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description Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:Elsevier BV Authors: José M. Liñeira del Río; Enriqueta R. López; Josefa Fernández;José M. Liñeira del Río; Enriqueta R. López; Josefa Fernández;handle: 10347/32147
Antifriction and antiwear performances of Al2O3 nanoparticles (NPs) as additives of an automatic transmission fluid, ATF, are presented in this research. For this purpose, four nanodispersions were formulated: ATF + 0.05 wt% Al2O3 NPs, ATF + 0.10 wt% Al2O3 NPs, ATF + 0.15 wt% Al2O3 NPs and ATF + 0.20 wt% Al2O3 NPs to identify the optimal concentration of additive. Tribological experiments were taken at pure sliding conditions, with the formulated nanolubricants and the ATF, under a working load of 20 N. The four nanolubricants tested resulted in lower friction coefficients than those obtained using ATF, reaching a maximum reduction of 6 % with the ATF + 0.10 wt% Al2O3 nanolubricant. The tribological pairs tested with the Al2O3 nanolubricants show lower wear than those tested with the ATF, having the best wear decrease with the ATF + 0.10 wt% Al2O3 nanolubricant, with reductions of 45, 57 and 78 %, respectively, in diameter, depth and area of the wear scar. Furthermore, by means of confocal Raman microscopy, roughness evaluation and SEM-EDX of the worn tribological specimens, it can be determined that mending, tribo-sintering as well as rolling mechanisms occur. This research is supported by Xunta de Galicia (ED431C 2020/10) and by MCIN/AEI/10.13039/501100011033 through the PID2020-112846RB-C22 project. JMLdR is grateful for financial support through the Margarita Salas program, funded by MCIN/AEI/10.13039/501100011033 and “NextGenerationEU/PRTR”. Furthermore, authors are also grateful to Repsol Lubricants for providing the ATF and to RIAIDT-USC for its analytical facilities. SI
Journal of Molecular... arrow_drop_down Minerva. Repositorio Institucional da Universidade de Santiago de CompostelaArticle . 2024License: CC BY NC NDadd 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=10.1016/j.molliq.2024.124036&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 Journal of Molecular... arrow_drop_down Minerva. Repositorio Institucional da Universidade de Santiago de CompostelaArticle . 2024License: CC BY NC NDadd 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=10.1016/j.molliq.2024.124036&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:Elsevier BV Authors: Daniel Castro Medina; MCarmen Guerrero Delgado; José Sánchez Ramos; Teresa Palomo Amores; +2 AuthorsDaniel Castro Medina; MCarmen Guerrero Delgado; José Sánchez Ramos; Teresa Palomo Amores; Laura Romero Rodríguez; Servando Álvarez Domínguez;The growing impact of climate change, including extreme weather events, represents a significant challenge for humanity. With most of the world's population living in urban areas, the urban heat island effect and anthropogenic heat contribute to elevated city temperatures. This increase in urban warming threatens human health and demands a deeper understanding of thermal distribution in urban environments. Collecting accessible and widespread temperature data in urban areas is essential to address this challenge. This study aims to develop a methodology for anticipating temperature distribution in urban environments, leveraging Citizen Weather Stations (CWS) as valuable crowdsourcing data sources. The ultimate goal is to create a predictive model that estimates urban temperatures based on government meteorological station forecasts, improving urban planning, regulating temperature-based routes, preventing health issues in vulnerable populations, and enhancing urban livability. The methodology is divided into three fundamental stages: data acquisition through CWS with citizen collaboration, the development and evaluation of optimal forecast models based on government weather stations (SWS) data, and its exploitation in terms of utility and applicability. This methodology encompasses data collection and filtering to ensure its usefulness and implement reliable models. The resulting tool facilitates informed decision-making and precise seasonal event planning in urban environments, effectively addressing the challenges of climate extrapolation and contributing to more effective adaptation and mitigation strategies in climate change and heatwaves. The results obtained probe the feasibility of using CWS to predict temperatures in urban environments, which has been demonstrated accurately. This is a significant achievement, as CWS has proven to be a reliable source of climate data for this context. Also, the filtering process described and applied to the case study has proven effective, discarding approximately 34.87 % of the data. This is achieved by detecting and eliminating anomalies, considering station availability, and adhering to specific quality criteria. Finally, the developed prediction model has demonstrated its ability to optimally estimate urban temperatures, utilizing climate prediction data provided by government weather stations (SWS). The model performance indicators support this claim. For the linear regression model, a Mean Squared Error (MSE) of 2.177 and an R-squared (R2) of 0.960 are obtained, while for the neural network, an MSE of 1.284 and an R2 of 0.976 are achieved.
idUS. Depósito de In... arrow_drop_down Sustainable Cities and SocietyArticle . 2024 . Peer-reviewedLicense: CC BY NCData 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=10.1016/j.scs.2024.105208&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 idUS. Depósito de In... arrow_drop_down Sustainable Cities and SocietyArticle . 2024 . Peer-reviewedLicense: CC BY NCData 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=10.1016/j.scs.2024.105208&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Authors: Santiago Criollo-C; Andrea Guerrero-Arias; Javier Guaña-Moya; Agariadne Dwinggo Samala; +1 AuthorsSantiago Criollo-C; Andrea Guerrero-Arias; Javier Guaña-Moya; Agariadne Dwinggo Samala; Sergio Luján-Mora;doi: 10.3390/su16031192
handle: 10045/140228
Over the years, educational institutions have faced significant difficulties in the teaching process at all educational levels, due to lack of motivation, concentration, attention, and confidence, among other aspects. In this sense, information and communication technologies can be the answer to transform educational models. One of the most promising and accessible technologies in recent years is mobile augmented reality (MAR), which allows students to visualize content through a mobile device combining the real environment with a virtual environment, providing an interactive and digital vision of the physical world in real time. The appropriate use of digital technologies in early childhood and primary education can promote socialization, comprehension, learning, language development, attention, and other educational benefits. However, due to the novelty of this technology, there is limited research and a gap in the literature on the use of MAR at these educational levels. This research work, through systematic mapping, aims to give an overview of how AR and mobile devices have been used in the last decade, which academic areas have benefited from the use of this innovative academic approach, and the main benefits and problems of using this technology in early and primary education. The findings are encouraging and show that AR technology, together with mobile devices, can be used to support the teaching of science, mathematics, reading, language, geography, etc. This work was financed by the Universidad de Las Américas through project code: TIC.LCC.22.01.
