Developmental differences in L1 and L2 text comprehension: An ERP study

Text comprehension relies on high-level cognitive processes. These processes might be challenging for young readers, especially when comprehension takes place in a non-native language, an issue that remains unexplored. Twenty-four children and twenty-six adolescent early sequential bilinguals, were presented with narratives in L1- Spanish and L2-English. Each text biased an initial inference (“baby”), which then required either literal (“The little cat…”) or inferential (“The little animal − meow…”) monitoring. Processing times at this sentence suggested less efficient comprehension monitoring in the L2, mainly with inferential information. Moreover, in a final sentence, either literal or inferential (depending on the previous sentence) revision was assessed by ERP to a disambiguating word (“cat”). N400 amplitude showed that adolescents semantically integrated the alternative concept into their situation model only in the native language, but not during L2 comprehension. Crucially, children struggled to do so in both languages. In contrast, the P600 suggested that children in the native language and adolescents in both languages performed semantic reanalyses by reducing interference from the no longer valid initial interpretation. Our findings indicate a complex interplay between development and bilingualism in the ability to revise a situation model during text comprehension.MICIU, Spanish Ministry of Science, Innovation and Universities (PID2022-143066NA-I00; PID2021-127728NB-100

ISOTOPE PRODUCTION IN DONES: Exhaustive analysis of different isotopes and preliminary design of their industrial production

La Medicina Nuclear engloba una parte importante de las aplicaciones médicas de las radiaciones ionizantes, basándose en el uso de radioisótopos como fuentes de radiación y permitiendo el diagnóstico y tratamiento médico de las principales enfermedades con mayor impacto social. Los radioisótopos utilizados en Medicina Nuclear son producidos mediante bombardeo de núcleos estables con partículas cargadas, fotones o neutrones, para inducir las reacciones nucleares deseadas, y tienen lugar en instalaciones nucleares como reactores de fisión o en aceleradores de partículas (linacs, sincrotrones, ciclotrones, etc.). Estas tecnologías, junto con los generadores de radionucleidos, son las principales vías de abastecimiento de radioisótopos médicos en los hospitales, y deben considerarse complementarias y no competitivas. El acelerador lineal de alta intensidad y última generación, IFMIF-DONES, podrá acelerar deuterones hasta una energía de 40 MeV y una corriente de 125 mA. Estas partículas cargadas golpearán un blanco de litio líquido produciendo neutrones a través de la reacción nuclear de producción D+ + 7Li, contenida dentro de la celda de prueba (Test Cell), produciendo un flujo de neutrones rápidos de 1014 n/cm2/s con un pico amplio entre 14–20 MeV en su espectro neutrónico. En el campo de la producción de radioisótopos, IFMIF-DONES facilitaría tanto las posibilidades de producción de radioisótopos mediante reacciones inducidas con haz de deuterones como con neutrones, gracias al flujo neutrónico residual dentro de la celda de prueba tras el módulo de alto flujo (High Flux Test Module). En el contenido de esta tesis se estudia de forma exhaustiva y detallada la viabilidad de producción de algunos de los radioisótopos más relevantes en la clínica actual, 165Er, 177Lu y 99Mo/99mTc, así como su adaptación realista de producción a la instalación, considerándose algunas