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Clasificación de Procedimientos de Ataques de Ciberseguridad mediante Generación Aumentada por Recuperación
No full textPublisher Copyright: © 2025 Sociedad Española para el Procesamiento del Lenguaje NaturalUnderstanding the tactics (why), techniques (how) and procedures (methods) behind a cybersecurity attack is paramount to develop defenses against them or to mitigate their effects. However, this task requires a high-level of technical expertise, is time-consuming and error prone. In this work we verify that open-source Llama 3.1 LLMs (Large Language Models) cannot automatically identify which of the 625 MITRE techniques is used within a cybersecurity attack procedure. We evaluate two RAG (Retrieval Augmented Generation) approaches to enhance the classification accuracy. Our experiments show the importance of the embedding model in information retrieval. Moreover, our analysis shows that selecting appropriate examples helps the language model reduce ambiguity. Specifically, a dynamic few-shot learning strategy performs best for larger models, whereas a multiple-choice strategy is more appropriate for smaller models. In contrast, corrective RAG techniques fail to provide significant enhancements, highlighting current methodological limitations and the inherent complexity of this task.Peer reviewe
Towards a new taxonomy of infrastructures: Implications for resilience
No full textPublisher Copyright: © 2025 IEEE.Socio-ecological systems experience cascading effects across multiple infrastructure levels during disaster response. These effects often involve not only a shift in the use of certain infrastructures, such as switching from highways to secondary roads, but also a repurposing of existing infrastructures. For example, when an energy pipeline is blocked, energy delivery may shift to delivery by road transport. This flexibility is a key aspect of resilience and should be anticipated in resilience strategies. Traditionally, infrastructure taxonomies have been based on function. However, this paper proposes a new taxonomy grounded in structural commonalities, focusing on the concept of 'linear transport' of essential resources - energy, water, and information - between nodes. All such infrastructures share the movement of goods, control mechanisms at nodes, and a driving force enabling transport. The proposed taxonomy distinguishes between infrastructures that move discrete elements along defined paths (such as roads and railways) and those that enable continuous flows (such as pipelines and power lines). Evidence from anthropology and archaeology supports this structural perspective. This novel classification provides a clearer understanding of infrastructure interdependencies and cascading effects, offering valuable insights for enhancing disaster resilience and response strategies.Peer reviewe
The fruits of data shepherding: A collection of open FAIR datasets for titanium dioxide coated photocatalytic surfaces
No full textPublisher Copyright: © 2025This paper presents a large-scale collaborative effort within a multi-partner consortium, to systematically structure, curate, and openly share data in alignment with the FAIR principles. The data result from a case study of titanium dioxide (TiO₂) nanomaterials (NMs) for photocatalytic depolluting surfaces, produced via various spray coating techniques under the Safe and Sustainable by Design (SSbD) approach. The data are publicly available through a dedicated Zenodo community (https://zenodo.org/communities/asina/records), comprising of individual records that separately host the data and the corresponding metadata. Each dataset is systematically named to reflect its context beginning with “ASINA dataset,” followed by i) the relevant life cycle stage (LCS) from synthesis to end-of-life, ii) the SSbD dimension (i.e., functionality, safety, and environmental aspects), and iii) the assessed features (e.g., physicochemical properties, hazard evaluation, functionality assessment) facilitating searchability. The data files include “descriptors” excel tab, which is a harmonized version derived from primary data for visualization, data integration and future modeling applications. Metadata are provided in separate records and include detailed information such as contributor name and affiliations, experimental protocols, instrumentation, dictionary definitions, ontologies, and licensing terms. The data and metadata files are mutually paired in Zenodo using related identifiers, where each data file includes the DOI of its corresponding metadata file, and vice versa. In total, 43 interlinked records are provided capturing the case study, offering structured and machine-actionable resources that support modeling, data integration and harmonization efforts within the nanosafety and nanoinformatics communities. This effort was coordinated through dedicated data shepherding, which enabled trust-building, metadata alignment, and consistent FAIR implementation across partners.Peer reviewe
Enhanced Mechanical Durability of Polymeric Nanowires via Carbyne-Enriched Plasma Coatings for Bactericidal Action
