Universidade da Coruña: Servizo de Publicacións
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Mapeo de controversias y juego de rol sobre la cuestión socialmente viva del modelo dominante de producción y consumo de carne para fomentar el pensamiento crítico
Full text linkThis article examines the use of controversy mapping and role-play as didactic strategies for the development of critical thinking among Spanish secondary school students based on the socially acute question (SAQ) of the prevailing model of meat production and consumption. The combination of controversy mapping and role-play is presented as a multifaceted approach to learning, designed to enable students to explore different perspectives and deepen their understanding of the issue addressed. Students were asked to explain their position on meat consumption and the creation of megafarms before and after the experience, with the majority expressing reservations about meat consumption and opposition to megafarm facilities. The results showed that this approach encourages holistic thinking and decision-making on SAQ among students.Este artículo examina la combinación del mapeo de controversias y el juego de rol como estrategias didácticas para desarrollar el pensamiento crítico de estudiantes de educación secundaria españoles, abordando la Cuestión Socialmente Viva (QSV) del modelo dominante de producción y consumo de carne. Estas estrategias se presentan como un enfoque multifacético de aprendizaje, permitiendo al alumnado explorar diversas perspectivas y profundizar en su comprensión de la QSV. Antes y después de la experiencia, se pidió al alumnado que justificara su posición sobre el consumo de carne y la instalación de macrogranjas, resultando que la mayoría indicó que existen problemas con el consumo de carne y manifestándose en contra de dichas instalaciones. La experiencia mostró que es posible desarrollar un enfoque holístico del alumnado hacia los problemas y la toma de decisiones sobre las QSV a través del mapeo de controversias y el juego de rol
Obrigado, Justino Magalhães - Memórias e Afetos
No full textAnthology of tributes and personal responses to Justino Magalhães by friends, family and colleagues from different stages of his life and careerObra sembrada con muchos afetos que fueron creciendo en la convivencia con el autor homenajeado. Conjunto de textos de autores que se cruzaron con Justino Magalhães en el recorrido de su vida académica, científica o simplemente amigos y familiares.Obra sementada con moitos afetos que foron crecendo na convivencia co autor homenaxeado. Conxunto de textos de autores que se cruzaron con Justino Magalhães no percorrido da súa vida académica, científica ou simplemente amigos e familiares.Obra semeada com muitos afetos que foram crescendo na convivência com o autor homenageado. Conjunto de textos de autores que se cruzaram com Justino Magalhães no percurso de vida académico, científico ou simplesmente amigos e familiares
Public debt and fiscal consolidation in the Western Balkans: a panel analysis of growth effects
Full text linkThis study examines the impact of public debt on economic growth and the effects of fiscal consolidation efforts in the Western Balkan countries (WB6)—Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, and Serbia. Utilizing a dual methodology of descriptive and panel data analysis, the research investigates whether higher public debt adversely affects economic growth and if fiscal consolidation measures lead to improved economic outcomes. The descriptive analysis identifies fiscal consolidation periods based on improvements in the cyclically-adjusted primary budget balance and subsequent changes in the public debt-to-GDP ratio. The econometric analysis employs both fixed-effects and random-effects panel regression models, using data from International Monetary Fund (IMF) - World Economic Outlook Databases covering the period 2000-2023. The findings reveal that higher levels of public debt are detrimental to economic growth across the WB6 countries. Conversely, successful fiscal consolidation, characterized by reductions in government expenditure relative to GDP, correlates with enhanced economic growth. The study underscores the importance of maintaining prudent debt levels and implementing effective fiscal policies. Recommendations for policymakers include prioritizing debt reduction strategies, improving revenue collection, and investing savings in infrastructure, education, and innovation to support long-term economic stability and growth
The implementation of socially responsible public procurement in Greece: barriers and prospects for Social Economy Entities
Full text linkThis study explores whether and how Social Economy Entities (SEEs) in Greece engage with Socially Responsible Public Procurement (SRPP), as introduced by Law 4412/2016. It investigates the extent to which SEEs—specifically KOINSEPs and KOISPEs—are aware of, participate in, and benefit from SRPP provisions such as Articles 20 and 110, and identifies institutional barriers they encounter. Using a mixed-methods approach combining surveys and interviews, the findings reveal that while KOISPEs demonstrate higher awareness and participation, KOINSEPs face legal unfamiliarity, bureaucratic complexity, and liquidity constraints. Public authorities, in turn, often lack SRPP-related knowledge, contributing to limited implementation. Despite these challenges, SEEs propose concrete reforms, including quotas, administrative simplification, and targeted support structures. The study contributes to the literature on strategic procurement and highlights the importance of institutional capacity, legal clarity, and trust in enabling inclusive economic policies
