Maria Garcia

Increasing concern about global water scarcity has highlighted the necessity to optimize the use of this resource, where AI and machine learning techniques can play a key role, serving as decision-making support tools that would help anticipate necessities and ensure a quality supply. This study proposes a methodology to characterize residential water users from daily consumption time series by applying feature extraction, dimensionality reduction and clustering techniques. Aggregated statistical features were first computed and then reduced via PCA. DBSCAN outperformed K-means in clustering, and both UMAP and t-SNE showed adequate embedded space results. Different characteristics were found between clusters, demonstrating the possibility of separating users of the same grid by behaviors or profiles.

When reasoning about causes of sustainability problems and possible solutions, sustainability scientists rely on disciplinary-based understanding of cause–effect relations. These disciplinary assumptions enable and constrain how causal knowledge is generated, yet they are rarely made explicit. In a multidisciplinary field like sustainability science, lack of understanding differences in causal reasoning impedes our ability to address complex sustainability problems. To support navigating the diversity of causal reasoning, we articulate when and how during a research process researchers engage in causal reasoning and discuss four common ideas about causation that direct it. This articulation provides guidance for researchers to make their own assumptions and choices transparent and to interpret other researchers’ approaches. Understanding how causal claims are made and justified enables sustainability researchers to evaluate the diversity of causal claims, to build collaborations across disciplines, and to assess whether proposed solutions are suitable for a given problem.

The detection of hydrocarbon spills in marine environments is a critical challenge due to their severe impact on aquatic ecosystems. Hyperspectral imaging technology has emerged as a promising tool for detecting such spills, offering high-resolution spectral data for accurate identification. This work aims to develop an automated procedure for detecting hydrocarbon spills in local marine areas using a compact hyperspectral camera installed on a drone. The methodology integrates machine learning with hyperspectral technology, employing hyperspectral signatures of various hydrocarbons and water to create a spectral knowledge base for classification. A novel approach is used in the classifier training, where hyperspectral signatures are directly utilized as input to an artificial neural network, bypassing the need for extensive image labelling, eliminating the requirement for a large image dataset, and significantly reducing the computational costs associated with deep learning models. The trained classifiers, using autoencoders for encoding hyperspectral signatures, were applied to classify hyperspectral profiles (hyperpixels) in hyperspectral images. The results were highly promising, with the classifiers achieving near-perfect accuracy in detecting contaminated water and distinguishing between different hydrocarbons. Recall and F-score values above 0.90 demonstrate the effectiveness of the proposed approach, offering an efficient, scalable solution for real-time monitoring of marine spills.

Robust road surface estimation is required for autonomous ground vehicles to navigate safely. Despite it becoming one of the main targets for autonomous mobility researchers in recent years, it is still an open problem in which cameras and LiDAR sensors have demonstrated to be adequate to predict the position, size and shape of the road a vehicle is driving on in different environments. In this work, a novel Convolutional Neural Network model is proposed for the accurate estimation of the roadway surface. Furthermore, an ablation study has been conducted to investigate how different encoding strategies affect model performance, testing 6 slightly different neural network architectures. Our model is based on the use of a Twin Encoder–Decoder Neural Network (TEDNet) for independent camera and LiDAR feature extraction and has been trained and evaluated on the Kitti–Road dataset. Bird’s Eye View projections of the camera and LiDAR data are used in this model to perform semantic segmentation on whether each pixel belongs to the road surface. The proposed method performs among other state-of-the-art methods and operates at the same frame rate as the LiDAR and cameras, so it is adequate for its use in real-time applications.

Francisco Fernández-Zarza Pérez conocido como Jano, fue un artista polifacético dentro del mundo publicitario y cinematográfico. Destacó por su versatilidad a la hora de retratar a las estrellas cinematográficas pertenecientes al “star-system” nacional e internacional durante la época de la posguerra y la transición española.Partiendo de la importancia del cartel como medio de transmisión del mensaje, pretendemos descubrir si sus carteles, entre los años 1940 y 1970, además de actuar como reclamo para dar a conocer las películas también actuaron como reflejo de los estereotipos sociales mediante la representación de los roles femeninos.