No full textPublisher Copyright: © 2025 by the authors.Carbon-based materials have emerged as promising biomaterials due to their biocompatibility and inherent antibacterial properties. Carbyne, a unique allotrope of carbon, characterized by sp-hybridized carbons forming alternating single and triple bonds, exhibits exceptional toughness. Herein, we explore the potential of carbyne-enriched plasma coatings for antibacterial applications in conjunction with micro- and nano-textured polymeric surfaces. We investigate and characterize carbyne-enriched plasma coatings onto superhydrophilic or superhydrophobic poly (methyl methacrylate) (PMMA) plasma micro-nanotextured surfaces. Our analysis evaluates the wetting properties and durability of these surfaces, particularly in liquid immersion conditions. The integration of carbyne-enriched plasma coatings serves a dual purpose: it enhances the chemical bactericidal action and protects surface micro-nanostructures from deformation due to capillary forces thanks to the material’s innate toughness. The results show that the micro-nanotextured and carbyne-enriched coated PMMA surfaces exhibit a significant bactericidal activity as expressed by a bactericidal index of approximately 50%, owing to the combined effect of both the surface topography and the plasma-deposited carbyne coating.Peer reviewe
Scalable synthesis of NiFe-layered double hydroxide for efficient anion exchange membrane electrolysis
No full textPublisher Copyright: © The Author(s) 2025.The alkaline oxygen evolution reaction is a key step in producing green hydrogen through water electrolysis, but its large-scale industrial application remains limited due to challenges with current electrocatalysts—particularly in terms of scalability, efficiency, and long-term stability. Here we show an industrially scalable synthesis of an active NiFe layered double hydroxide (NiFe-LDH) catalyst using a room-temperature, atmospheric-pressure route. The process involves homogeneous alkalinization, where chloride ions nucleophilically attack an epoxide ring, producing a low-dimensional, defect-rich NiFe-LDH with pronounced iron clustering. In-situ spectroscopy and ab-initio calculations reveal that these structural features maximize the conversion of the NiFe-LDH to the catalytic active phase and minimize the energy barrier, improving catalytic efficiency. When used as the anode in an anion exchange membrane water electrolyzer operating at 70 °C, our material delivers 1 A cm⁻² at 1.69 V in a 5 cm2 full-cell setup, with notable durability compared to conventional NiFe-LDHs. This scalable approach could considerably lower the cost of green hydrogen production by enabling more efficient alkaline electrolyzers.Peer reviewe
Temporal clustering for accurate short-term load forecasting using Bayesian multiple linear regression
No full textPublisher Copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.Effective short-term load forecasting (STLF) is essential for optimizing electricity grid operations. This study focuses on refining STLF for day-ahead predictions using Bayesian multiple linear regression (BMLR). This study’s originality lies in its innovative use of BMLR combined with data clustering techniques to improve prediction accuracy, a method not previously explored in existing literature. We address the critical issue of input data clustering, highlighting its impact on prediction accuracy. Four clustering methods based on temporality were examined, with clustering by weekday and hour proving most effective for BMLR-based STLF. Predictors included historical load, temperature, season, weekday, and hour, selected using the Akaike information criterion (AIC). Linear regression assumptions were verified, and solutions were proposed for deviations, notably addressing heteroscedasticity. Autocorrelation in residuals was addressed to improve forecasting efficiency. Time-cross validation and performance metrics demonstrated model effectiveness. Second-degree polynomial terms are included for better fitting. Clustering by weekday and hour is optimal for BMLR-based STLF, aiding accurate load forecasts. The main objectives of this research are to determine the optimal clustering method for BMLR in STLF and to provide practical insights into the application of Bayesian techniques in load forecasting. This research significantly contributes to the field of STLF by providing practical insights into data clustering and model refinement, offering valuable perspectives for enhanced energy management and grid stability.Peer reviewe
Advanced Flame Retardant Strategies and Fire Performance Assessment for Safer Photovoltaics in Buildings: A Two-Part Review