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/su16031192&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/su16031192&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2024 SpainPublisher:MDPI AG Ahmed Faris Amiri; Sofiane Kichou; Houcine Oudira; Aissa Chouder; Santiago Silvestre;doi: 10.3390/su16031012
handle: 2117/400474
The meticulous monitoring and diagnosis of faults in photovoltaic (PV) systems enhances their reliability and facilitates a smooth transition to sustainable energy. This paper introduces a novel application of deep learning for fault detection and diagnosis in PV systems, employing a three-step approach. Firstly, a robust PV model is developed and fine-tuned using a heuristic optimization approach. Secondly, a comprehensive database is constructed, incorporating PV model data alongside monitored module temperature and solar irradiance for both healthy and faulty operation conditions. Lastly, fault classification utilizes features extracted from a combination consisting of a Convolutional Neural Network (CNN) and Bidirectional Gated Recurrent Unit (Bi-GRU). The amalgamation of parallel and sequential processing enables the neural network to leverage the strengths of both convolutional and recurrent layers concurrently, facilitating effective fault detection and diagnosis. The results affirm the proposed technique’s efficacy in detecting and classifying various PV fault types, such as open circuits, short circuits, and partial shading. Furthermore, this work underscores the significance of dividing fault detection and diagnosis into two distinct steps rather than employing deep learning neural networks to determine fault types directly. Peer Reviewed
UPCommons. Portal de... arrow_drop_down UPCommons. Portal del coneixement obert de la UPCOther literature type . 2024 . Peer-reviewedLicense: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCadd 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/su16031012&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 UPCommons. Portal de... arrow_drop_down UPCommons. Portal del coneixement obert de la UPCOther literature type . 2024 . Peer-reviewedLicense: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCadd 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/su16031012&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 Netherlands, Germany, SpainPublisher:Wiley Phillip J. Haubrock; Ismael Soto; Melina Kourantidou; Danish A. Ahmed; Ali Serhan Tarkan; Paride Balzani; Kristi Bego; Antonín Kouba; Sadi Aksu; Elizabeta Briski; Francisco Sylvester; Vanessa De Santis; Gaït Archambaud‐Suard; Núria Bonada; Miguel Cañedo‐Argüelles; Zoltán Csabai; Thibault Datry; Mathieu Floury; Jean‐François Fruget; John Iwan Jones; Marie‐Helene Lizee; Anthony Maire; John F. Murphy; Davis Ozolins; Jes Jessen Rasmussen; Agnija Skuja; Gábor Várbíró; Piet Verdonschot; Ralf C. M. Verdonschot; Peter Wiberg‐Larsen; Ross N. Cuthbert;doi: 10.1111/oik.10283
handle: 10261/344206
The zebra mussel Dreissena polymorpha is one of the most successful, notorious, and detrimental aquatic invasive non-native species worldwide, having invaded Europe and North America while causing substantial ecological and socio-economic impacts. Here, we investigated the spatiotemporal trends in this species' invasion success using 178 macroinvertebrate abundance time series, containing 1451 records of D. polymorpha collected across nine European countries between 1972–2019. Using these raw (absolute) abundance data, we examined trends and drivers of occurrences and relative abundances of D. polymorpha within invaded communities. Meta-regression models revealed non-significant trends both at the European level and for the majority of the invaded countries, except for France (significant decreasing trend) and Hungary (marginally positive trend). At the European level, the number of D. polymorpha occurrences over time followed a flat-top bell-shaped distribution, with a steep increase between 1973–1989 followed by a plateau phase prior to significantly declining post-1998. Using a series of climatic and hydromorphological site-specific characteristics of invaded and uninvaded sites from two periods (1998–2002; 2011–2015), we found that native richness, non-native abundance, distance to the next barrier, and elevation were associated with the occurrence of D. polymorpha. We also found that higher native richness and lower latitude were related to lower relative abundances. Using Cohen's D as a measure of D. polymorpha impact, we found that biodiversity within the invaded sites was initially higher than in uninvaded ones, but then declined, suggesting differences in biodiversity trends across invaded and uninvaded sites. While our results emphasise the high invasion success of D. polymorpha, increasing stressors within the context of global change – particularly ongoing climate change – are likely to enhance invasion rates and the impact of D. polymorpha in the near future, exacerbated by the lack of timely and effective management actions. – PJH received funding from the EU Horizon 2020 project eLTER PLUS (Grand agreement no. 871128). RNC is funded by the Leverhulme Trust (ECF-2021-001). This study was supported by the Grant Agency of the University of South Bohemia, project no. 065/2022/Z. MC was supported by a Ramón y Cajal contract funded by the Spanish Ministry of Science and Innovation (RYC2020-029829-I). Peer reviewed
OceanRep arrow_drop_down Research@WUR; OikosOther literature type . Article . 2024 . Peer-reviewedLicense: Wiley Online Library User Agreementadd 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=10.1111/oik.10283&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 OceanRep arrow_drop_down Research@WUR; OikosOther literature type . Article . 2024 . Peer-reviewedLicense: Wiley Online Library User Agreementadd 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=10.1111/oik.10283&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 SpainPublisher:MDPI AG Reza Naimaee; Abbas Kiani; Sina Jarahizadeh; Seyed Babak Haji Seyed Asadollah; Pablo Melgarejo; Antonio Jodar-Abellan;doi: 10.3390/su16020646
handle: 10045/139762
Thermal pollution reduces water quality through any process that leads to a change in the water’s ambient temperature. Karun is one of the most relevant sources of water supply in Iran, and its pollution, created by industrial, urban, and agricultural issues, has been one of the most critical challenges throughout the last few years. As the water temperature rises, the amount of dissolved oxygen in it decreases, thereby affecting the entire ecosystem associated with it. Drainage of urban and industrial runoff into surface water sources can increase the water temperature. Dams also constitute a significant part, modifying spatial patterns of temperature along river routes and causing thermal contamination. In this paper, the thermal pollution of the Karun River was assessed, and regions along this river with unusually raised water temperatures were identified and compared over 20 years. By analyzing the results, it can be found that the thermal pollution from dams has a significant impact on the downstream river environment and ecology that is considerably relevant during summer periods, showing average decreases of 3 degrees Celsius immediately beyond the dams’ locations (from 41 degrees Celsius upstream dams to 38 degrees Celsius beyond them) or even bigger (reductions of 13 degrees Celsius in one of the studied dams). Hence, our results showed that water temperature is colder downstream in the hot seasons of the year than upstream of the dams. The results suggest that the usage of remote sensing data effectively could complement collected data from ground-based sensors to estimate water temperature and to identify pollution areas. It provides experts with spatially extensive and highly synchronized data.
