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Methodology to Assess the Level of Service and Resilience of Rural Roads in Italian Seismic Zones: Challenges and Strategies for Improvement
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.This study investigates the level of service (LOS) and level of resilience (LOR) of rural road transport infrastructures in Italian seismic zones, focusing on their unique vulnerabilities and the implications for local populations. Italy’s rural road network, characterized by its age and issues associated, faces significant challenges, especially during and after extreme events like seismic events, landslides, floodings and others. High travel times on these roads are exacerbated by frequent closures due to these extreme events induced damages, severely impacting accessibility. This research applies a new methodology to analyse the current LOS and LOR, highlighting the extended travel times and the roads’ inability to efficiently accommodate traffic flow as during normal conditions. Additionally, the study assesses the LOR, considering the duration and impact of road closures on community access to essential services, such as hospitals and workplaces. Using a combination of historical records, and resilience metrics, the study identifies critical weaknesses in the rural road network’s response and recovery capabilities.Peer reviewe
Interplay of magnetocrystalline and magnetoelastic anisotropy in epitaxial Co(10 1¯ 0) films
No full textPublisher Copyright: © 2025 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.With the goal of creating an in-plane (IP) uniaxial anisotropy system, we deposited a thickness series of epitaxial Co(101¯0) films grown on Si(110) substrates with Ag(110) and Cr(211) buffer layers by magnetron sputtering. However, quantifying the IP magnetic anisotropy using ferromagnetic resonance measurements revealed a much more complex behavior than expected for a simple uniaxial system like hexagonally close-packed (hcp) Co. To understand the experimental results, an in-depth x-ray diffraction analysis of the film structure was performed. Even at a thickness of 100 nm, it revealed an anisotropic strain in the Co films, mainly within the Co basal plane, while the c axis remained mostly unaffected. Calculations show that such unrelaxed strain induces a significant magnetoelastic anisotropy, which counteracts the magnetocrystalline one and, as a result, reduces the overall effective anisotropy. A detailed analysis revealed that mainly the compressive strain along the Co[101¯0] out-of-plane direction is responsible for the observed magnetoelastic anisotropy, while the tensile strain along the Co[1¯21¯0] IP direction only plays a minor role.Peer reviewe
A Modern Roman-Inspired Concrete with Daytime Radiative Cooling Capacity
Get PDFPublisher Copyright: © 2025 The Author(s). Advanced Science published by Wiley-VCH GmbH.Addressing global warming through the modernization of buildings and urban areas is a major challenge. Passive daytime radiative cooling (PDRC) materials offer potential solutions, but none have effectively replaced concrete's dominant role in urban environments. Here, a Roman-inspired concrete with PDRC capabilities is presented, combining high solar reflectance (≈0.95) and long-wave infrared (LWIR) emittance (≈0.91). It delivers cooling powers over 45 W m−2 under average solar intensities of 850 W m−2 without a convection shield. On hot days (above 30°C), it stays 2°C cooler than the surrounding air under solar irradiance up to 985 W m−2. Simulations predict this concrete can reduce energy use and CO2 emissions by ≈50% in hot regions and lower urban surface temperatures by up to 10°C during heat waves. This breakthrough offers a cheap, scalable and sustainable solution for energy efficiency and climate resilience.Peer reviewe
Methodology for Identifying Mesoscale Weather Patterns from High-Dimensional Climate Datasets
No full textPublisher Copyright: © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.We develop a new methodology to solve the problem of identifying and selecting mesoscale weather patterns (MWPs) from high-dimensional spatio-temporal climate datasets. This problem is important and topical and has many implications for decision-makers across multiple sectors, such as urban design, urban climate, agriculture, transportation, energy, and disaster management. This problem involves selecting a small subset of data (specific days) from the original large dataset (decades long), such that it captures the essential information and characteristics of the large dataset, while minimizing redundancy. This is useful as it makes the dataset more manageable for processing, analysis, and insight gathering without degrading the overall quality of the information content. We develop a novel algorithm that is based on advanced machine learning and optimization techniques and consists of two stages: (1) spatial dimensionality reduction (SDR) to reduce the number of spatial cells analyzed while preserving as much relevant information as possible and (2) representative subset selection (RSS) to find a small subset of days in the dataset that captures the essential patterns, relationships, and information present in the full dataset—these are the mesoscale weather patterns. We demonstrate our methodology by applying it to a spatio-temporal dataset of atmospheric observations, the ERA5 dataset, in Singapore. The MWPs offer valuable insights into the region’s diverse weather conditions and help researchers, climatologists, and policymakers comprehend the complex interactions between atmospheric elements.Peer reviewe
