A multi-level IIOT platform for boosting mines digitalization

Publisher Copyright: © 2024This paper presents an innovative IIoT multi-level platform tailored to address the specific needs of the mining domain. The platform has been conceptualized and built in the context of the illuMINEation European project. For this purpose, mining specific use cases have been designed such as promoting underground safe areas, performing efficient mining operations or boosting predictive maintenance approaches. Then, specific requirements have been identified and, as a result, the platform has been developed. It consists of four-level layered platform: (1) edge devices layer to manage several sensors deployed in the mines; (2) edge box layer to provide in-mine operations such as filtering, streaming and processing; (3) fog layer which offers an overall perspective of each mine; and (4) cloud layer to centralize the data of all the mines and to provide powerful processing capabilities. In addition, the platform is robustly secured in terms of protecting communications confidentiality and access control and also provides a toolbox aimed at manipulating 3D complex images to obtain operable mine-domain novel user interfaces. Finally, a platform validation is proposed where three different use cases are explained to better show and demonstrate the capabilities of the platform.Peer reviewe

PRoT-FL: A privacy-preserving and robust Training Manager for Federated Learning

Publisher Copyright: © 2024 The AuthorsFederated Learning emerged as a promising solution to enable collaborative training between organizations while avoiding centralization. However, it remains vulnerable to privacy breaches and attacks that compromise model robustness, such as data and model poisoning. This work presents PRoT-FL, a privacy-preserving and robust Training Manager capable of coordinating different training sessions at the same time. PRoT-FL conducts each training session through a Federated Learning scheme that is resistant to privacy attacks while ensuring robustness. To do so, the model exchange is conducted by a “Private Training Protocol” through secure channels and the protocol is combined with a public blockchain network to provide auditability, integrity and transparency. The original contribution of this work includes: (i) the proposal of a “Private Training Protocol” that breaks the link between a model and its generator, (ii) the integration of this protocol into a complete system, PRoT-FL, which acts as an orchestrator and manages multiple trainings and (iii) a privacy, robustness and performance evaluation. The theoretical analysis shows that PRoT-FL is suitable for a wide range of scenarios, being capable of dealing with multiple privacy attacks while maintaining a flexible selection of methods against attacks that compromise robustness. The experimental results are conducted using three benchmark datasets and compared with traditional Federated Learning using different robust aggregation rules. The results show that those rules still apply to PRoT-FL and that the accuracy of the final model is not degraded while maintaining data privacy.Peer reviewe

Diverse policy generation for the flexible job-shop scheduling problem via deep reinforcement learning with a novel graph representation

Publisher Copyright: © 2024 The AuthorsIn scheduling problems common in the industry and various real-world scenarios, responding in real-time to disruptive events is important. Recent methods propose the use of deep reinforcement learning (DRL) to learn policies capable of generating solutions under this constraint. However, current DRL approaches struggle with large instances, which are common in real-world scenarios. The objective of this paper is to introduce a new DRL method for solving the flexible job-shop scheduling problem, with a focus on these type of instances. The approach is based on the use of heterogeneous graph neural networks to a more informative graph representation of the problem. This novel modeling of the problem enhances the policy's ability to capture state information and improve its decision-making capacity. Additionally, we introduce two novel approaches to enhance the performance of the DRL approach: the first involves generating a diverse set of scheduling policies, while the second combines DRL with dispatching rules (DRs) constraining the action space, with a variable degree of freedom depending on the chosen policy. Experimental results on two public benchmarks show that our approach outperforms DRs and achieves superior results compared to three state-of-the-art DRL methods, particularly for large instances.Peer reviewe

Resilience to the Flowing Unknown: An Open Set Recognition Framework for Data Streams

Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Modern digital applications extensively integrate Artificial Intelligence models for automated decision-making. However, these AI-based systems encounter reliability and safety challenges when handling continuous data streams in dynamic scenarios. This work explores the concept of resilient AI systems that must operate in the face of unexpected events and unseen patterns. This is a common issue that regular closed-set classifiers encounter in streaming scenarios, as they are designed to compulsory classify any new observation into one of the training patterns (i.e., the so-called over-occupied space problem). In batch learning, the Open Set Recognition field addresses this issue by requiring models to maintain classification performance when processing unknown patterns. This work investigates the application of an Open Set Recognition framework that combines classification and clustering to address the over-occupied space problem in streaming scenarios. We devise a benchmark comprising different classification datasets with varying ratios of known to unknown classes, and experiments compare the performance of the proposed framework with that of individual incremental classifiers. Discussions held over the obtained results highlight situations where the framework performs best and the limitations of incremental classifiers in open-world streaming environments.Peer reviewe

