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description Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | F-CUBEDEC| F-CUBEDDouwe S. Zijlstra; Mark Visser; Esther Cobussen-Pool; Dennis J. Slort; Pavlina Nanou; Jan R. Pels; Heather E. Wray;doi: 10.3390/su16020850
The ever-increasing volumes of food waste generated and the associated environmental issues require the development of new processing methods for these difficult waste streams. One of the technologies that can treat these waste streams directly is hydrothermal carbonization. In this work, olive pomace and orange peels were treated via a mild hydrothermal carbonization process (TORWASH®) in a continuous-flow pilot plant. For olive pomace, a solid yield of 46 wt% and a dry matter content of 58% for the solid press cakes were obtained during continuous operation for 18 days. For orange peels, the values were lower with 31 wt% solid yield and a 42% dry matter content during 28 days of continuous operation. These values corresponded fully with initial laboratory-scale batch experiments, showing the successful transformation from batch to continuous processing. The obtained hydrochar from both feedstocks showed an increase in higher heating value (HHV) and a significant reduction in ash content. Pellets produced from the solids met the requirements for industrial use, demonstrating a large increase in the deformation temperature and a significant reduction in the potassium and chlorine content compared to the original feedstock. These results indicate the excellent potential of these pellets for combustion applications.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020850&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020850&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:SAGE Publications Funded by:EC | URANUS, EC | BITSEC| URANUS ,EC| BITSAuthors: Kyriacos Theocharides; Charalambos Menelaou; Yiolanda Englezou; Stelios Timotheou;Kyriacos Theocharides; Charalambos Menelaou; Yiolanda Englezou; Stelios Timotheou;Traffic state estimation is a challenging task because of the collection of sparse and noisy measurements from fixed points in the traffic network. Induction loops, as they are non-intrusive, can observe any area of the traffic network on demand and provide accurate traffic density and speed measurements. Our main contribution is the development of an optimization framework where small parts of the traffic network are monitored by Unmanned Aerial Vehicles (UAVs) and accurate estimates of traffic density and mean speeds for every region in the traffic network are returned in real-time. Assuming regional-based traffic dynamics, a cyclical UAV flight path is defined for each region. One UAV is assigned to each flight path and monitors a small area of the region below. The UAV-based traffic measurements are expressed as moving averages to smooth out fluctuations in traffic density and mean speed. A moving horizon optimization problem is formulated, which minimizes the estimation and process errors over a moving time window. The problem is non-convex and challenging to solve, because of the presence of nonlinear traffic dynamics. By considering free-flow conditions, the optimization problem is recast to a quadratic program that returns density estimations for each region of the traffic network in real-time. Simulation results compare our UAV framework to an alternative, where the whole traffic network is monitored by UAVs. Both frameworks obtain similar results, despite the alternative framework using more UAVs than our framework.