Upright Posture: A Singular Condition Stabilizing Sensorimotor Coordination
Get PDFPublisher Copyright: © 2025 Vandergooten et al.It has long been hypothesized that the nervous system uses the direction of gravity to align the various sensory systems when interacting with the external world. In line with this hypothesis, systematic drift in hand-path orientation was recently observed during targeted arm motions performed with eyes closed in weightlessness or, on Earth, for longitudinal movements in a supine posture. No such drift was observed in upright posture on Earth. But the precise conditions under which participants exhibit such drift, and the factors that influence the magnitude of the drift, are not yet known. The objective of our study was to investigate if the upright posture, by virtue of being at a biomechanical singularity induced by the force of gravity, represents a unique condition in which drift in hand-path orientation is prevented. Human participants (male and female) performed sequences of repeated point-to-point arm movements between two visual targets aligned with the longitudinal body axis, first with eyes open, then with eyes closed. Participants performed these movements in various body orientations: seated upright, and tilted backward at 45, 90, and 135°. We observed drift in hand-path orientation in the eyes-closed condition when the body was tilted, but not when it was upright. The directions and rates of drift were indistinguishable between the three tilted orientations tested (45, 90, and 135°). These findings support the hypothesis that the upright posture is a unique configuration that facilitates sensorimotor transformations and prevents drift in path orientation when the eyes are closed.Peer reviewe
An approach based on machine learning and mel-frequency cepstral coefficients for locating faults in transmission lines
No full textPublisher Copyright: © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.Faults in transmission lines may cause great loss to users and managers of electric power systems. Thus, it’s important making the process of locating these faults more efficient, in order to repair them as quickly as possible. In this study, mel-frequency cepstral coefficients were used for processing voltage signals collected on both transmission line terminals during faults, along with an machine learning (ML) model, responsible for locating faults. Different ML models were tested: artificial neural network (ANN), support vector machine and least squares support vector regression, among which was noticed that ANN had the best overall result, processing all simulations. A modeled line based on parameters of a real line was also used. The proposed method provided results with high precision in locating faults in environments without noise, with mean relative error of 0.00004% and mean absolute error of 0.13 ms. Subsequently, the influences of training dataset size, noise, fault’s types, fault’s resistances, fault’s angles and fault’s distances in the location method were evaluated through the results of the best ANN architecture. The proposed method was still able to detect the faults quickly and precisely, even with small size of the data set and/or different signal to noise ratio. These results indicate that the proposed procedure is a good alternative for fault location in LT in practical scenarios.Peer reviewe
Spanish Embassy in LondonRefuge for English Catholics. Anne Jay (1586-1661)
No full textPublisher Copyright: © 2025, Universitat Jaume I. All rights reserved.Hispanic embassy in London played a critical role during 17th century, not only regarding the diplomatic relationship with the English crown but also as a reference for English Catholicism. Thus, many English Catholics were hosted and sheltered by the Spanish delegation involving both names of the social elite and people of humble origins. This study aims at illustrating how Spanish ambassadors influenced this latter social group through the profile of Anne Jay as a case study. She represents a paradigmatic case of an English Catholic whose fate was tightly bound to the ambassadors’ intervention and the own destiny of the Embassy.Peer reviewe
Operational Performance of an MVHR System in a Retrofitted Heritage Dwelling: Indoor Air Quality, Efficiency and Duct Constraints