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/su16020646&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/su16020646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Authors: Cristina Villanueva-Díaz; Milagros Álvarez-Sanz; Álvaro Campos-Celador; Jon Terés-Zubiaga;Cristina Villanueva-Díaz; Milagros Álvarez-Sanz; Álvaro Campos-Celador; Jon Terés-Zubiaga;doi: 10.3390/su16020652
Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance of buildings on an urban scale, in order to evaluate the impact of these improvements. In this regard, the data collection for feeding building energy models plays a key role in the accuracy and reliability of this issue, and the significant increase in recent years of available data from open data sources offers great potential in this respect. Thus, this study focuses on proposing a systematised and automated method for obtaining information from open data sources so as to obtain the most relevant geometric and thermal characteristics of residential buildings on an urban scale. The criteria for selecting the parameters to be obtained are based on their potential use as input data in different energy demand models aimed at assessing the energy performance of the building stock in a given area and, eventually, to evaluate the potential for improvement and the mitigation of different strategies. Geometric characterisation relies on obtaining and processing open data from cadastres to extract envelope surfaces categorised by orientation through QGIS (Free and Open Source Geographic Information System). For thermal characterisation, an automated process assigns different parameter-based information obtained from cadastral data, such as the year of construction. Finally, the applicability of the method is demonstrated through its implementation in the case study of Bilbao (Spain). The obtained results show that, although additional data should be collected when a detailed analysis of a building or building cluster has to be carried out, the existing open data can provide a first approximation, providing a first global view of the building stock in a region. It demonstrates the usability of the proposed method as an effective way to obtain and process these relevant data. The work presented in this paper was carried out within the EnePoMAP Project that was funded by “La Caixa” Foundation under the project code LCF/PR/SR20/52550013. The recruitment of the Author Cristina Villanueva-Díaz was funded by the European Union-Next Generation EU. The author Milagros Álvarez-Sanz is benefiting from the financial support of the University of the Basque Country (UPV-EHU), through the Vice-Rectorate of Research’s Personnel Research Training Program (2020). The publication fees of the paper were funded by the organisation of the 14th edition of the International Conference on Energy Efficiency and Sustainability in Architecture and Urbanism (EESAP 14), through a prize awarded to the material of this publication in recognition of the best communication submitted to the congress.
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/su16020652&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/su16020652&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Doctoral thesis 2024 Spain EnglishPublisher:Universitat de Girona Authors: Cañigueral Maurici, Marc;Cañigueral Maurici, Marc;handle: 10803/689718
La transició a la mobilitat elèctrica s’enfronta a múltiples reptes, generalment associats amb el desplegament de la infraestructura de càrrega. D’una banda, les ciutats han de desenvolupar una infraestructura de càrrega que satisfaci les necessitats dels usuaris, mentre que el tipus d’usuaris de vehicles elèctrics (VE) són específics per a cada àrea de càrrega. D’altra banda, una alta demanda de VE en el sistema d’energia pot portar problemes de congestió a la xarxa elèctrica de baixa tensió i això pot implicar problemes en la qualitat del subministrament elèctric i una barrera per a un major desenvolupament de la infraestructura de càrrega. Aquesta tesi pretén proporcionar eines per resoldre els reptes plantejats en les dues etapes de l’adopció de la mobilitat elèctrica. Amb aquest objectiu, es proposa una metodologia per agrupar i modelar perfils d’usuari genèrics de VEs basats en patrons de connexió, la qual s’aplica en dues àrees clau: gestió de la flexibilitat i planificació d’infraestructures de càrrega. El concepte de perfils d’usuari s’introdueix com una eina per identificar patrons de connexió comuns amb un potencial de flexibilitat característic. Una metodologia d’agrupament que utilitza Models Mixtos Gaussians (MMG) s’aplica basant-se en variables com l’hora d’inici i la durada de la connexió. S’observen patrons d’ús comuns en la infraestructura de càrrega pública, proporcionant informació sobre el comportament dels usuaris de VEs. La metodologia d’elaboració de perfils es valida amb tres conjunts de dades reals de sessions de càrrega juntament amb els tres articles de revista que configuren el nucli d’aquesta tesi. La metodologia d’agrupació és seguida per una metodologia de modelatge per realitzar simulacions estocàstiques de les sessions de càrrega del VE en termes de temps de connexió, energia requerida i potència de càrrega. Modelar cada perfil d’usuari independentment permet simular una àmplia gamma d’escenaris, ja que la presència de cada perfil d’usuari sobre la demanda total del VE es pot configurar segons l’entorn, és a dir, la ubicació, l’horitzó temporal, etc. Aquesta aplicació s’explora amb dos articles de revista on es simulen escenaris amb alta penetració de sessions de VE per (1) dimensionar de manera òptima una àrea de càrrega i (2) analitzar el nombre requerit de punts de càrrega a nivell de ciutat. En ambdues contribucions, la configuració de perfils d’usuari en àrees específiques és crucial per un dimensionament adequat de la infraestructura de càrrega, evitant costos addicionals que perjudiquin el model de negoci o la pèrdua de confiança dels usuaris del VE amb instal·lacions sotadimensionades. Aquesta tesi també compara diferents estratègies de càrrega intel·ligent a través de simulacions, així com els beneficis que l’enfocament de perfilat d’usuaris podria aportar als programes de càrrega intel·ligents. Quan es programen sessions individuals d’acord amb una consigna de demanda agregada, el coneixement addicional de perfils de VE poden proporcionar informació per a una predicció de flexibilitat més fiable. A més, les sessions de programació dels perfils seleccionats podrien conduir a un estalvi de costos d’explotació i a una reducció de l’impacte sobre els usuaris de VEs. Finalment, l’aplicació d’un