Transportation Resea... arrow_drop_down Transportation Research Record Journal of the Transportation Research BoardArticle . 2024 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/03611981231213079&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Transportation Resea... arrow_drop_down Transportation Research Record Journal of the Transportation Research BoardArticle . 2024 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/03611981231213079&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | X5gonEC| X5gonSahan Bulathwela; María Pérez-Ortiz; Catherine Holloway; Mutlu Cukurova; John Shawe-Taylor;doi: 10.3390/su16020781
Artificial Intelligence (AI) in Education claims to have the potential for building personalised curricula, as well as bringing opportunities for democratising education and creating a renaissance of new ways of teaching and learning. Millions of students are starting to benefit from the use of these technologies, but millions more around the world are not, due to the digital divide and deep pre-existing social and educational inequalities. If this trend continues, the first large-scale delivery of AI in Education could lead to greater educational inequality, along with a global misallocation of educational resources motivated by the current techno-solutionist narrative, which proposes technological solutions as a quick and flawless way to solve complex real-world problems. This work focuses on posing questions about the future of AI in Education, intending to initiate the pressing conversation that could set the right foundations (e.g., inclusion and diversity) for a new generation of education that is permeated with AI technology. The main goal of our opinion piece is to conceptualise a sustainable, large-scale and inclusive AI for the education ecosystem that facilitates equitable, high-quality lifelong learning opportunities for all. The contribution starts by synthesising how AI might change how we learn and teach, focusing on the case of personalised learning companions and assistive technology for disability. Then, we move on to discuss some socio-technical features that will be crucial to avoiding the perils of these AI systems worldwide (and perhaps ensuring their success by leveraging more inclusive education). This work also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We emphasise the need for collectively designing human-centred, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as supporting new emerging pedagogies. Finally, we ask what it would take for this educational revolution to provide egalitarian and empowering access to education that transcends any political, cultural, language, geographical and learning-ability barriers, so that educational systems can be responsive to all learners’ needs.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020781&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020781&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 Switzerland, BelgiumPublisher:MDPI AG Funded by:EC | DuRSAAMEC| DuRSAAMIvana Krajnović; Anastasija Komkova; Bryan Barragán; Gérard Tardy; Léo Bos; Stijn Matthys;The repair of concrete structures is increasing in prevalence. Conventional repair mortars are expensive materials rich in Portland cement (PC) and other organic and inorganic components that question their economic efficiency and carbon footprint. Alkali-activated materials (AAMs) are an eco-friendly alternative to PC that possess properties desirable for repair mortars. The article presents the mix design, mechanical, bond, and shrinkage properties of alkali-activated binary mortars intended for structural concrete repair. Mix optimisation based on mechanical properties of repair mortar and utilisation of glass waste (GW) is presented together with total and restrained shrinkage, pull-off bond tests, and life cycle assessment (LCA) for selected configurations. Results demonstrate good compressive and flexural strength, exceeding 45 N/mm2 and 7 N/mm2, an excellent pull-off bond strength (1.8–2.3 N/mm2) of the alkali-activated mortar to the concrete substrate, in spite of extensive shrinkage, with an order of magnitude of a couple of thousands of microstrains, which is also reported. Shrinkage appears to increase with the increase of the applied GW in the mixture. LCA revealed that alkali-activated mortars have up to 54% lower CO2 eq. emissions compared to PC-based repair mortar. Sustainability, 16 (2) ISSN:2071-1050
Ghent University Aca... arrow_drop_down Ghent University Academic BibliographyArticle . 2024Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Ghent University Aca... arrow_drop_down Ghent University Academic BibliographyArticle . 2024Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Funded by:EC | HADRIANEC| HADRIANJoseba Sarabia; Mauricio Marcano; Sergio Díaz; Asier Zubizarreta; Joshué Pérez;doi: 10.3390/s24020562
Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop. Given this perspective, this paper presents and analyzes the results of a simulator-based study conducted to evaluate a shared control algorithm for a critical lateral maneuver. The maneuver involves the automated system helping to avoid an oncoming motorcycle that enters the vehicle’s lane. The study’s goal is to assess the algorithm’s performance, safety, and user acceptance within this specific scenario. For this purpose, objective measures, such as collision avoidance and lane departure prevention, as well as subjective measures related to the driver’s sense of safety and comfort are studied. In addition, three levels of assistance (gentle, intermediate, and aggressive) are tested in two driver state conditions (focused and distracted). The findings have important implications for the development and execution of shared control algorithms, paving the way for their incorporation into actual vehicles. This research is supported by the EU Commission HADRIAN project. HADRIAN has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875597. The publication is supported by the EU Commission Aware2All project, under grant agreement No 97878.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/s24020562&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/s24020562&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 ItalyPublisher:Springer Science and Business Media LLC Funded by:EC | IN2SMART2EC| IN2SMART2Alice Consilvio; Giulia Vignola; Paula López Arévalo; Federico Gallo; Marco Borinato; Carlo Crovetto;handle: 11567/1161241
AbstractThe application of artificial intelligence (AI) techniques may lead to significant improvements in different aspects of rail sector. Considering asset management and maintenance, AI can improve data analysis and asset status forecasting and decision-making processes, fostering predictive and prescriptive maintenance strategies. A prescriptive approach should be able to predict future scenarios as well as to suggest a course of actions. Nevertheless, the decision-making in rail asset management is often based on the classical asset-oriented approach, concentrating on the function of the asset itself as a main key performance indicator (KPI), whereas a user-oriented approach could lead to improved performance in terms of level of service. This paper is aimed at integrating the passengers’ perspective in the decision-making process for asset management to mitigate the impact that service interruptions may have on the final users. A data-driven prioritisation framework is developed to prioritise maintenance interventions taking into account asset status and criticality. In particular, a three-step approach is proposed, which focuses on the analysis of passenger data to evaluate the failure impact on the service, the analysis of alarms and anomalies to evaluate the asset status, and the suggestion of maintenance interventions. The proposed approach is applied to the maintenance of the metro line M5 in the Italian city of Milan. Results show the usefulness of the proposed approach to support infrastructure managers and maintenance operators in making decisions regarding the priority of maintenance activities, reducing the risk of critical failures and service interruptions.