Get PDFPublisher Copyright: © 2025 The Author(s). Advanced Functional Materials published by Wiley-VCH GmbH.As global decarbonization accelerates the need for extensive solar photovoltaic deployment, land-use conflicts have become increasingly pressing. Integrating PV into the built environment emerges as an effective strategy to mitigate these challenges by generating electricity where it is consumed. However, the polymeric encapsulant—a core material in photovoltaic (PV) modules—introduces critical fire safety concerns, particularly in building applications with strict regulatory requirements. This review addresses the issue with a dual approach. First, it presents various solutions to mitigate fire hazards, such as the incorporation of flame retardants, and defines five families of the latter solutions. Despite the central role of the encapsulant in module flammability, little research has focused on the use of flame retardants in photovoltaic modules. Then, a review of the existing standards and testing approaches that can be used for the assessment of building-integrated photovoltaic fire safety is presented. Based on the findings, a methodology for the evaluation of the fire performance is also proposed, with this framework evaluated at both the material and module levels.Peer reviewe
Momentum-locked spin between topological and defect states in 1D patterns on bilayer graphene
Get PDFPublisher Copyright: © The Author(s) 2025.Gating Bernal bilayer graphene breaks the inversion symmetry so that the stacking AB/BA boundaries within the gap reveal topologically protected states. In this study, we theoretically investigate arrays where the AB and BA domains are periodically patterned with experimentally identified defect lines. In the calculations we consider electron-electron interaction effects using density functional theory. Our findings reveal the existence of topological states within a gap induced by the patterning without an applied gate voltage. Furthermore, with an applied gate potential, the defect lines introduce spin-polarized states pinned within the gap and exhibit ferromagnetically coupled states. Importantly, we observe a hybridization of magnetic and topological states near the valleys that form conducting channels characterized by spin-momentum locking. The effect persists even with slight n-doping and gate voltage; however, the progressively pinned n-doped defect states induce spin polarization in the topological and valley states. Additionally, the two-dimensional bands under doping conditions exhibit nesting across the Fermi surface, allowing for modulation of charge densities along the lines which are nearly commensurate with the underlying graphene-defect lines. These quasi-one-dimensional patterns in bilayer graphene show a new kind of spin-conducting channels with novel characteristics common to both spintronics and valleytronics.Peer reviewe
Rule-Based Behavior Planning to Resolve Separation Loss in UAM Off-Nominal Situations
No full textPublisher Copyright: © 2025 IEEE.This paper develops an on-the-fly decision-making framework to address the separation losses caused by off-nominal conditions, such as Loss of Control In-flight (LOC-I) of aircraft in congested Urban Air Mobility (UAM) airspace. Often, separation loss caused by LOC-I results in subsequent separation losses, triggering domino effects as one aircraft maneuvers to avoid another aircraft experiencing LOC-I in congested airspace. A behavior tree-based decentralized decision-making is developed to execute a separation assurance task assigned by the Provider of Service (PSU) to UAM aircraft, coordinating and selecting the necessary maneuvers following Federal Aviation Administration (FAA) right-of-way rules to resolve the encountered separation losses. The significance of the proposed decision-making framework is demonstrated through simulations that consider separation loss scenarios arising from LOC-I by implementing on-the-fly conflict detection, tasking, and maneuver planning algorithms for aircraft involved in the conflict.Peer reviewe
Enhanced ammonia decomposition in a structured membrane reactor using a Ru-coated SiC open-cell foam and a Pd-based membrane
Get PDFPublisher Copyright: © 2025 The AuthorsAmmonia decomposition into nitrogen and hydrogen was carried in a structured membrane reactor in this work. The performance of the structured catalyst and the effect of hydrogen permeation through a Pd-based membrane were evaluated. The structured catalyst is based on a commercial silicon carbide open cell foam (40 PPI). The catalyst (3 wt% Ru/CeO2) was coated by in situ-solution combustion deposition method with sequential cycles to reach the desired catalyst loading (0.31 g cm−3). TEM, SEM, XRD, TPR analysis and adhesion tests were used to characterize the prepared sample. A double-skinned Pd-based membrane has been prepared depositing a selective layer by electroless plating onto porous asymmetric α-Al2O3 support. The results proved a successful integration of structured catalyst and membrane. The beneficial effects of the proposed structured membrane reactor configuration enabled an increase in conversion up to 29 % compared with the structured catalyst system. The reaction system allowed an ammonia conversion of 98.4 % and hydrogen purity of 99.2 % at 450 °C and 4 bar. Furthermore, at fixed flow rate, the structured membrane reactor can achieve comparable conversion at operating temperatures about 55 °C lower than in the case of the structured reactor. Moreover, the proposed configuration enabled a conversion higher than the thermodynamic value at 4 and 5.5 bar at fixed temperature (480 °C) and fixed feed flow rate (62 ml min−1). To the best of our knowledge, this work is the first study combining a structured catalyst and a Pd-based membrane for ammonia decomposition.Peer reviewe