programa de càrrega intel·ligent a nivell de ciutat amb alta penetració de VEs també s’ha simulat per analitzar el seu impacte en totes les parts interessades implicades en el sector de càrrega del VE, des de l’usuari final fins al model de negoci del gestor de càrrega. Una limitació de la potència de càrrega basada en senyals de capacitat dinàmica resulta eficaç per evitar la congestió de la xarxa i ajornar millores en la xarxa elèctrica existent mentre s’expandeix la infraestructura de càrrega i es subministra la majoria de l’energia requerida pels usuaris de VEs. En general, aquesta tesi millora la comprensió del comportament de l’usuari de VE, analitza diferents estratègies de càrrega intel·ligents i proporciona informació per a la planificació de la infraestructura de càrrega. Aquests resultats tenen implicacions pràctiques per a les parts implicades en l’ecosistema del VE, contribuint a la transició cap a la mobilitat elèctrica. The transition to electric mobility is facing multiple challenges, usually associated with the roll-out of the charging infrastructure. On one hand, cities must develop a charging infrastructure that meets the user needs while the type of electric vehicle (EV) users is specific for every charging area. On the other hand, a high EV demand in the power system can bring congestion issues at the low-voltage power grid and this can involve power supply quality issues and a barrier to further development of the charging infrastructure. This thesis aims to provide tools to solve the challenges raised in both stages of the adoption of electric mobility. With this purpose, a methodology to cluster and model generic EV user profiles based on connection patterns is proposed and applied to these two key areas: flexibility management and charging infrastructure planning. The concept of user profiles is introduced as a tool to identify common connection patterns with a characteristic flexibility potential. A clustering methodology using Gaussian Mixture Models (GMM) is applied based on variables such as connection start time and duration. Common usage patterns in public charging infrastructure are observed, providing insights into EV user behaviour. The profiling methodology is validated with three different real data sets of charging sessions along with the three journal articles that shape the core of this thesis. The clustering methodology is followed by a modelling methodology to perform stochastic simulations of EV charging sessions in terms of connection times, required energy and charging power rate. Modelling every user profile independently lets to simulate a wide range of scenarios since the share of each user profile over the total EV demand can be configured according to the environment (i.e. location, time horizon, etc.). This application is explored with two journal articles where scenarios with high penetration of EV sessions are simulated to (1) optimally size a charging hub and (2) analyse the required number of charging points of city-level charging infrastructure. In both contributions, the configuration of user profiles in specific areas is crucial for properly sizing charging infrastructure, avoiding extra costs that harm the business model or losing EV users’ confidence with undersized installations. This thesis also compares different smart charging strategies through simulations, as well as the benefits that the user-profile approach could bring to smart charging programs. When scheduling individual sessions according to an aggregated demand setpoint, the extra knowledge of profiling EV users beforehand can provide insights for a more reliable flexibility prediction. Moreover, scheduling sessions from selected user profiles could lead to exploitation cost savings and reduced impact on EV users. Finally, the application of a smart charging program at the city level with high penetration of EVs has been also simulated to analyse its impact on all stakeholders involved in the EV charging sector, from the final EV user to the charging operator business model. Curtailing charging power based on dynamic capacity signals proves effective to avoid grid congestion and defer reinforcements of the existing power grid while expanding the charging infrastructure and supplying the majority of the energy required by EV users. Overall, this thesis enhances understanding of EV user behaviour, analyses different smart charging strategies, and provides insights for charging infrastructure planning. These findings have practical implications for stakeholders involved in the EV ecosystem, contributing to the ongoing transition to electric mobility. Programa de Doctorat en Tecnologia
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Authors: José Rey-García; María-Araceli Calvo-Serrano; Francisco de Paula Montes-Tubío; Elena Bellido-Vela; +1 AuthorsJosé Rey-García; María-Araceli Calvo-Serrano; Francisco de Paula Montes-Tubío; Elena Bellido-Vela; Paula Triviño-Tarradas;doi: 10.3390/su16020541
handle: 10396/26576
On the 550th anniversary of the introduction of the printing press to Spain, it is planned to review this art. Through a literature review, we studied how the printing press has contributed to the dissemination and preservation of cultural and industrial heritage, which are key for knowledge dissemination. The main objective of this study was to characterize the Spanish printing press of the 17th century through the analysis of an etching by Stradanus, relating it to the founding of the first typographic workshops in the rural Andalusian territory, and studying, for the first time, the specific case of Montilla. No scientific research has been carried out so far on this specific case. It was a region of utmost importance in Andalusia at the time due to its relations with the Spanish monarchy. The development of the printing press from inception until today is also analyzed to study the evolution of this type of industry in relation to the times. The printing press was key for the dissemination of culture and knowledge in the Modern Age. It was used to produce books, documents, and etchings, which are key elements for the dissemination of knowledge and the preservation of human heritage. This research has allowed us to comprehend and analyze, for the first time, the process of establishing the printing press in the case of Montilla coinciding with the 450th anniversary of the founding of the first printing press in Spain. This manuscript contributes to the achievement of some of the objectives of the Sustainable Development Goals (SDGs), protecting and disseminating the heritage of the typographic industry in Montilla-Moriles.