European Transport R... arrow_drop_down European Transport Research ReviewArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12544-023-00631-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert European Transport R... arrow_drop_down European Transport Research ReviewArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12544-023-00631-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | SAFE-UPEC| SAFE-UPLars Schories; Nico Dahringer; Udo Piram; Anay Raut; Stella Nikolaou; Ioannis Gragkopoulos; Ioannis Tsetsinas; Maria Panou;doi: 10.3390/su16020610
The overall crash statistics in the EU still show a very significant number of car–cyclist crashes. Within the Horizon 2020 project Safe-Up, countermeasures have been developed to reduce this number. One of these countermeasures involves a V2X-enhanced on-board unit for cycles, which can provide on-time warning triggers. The research assumption was based on studying the benefits of connectivity in enhancing cyclists’ safety. This study assessed the performance of this potential technology both qualitatively by analyzing volunteer feedback during physical testing and quantitatively by virtual simulations. The volunteers’ study showed positive findings on system’s safety relevance, user experience, and user acceptance. The method applied for the virtual simulation is a prospective safety performance assessment with reconstructed accident scenarios based on the GIDAS database and cyclist behavior models, obtained from physical testing. The results using a warning trigger 4 s prior to the collision showed a potential safety benefit of approximately 98%. It should be noted that this trigger time was found to be quite early in both physical testing and virtual simulation. Further research is required to evaluate the system’s performance in more complex urban scenarios, as well as to design the human–machine interaction strategies for optimal accident avoidance.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020610&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020610&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Springer Science and Business Media LLC Funded by:EC | IN2TRACK2EC| IN2TRACK2Saikat Dutta; Tim Harrison; Christopher Ward; Roger Dixon; Phil Winship;AbstractThe main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment. This is important because, globally, railway track switches are used to allow trains to change routes; they are a key part of all railway networks. However, because track switches are single points of failure and safety-critical, their inability to operate correctly can cause significant delays and concomitant costs. In order to better understand the dynamic behaviour of switches during operation, this paper has developed a full simulation twin of a complete track switch system. The approach fuses finite element for the rail bending and motion, with physics-based models of the electromechanical actuator system and the control system. Hence, it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built. This is useful for looking at the modification or monitoring of existing switches, and it becomes even more important when new switch concepts are being considered and evaluated. The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively. The paper describes the modelling approach, demonstrates the methodology by developing the system model for a novel “REPOINT” switch system, and evaluates the system level performance against the dynamic performance requirements for the switch. In the context of that case study, it is found that the proposed new actuation system as designed can meet (and exceed) the system performance requirements, and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s40534-023-00324-2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s40534-023-00324-2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type 2024 GermanyPublisher:Copernicus GmbH Funded by:EC | EurofleetsPlus, NWO | The melting of the Greenl...EC| EurofleetsPlus ,NWO| The melting of the Greenland Ice Sheet and its impact on coastal ecosystemsJana Krause; Dustin Carroll; Juan Höfer; Jeremy