modificaciones en el diseño actual del acelerador para la correcta implementación de esta aplicación complementaria relevante en el campo de la Medicina Nuclear. Finalmente, se ha cerrado esta tesis con un caso práctico de aplicación en el campo de la Medicina Nuclear. Concretamente, se ha evaluado un radiofármaco experimental radiomarcado con 177Lu en modelo animal para definir sus posibilidades preclínicas ante una potencial investigación traslacional desde el ámbito de las terapias dirigidas con radionucleidos a otras estrategias terapéuticasNuclearMedicine covers an important part of the medical applications of ionising radiation, based on the use of radioisotopes as radiation sources and allowing the diagnosis and medical treatment of the main diseases with the greatest social impact. Radioisotopes used in Nuclear Medicine are produced by bombarding stable nuclei with charged-particles, photons or neutrons, to induce the required nuclear reactions, and take place in nuclear facilities such as fission reactors or particle accelerators (Linacs, synchrotrons, cyclotrons, etc.). These technologies, together with radionuclide generators, are the main supply routes for medical radioisotopes in hospitals and should be seen as complementary and non-competitive. The state-of-the-art, high-intensity linear accelerator, IFMIF-DONES, will be able to accelerate deuterons up to 40 MeV of energy and 125 mA of current. The charged-particle beam will strike a liquid lithium target producing neutrons through the nuclear production reaction D+ + 7Li, contained inside the Test Cell, producing a fast neutron flux of 1014 n/cm2/s with a broad peak between 14 − 20 MeV in its neutron spectrum. In the framework of radioisotope production, IFMIF-DONES would allow radioisotope production by deuteron- induced and neutron-induced nuclear reactions, the latter thanks to the residual neutron flux inside the Test Cell behind the High Flux Test Module. In the content of this thesis, the production feasibility of 165Er, 177Lu and 99Mo/99mTc, some of the most relevant radioisotopes in the current clinic is analysed in an exhaustive and detailed study, as well as their realistic production within the facility, considering some updates in the design of the accelerator for the correct implementation of this relevant complementary application in the field of Nuclear Medicine. Finally, this thesis has been closed with a practical case of application in the field of Nuclear Medicine. Specifically, an experimental radiopharmaceutical radiolabelled with 177Lu has been evaluated in an animal model to define its preclinical possibilities for a potential translational research from the field of targeted radionuclides therapies to other therapeutic strategies.Tesis Univ. Granada.MCIN/AEI/10.13039/501100011033 from the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No 101052200 — EUROfusion)Partially, this work was supported by Spanish Ministerio de Ciencia e Innovación (PID2020-117969RBI00)Junta de Andalucía (FEDER Andalucia 2014–2020) projects P20-00665 and B-FQM-156- UGR20Empresarios Agrupados Internacional, S.A. with funding from Spanish CDTI (Misiones DONES-EVO) (Contrato UGR-OTRI 5270)Instituto Carlos III (ISCIII DTS22 /00147)France State aid managed by the Agence Nationale de la Recherche under the Programme d’Investissements d’Avenir (ANR-16-IDEX-0007)Financial support from the Pays de la Loire Region.Junta de Andaluc´ıa, European Regional Development Fund (ERDF), Euratom Research, co-founded by the European Union, ENEN2Plus and Training Programme IRC TransForMed mobility grant