Get PDFPublisher Copyright: © 2025 by the authors.The integration of Mechanical Ventilation with Heat Recovery (MVHR) systems into heritage buildings poses a series of challenges, largely attributable to architectural constraints and conservation requirements. The present study offers an operational campaign of an MVHR system installed during the energy retrofit of a protected residential heritage dwelling in Vitoria-Gasteiz, Spain. Although environmental monitoring was carried out throughout the year, representative spring, autumn and winter days of continuous operation were analysed, as the occupants frequently avoided using the system due to noise perception. This limitation highlights the importance of considering acoustic comfort and user acceptance as critical factors in the long-term viability of MVHR in heritage contexts. The system was assessed under real-life conditions using continuous environmental monitoring, with a focus on indoor air quality (IAQ), thermal efficiency, airflow balance, and pressure losses. Despite the acceptable mean apparent thermal effectiveness (0.74) and total useful efficiency (0.96), the system’s performance was found to be constrained by significant flow imbalance (up to 106%) and elevated pressure drops, which were attributed to the legacy of the duct geometry. The results obtained demonstrate IAQ improved overall, with mean CO2 concentrations below ~650 ppm across the analysed dataset; however, daily means occasionally exceeded 900–1000 ppm during high-occupancy periods and in the absence of spatially distributed demand control. These exceedances are consistent with the measured outdoor baseline (~400–450 ppm) and reflect the need for post-commissioning balancing and room-level sensing to sustain Category II performance in heritage dwellings. This study provides empirical evidence on the limitations and opportunities of MVHR deployment in historic retrofits, thus informing future guidelines for sustainable interventions in heritage contexts.Peer reviewe
Lowering Transport Environmental Impact Along the Whole Life Cycle of the Future Transport Infrastructure: LIAISON
Get PDFPublisher Copyright: © The Author(s) 2025.Liaison Horizon Europe Project provides knowledge and technical solutions to limit transport infrastructures (TI) emissions, both caused by transport infrastructure itself and to which transport infrastructure contributes. This project covers the whole life cycle of TI to which extent TI design can influence and limit the overall emissions from construction, maintenance, operation and decommissioning of the infrastructure in a digital environment for next future TI. Liaison adopts a holistic approach to tackle this challenge, because the development of particular technical solutions is not sufficient to achieve low environmental impact TI if they are not part of a broader strategy. The only effective way to ensure the implementation of paradigm-shifting technical solutions in the TI sector is to implement a governance framework (Dynamic Multi-Infrastructure Governance Framework -DMIGF) that activates, articulates, and monitors compliance with circular economy principles throughout the life of the infrastructure when developing and implementing these solutions. Liaison develops smart and sustainable beams, rigid road pavements and improved ballast; bio-asphalt and smart pavement inspection system; intelligent tunnel control system and photovoltaic guardrails.Peer reviewe
Comparative Benchmark of Sampling-Based and DRL Motion Planning Methods for Industrial Robotic Arms
Get PDFPublisher Copyright: © 2025 by the authors.This study presents a comprehensive comparison between classical sampling-based motion planners from the Open Motion Planning Library (OMPL) and a learning-based planner based on Soft Actor–Critic (SAC) for motion planning in industrial robotic arms. Using a UR3e robot equipped with an RG2 gripper, we constructed a large-scale dataset of over 100,000 collision-free trajectories generated with MoveIt-integrated OMPL planners. These trajectories were used to train a DRL agent via curriculum learning and expert demonstrations. Both approaches were evaluated on key metrics such as planning time, success rate, and trajectory smoothness. Results show that the DRL-based planner achieves higher success rates and significantly lower planning times, producing more compact and deterministic trajectories. Time-optimal parameterization using TOPPRA ensured the dynamic feasibility of all trajectories. While classical planners retain advantages in zero-shot adaptability and environmental generality, our findings highlight the potential of DRL for real-time and high-throughput motion planning in industrial contexts. This work provides practical insights into the trade-offs between traditional and learning-based planning paradigms, paving the way for hybrid architectures that combine their strengths.Peer reviewe