Donaire; Eric Pieter Achterberg; Emilio Alarcón; Te Liu; Lorenz Meire; Kechen Zhu; Mark James Hopwood;Ice calved from the Antarctic and Greenland Ice Sheets or tidewater glaciers ultimately melts in the ocean contributing to sea-level rise. Icebergs have also been described as biological hotspots due to their potential roles as platforms for marine mammals and birds, and as micronutrient fertilizing agents. Icebergs may be especially important in the Southern Ocean where availability of the micronutrients iron and manganese extensively limits marine primary production. Whilst icebergs have long been described as a source of iron to the ocean, their nutrient signature is poorly constrained and it is unclear if there are regional differences. Here we show that 589 ice fragments collected from floating ice in contrasting regions spanning the Antarctic Peninsula, Greenland, and smaller tidewater systems in Svalbard, Patagonia and Iceland have similar characteristic (micro)nutrient signatures with limited or no significant differences between regions. Icebergs are a minor or negligible source of macronutrients to the ocean with low concentrations of NOx (NO3 + NO2, median 0.51 µM), PO4 (median 0.04 µM), and dissolved Si (dSi, median 0.02 µM). In contrast, icebergs deliver elevated concentrations of dissolved Fe (dFe; mean 82 nM, median 12 nM) and Mn (dMn; mean 26 nM, median 2.6 nM). A tight correlation between total dissolvable Fe and Mn (R2 = 0.95) and a Mn:Fe ratio of 0.024 suggested a lithogenic origin for the majority of sediment present in ice. Total dissolvable Fe and Mn retained a strong relationship with sediment load (both R2 = 0.43, p<0.001), whereas weaker relationships were observed for dFe, dMn and dSi. Sediment load for Antarctic ice (median 9 mg L-1, n=144) was low compared to prior reported values for the Arctic. A particularly curious incidental finding was that melting samples of ice were observed to rapidly lose their sediment load, even when sediment layers were embedded within the ice and stored in the dark. Our results demonstrated that the nutrient signature of icebergs is consistent with an atmospheric source of NOx and PO4. Conversely, high Fe and Mn, and modest dSi concentrations, are associated with englacial sediment, which experiences limited biogeochemical processing prior to release into the ocean.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5194/egusphere-2023-2991&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5194/egusphere-2023-2991&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 BelgiumPublisher:MDPI AG Funded by:EC | i-DREAMSEC| i-DREAMSStella Roussou; Thodoris Garefalakis; Eva Michelaraki; Tom Brijs; George Yannis;doi: 10.3390/su16020518
The i-DREAMS project has a core objective: to establish a comprehensive framework that defines, develops, and validates a context-aware 'Safety Tolerance Zone' (STZ). This zone is crucial for maintaining drivers within safe operational boundaries. The primary focus of this research is to conduct a detailed comparison between two machine learning approaches: long short-term memory networks and shallow neural networks. The goal is to evaluate the safety levels of participants as they engage in natural driving experiences within the i-DREAMS on-road field trials. To accomplish this objective, the study gathered a series of trips from a sample group consisting of 30 German drivers, 43 Belgian drivers, and 26 drivers from the United Kingdom. These trips were then input into the aforementioned machine learning methods to reveal the factors contributing to unsafe driving behaviour across various experiment stages. The results obtained highlight the significant positive impact of i-DREAMS' real-time interventions and post-trip assessments on enhancing driving behaviour. Furthermore, it is worth noting that neural networks demonstrated superior performance compared to other algorithms considered within this research context. The research was funded by the EU H2020 i-DREAMS project (Project Number: 814761) funded by the European Commission under the MG-2-1-2018 Research and Innovation Action (RIA).