Data quality tools to enhance a network anomaly detection benchmark

Network traffic datasets are essential for the construction of traffic models, often using machine learning (ML) techniques. Among other applications, these models can be employed to solve complex optimization problems or to identify anomalous behaviors, i.e., behaviors that deviate from the established model. However, the performance of the ML model depends, among other factors, on the quality of the data used to train it. Benchmark datasets, with a profound impact on research findings, are often assumed to be of good quality by default. In this paper, we derive four variants of a benchmark dataset in network anomaly detection (UGR’16, a flow-based real-world traffic dataset designed for anomaly detection), and show that the choice among variants has a larger impact on model performance than the ML technique used to build the model. To analyze this phenomenon, we propose a methodology to investigate the causes of these differences and to assess the quality of the data labeling. Our results underline the importance of paying more attention to data quality assessment in network anomaly detection.Agencia Estatal de Investigación in Spain, MCIN/AEI/ 10.13039/501100011033, grant No. PID2020-113462RB-I0

A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms

This work has been developed under the grant PID2023-147409NB-C21, funded by the Spanish Ministerio de Ciencia Innovación y Universidades (Agencia Estatal de Investigación) MICIU/AEI/10.13039/501100011033, as well as by ERDF (European Union). The research has also been funded by projects TED2021-131699B-I00 and TED2021-129938B-I00 (MICU and AEI), as well as projects PID2020-113462RB-I00 and PID2020-115570GB-C22 of the Spanish Ministry of Economy and Competitiveness; project C-ING-179-UGR23 financed by the “Consejería de Universidades, Investigación e Inno-vación” (Andalusian Government, FEDER Program 2021-2027); and project PPJIA2023-031 (Plan Propio de Investigación y Transferencia UGR).This study introduces a novel evaluation framework for predicting web page performance, utilizing state-of-the-art machine learning algorithms to enhance the accuracy and efficiency of web quality assessment. We systematically identify and analyze 59 key attributes that influence website performance, derived from an extensive literature review spanning from 2010 to 2024. By integrating a comprehensive set of performance metrics—encompassing usability, accessibility, content relevance, visual appeal, and technical performance—our framework transcends traditional methods that often rely on limited indicators. Employing various classification algorithms, including Support Vector Machines (SVMs), Logistic Regression, and Random Forest, we compare their effectiveness on both original and feature-selected datasets. Our findings reveal that SVMs achieved the highest predictive accuracy of 89% with feature selection, compared to 87% without feature selection. Similarly, Random Forest models showed a slight improvement, reaching 81% with feature selection versus 80% without. The application of feature selection techniques significantly enhances model performance, demonstrating the importance of focusing on impactful predictors. This research addresses critical gaps in the existing literature by proposing a methodology that utilizes newly extracted features, making it adaptable for evaluating the performance of various website types. The integration of automated tools for evaluation and predictive capabilities allows for proactive identification of potential performance issues, facilitating informed decision-making during the design and development phases. By bridging the gap between predictive modeling and optimization, this study contributes valuable insights to practitioners and researchers alike, establishing new benchmarks for future investigations in web page performance evaluation.MICIU/AEI/10.13039/501100011033 PID2023-147409NB-C21ERDF (European Union)TED2021-131699B-I00 and TED2021-129938B-I00 (MICU and AEI)Spanish Ministry of Economy and Competitiveness PID2020-113462RB-I00 and PID2020-115570GB-C22Andalusian Government C-ING-179-UGR23FEDER Program 2021-2027Universidad de Granada PPJIA2023-03

Libro de Actas del Congreso Internacional Comunicación Inclusiva y Multilingüe, 2025: Calidad en la educación superior. Argumentación científica del conocimiento sostenible

En la Resolución aprobada por la Asamblea General el 25 de septiembre de 2015, la Unión Europea aprobó la Agenda 2030 para el Desarrollo Sostenible. En esta agenda, la Meta 4 busca garantizar una educación inclusiva, equitativa y de calidad. Más específicamente, la Meta 4.3 pretende garantizar la igualdad de acceso para todos a la educación superior profesional. Por lo tanto, esta meta estimula la creación de las condiciones didácticas que garanticen una educación universitaria de alta calidad. La calidad de la educación superior exige la mejora de las capacidades cognitivas, motivacionales y comunicativas de todos los ciudadanos, para posibilitar una cultura de paz y cooperación, en el marco del desarrollo global sostenible. Por lo tanto, este tipo de la calidad propone el diseño de modelos didácticos que proporcionen apoyo logístico y material (es decir, instrucciones y recursos suficientes adaptados a la diversidad) a fin guiar el aprendizaje de la comunicación humana para el desarrollo de modelos sociales, económicos y ecológicos, que contribuyan, significativamente, a la resolución de problemas de sostenibilidad. En definitiva, garantizar la calidad en la educación universitaria implica, esencialmente, garantizar el aprendizaje de las competencias comunicativas, que siempre suponen el desarrollo de procesos metacognitivos, motivacionales y sociales. Además, al abordar las competencias comunicativas verbales, no se deben olvidar los factores lingüísticos.Ed. InvestMCIN/AEI/ 10.13039/ 501100011033/ por la “Unión Europea NextGenerationEU/PRTR

International norms for adult handgrip strength: A systematic review of data on 2.4 million adults aged 20 to 100+ years from 69 countries and regions