Design and experimental characterization of a propane-based reversible dual source/sink heat pump

Publisher Copyright: © 2024 The Author(s)The current paper presents the design and energy performance analysis of a propane-based reversible Dual Source/Sink Heat Pump (DSHP). DSHPs offer an alternative to conventional water to water and air to water heat pumps, leveraging the strengths of both technologies in an efficient manner. The developed prototype incorporates an innovative Dual Source/Sink Heat eXchanger (DSHX), enabling the unit operating in various modes, including space heating, space cooling, and domestic hot water production using brine, air or both simultaneously as a source/sink. The DSHX serves as as both a condenser or an evaporator, directly rejecting or absorbing heat from air and/or brine. By eliminating secondary loops and defrost cycles, the DSHX minimizes energy losses. The main novelty of this work lies in the DSHX that integrates external units typically duplicated in DSHPs into a single component, eliminating the need for split refrigerant flow rates, thus avoiding maldistribution, refrigerant charge increase and draining valves. A steady state experimental campaign was conducted in a climatic chamber to characterize the DSHP prototype and validate the DSHX performance models. Heating capacity up to 11.2 kW and COP values up to 4.7 were achieved at nominal compressor speed by supplying hot water at 35 °C with an ambient temperature of 7 °C. Similarly, when producing cold water at 7 °C, cooling capacity and EER reached 9.8 kW and 3.6, respectively, at nominal compressor speed using air as heat sink at 35 °C. The effects of various operating parameters on the overall coefficient of performance and heat duty in both heating and cooling modes, considering air or brine as heat source/sink are analyzed in detail. Results demonstrate enhancements of approximately 15 % in capacity and efficiency compared to earlier work. Moreover, four deterministic models were created in order to predict the behaviour of the DSHX and validated against experimental results, reaching deviation values below 15 %.Peer reviewe

Foaming and cross-linking of cellulose fibers using phytic acid

Publisher Copyright: © 2024 The Author(s)Bio-based compounds have become the focus in the development of next-generation materials. The polyphosphated structure and availability of phytic acid has sparked an interest to understand its properties and apply it to making fire-retardant fabrics. However, its degradative effect on natural fibers sets limitations to its potential uses. In this study, we unveiled a new dimension to explore with phytic acid: cellulose fiber foams. Phytic acid enabled synergistic foaming with carboxymethyl cellulose albeit causing issues in long-term wet foam stability. Adding cellulose fibers to this mixture and drying at 160 °C produced solid foams with increased compressive strength and stiffness; comparable to foams cross-linked with the commonly used citric acid. The reduced contact area in low-density fiber networks allowed the cross-linking between phytic acid and the fiber network to mitigate structural weakening due to fiber degradation. Imaging also revealed the formation of a film encompassing fiber bonds; attributed to the strong interaction between phytic acid and carboxymethyl cellulose. Furthermore, phytic acid imparted self-extinguishing fire-retardant properties to the cellulose fiber foams measured using thermogravimetric analysis and cone calorimetry. This work showcases a simple new application for phytic acid without the use of catalysts or solvents. It serves to encourage further development of green practices to continuously challenge the industrial landscape.Peer reviewe

Tailoring the properties of carbon molecular sieves membranes for the separation of propionic acid from aqueous solutions