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | F-CUBEDEC| F-CUBEDDouwe S. Zijlstra; Mark Visser; Esther Cobussen-Pool; Dennis J. Slort; Pavlina Nanou; Jan R. Pels; Heather E. Wray;doi: 10.3390/su16020850
The ever-increasing volumes of food waste generated and the associated environmental issues require the development of new processing methods for these difficult waste streams. One of the technologies that can treat these waste streams directly is hydrothermal carbonization. In this work, olive pomace and orange peels were treated via a mild hydrothermal carbonization process (TORWASH®) in a continuous-flow pilot plant. For olive pomace, a solid yield of 46 wt% and a dry matter content of 58% for the solid press cakes were obtained during continuous operation for 18 days. For orange peels, the values were lower with 31 wt% solid yield and a 42% dry matter content during 28 days of continuous operation. These values corresponded fully with initial laboratory-scale batch experiments, showing the successful transformation from batch to continuous processing. The obtained hydrochar from both feedstocks showed an increase in higher heating value (HHV) and a significant reduction in ash content. Pellets produced from the solids met the requirements for industrial use, demonstrating a large increase in the deformation temperature and a significant reduction in the potassium and chlorine content compared to the original feedstock. These results indicate the excellent potential of these pellets for combustion applications.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020850&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020850&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:SAGE Publications Funded by:EC | URANUS, EC | BITSEC| URANUS ,EC| BITSAuthors: Kyriacos Theocharides; Charalambos Menelaou; Yiolanda Englezou; Stelios Timotheou;Kyriacos Theocharides; Charalambos Menelaou; Yiolanda Englezou; Stelios Timotheou;Traffic state estimation is a challenging task because of the collection of sparse and noisy measurements from fixed points in the traffic network. Induction loops, as they are non-intrusive, can observe any area of the traffic network on demand and provide accurate traffic density and speed measurements. Our main contribution is the development of an optimization framework where small parts of the traffic network are monitored by Unmanned Aerial Vehicles (UAVs) and accurate estimates of traffic density and mean speeds for every region in the traffic network are returned in real-time. Assuming regional-based traffic dynamics, a cyclical UAV flight path is defined for each region. One UAV is assigned to each flight path and monitors a small area of the region below. The UAV-based traffic measurements are expressed as moving averages to smooth out fluctuations in traffic density and mean speed. A moving horizon optimization problem is formulated, which minimizes the estimation and process errors over a moving time window. The problem is non-convex and challenging to solve, because of the presence of nonlinear traffic dynamics. By considering free-flow conditions, the optimization problem is recast to a quadratic program that returns density estimations for each region of the traffic network in real-time. Simulation results compare our UAV framework to an alternative, where the whole traffic network is monitored by UAVs. Both frameworks obtain similar results, despite the alternative framework using more UAVs than our framework.
Transportation Resea... arrow_drop_down Transportation Research Record Journal of the Transportation Research BoardArticle . 2024 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/03611981231213079&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Transportation Resea... arrow_drop_down Transportation Research Record Journal of the Transportation Research BoardArticle . 2024 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1177/03611981231213079&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | X5gonEC| X5gonSahan Bulathwela; María Pérez-Ortiz; Catherine Holloway; Mutlu Cukurova; John Shawe-Taylor;doi: 10.3390/su16020781
Artificial Intelligence (AI) in Education claims to have the potential for building personalised curricula, as well as bringing opportunities for democratising education and creating a renaissance of new ways of teaching and learning. Millions of students are starting to benefit from the use of these technologies, but millions more around the world are not, due to the digital divide and deep pre-existing social and educational inequalities. If this trend continues, the first large-scale delivery of AI in Education could lead to greater educational inequality, along with a global misallocation of educational resources motivated by the current techno-solutionist narrative, which proposes technological solutions as a quick and flawless way to solve complex real-world problems. This work focuses on posing questions about the future of AI in Education, intending to initiate the pressing conversation that could set the right foundations (e.g., inclusion and diversity) for a new generation of education that is permeated with AI technology. The main goal of our opinion piece is to conceptualise a sustainable, large-scale and inclusive AI for the education ecosystem that facilitates equitable, high-quality lifelong learning opportunities for all. The contribution starts by synthesising how AI might change how we learn and teach, focusing on the case of personalised learning companions and assistive technology for disability. Then, we move on to discuss some socio-technical features that will be crucial to avoiding the perils of these AI systems worldwide (and perhaps ensuring their success by leveraging more inclusive education). This work also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We emphasise the need for collectively designing human-centred, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as supporting new emerging pedagogies. Finally, we ask what it would take for this educational revolution to provide egalitarian and empowering access to education that transcends any political, cultural, language, geographical and learning-ability barriers, so that educational systems can be responsive to all learners’ needs.