodied carbon and material inputs within façade components, offering a transparent assessment of their circularity potential. The study further refines the selection process through a contextualization framework, which contrasts CFA results against environmental performance ranges derived from Environmental Product Declarations (EPDs) and environmental databanks. Findings demonstrate the variable role of secondary materials in reducing carbon emissions, due to the large variability of impact across materials and components. While CFA provides actionable insights into material selection for façade components, the study highlights the need for standardized circularity indicators and reliable databanks to enhance decision-making in architectural design. By combining quantitative carbon tracking with performance- based contextualization, this research contributes to the development of practical guidelines for achieving carbon-neutral façade renovations.Peer reviewe
A simulation-based thermal process control method for multi-material laser-joining operations
No full textPublisher Copyright: © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.The use of multi-material assemblies is becoming increasingly common in sectors such as aeronautics. In this context, laser joining process offers the possibility to obtain strong and reliable metal-composite bonds without the need of mechanical fasteners or adhesives but temperature control during the process is a critical aspect to obtain good-quality joints. Controlling the temperature at the multi-material interface is the key to obtain high-quality joints. However, this is a variable that cannot be monitored during the process. In this paper, a method for thermal control in laser joining operations is presented which is based on creating temperature synthetic data, from ANSYS® simulation models, both for process planning optimization and for the creation of AI-based regression models to predict the interface temperature over time. A case study involving the laser joining of aluminium and PEEK (Polyether Ether Ketone) components is used. The results demonstrate that the experimentally validated temperature synthetic data, enhance process optimization, reducing the need for extensive physical experiments. Moreover, the creation and use of regression models has been demonstrated a viable approach for predicting the temperature at the interface. However, the accuracy on temperature prediction depends on the type of sensor used to monitor the temperature.Peer reviewe
Data Harmonization as a Keystone for Data Spaces: Challenges, Techniques, and Future Trends
No full textPublisher Copyright: © 2025 University of Split, FESB.In spite of the efforts to become more data-driven, organizations still need to overcome common data governance challenges such as interoperability, data sovereignty, and data value generation. On top of this, the large volumes of data being generated in the computing continuum generate innovative business models. In this regard, data spaces facilitate the safe exchange of data assets to improve decision-making, foster innovation, and create novel services, products, and business models. The standardization, integration, cleaning, and transformation of the various data sources is crucial for delivering reliable data assets. To this end, data harmonization is key as it raises data quality and usability, reduces redundancy, and helps organizations meet regulatory and industry standards. In this manuscript, we dive into the scientific literature to better understand the various stages that comprise the data harmonization lifecycle and the challenges of it in the field of data spaces. Then, we analyze the various artificial intelligence techniques utilized for data harmonization and its role as a standardizing agent for data definition and interoperability, looking at the current studies and the overwhelming related regulation.Peer reviewe
Comparative Analysis of Classical and Quantum-Inspired Solvers: A Preliminary Study on the Weighted Max-Cut Problem
No full textPublisher Copyright: © 2025 Copyright held by the owner/author(s).Combinatorial optimization is essential across numerous disciplines. Traditional metaheuristics excel at exploring complex solution spaces efficiently, yet they often struggle with scalability. Deep learning has become a viable alternative for quickly generating high-quality solutions, particularly when metaheuristics underperform. In recent years, quantum-inspired approaches such as tensor networks have shown promise in addressing these challenges. Despite these advancements, a thorough comparison of the different paradigms is missing. This study evaluates eight algorithms on Weighted Max-Cut graphs ranging from 10 to 250 nodes. Specifically, we compare a Genetic Algorithm representing metaheuristics, a Graph Neural Network for deep learning, and the Density Matrix Renormalization Group as a tensor network approach. Our analysis focuses on solution quality and computational efficiency (i.e., time and memory usage). Numerical results show that the Genetic Algorithm achieves near-optimal results for small graphs, although its computation time grows significantly with problem size. The Graph Neural Network offers a balanced solution for medium-sized instances with low memory demands and rapid inference, yet it exhibits more significant variability on larger graphs. Meanwhile, the Tensor Network approach consistently yields high approximation ratios and efficient execution on larger graphs, albeit with increased memory consumption.Peer reviewe
Validation of the use of concept maps as an evaluation tool for the teaching and learning of mechanical and industrial engineering
No full textPublisher Copyright: © The Author(s) 2024.This paper presents the experimental work developed to measure the learning process through concept map analysis. The development of a concept map is requested by the students for each chapter or theme of the subject. As a result, maps from engineering courses have been analyzed. The measurements carried out consider several parameters, such as individual and team map building, student progressive knowledge level, and map complexity. Concerning the complexity analysis, the focus is qualitative, and it is based on the data extracted from the concept maps elaborated by the students. The study, conducted during the 2018–2019 academic year, included students from various academic levels and institutions, such as the Public University of Navarra UPNA and the University of the Basque Country UPV-EHU, covering first-degree students of Bachelor's Degree in Mechanical Engineering and first-degree students of Master's Degree in Industrial Engineering at UPNA, third-degree students of Bachelor's Degree in Mechanical Engineering at UPV-EHU. The data collected from 37 individual maps in Industrial Drawing, 31 group maps in Industrial Drawing, 12 individual maps in Design of Machinery, and 12 group maps in Design of Machinery, along with a control group of 79 students who did not participate in any activity, provided valuable insights into the effectiveness of concept maps for evaluating understanding levels and learning outcomes across various engineering subjects and academic levels. The learning outcome of the students is treated to obtain the level of understanding of complex systems shown by the students through the concept maps previously drawn and the questionnaire answered by each student about the achievement of learning results through the use of concept maps. This work shows the research methodology established and the learning results achieved qualitatively: measuring the maps by means of a rubric, self-assessment based on a survey, and through the questionnaires. Also, the results obtained in the final exams have been compared. From the observed results, this methodology is presented as a suitable alternative for evaluating the correct acquisition of concepts in online teaching situations.Peer reviewe