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Assessing Forest Structure and Biomass with Multi-Sensor Remote Sensing: Insights from Mediterranean and Temperate Forests
Get PDF19 p.Forests provide habitat for diverse species and play a key role in mitigating climate change. Remote sensing enables efficient monitoring of many forest attributes across vast areas, thus supporting effective and efficient management strategies. This study aimed to identify an effective combination of remote sensing sensors for estimating biophysical variables in Mediterranean and temperate forests that can be easily translated into an operational context. Aboveground biomass (AGB), canopy height (CH), and forest canopy cover (FCC) were estimated using a combination of optical (Sentinel-2, Landsat) and radar sensors (Sentinel-1 and TerraSAR-X/TanDEM-X), along with records of past forest disturbances and topography-related variables. As a reference, lidar-derived AGB, CH, and FCC were used. Model performance was assessed not only with standard approaches such as out-of-bag sampling but also with completely independent lidar-derived reference datasets, thus enabling evaluation of the model?s temporal inference capacity. In Mediterranean forests, models based on optical imagery outperformed the radar-enhanced models when estimating FCC and CH, with elevation and spectral indices being key predictors of forest structure. In contrast, in denser temperate forests, radar data (especially X-band relative heights) were crucial for estimating CH and AGB. Incorporating past disturbance data further improved model accuracy in these denser ecosystems. Overall, this study underscores the value of integrating multi-source remote sensing data while highlighting the limitations of temporal extrapolation. The presented methodology can be adapted to enhance forest variable estimation across many forest ecosystems.Ministerio de Ciencia, Innovación y UniversidadesAgencia Estatal de Investigación (AEI
Diseño de un nivómetro multisensor para un monitor de neutrones
Get PDFLos monitores de neutrones son esenciales para estudiar la radiación cósmica y su interacción con la atmósfera. En la base antártica española Juan Carlos I, las mediciones de uno de estos dispositivos se ven alteradas por la acumulación de nieve, que por su contenido en hidrógeno modera neutrones y compromete la fiabilidad de los datos.
Este trabajo presenta un nivómetro multisensor para monitorizar con precisión la nieve sobre el monitor. El sistema integra sensores ultrasónicos HC-SR04P, sensores de peso HX711 con células de carga y un microcontrolador ESP32 con transmisión MQTT, permitiendo estimar densidad y corregir registros científicos.Neutron monitors are essential for studying cosmic radiation and its interaction with the atmosphere. At the Spanish Antarctic base Juan Carlos I, the measurements of one of these devices are affected by snow accumulation, since its hydrogen content moderates neutrons and compromises data reliability.
This project presents a multisensor snow gauge designed to accurately monitor snow accumulation on the monitor. The system integrates HC-SR04P ultrasonic sensors, HX711 weight sensors with load cells, and an ESP32 microcontroller with MQTT transmission, enabling snow density estimation and scientific data correction.Grado en Ingeniería Telemátic
Romantic beliefs in pre-service teachers in Colombia
Get PDFEsta investigación analizó las creencias románticas en docentes en
formación en Colombia, considerando su relación con un conjunto de variables
individuales, ideológicas y socioculturales como sexo, religiosidad, ideología
política, percepción del machismo, posicionamiento feminista y consumo de
pornografía. Participaron 446 docentes en formación (65.5% mujeres, 33%
hombres, 1.6% que se identificó con la categoría 'otro”; M = 22.20 años, SD = 4.53).