La Compañía de Jesús ha intentado en los últimos años establecer algunas directrices para ayudar a sus instituciones educativas a enfocar sus acciones por y para la misión. El “Paradigma Ledesma-Kolvenbach” se considera una buena base para hacerlo. Presenta cuatro dimensiones interdependientes (utilidad, justicia, humanismo y fe), que reflejan una visión integral y holística de la finalidad de una universidad. Sin embargo, es necesario hacer operativas estas dimensiones. Esta investigación desarrolla un modelo que ayuda a las universidades jesuitas a evaluar su nivel de despliegue de las dimensiones en el ámbito de la docencia.

Este artículo expone el resultado de la puesta en práctica de una metodología docente novedosa a través de la que se busca superar las dificultades que el proceso de enseñanza/aprendizaje encuentra en las asignaturas jurídicas que forman parte de los grados universitarios no jurídicos. Comienza destacando el papel que tienen las tecnologías de la información y la comunicación en dicho proceso y, significativamente, el campus virtual. Seguidamente, desgrana cada uno de los elementos de la metodología docente aplicaba, entre los que encuentra la gamificación. Concluye con la determinación de las consecuencias de la experiencia desarrollada.

La concepción de los espacios educativos se genera dentro de una sociedad tecnológica afanada en preparar al alumnado. Se plantea descubrir qué conceptos se barajan acerca de los espacios educativos creando tendencias. La metodología de revisión bibliográfica tiene en cuenta la base de datos WOS seleccionando y revisando críticamente 10 publicaciones de actualidad. Se concluye que hay profusión de nuevos conceptos que se barajan teniendo en cuenta la asimilación de estos nuevos espacios, los espacios de aprendizaje y las tecnologías usadas. También se barajan temáticas teniendo en cuenta la situación del alumnado y del profesorado adaptándose a estos nuevos espacios.

Taller, estudio, laboratorio, fábrica… el espacio de trabajo del artista ha ido tomando diversos nombres, asumiendo diferentes formas y configuraciones. Pero en esencia se trata de un espacio funcional donde cada artista crea y produce su obra. Es un contexto altamente simbólico, activo y performativo, un lugar ideal para la ejecución de acciones y procesos en los que explorar la fenomenología del medio como un espacio educacional.“Espacio de artista” es un proyecto artístico-pedagógico que toma el estudio o taller en tanto que mediador de la experiencia artística dentro del XXII Salón del libro Infantil e Xuvenil de Pontevedra.

En el presente trabajo, pretendo explorar la historia de una búsqueda de la filosofía medieval, que trasciende incluso su propia época, ya que condujo a la ciencia de lo material, dejó sentadas las bases para el futuro desarrollo de las ciencias y de la propia filosofía occidentales, ya en los tiempos modernos; y donde creo percibir la presencia de una constante: la búsqueda de lo individual, de lo singular, dentro de los conceptos filosóficos que el pensamiento medieval fue formando. Es lo que llamo la Adversus Pluralitas de la filosofía escolástica occidental. Esta exploración la realizo tanto desde el punto de vista del análisis doctrinal como del contexto histórico, mediante el estudio de fragmentos de las obras de los más importantes representantes de la filosofía de la época medieval, así como de textos más recientes a ellos referidos. In the present work I intend to explore the history of a quest of medieval philosophy that transcends even its own era, since it led to the science of material things, laid the foundations for the future development of Western sciences and of philosophy itself, already in the modern age; and in which I believe I perceive the presence of a constant: the search for the individual, for the singular, within the philosophical concepts that medieval thought was forming. This is what I call the adversus pluralitas of Western scholastic philosophy. This research is carried out both from the point of view of doctrinal analysis and historical context, through the study of fragments of the works of the most important representatives of the philosophy of the Medieval time, as well as more recent texts referring to them.