Helvia. Repositorio ... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:Elsevier BV Authors: José M. Liñeira del Río; Enriqueta R. López; Josefa Fernández;José M. Liñeira del Río; Enriqueta R. López; Josefa Fernández;handle: 10347/32147
Antifriction and antiwear performances of Al2O3 nanoparticles (NPs) as additives of an automatic transmission fluid, ATF, are presented in this research. For this purpose, four nanodispersions were formulated: ATF + 0.05 wt% Al2O3 NPs, ATF + 0.10 wt% Al2O3 NPs, ATF + 0.15 wt% Al2O3 NPs and ATF + 0.20 wt% Al2O3 NPs to identify the optimal concentration of additive. Tribological experiments were taken at pure sliding conditions, with the formulated nanolubricants and the ATF, under a working load of 20 N. The four nanolubricants tested resulted in lower friction coefficients than those obtained using ATF, reaching a maximum reduction of 6 % with the ATF + 0.10 wt% Al2O3 nanolubricant. The tribological pairs tested with the Al2O3 nanolubricants show lower wear than those tested with the ATF, having the best wear decrease with the ATF + 0.10 wt% Al2O3 nanolubricant, with reductions of 45, 57 and 78 %, respectively, in diameter, depth and area of the wear scar. Furthermore, by means of confocal Raman microscopy, roughness evaluation and SEM-EDX of the worn tribological specimens, it can be determined that mending, tribo-sintering as well as rolling mechanisms occur. This research is supported by Xunta de Galicia (ED431C 2020/10) and by MCIN/AEI/10.13039/501100011033 through the PID2020-112846RB-C22 project. JMLdR is grateful for financial support through the Margarita Salas program, funded by MCIN/AEI/10.13039/501100011033 and “NextGenerationEU/PRTR”. Furthermore, authors are also grateful to Repsol Lubricants for providing the ATF and to RIAIDT-USC for its analytical facilities. SI
Journal of Molecular... arrow_drop_down Minerva. Repositorio Institucional da Universidade de Santiago de CompostelaArticle . 2024License: CC BY NC NDadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 Journal of Molecular... arrow_drop_down Minerva. Repositorio Institucional da Universidade de Santiago de CompostelaArticle . 2024License: CC BY NC NDadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 SpainPublisher:Elsevier BV Authors: Daniel Castro Medina; MCarmen Guerrero Delgado; José Sánchez Ramos; Teresa Palomo Amores; +2 AuthorsDaniel Castro Medina; MCarmen Guerrero Delgado; José Sánchez Ramos; Teresa Palomo Amores; Laura Romero Rodríguez; Servando Álvarez Domínguez;The growing impact of climate change, including extreme weather events, represents a significant challenge for humanity. With most of the world's population living in urban areas, the urban heat island effect and anthropogenic heat contribute to elevated city temperatures. This increase in urban warming threatens human health and demands a deeper understanding of thermal distribution in urban environments. Collecting accessible and widespread temperature data in urban areas is essential to address this challenge. This study aims to develop a methodology for anticipating temperature distribution in urban environments, leveraging Citizen Weather Stations (CWS) as valuable crowdsourcing data sources. The ultimate goal is to create a predictive model that estimates urban temperatures based on government meteorological station forecasts, improving urban planning, regulating temperature-based routes, preventing health issues in vulnerable populations, and enhancing urban livability. The methodology is divided into three fundamental stages: data acquisition through CWS with citizen collaboration, the development and evaluation of optimal forecast models based on government weather stations (SWS) data, and its exploitation in terms of utility and applicability. This methodology encompasses data collection and filtering to ensure its usefulness and implement reliable models. The resulting tool facilitates informed decision-making and precise seasonal event planning in urban environments, effectively addressing the challenges of climate extrapolation and contributing to more effective adaptation and mitigation strategies in climate change and heatwaves. The results obtained probe the feasibility of using CWS to predict temperatures in urban environments, which has been demonstrated accurately. This is a significant achievement, as CWS has proven to be a reliable source of climate data for this context. Also, the filtering process described and applied to the case study has proven effective, discarding approximately 34.87 % of the data. This is achieved by detecting and eliminating anomalies, considering station availability, and adhering to specific quality criteria. Finally, the developed prediction model has demonstrated its ability to optimally estimate urban temperatures, utilizing climate prediction data provided by government weather stations (SWS). The model performance indicators support this claim. For the linear regression model, a Mean Squared Error (MSE) of 2.177 and an R-squared (R2) of 0.960 are obtained, while for the neural network, an MSE of 1.284 and an R2 of 0.976 are achieved.
idUS. Depósito de In... arrow_drop_down Sustainable Cities and SocietyArticle . 2024 . Peer-reviewedLicense: CC BY NCData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 idUS. Depósito de In... arrow_drop_down Sustainable Cities and SocietyArticle . 2024 . Peer-reviewedLicense: CC BY NCData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 SpainPublisher:MDPI AG Authors: Santiago Criollo-C; Andrea Guerrero-Arias; Javier Guaña-Moya; Agariadne Dwinggo Samala; +1 AuthorsSantiago Criollo-C; Andrea Guerrero-Arias; Javier Guaña-Moya; Agariadne Dwinggo Samala; Sergio Luján-Mora;doi: 10.3390/su16031192
handle: 10045/140228
Over the years, educational institutions have faced significant difficulties in the teaching process at all educational levels, due to lack of motivation, concentration, attention, and confidence, among other aspects. In this sense, information and communication technologies can be the answer to transform educational models. One of the most promising and accessible technologies in recent years is mobile augmented reality (MAR), which allows students to visualize content through a mobile device combining the real environment with a virtual environment, providing an interactive and digital vision of the physical world in real time. The appropriate use of digital technologies in early childhood and primary education can promote socialization, comprehension, learning, language development, attention, and other educational benefits. However, due to the novelty of this technology, there is limited research and a gap in the literature on the use of MAR at these educational levels. This research work, through systematic mapping, aims to give an overview of how AR and mobile devices have been used in the last decade, which academic areas have benefited from the use of this innovative academic approach, and the main benefits and problems of using this technology in early and primary education. The findings are encouraging and show that AR technology, together with mobile devices, can be used to support the teaching of science, mathematics, reading, language, geography, etc. This work was financed by the Universidad de Las Américas through project code: TIC.LCC.22.01.