Se aplicó la Escala de Creencias Románticas (ECR) mediante un cuestionario
estructurado y autoadministrado. Aunque no se encontraron diferencias
significativas globales entre hombres y mujeres, los hombres mostraron mayor
aceptación de ciertas creencias específicas, como los celos como prueba de amor,
la necesidad de pareja para la felicidad y la entrega total en la relación. La
religiosidad y el posicionamiento feminista emergieron como predictores
significativos en los análisis de regresión. Los hallazgos destacan la influencia del
contexto sociocultural en la configuración de las creencias románticas y señalan la
necesidad de abordar estas ideas en la formación docente. Se recomienda
implementar intervenciones educativas que fomenten relaciones igualitarias y
cuestionen discursos que puedan justificar dinámicas violentas en las relaciones de
pareja.This study analyzed romantic beliefs among pre-service teachers in
Colombia, considering their relationship with a set of individual, ideological, and
sociocultural variables such as sex, religiosity, political ideology, perception of
machismo, feminist positioning, and pornography consumption. A total of 446 preservice teachers participated (65.5% women, 33% men, and 1.6% who identified
with the “other” category; M = 22.20 years, SD = 4.53). The Romantic Beliefs Scale
(RBS) was applied through a structured, self-administered questionnaire. Although no significant overall differences were found between men and women, men showed
greater endorsement of specific beliefs, such as jealousy as a sign of love, the need
for a partner to be happy, and total devotion in romantic relationships. Religiosity
and feminist positioning emerged as significant predictors in the regression
analyses. The findings highlight the influence of sociocultural context in shaping
romantic beliefs and underscore the need to address these ideas within teacher
education. Educational interventions are recommended to promote more egalitarian
relationships and challenge discourses that may justify violent dynamics in romantic
partnerships
Integrating static and dynamic hierarchical clustering and its application to retail segmentation
Get PDFThis paper focuses on an approach to address large-scale data gathered from heterogeneous sources by integrating static and dynamic data in hierarchical clusterization, and its application to the analysis of retail branches. Traditionally, branch clustering analysis has relied on static information and the utilization of statistical measures to extract relevant features from the dynamic data and incorporate them into the static dataset; however, the application of this approach presents several challenges. This research proposes a solution that addresses these disadvantages while aiming to maintain the success achieved when applying unsupervised machine learning algorithms. The paper presents an approach based on the integration of static attributes and time series data in a hierarchical clustering manner that enables the identification of key performance indicators and offers insight into factors that influence branch performance over time. The results show the potential to optimize resource allocation, inventory management, and customer service strategies. The proposed approach is demonstrated using retail shop data from a Spanish telecommunications company (Grupo Masmovil), highlighting its effectiveness in enhancing cluster profiling and offering meaningful insights beyond the prevailing approaches. This method presents significant enrichment for clustering analysis that can be applied to different domains
Dancing towards inclusion : The integration of students with Ataxic Cerebral Palsy
Get PDFEste presente Trabajo de Fin de Máster aborda el uso del baile como herramienta
de inclusión educativa en un niño con parálisis cerebral atáxica, más concretamente la
ataxia de Friedreich, una enfermedad neurodegenerativa.
El trabajo destaca la importancia de la psicomotricidad como base de un desarrollo integral para las habilidades motrices del alumnado con discapacidad motora.
Desde la perspectiva de la educación inclusiva, se propone una propuesta pedagógica centrada en actividades previas a la creación de un baile de manera adaptada con el objetivo de que sea una práctica inclusiva, trasformadora y accesible para todos de tal manera que el aprendizaje sea significativo, favoreciendo al bienestar del alumno que padece la patología como al grupo al que pertenece.Máster Universitario en Atención a la Diversidad y Apoyos Educativos (M121
A.-M. Cheny, Le cercle des byzantinistes. Comment bibliothécaires, savants et voyageurs inventèrent Byzance (XVIe-XIXe siècle), avec Préface de Marie-France Auzépy, Paris, Les Belles Lettres, 2024, 304 pp. (43 illustrations couleurs, Index, Glossaire). [ISBN: 978-2-251-45578-5] [Reseña de libro]
Get PDFReseña de libro: PÉREZ MARTÍN, I. A.-M. Cheny, Le cercle des byzantinistes. Comment bibliothécaires, savants et voyageurs inventèrent Byzance (XVIe-XIXe siècle), avec Préface de Marie-France Auzépy, Paris, Les Belles Lettres, 2024, 304 pp. (43 illustrations couleurs, Index, Glossaire). [ISBN: 978-2-251-45578-5]
Interpreter training for gender-based violence settings. A study on their preparedness for cases of psychological abuse and the use of related emerging terms
Get PDFEn el mundo globalizado en el que vivimos, el contacto con personas inmigrantes de diferentes
culturas es ya una realidad, principalmente en el ámbito de los servicios públicos. La interacción
en estos casos se vuelve especialmente compleja cuando se trabaja con colectivos vulnerables,
como son las mujeres inmigrantes, sobre todo en situaciones delicadas, como aquellas
relacionadas con la violencia de género psicológica. En estos contextos, la figura del intérprete
adquiere un papel esencial, ya que no solo debe facilitar la comunicación entre partes que no
comparten un mismo idioma, sino también interpretar conceptos y términos emergentes que, en
muchos casos, pueden no existir o concebirse de forma distinta en las culturas de origen de las
víctimas.