We would like to acknowledge the funding received by the following primary authors: CC-S is supported by European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska Curie grant agreement (No.101028929). BJF is supported by National Heart Foundation of Australia Postdoctoral Fellowship (No. 106588). BG is supported by Australian Government Research Training Program Scholarship. DPL is supported by Clive Kearon Award, McMaster University. Additional funding information can be found in Supplementary Funding.Background Muscular strength is a powerful marker of current health status and robust predictor of age-related disease and disability. Handgrip strength (HGS) using isometric dynamometry is a convenient, feasible, and widely used method of assessing muscular strength among people of all ages. While adult HGS norms have been published for many countries, no study has yet synthesized available data to produce international norms. The objective of this study was to generate international sex- and age-specific norms for absolute and body size-normalized HGS across the adult lifespan. Methods Systematic searches were conducted in 6 databases/web search engines (MEDLINE, SPORTDiscus, Embase, Web of Science, CINAHL, and Google Scholar) up to December 1, 2023. We included full-text peer-reviewed observational studies that reported normative HGS data for adults aged ≥20 years by sex and age. Pseudo data were generated using Monte Carlo simulation following harmonization for methodological variation. Population-weighted Generalized Additive Models for Location, Scale, and Shape were used to develop sex- and age-specific norms for absolute HGS (kg) and HGS normalized by height (Ht, m) squared (i.e., HGS/Ht2 in kg/m2). Norms were tabulated as percentile values (5th to 95th) and visualized as smoothed percentile curves. Results We included data from 100 unique observational studies representing 2,405,863 adults (51.9% female) aged 20 to 100+ years from 69 countries and regions tested from the year 2000 onward. On average, absolute and normalized HGS values negligibly improved throughout early adulthood, peaked from age 30–39 years (at 49.7 kg (males) and 29.7 kg (females) for absolute HGS or 16.3 kg/m2 (males) and 11.3 kg/m2 (females) for HGS/Ht2), and declined afterwards. The age-related decline in HGS accelerated from middle to late adulthood and was slightly larger for males than for females during middle adulthood. Conclusion This study provides the world's largest and most geographically comprehensive international norms for adult HGS by sex and age. These norms have utility for global peer-comparisons, health screening, and surveillance.European Union's Horizon 2020 Marie Sklodowska Curie (No.101028929)National Heart Foundation of Australia Postdoctoral Fellowship (No. 106588)Australian Government Research Training Program ScholarshipClive Kearon Award, McMaster Universit

Geometrical variability impact on the gate tunneling leakage mechanisms in FinFETs

Given the critical role that quantum tunneling effects play in the behavior of nanoelectronic devices, it is essential to investigate the influence and restraints of these phenomena on the overall transistor performance. In this work, a previously developed gate leakage model, incorporated into an in-house 2D Multi-Subband Ensemble Monte Carlo simulation framework, is employed to analyze the leakage current flowing across the gate insulator. The primary objective is to evaluate how variations in key geometrical parameters (specifically, gate oxide and semiconductor thicknesses dimensions) affect the magnitude and bias dependence of tunnelinginduced leakage. Simulations are performed on a representative FinFET structure, and the results reveal that tunneling effects become increasingly pronounced at low gate voltages in devices with thinner oxides and thicker semiconductor thickness. These findings underscore the relevance of incorporating quantum tunneling mechanisms in predictive modeling of advanced transistor architectures

Whole genome DNA methylation profles defne Meniere’s disease subclusters

Meniere disease (MD) is a cochleo-vestibular syndrome defned by episodes of vertigo associated with tinnitus and sensorineural hearing loss. While MD immune response has been linked to autoinfammation and type 2 cytokines, other molecular mechanisms such as DNA methylation have an emerging yet underexplored role in MD pathophysiology.To understand the role of DNA methylation in MD, we performed whole-genome bisulphite sequencing in MD patients (n=40) and controls (n=13) and used diferentially methylated cytosines (DMCs) to defne clusters, cell types, and biochemical pathways in MD. We found three MD subclusters: Cluster 1 (40% of patients) and Cluster 3 (25%) showed DMC profles against controls, while Cluster 2 (35%) did not. Signifcant DMCs from Cluster 1 and Cluster 3 versus Control analysis were annotated to 3033 and 59 unique genes, respectively. Each cluster showed a diferent gene enrichment; however, the KDMB4 gene had signifcant upregulated DNA accessibility in a complementary ATAC-seq dataset and showed signifcant DMCs in both Cluster 1 and Cluster 3. DNA methylation patterns in MD reveal three clusters which are refective of an underlying diference in pathways related to cytokine stimulus, immunity T-cell, and NK-cell pathways. KDMB4 emerges as a critical MD gene which deserves further research.Andalusian Health Department (EPIVERT) - (PI027-2020)University of Sydney (K7013_B3413