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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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article 2024 SpainPublisher:MDPI AG Ahmed Faris Amiri; Sofiane Kichou; Houcine Oudira; Aissa Chouder; Santiago Silvestre;doi: 10.3390/su16031012
handle: 2117/400474
The meticulous monitoring and diagnosis of faults in photovoltaic (PV) systems enhances their reliability and facilitates a smooth transition to sustainable energy. This paper introduces a novel application of deep learning for fault detection and diagnosis in PV systems, employing a three-step approach. Firstly, a robust PV model is developed and fine-tuned using a heuristic optimization approach. Secondly, a comprehensive database is constructed, incorporating PV model data alongside monitored module temperature and solar irradiance for both healthy and faulty operation conditions. Lastly, fault classification utilizes features extracted from a combination consisting of a Convolutional Neural Network (CNN) and Bidirectional Gated Recurrent Unit (Bi-GRU). The amalgamation of parallel and sequential processing enables the neural network to leverage the strengths of both convolutional and recurrent layers concurrently, facilitating effective fault detection and diagnosis. The results affirm the proposed technique’s efficacy in detecting and classifying various PV fault types, such as open circuits, short circuits, and partial shading. Furthermore, this work underscores the significance of dividing fault detection and diagnosis into two distinct steps rather than employing deep learning neural networks to determine fault types directly. Peer Reviewed
UPCommons. Portal de... arrow_drop_down UPCommons. Portal del coneixement obert de la UPCOther literature type . 2024 . Peer-reviewedLicense: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 UPCommons. Portal de... arrow_drop_down UPCommons. Portal del coneixement obert de la UPCOther literature type . 2024 . Peer-reviewedLicense: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCadd 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 Netherlands, Germany, SpainPublisher:Wiley Phillip J. Haubrock; Ismael Soto; Melina Kourantidou; Danish A. Ahmed; Ali Serhan Tarkan; Paride Balzani; Kristi Bego; Antonín Kouba; Sadi Aksu; Elizabeta Briski; Francisco Sylvester; Vanessa De Santis; Gaït Archambaud‐Suard; Núria Bonada; Miguel Cañedo‐Argüelles; Zoltán Csabai; Thibault Datry; Mathieu Floury; Jean‐François Fruget; John Iwan Jones; Marie‐Helene Lizee; Anthony Maire; John F. Murphy; Davis Ozolins; Jes Jessen Rasmussen; Agnija Skuja; Gábor Várbíró; Piet Verdonschot; Ralf C. M. Verdonschot; Peter Wiberg‐Larsen; Ross N. Cuthbert;doi: 10.1111/oik.10283
handle: 10261/344206
The zebra mussel Dreissena polymorpha is one of the most successful, notorious, and detrimental aquatic invasive non-native species worldwide, having invaded Europe and North America while causing substantial ecological and socio-economic impacts. Here, we investigated the spatiotemporal trends in this species' invasion success using 178 macroinvertebrate abundance time series, containing 1451 records of D. polymorpha collected across nine European countries between 1972–2019. Using these raw (absolute) abundance data, we examined trends and drivers of occurrences and relative abundances of D. polymorpha within invaded communities. Meta-regression models revealed non-significant trends both at the European level and for the majority of the invaded countries, except for France (significant decreasing trend) and Hungary (marginally positive trend). At the European level, the number of D. polymorpha occurrences over time followed a flat-top bell-shaped distribution, with a steep increase between 1973–1989 followed by a plateau phase prior to significantly declining post-1998. Using a series of climatic and hydromorphological site-specific characteristics of invaded and uninvaded sites from two periods (1998–2002; 2011–2015), we found that native richness, non-native abundance, distance to the next barrier, and elevation were associated with the occurrence of D. polymorpha. We also found that higher native richness and lower latitude were related to lower relative abundances. Using Cohen's D as a measure of D. polymorpha impact, we found that biodiversity within the invaded sites was initially higher than in uninvaded ones, but then declined, suggesting differences in biodiversity trends across invaded and uninvaded sites. While our results emphasise the high invasion success of D. polymorpha, increasing stressors within the context of global change – particularly ongoing climate change – are likely to enhance invasion rates and the impact of D. polymorpha in the near future, exacerbated by the lack of timely and effective management actions. – PJH received funding from the EU Horizon 2020 project eLTER PLUS (Grand agreement no. 871128). RNC is funded by the Leverhulme Trust (ECF-2021-001). This study was supported by the Grant Agency of the University of South Bohemia, project no. 065/2022/Z. MC was supported by a Ramón y Cajal contract funded by the Spanish Ministry of Science and Innovation (RYC2020-029829-I). Peer reviewed
OceanRep arrow_drop_down Research@WUR; OikosOther literature type . Article . 2024 . Peer-reviewedLicense: Wiley Online Library User Agreementadd ClaimPlease grant OpenAIRE to access and update your ORCID works.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 OceanRep arrow_drop_down Research@WUR; OikosOther literature type . Article . 2024 . Peer-reviewedLicense: Wiley Online Library User Agreementadd 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 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.