This paper investigates the relationship between voluntary participation in environmental organisations and the justifiability of littering behaviour. Previous empirical work regarding determinants of littering and littering behaviour remains scarce, particularly in socio-economic analysis. We address these deficiencies, demonstrating a strong empirical link between environmental participation and reduced public littering in the European Values Survey (EVS) data for 30 Western and Eastern European countries. The results suggest that membership in environmental organisations is related to a stronger commitment to anti-littering behaviour, thereby supporting improved environmental quality.

The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threaten data integrity but also the overall functionality of IoT systems. This study addresses these challenges by exploring efficient data reduction techniques within a model-based intrusion detection system (IDS) for IoT environments. Specifically, the study explores the efficacy of an autoencoder’s latent space combined with three different classification techniques. Utilizing a validated IoT dataset, particularly focusing on the Constrained Application Protocol (CoAP), the study seeks to develop a robust model capable of identifying security breaches targeting this protocol. The research culminates in a comprehensive evaluation, presenting encouraging results that demonstrate the effectiveness of the proposed methodologies in strengthening IoT cybersecurity with more than a 99% of precision using only 2 learned features.

The effect of ASDEX Upgrade edge localized mode -mitigation coils on fast ion wall loads was studied with the fast particle following Monte Carlo code ASCOT. Neutral beam injected particles were simulated in two AUG discharges both in the presence and in the absence of the magnetic field perturbation induced by the eight newly installed in-vessel coils. In one of the discharges beams were applied individually, making it a useful basis for investigating the effect of the coils on different beams. However, no ELM mitigation was observed in #26476, probably due to the low plasma density. Therefore, another discharge demonstrating clear ELM mitigation was also studied. The magnetic perturbation due to the in-vessel coils has a significant effect on the fast particle confinement, but only when total magnetic field, B tot, is low. When B tot was high, the perturbation did not increase the losses, but merely resulted in redistribution of the wall power loads. Hence, it seems to be possible to achieve ELM mitigation using in-vessel coils, while still avoiding increased fast ion losses, by simply using a strong B tot. Preliminary comparisons between simulated and experimental fast ion lost detector signals show a reasonable correspondence. © 2012 IAEA, Vienna.

En este artículo se estudia la transformación del concepto de Belleza en la obra de Agostino Nifo. Para ello compararemos las princiales tesis defendidas por Nifo con las que defiende Santo Tomás de Aquino en esta materia. El resultado es el siguiente: los aspectos referidos a la Belleza en la obra de Nifo, están presentes en la tradición, pero vacíos de contenido. Como quiera que la Belleza es reducida al ámbito sensible, por eso pierde el carácter transcendental.This article studies the transformation of the concept of Beauty in Nifo's work. For that purpose the most relevant thesis of his work De pulchro are being compared with the most significant writings of the work of Thomas d'Aquino. The results of this study lead us to the following conclusion: In Nifo's work we find the elements related to Beauty, that are present in the Tradition, but empty of content. As Beauty is reduced to the sensitive ambitus, it losses its transcendental character

En el pensamiento de Leibniz la lógica y la ontología se mezclan de tal modo que, en ocasiones, no es fácil discernir los planos en los que se mueve el filósofo de Hannover. El propósito de este artículo es estudiar este tema en relación con una cuestión de importancia capital en el pensamiento leibniciano: la verdad eterna. El estatuto lógico y ontológico de las verdades eternas en Leibniz son la causa, la razón que justifican la racionalidad de lo creado. En segundo lugar, también se resaltará la diferencia de Leibniz frente a la postura cartesiana, para quien la arbitrariedad de la verdad no puede justificar la racionalidad de lo que existe, porque supondría poner límites a la libertad divina