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020781&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020781&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 Switzerland, BelgiumPublisher:MDPI AG Funded by:EC | DuRSAAMEC| DuRSAAMIvana Krajnović; Anastasija Komkova; Bryan Barragán; Gérard Tardy; Léo Bos; Stijn Matthys;The repair of concrete structures is increasing in prevalence. Conventional repair mortars are expensive materials rich in Portland cement (PC) and other organic and inorganic components that question their economic efficiency and carbon footprint. Alkali-activated materials (AAMs) are an eco-friendly alternative to PC that possess properties desirable for repair mortars. The article presents the mix design, mechanical, bond, and shrinkage properties of alkali-activated binary mortars intended for structural concrete repair. Mix optimisation based on mechanical properties of repair mortar and utilisation of glass waste (GW) is presented together with total and restrained shrinkage, pull-off bond tests, and life cycle assessment (LCA) for selected configurations. Results demonstrate good compressive and flexural strength, exceeding 45 N/mm2 and 7 N/mm2, an excellent pull-off bond strength (1.8–2.3 N/mm2) of the alkali-activated mortar to the concrete substrate, in spite of extensive shrinkage, with an order of magnitude of a couple of thousands of microstrains, which is also reported. Shrinkage appears to increase with the increase of the applied GW in the mixture. LCA revealed that alkali-activated mortars have up to 54% lower CO2 eq. emissions compared to PC-based repair mortar. Sustainability, 16 (2) ISSN:2071-1050
Ghent University Aca... arrow_drop_down Ghent University Academic BibliographyArticle . 2024Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Ghent University Aca... arrow_drop_down Ghent University Academic BibliographyArticle . 2024Data sources: Ghent University Academic Bibliographyadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020764&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Funded by:EC | HADRIANEC| HADRIANJoseba Sarabia; Mauricio Marcano; Sergio Díaz; Asier Zubizarreta; Joshué Pérez;doi: 10.3390/s24020562
Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop. Given this perspective, this paper presents and analyzes the results of a simulator-based study conducted to evaluate a shared control algorithm for a critical lateral maneuver. The maneuver involves the automated system helping to avoid an oncoming motorcycle that enters the vehicle’s lane. The study’s goal is to assess the algorithm’s performance, safety, and user acceptance within this specific scenario. For this purpose, objective measures, such as collision avoidance and lane departure prevention, as well as subjective measures related to the driver’s sense of safety and comfort are studied. In addition, three levels of assistance (gentle, intermediate, and aggressive) are tested in two driver state conditions (focused and distracted). The findings have important implications for the development and execution of shared control algorithms, paving the way for their incorporation into actual vehicles. This research is supported by the EU Commission HADRIAN project. HADRIAN has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875597. The publication is supported by the EU Commission Aware2All project, under grant agreement No 97878.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/s24020562&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/s24020562&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 ItalyPublisher:Springer Science and Business Media LLC Funded by:EC | IN2SMART2EC| IN2SMART2Alice Consilvio; Giulia Vignola; Paula López Arévalo; Federico Gallo; Marco Borinato; Carlo Crovetto;handle: 11567/1161241
AbstractThe application of artificial intelligence (AI) techniques may lead to significant improvements in different aspects of rail sector. Considering asset management and maintenance, AI can improve data analysis and asset status forecasting and decision-making processes, fostering predictive and prescriptive maintenance strategies. A prescriptive approach should be able to predict future scenarios as well as to suggest a course of actions. Nevertheless, the decision-making in rail asset management is often based on the classical asset-oriented approach, concentrating on the function of the asset itself as a main key performance indicator (KPI), whereas a user-oriented approach could lead to improved performance in terms of level of service. This paper is aimed at integrating the passengers’ perspective in the decision-making process for asset management to mitigate the impact that service interruptions may have on the final users. A data-driven prioritisation framework is developed to prioritise maintenance interventions taking into account asset status and criticality. In particular, a three-step approach is proposed, which focuses on the analysis of passenger data to evaluate the failure impact on the service, the analysis of alarms and anomalies to evaluate the asset status, and the suggestion of maintenance interventions. The proposed approach is applied to the maintenance of the metro line M5 in the Italian city of Milan. Results show the usefulness of the proposed approach to support infrastructure managers and maintenance operators in making decisions regarding the priority of maintenance activities, reducing the risk of critical failures and service interruptions.