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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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Reza Naimaee; Abbas Kiani; Sina Jarahizadeh; Seyed Babak Haji Seyed Asadollah; Pablo Melgarejo; Antonio Jodar-Abellan;doi: 10.3390/su16020646
handle: 10045/139762
Thermal pollution reduces water quality through any process that leads to a change in the water’s ambient temperature. Karun is one of the most relevant sources of water supply in Iran, and its pollution, created by industrial, urban, and agricultural issues, has been one of the most critical challenges throughout the last few years. As the water temperature rises, the amount of dissolved oxygen in it decreases, thereby affecting the entire ecosystem associated with it. Drainage of urban and industrial runoff into surface water sources can increase the water temperature. Dams also constitute a significant part, modifying spatial patterns of temperature along river routes and causing thermal contamination. In this paper, the thermal pollution of the Karun River was assessed, and regions along this river with unusually raised water temperatures were identified and compared over 20 years. By analyzing the results, it can be found that the thermal pollution from dams has a significant impact on the downstream river environment and ecology that is considerably relevant during summer periods, showing average decreases of 3 degrees Celsius immediately beyond the dams’ locations (from 41 degrees Celsius upstream dams to 38 degrees Celsius beyond them) or even bigger (reductions of 13 degrees Celsius in one of the studied dams). Hence, our results showed that water temperature is colder downstream in the hot seasons of the year than upstream of the dams. The results suggest that the usage of remote sensing data effectively could complement collected data from ground-based sensors to estimate water temperature and to identify pollution areas. It provides experts with spatially extensive and highly synchronized data.
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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Authors: Cristina Villanueva-Díaz; Milagros Álvarez-Sanz; Álvaro Campos-Celador; Jon Terés-Zubiaga;Cristina Villanueva-Díaz; Milagros Álvarez-Sanz; Álvaro Campos-Celador; Jon Terés-Zubiaga;doi: 10.3390/su16020652
Energy renovation in buildings is one of the major challenges for the decarbonisation of the building stock. To effectively prioritise decision making regarding the adoption of the most efficient solutions and strategies, it is imperative to develop agile methods to determine the energy performance of buildings on an urban scale, in order to evaluate the impact of these improvements. In this regard, the data collection for feeding building energy models plays a key role in the accuracy and reliability of this issue, and the significant increase in recent years of available data from open data sources offers great potential in this respect. Thus, this study focuses on proposing a systematised and automated method for obtaining information from open data sources so as to obtain the most relevant geometric and thermal characteristics of residential buildings on an urban scale. The criteria for selecting the parameters to be obtained are based on their potential use as input data in different energy demand models aimed at assessing the energy performance of the building stock in a given area and, eventually, to evaluate the potential for improvement and the mitigation of different strategies. Geometric characterisation relies on obtaining and processing open data from cadastres to extract envelope surfaces categorised by orientation through QGIS (Free and Open Source Geographic Information System). For thermal characterisation, an automated process assigns different parameter-based information obtained from cadastral data, such as the year of construction. Finally, the applicability of the method is demonstrated through its implementation in the case study of Bilbao (Spain). The obtained results show that, although additional data should be collected when a detailed analysis of a building or building cluster has to be carried out, the existing open data can provide a first approximation, providing a first global view of the building stock in a region. It demonstrates the usability of the proposed method as an effective way to obtain and process these relevant data. The work presented in this paper was carried out within the EnePoMAP Project that was funded by “La Caixa” Foundation under the project code LCF/PR/SR20/52550013. The recruitment of the Author Cristina Villanueva-Díaz was funded by the European Union-Next Generation EU. The author Milagros Álvarez-Sanz is benefiting from the financial support of the University of the Basque Country (UPV-EHU), through the Vice-Rectorate of Research’s Personnel Research Training Program (2020). The publication fees of the paper were funded by the organisation of the 14th edition of the International Conference on Energy Efficiency and Sustainability in Architecture and Urbanism (EESAP 14), through a prize awarded to the material of this publication in recognition of the best communication submitted to the congress.
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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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Doctoral thesis 2024 Spain EnglishPublisher:Universitat de Girona Authors: Cañigueral Maurici, Marc;Cañigueral Maurici, Marc;handle: 10803/689718
La transició a la mobilitat elèctrica s’enfronta a múltiples reptes, generalment associats amb el desplegament de la infraestructura de càrrega. D’una banda, les ciutats han de desenvolupar una infraestructura de càrrega que satisfaci les necessitats dels usuaris, mentre que el tipus d’usuaris de vehicles elèctrics (VE) són específics per a cada àrea de càrrega. D’altra banda, una alta demanda de VE en el sistema d’energia pot portar problemes de congestió a la xarxa elèctrica de baixa tensió i això pot implicar problemes en la qualitat del subministrament elèctric i una barrera per a un major desenvolupament de la infraestructura de càrrega. Aquesta tesi pretén proporcionar eines per resoldre els reptes plantejats en les dues etapes de l’adopció de la mobilitat elèctrica. Amb aquest objectiu, es proposa una metodologia per agrupar i modelar perfils d’usuari genèrics de VEs basats en patrons de connexió, la qual s’aplica en dues àrees clau: gestió de la flexibilitat i planificació d’infraestructures de càrrega. El concepte de perfils d’usuari s’introdueix com una eina per identificar patrons de connexió comuns amb un potencial de flexibilitat característic. Una metodologia d’agrupament que utilitza Models Mixtos Gaussians (MMG) s’aplica basant-se en variables com l’hora d’inici i la durada de la connexió. S’observen patrons d’ús comuns en la infraestructura de càrrega pública, proporcionant informació sobre el comportament dels usuaris de VEs. La metodologia d’elaboració de perfils es valida amb tres conjunts de dades reals de sessions de càrrega juntament amb els tres articles de revista que configuren el nucli d’aquesta tesi. La metodologia d’agrupació és seguida per una metodologia de modelatge per realitzar simulacions estocàstiques de les sessions de càrrega del VE en termes de temps de connexió, energia requerida i potència de càrrega. Modelar cada perfil d’usuari independentment permet simular una àmplia gamma d’escenaris, ja que la presència de cada perfil d’usuari sobre la demanda total del VE es pot configurar segons l’entorn, és a dir, la ubicació, l’horitzó temporal, etc. Aquesta aplicació s’explora amb dos articles de revista on es simulen escenaris amb alta penetració de sessions de VE per (1) dimensionar de manera òptima una àrea de càrrega i (2) analitzar el nombre requerit de punts de càrrega a nivell de ciutat. En ambdues contribucions, la configuració