From Atoms to Waves: Rhythmic Stylometry for Authorship Studies of Early Modern Spanish Theatre
Full text linkEach comedy from the Spanish Early Modern period can be decomposed into hundreds of rhythmic patterns—one for each verse—whose overlapping creates a characteristic authorial fingerprint. Stylometric techniques can be employed to compare these patterns, formed by the concatenation of stressed and unstressed syllables, in order to establish authorial inferences. In this exploratory work, we designed an experiment comprising a corpus of one hundred securely attributed plays by nine different authors, conducting a series of tests to determine whether these rhythmic patterns can discriminate the authorship of a theatrical piece. The results, although inferior to those obtained through traditional lexical stylometry, show promise as an alternative path for authorial investigation.Each comedy from the Spanish Early Modern period can be decomposed into hundreds of rhythmic patterns—one for each verse—whose overlapping creates a characteristic authorial fingerprint. Stylometric techniques can be employed to compare these patterns, formed by the concatenation of stressed and unstressed syllables, in order to establish authorial inferences. In this exploratory work, we designed an experiment comprising a corpus of one hundred securely attributed plays by nine different authors, conducting a series of tests to determine whether these rhythmic patterns can discriminate the authorship of a theatrical piece. The results, although inferior to those obtained through traditional lexical stylometry, show promise as an alternative path for authorial investigatio
Aplicación de grandes modelos de lenguaje en diagnóstico de glaucoma
Full text linkThis research explores the potential of Visual Large Language-Language Models (Visual LLM) in the diagnosis of glaucoma from retinographies. Specifically, the use of the Visual LLM known as Moondream is analysed. Using transfer learning techniques, the model has been re-trained with retinal images, with the aim of learning to distinguish between healthy eyes and eyes with glaucomatous signs. The designed methodology combines visual feature extraction and textual reasoning, opening new ways for automated clinical interpretation. This work positions Visual LLMs as an attractive option for integrating multimodal Artificial Intelligence in Ophthalmology and improving glaucoma detection.En esta investigación se explora el potencial de los Grandes Modelos de Lenguaje-Visión (Visual LLM) en el diagnóstico de glaucoma a partir de retinografías. En concreto, se investiga el uso de la Visual LLM conocida como Moondream. Empleando técnicas de transferencia de aprendizaje, el modelo se ha re-entrenado con imágenes de retinografías, con el objetivo de que aprenda a distinguir ojos sanos y ojos con signos glaucomatosos. La metodología diseñada combina la extracción de características visuales y el razonamiento textual, abriendo nuevas vías para la interpretación clínica automatizada. Este trabajo sitúa a los Visual LLMs como una opción atractiva para integrar la Inteligencia Artificial multimodal en Oftalmología y mejorar la detección del glaucoma
Development and validation of a safe reinforcement learning drone controller
Full text linkThis paper presents the work in progress that aims to develop, validate, and verify the use of Reinforcement Learning~(RL) and neural networks for safety real-time systems. A \gls{UAV} controller is utilized as a use case. These techniques are particularly promising for autonomous control as they learn from a dynamic environment without human intervention. The proposed solution shows the behavior of a UAV that has been trained to maintain altitude and avoid incoming obstacles such as other UAVs. The AirSim simulator was used to simulate a realistic flight scenario with two UAVs. One of the vehicles contains the RL controller, while the other is constantly attempting to collide with it. Preliminary results show that neural networks trained with the Soft Actor-Critic (SAC) algorithm can avoid collisions, especially in cases unseen during training. Despite the satisfactory results, further research is needed to verify that the RL agent can operate correctly in a safe and real-time environment.Este artículo presenta el trabajo en curso que busca desarrollar, validar y verificar el uso del Aprendizaje por Refuerzo (RL)y redes neuronales en sistemas de tiempo real críticos. Para ello, se utiliza un controlador de un Vehículo Aéreo no Tripulado(UAV) como caso de estudio. Estas técnicas son prometedoras para el control autónomo, ya que pueden aprender de entornosdinámicos sin intervención humana. La solución propuesta demuestra el comportamiento de un UAV entrenado para mantener laaltitud y evitar obstáculos dinámicos, como otros UAVs. Se usó el simulador AirSim para recrear un escenario de vuelo realistacon dos UAVs: uno controlado mediante RL y otro que intenta colisionar con él. Los resultados preliminares muestran quelas redes neuronales entrenadas con el algoritmo Soft Actor-Critic (SAC) pueden evitar colisiones, incluso en situaciones nocontempladas durante el entrenamiento. Aunque los resultados son prometedores, se requiere más investigación para garantizarel funcionamiento fiable del agent RL en entornos de tiempo real
Automated Image Analysis of CNS Cell Cultures Exposed to Microplastics