Publisher Copyright: © 2024 The AuthorsIn the fermentative production of propionic acid (PA), the major problem with batch fermentation systems is the strong inhibitory effect of PA on the production yield; one way to increase the yield is the in-situ removal of PA by using pervaporation. Acetic acid (AA) is the most important by-product in the fermentation; therefore, the membrane should be able to remove selectively PA from an aqueous solution containing AA. Considering that PA is more hydrophobic than AA and their kinetic diameter are 0.480 and 0.436 nm respectively, hydrophobic membranes with main pores in the range of around 0.5–0.6 nm with high permeation are required. Supported thin Carbon Molecular Sieve Membranes (CMSM) were prepared by the dip coating a porous alumina support into a solution containing resorcinol phenolic resin as carbon source. The hydrophobicity was obtained by carbonizing the polymer at temperatures higher than 750 °C and adding polyvinyl butyral (PVB) as pore forming agent and carbon contributor. PA with 88 % of purity was obtained by pervaporation of an aqueous solution containing 5 % of PA and 5 % of AA using a CMSM carbonized at 850 °C containing 1 % of PVB in the dipping solution.Peer reviewe

Modality-Independent Effect of Gravity in Shaping the Internal Representation of 3D Space for Visual and Haptic Object Perception

Publisher Copyright: Copyright © 2024 the authors.Visual and haptic perceptions of 3D shape are plagued by distortions, which are influenced by nonvisual factors, such as gravitational vestibular signals. Whether gravity acts directly on the visual or haptic systems or at a higher, modality-independent level of information processing remains unknown. To test these hypotheses, we examined visual and haptic 3D shape perception by asking male and female human subjects to perform a “squaring” task in upright and supine postures and in microgravity. Subjects adjusted one edge of a 3D object to match the length of another in each of the three canonical reference planes, and we recorded the matching errors to obtain a characterization of the perceived 3D shape. The results show opposing, body-centered patterns of errors for visual and haptic modalities, whose amplitudes are negatively correlated, suggesting that they arise in distinct, modality-specific representations that are nevertheless linked at some level. On the other hand, weightlessness significantly modulated both visual and haptic perceptual distortions in the same way, indicating a common, modality-independent origin for gravity’s effects. Overall, our findings show a link between modality-specific visual and haptic perceptual distortions and demonstrate a role of gravity-related signals on a modality-independent internal representation of the body and peripersonal 3D space used to interpret incoming sensory inputs.Peer reviewe

Enhancing stress measurements accuracy control in the construction of long-span bridges

Publisher Copyright: © The Author(s) 2024.This paper introduces new contributions for construction procedures designed to enhance the robustness and precision of stress control in active anchorage and short presetressing units for long-span bridges, particularly addressing potential technical risks. The primary focus is on optimizing stress management for bridge stays, suspension cables, and short prestressing units by emphasizing a unified parameter: stress. The contributions of this research encompass (1) the introduction of advanced load cells for stress control in active anchorages and (2) the implementation of a novel synchronized multi-strain gage load cell network for short prestressing units, crucial in situations where prestressing losses can attain significant magnitudes. To validate these advancements, the authors present (3) a practical experience and results obtained from applying these methodologies in monitoring the structural response during the construction of the Tajo Bridge using the cable-stayed cantilever technique.Peer reviewe

Vibrio vulnificus marine pathogen detection with thin-film impedance biosensors

Publisher Copyright: © 2024 The AuthorsVibrio vulnificus (Vv) is a marine pathogen that can cause rapid death by septicemia (vibriosis) in humans and several fish species. This pathogen is considered a biomarker of climate change, as both its presence and vibriosis incidence in coastal environments are increasing because of global warming. Currently, gold-standard methods for Vv detection are all PCR-based, requiring expensive equipment and skilled personnel, which hinders their use on a global scale. The aim of this work was to design and test a more affordable method that could be used worldwide for both vibriosis diagnosis and pathogen monitoring in water. To this end, we functionalized thin film microelectrodes with thiolated single-stranded DNA sequences complementary to the species-specific genetic marker, the gene vvha, and monitored the impedance changes upon hybridization. We tested the biosensor specificity with synthetic and natural DNA samples (from cultures of Vv and V. cholerae, a closely related species) and determined the detectable concentration range. The results obtained showed that this biosensor was specific for Vv, achieving detection down to 1 pM synthetic DNA and DNA extracted from 102 bacteria mL−1, which is equivalent to that obtained by PCR. Consequently, this biosensor could be used on a global scale for vibriosis diagnostics, health risk studies and climate change monitoring, with potential application for in situ detection.Peer reviewe