Quantum Physics and the Breakdown of the Reality/Fiction Dualism: The Cultural Field of the 21st Century

El artículo propone considerar una tercera mutación del capitalismo como base infraestructural para ampliar la interpretación de Edmond Cros sobre la desaparición del patrón oro y sus consecuencias simbólicas. En este contexto, se exploran ideologemas como posverdad, metaverso y realidad virtual, así como otras mutaciones simbólicas como la fractura entre realidad y ficción en la cinematografía, las artes escénicas y otros discursos sociales. Se sugiere que todos estos fenómenos podrían estar mediando hallazgos experimentales de la física cuántica, funcionando de manera similar a lo descrito por Cros en la óptica fisiológica de von Helmholtz.Nous proposons de considérer une troisième mutation du capitalisme comme base infraestructurale pour élargir l'interprétation d'Edmond Cros concernant la disparition de l'étalon-or et ses conséquences symboliques. Dans ce cadre, des idéologèmes tels que la post-vérité, le métavers et la réalité virtuelle sont explorés, ainsi que d’autres mutations symboliques comme la fracture entre réalité et fiction dans la cinématographie, les arts de la scène et d'autres discours sociaux. Il est suggéré que tous ces phénomènes pourraient médiatiser les découvertes expérimentales de la physique quantique, fonctionnant de manière similaire à ce que Cros a décrit dans l'optique physiologique de von Helmholtz.This article proposes considering a third mutation of capitalism as an infrastructural foundation to expand Edmond Cros' interpretation of the disappearance of the gold standard and its symbolic consequences. In this context, ideologemes such as post-truth, metaverse, and virtual reality are explored, along with other symbolic mutations like the fracture between reality and fiction in cinematography, performing arts, and other social discourses. It is suggested that all these phenomena could mediate experimental findings from quantum physics, functioning in a way similar to what Cros described in von Helmholtz's physiological optics

Towards an energy consumption index for deep learning models: a comparative analysis of architectures, GPUs, and measurement Tools

The growing global demand for computational resources, particularly in Artificial Intelligence (AI) applications, raises increasing concerns about energy consumption and its environmental impact. This study introduces a newly developed energy consumption index that evaluates the energy efficiency of Deep Learning (DL) models, providing a standardized and adaptable approach for various models. Convolutional neural networks, including both classical and modern architectures, serve as the primary case study to demonstrate the applicability of the index. Furthermore, the inclusion of the Swin Transformer, a state-of-the-art and modern non-convolutional model, highlights the adaptability of the framework to diverse architectural paradigms. This study analyzes the energy consumption during both training and inference of representative DL architectures, including AlexNet, ResNet18, VGG16, EfficientNet-B3, ConvNeXt-T, and Swin Transformer, trained on the Imagenette dataset using TITAN XP and GTX 1080 GPUs. Energy measurements are obtained using sensor-based tools, including OpenZmeter (v2) with integrated electrical sensors. Additionally, software-based tools such as CarbonTracker (v1.2.5) and CodeCarbon (v2.4.1) retrieve energy consumption data from computational component sensors. The results reveal significant differences in energy efficiency across architectures and GPUs, providing insights into the trade-offs between model performance and energy use. By offering a flexible framework for comparing energy efficiency across DL models, this study advances sustainability in AI systems, supporting accurate and standardized energy evaluations applicable to various computational settings.PID2023-147409NB-C21. MICIU/AEI/10.13039/501100011033 and by ERDF/EU. Ministerio Español de Ciencia e InnovaciónPID2020-115570GB-C22. MICIU/AEI/10.13039/501100011033 and by ERDF/EU. Ministerio Español de Ciencia e InnovaciónPID2022-137461NB-C32. MICIU/AEI/10.13039/501100011033 and by ERDF/EU. Ministerio Español de Ciencia e InnovaciónTIC251-G-FEDER. ERDF/EUC-ING-027-UGR23. ERDF/E