de perfils d’usuari en àrees específiques és crucial per un dimensionament adequat de la infraestructura de càrrega, evitant costos addicionals que perjudiquin el model de negoci o la pèrdua de confiança dels usuaris del VE amb instal·lacions sotadimensionades. Aquesta tesi també compara diferents estratègies de càrrega intel·ligent a través de simulacions, així com els beneficis que l’enfocament de perfilat d’usuaris podria aportar als programes de càrrega intel·ligents. Quan es programen sessions individuals d’acord amb una consigna de demanda agregada, el coneixement addicional de perfils de VE poden proporcionar informació per a una predicció de flexibilitat més fiable. A més, les sessions de programació dels perfils seleccionats podrien conduir a un estalvi de costos d’explotació i a una reducció de l’impacte sobre els usuaris de VEs. Finalment, l’aplicació d’un programa de càrrega intel·ligent a nivell de ciutat amb alta penetració de VEs també s’ha simulat per analitzar el seu impacte en totes les parts interessades implicades en el sector de càrrega del VE, des de l’usuari final fins al model de negoci del gestor de càrrega. Una limitació de la potència de càrrega basada en senyals de capacitat dinàmica resulta eficaç per evitar la congestió de la xarxa i ajornar millores en la xarxa elèctrica existent mentre s’expandeix la infraestructura de càrrega i es subministra la majoria de l’energia requerida pels usuaris de VEs. En general, aquesta tesi millora la comprensió del comportament de l’usuari de VE, analitza diferents estratègies de càrrega intel·ligents i proporciona informació per a la planificació de la infraestructura de càrrega. Aquests resultats tenen implicacions pràctiques per a les parts implicades en l’ecosistema del VE, contribuint a la transició cap a la mobilitat elèctrica. The transition to electric mobility is facing multiple challenges, usually associated with the roll-out of the charging infrastructure. On one hand, cities must develop a charging infrastructure that meets the user needs while the type of electric vehicle (EV) users is specific for every charging area. On the other hand, a high EV demand in the power system can bring congestion issues at the low-voltage power grid and this can involve power supply quality issues and a barrier to further development of the charging infrastructure. This thesis aims to provide tools to solve the challenges raised in both stages of the adoption of electric mobility. With this purpose, a methodology to cluster and model generic EV user profiles based on connection patterns is proposed and applied to these two key areas: flexibility management and charging infrastructure planning. The concept of user profiles is introduced as a tool to identify common connection patterns with a characteristic flexibility potential. A clustering methodology using Gaussian Mixture Models (GMM) is applied based on variables such as connection start time and duration. Common usage patterns in public charging infrastructure are observed, providing insights into EV user behaviour. The profiling methodology is validated with three different real data sets of charging sessions along with the three journal articles that shape the core of this thesis. The clustering methodology is followed by a modelling methodology to perform stochastic simulations of EV charging sessions in terms of connection times, required energy and charging power rate. Modelling every user profile independently lets to simulate a wide range of scenarios since the share of each user profile over the total EV demand can be configured according to the environment (i.e. location, time horizon, etc.). This application is explored with two journal articles where scenarios with high penetration of EV sessions are simulated to (1) optimally size a charging hub and (2) analyse the required number of charging points of city-level charging infrastructure. In both contributions, the configuration of user profiles in specific areas is crucial for properly sizing charging infrastructure, avoiding extra costs that harm the business model or losing EV users’ confidence with undersized installations. This thesis also compares different smart charging strategies through simulations, as well as the benefits that the user-profile approach could bring to smart charging programs. When scheduling individual sessions according to an aggregated demand setpoint, the extra knowledge of profiling EV users beforehand can provide insights for a more reliable flexibility prediction. Moreover, scheduling sessions from selected user profiles could lead to exploitation cost savings and reduced impact on EV users. Finally, the application of a smart charging program at the city level with high penetration of EVs has been also simulated to analyse its impact on all stakeholders involved in the EV charging sector, from the final EV user to the charging operator business model. Curtailing charging power based on dynamic capacity signals proves effective to avoid grid congestion and defer reinforcements of the existing power grid while expanding the charging infrastructure and supplying the majority of the energy required by EV users. Overall, this thesis enhances understanding of EV user behaviour, analyses different smart charging strategies, and provides insights for charging infrastructure planning. These findings have practical implications for stakeholders involved in the EV ecosystem, contributing to the ongoing transition to electric mobility. Programa de Doctorat en Tecnologia
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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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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SpainPublisher:MDPI AG Authors: José Rey-García; María-Araceli Calvo-Serrano; Francisco de Paula Montes-Tubío; Elena Bellido-Vela; +1 AuthorsJosé Rey-García; María-Araceli Calvo-Serrano; Francisco de Paula Montes-Tubío; Elena Bellido-Vela; Paula Triviño-Tarradas;doi: 10.3390/su16020541
handle: 10396/26576
On the 550th anniversary of the introduction of the printing press to Spain, it is planned to review this art. Through a literature review, we studied how the printing press has contributed to the dissemination and preservation of cultural and industrial heritage, which are key for knowledge dissemination. The main objective of this study was to characterize the Spanish printing press of the 17th century through the analysis of an etching by Stradanus, relating it to the founding of the first typographic workshops in the rural Andalusian territory, and studying, for the first time, the specific case of Montilla. No scientific research has been carried out so far on this specific case. It was a region of utmost importance in Andalusia at the time due to its relations with the Spanish monarchy. The development of the printing press from inception until today is also analyzed to study the evolution of this type of industry in relation to the times. The printing press was key for the dissemination of culture and knowledge in the Modern Age. It was used to produce books, documents, and etchings, which are key elements for the dissemination of knowledge and the preservation of human heritage. This research has allowed us to comprehend and analyze, for the first time, the process of establishing the printing press in the case of Montilla coinciding with the 450th anniversary of the founding of the first printing press in Spain. This manuscript contributes to the achievement of some of the objectives of the Sustainable Development Goals (SDGs), protecting and disseminating the heritage of the typographic industry in Montilla-Moriles.
Helvia. Repositorio ... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.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 Helvia. Repositorio ... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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