Full text linkThis study investigates the effects of polyethylene terephthalate (PET) and polypropylene (PP) micro- and nanoplastics on primary central nervous system (CNS) cell cultures containing neurons and glial cells. Cultures were continuously exposed for 28 days to PET and PP at 100 and 500 μg/mL. Phase-contrast microscopy images were acquired at multiple time points and analyzed using FIJI software to quantify non-cellular (void) areas and glial cell coverage. The most significant morphologicalalterations were observed in PET100 and PP500 conditions, showing increased void areas and glial proliferation compared tocontrols. These changes suggest a stress response consistent with glial reactivity. The method enabled non-invasive, longitudinalanalysis without affecting cell viability and demonstrated the value of phase-contrast imaging for toxicological assessment. The approach proved reproducible and scalable, supporting its use in mechanistic studies. Overall, the findings highlight the potentialneurotoxic impact of environmental microplastics and the usefulness of image-based tools for evaluating long-term effects in in vitro CNS models.Este estudio evalúa los efectos de micro- y nanoplásticos de tereftalato de polietileno (PET) y polipropileno (PP) sobre cultivos primarios de células del sistema nervioso central (SNC), compuestos por neuronas y células gliales. Las células fueron expuestas durante 28 días a concentraciones de 100 y 500 µg/mL de PET y PP. Las imágenes obtenidas mediante microscopía de contraste de fases se analizaron con FIJI para cuantificar áreas vacías y la proliferación glial. Los resultados mostraron que PET100 y PP500 provocaron las alteraciones morfológicas más significativas, con aumento de zonas sin células y de células gliales, lo que sugiere una respuesta de estrés celular asociada a reactividad glial. La metodología aplicada permitió un seguimiento no invasivo a lo largo del tiempo, sin afectar la viabilidad celular. Estos hallazgos subrayan el potencial impacto neurotóxico de los microplásticos y respaldan el uso del análisis automatizado de imágenes como herramienta útil para evaluar contaminantes ambientales en modelos in vitro del SNC
Soft deformable surface based on origami structures
Full text linkThe present paper proposes a design for a deformable surface using hexagonal origami modules based on the Kresling pattern. These modules function as structural elements and deformation sensors, with the capacity to detect external loads. The experimental validation process involves a series of tests. These include the configuration of modules in different arrangements, the evaluation of static behavior under controlled loads, and the analysis of dynamic object movement. The findings of the study demonstrate the viability and effectiveness of origami modules for sensorised surfaces, highlighting their potential across a range of practical applications.Este trabajo presenta el diseño de una superficie deformable compuesta por módulos hexagonales de origami basados en el patrón de Kresling. Estos módulos actúan simultáneamente como elementos estructurales y sensores de deformación, con la capacidad de detectar cargas externas aplicadas sobre la superficie. El proceso de validación experimental incluye una serie de pruebas. Entre ellas figuran la configuración de los módulos en diferentes topologías, la evaluación del comportamiento estático bajo cargas controladas y el análisis del movimiento dinámico de objetos. Los resultados obtenidos demuestran la viabilidad y efectividad de los módulos de origami para la implementación de superficies deformables sensorizadas, destacando su potencial en una variedad de aplicaciones
Desafíos en manipulación robótica inteligente en laboratorios autónomos
Full text linkSelf-driving labs (SDLs) represent an innovative approach that combines artificial intelligence, process automation, robotics, and materials science. These environments are designed to perform experiments without direct human intervention, significantly accelerating the discovery and optimization of new materials. This article presents the general components of an SDL, describing their functionality, dependencies, and interactions with each other to perform chemical experiments. Within these components, one of the fundamental blocks is robotic manipulation, which allows experimental tasks to be executed in a precise, repeatable, and efficient manner. Programmable robotic arms perform operations such as liquid dispensing, compound mixing, sample transfer, and instrument cleaning, replacing tasks traditionally performed by human technicians. Therefore, this article also identifies the main challenges in intelligent robotic manipulation required for the optimal functioning of SDLs.Los laboratorios autónomos o self-driving labs (SDL) representan un enfoque innovador que combina inteligencia artificial, automatización de procesos, robótica, y ciencia de materiales. Estos entornos están diseñados para realizar experimentos sin intervención humana directa, acelerando significativamente el descubrimiento y optimización de nuevos materiales. En este artículo se presentan los componentes generales de un SDL, describiendo su funcionalidad, dependencia e interacción entre ellos para realizar los experimentos químicos. Dentro de estos componentes, uno de los bloques fundamentales es la manipulación robótica, que permite ejecutar tareas experimentales de manera precisa, repetible y eficiente. Los brazos robóticos programables realizan operaciones como dispensado de líquidos, mezcla de compuestos, transferencia de muestras, y limpieza de instrumental, reemplazando tareas tradicionalmente realizadas por técnicos humanos. Por ello, este artículo también identifica los principales desafíos en manipulación robótica inteligente requerida para el óptimo funcionamiento de SDL