European Transport R... arrow_drop_down European Transport Research ReviewArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12544-023-00631-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert European Transport R... arrow_drop_down European Transport Research ReviewArticle . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12544-023-00631-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:MDPI AG Funded by:EC | SAFE-UPEC| SAFE-UPLars Schories; Nico Dahringer; Udo Piram; Anay Raut; Stella Nikolaou; Ioannis Gragkopoulos; Ioannis Tsetsinas; Maria Panou;doi: 10.3390/su16020610
The overall crash statistics in the EU still show a very significant number of car–cyclist crashes. Within the Horizon 2020 project Safe-Up, countermeasures have been developed to reduce this number. One of these countermeasures involves a V2X-enhanced on-board unit for cycles, which can provide on-time warning triggers. The research assumption was based on studying the benefits of connectivity in enhancing cyclists’ safety. This study assessed the performance of this potential technology both qualitatively by analyzing volunteer feedback during physical testing and quantitatively by virtual simulations. The volunteers’ study showed positive findings on system’s safety relevance, user experience, and user acceptance. The method applied for the virtual simulation is a prospective safety performance assessment with reconstructed accident scenarios based on the GIDAS database and cyclist behavior models, obtained from physical testing. The results using a warning trigger 4 s prior to the collision showed a potential safety benefit of approximately 98%. It should be noted that this trigger time was found to be quite early in both physical testing and virtual simulation. Further research is required to evaluate the system’s performance in more complex urban scenarios, as well as to design the human–machine interaction strategies for optimal accident avoidance.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020610&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020610&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Springer Science and Business Media LLC Funded by:EC | IN2TRACK2EC| IN2TRACK2Saikat Dutta; Tim Harrison; Christopher Ward; Roger Dixon; Phil Winship;AbstractThe main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment. This is important because, globally, railway track switches are used to allow trains to change routes; they are a key part of all railway networks. However, because track switches are single points of failure and safety-critical, their inability to operate correctly can cause significant delays and concomitant costs. In order to better understand the dynamic behaviour of switches during operation, this paper has developed a full simulation twin of a complete track switch system. The approach fuses finite element for the rail bending and motion, with physics-based models of the electromechanical actuator system and the control system. Hence, it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built. This is useful for looking at the modification or monitoring of existing switches, and it becomes even more important when new switch concepts are being considered and evaluated. The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively. The paper describes the modelling approach, demonstrates the methodology by developing the system model for a novel “REPOINT” switch system, and evaluates the system level performance against the dynamic performance requirements for the switch. In the context of that case study, it is found that the proposed new actuation system as designed can meet (and exceed) the system performance requirements, and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s40534-023-00324-2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s40534-023-00324-2&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type 2024 GermanyPublisher:Copernicus GmbH Funded by:EC | EurofleetsPlus, NWO | The melting of the Greenl...EC| EurofleetsPlus ,NWO| The melting of the Greenland Ice Sheet and its impact on coastal ecosystemsJana Krause; Dustin Carroll; Juan Höfer; Jeremy Donaire; Eric Pieter Achterberg; Emilio Alarcón; Te Liu; Lorenz Meire; Kechen Zhu; Mark James Hopwood;Ice calved from the Antarctic and Greenland Ice Sheets or tidewater glaciers ultimately melts in the ocean contributing to sea-level rise. Icebergs have also been described as biological hotspots due to their potential roles as platforms for marine mammals and birds, and as micronutrient fertilizing agents. Icebergs may be especially important in the Southern Ocean where availability of the micronutrients iron and manganese extensively limits marine primary production. Whilst icebergs have long been described as a source of iron to the ocean, their nutrient signature is poorly constrained and it is unclear if there are regional differences. Here we show that 589 ice fragments collected from floating ice in contrasting regions spanning the Antarctic Peninsula, Greenland, and smaller tidewater systems in Svalbard, Patagonia and Iceland have similar characteristic (micro)nutrient signatures with limited or no significant differences between regions. Icebergs are a minor or negligible source of macronutrients to the ocean with low concentrations of NOx (NO3 + NO2, median 0.51 µM), PO4 (median 0.04 µM), and dissolved Si (dSi, median 0.02 µM). In contrast, icebergs deliver elevated concentrations of dissolved Fe (dFe; mean 82 nM, median 12 nM) and Mn (dMn; mean 26 nM, median 2.6 nM). A tight correlation between total dissolvable Fe and Mn (R2 = 0.95) and a Mn:Fe ratio of 0.024 suggested a lithogenic origin for the majority of sediment present in ice. Total dissolvable Fe and Mn retained a strong relationship with sediment load (both R2 = 0.43, p<0.001), whereas weaker relationships were observed for dFe, dMn and dSi. Sediment load for Antarctic ice (median 9 mg L-1, n=144) was low compared to prior reported values for the Arctic. A particularly curious incidental finding was that melting samples of ice were observed to rapidly lose their sediment load, even when sediment layers were embedded within the ice and stored in the dark. Our results demonstrated that the nutrient signature of icebergs is consistent with an atmospheric source of NOx and PO4. Conversely, high Fe and Mn, and modest dSi concentrations, are associated with englacial sediment, which experiences limited biogeochemical processing prior to release into the ocean.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5194/egusphere-2023-2991&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 BelgiumPublisher:MDPI AG Funded by:EC | i-DREAMSEC| i-DREAMSStella Roussou; Thodoris Garefalakis; Eva Michelaraki; Tom Brijs; George Yannis;doi: 10.3390/su16020518
The i-DREAMS project has a core objective: to establish a comprehensive framework that defines, develops, and validates a context-aware 'Safety Tolerance Zone' (STZ). This zone is crucial for maintaining drivers within safe operational boundaries. The primary focus of this research is to conduct a detailed comparison between two machine learning approaches: long short-term memory networks and shallow neural networks. The goal is to evaluate the safety levels of participants as they engage in natural driving experiences within the i-DREAMS on-road field trials. To accomplish this objective, the study gathered a series of trips from a sample group consisting of 30 German drivers, 43 Belgian drivers, and 26 drivers from the United Kingdom. These trips were then input into the aforementioned machine learning methods to reveal the factors contributing to unsafe driving behaviour across various experiment stages. The results obtained highlight the significant positive impact of i-DREAMS' real-time interventions and post-trip assessments on enhancing driving behaviour. Furthermore, it is worth noting that neural networks demonstrated superior performance compared to other algorithms considered within this research context. The research was funded by the EU H2020 i-DREAMS project (Project Number: 814761) funded by the European Commission under the MG-2-1-2018 Research and Innovation Action (RIA).
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020518&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16020518&type=result"></script>'); --> </script>
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