Por tanto, el trabajo del intérprete en estos escenarios implica una gran responsabilidad, y exige
una preparación especializada. Se trata de contextos en los que confluyen marcos culturales
muy distintos, barreras lingüísticas y situaciones personales extremadamente delicadas. En este
sentido, parece evidente la necesidad de que los intérpretes que trabajan en estos ámbitos
cuenten con una formación específica, profunda, actualizada y adaptada a las exigencias de este
tipo de intervenciones.
El objetivo principal de este estudio es precisamente evaluar el tipo de formación que reciben
actualmente los intérpretes de servicios públicos que trabajan en contextos de violencia
psicológica, con especial atención a su preparación para afrontar los retos terminológicos y
conceptuales emergentes, con el fin de valorar si dicha formación es suficiente o si existen
carencias que deben ser atendidas. Para alcanzar este objetivo, se ha diseñado una metodología
mixta, basada en la difusión de una encuesta anónima dirigida a los profesionales del sector,
con la intención de obtener datos representativos empíricos que permitan reflexionar sobre el
estado actual de la formación y sus posibles áreas de mejoraWe live in an increasingly globalised world, in which interaction with immigrant individuals
from different cultural backgrounds has become a reality, mainly within the field of public
services. Communication in such cases becomes especially complex when working with
vulnerable groups, such as immigrant women, especially in delicate situations such as those
involving psychological gender-based violence. In these contexts, the interpreter plays a crucial
role. They must not only facilitate communication between parties who do not share a common
language, but also interpret emerging terms and concepts that may not exist or may be
understood differently in the victims’ cultures of origin.
Therefore, interpreting in these scenarios entails a great deal of responsibility and requires
specialised preparation. These are contexts where widely different cultural frameworks,
language barriers, and extremely sensitive personal circumstances converge. Hence, there is a
clear need for interpreters working in such settings to get specific, deep, up-to-date training that
is suited to the demands of these kinds of intervention.
The main objective of this study is, in fact, to evaluate the kind of training that is currently
offered to public service interpreters working in contexts of psychological violence, with
particular attention to their preparedness for addressing emerging terminological and
conceptual challenges. The aim is to assess whether such training is enough or whether there
are shortcomings that need to be addressed. In order to achieve this goal, a mixed methodology
has been designed, based on the dissemination of an anonymous survey directed at professionals
from this field, with the aim of obtaining representative empirical data that will enable the
assessment of the current state of interpreter training and its potential areas for improvementMáster Universitario en Comunicación Intercultural, Interpretación y Traducción en los Servicios Públicos. Especialidad en Inglés-Español (M198
Evolution and perspectives in IT governance: a systematic literature review
Get PDFThe study presents a systematic review of the state of the art on Information Technology (IT) governance research. Following the PRISMA 2020 protocol and drawing on Scopus and Web of Science, covering publications from 1999 to May 2025, 380 relevant articles were identified, analysed and categorised. A bibliometric analysis supported by tools such as VOSviewer and SciMaT mapped the principal thematic strands, influential authors and institutions, and revealed research gaps. The results indicate a consolidated field in which resource allocation, industrial management, strategic alignment and board-level IT governance operate as driving themes, while information management, the configuration of the IT function and the regulatory nexus between laws and information security remain emerging areas. The conclusions emphasise the theoretical implications of clarifying how IT governance shapes IT investment and initiative prioritisation, sectoral configurations and strategic alignment, and the practical implications of using these mechanisms to design and refine governance structures, processes and metrics in regulated organisations so that value creation risk control and accountability are more explicitly aligned
Predicting weather-related power outages in large scale distribution grids with deep learning ensembles
Get PDFLos eventos meteorológicos son los principales responsables de las interrupciones en el suministro eléctrico, lo que pone de manifiesto la necesidad de predecir con precisión estos cortes de energía relacionados con el clima. Este artículo se centra en la predicción de las incidencias diarias reportadas en redes eléctricas dentro de regiones específicas, utilizando las condiciones meteorológicas como variables predictivas clave. Para la selección de las ubicaciones óptimas de nodos de Reanálisis empleados como predictores, se ha considerado un enfoque de selección de características basado en optimización. Con el fin de superar el problema del desbalance de datos y mejorar la precisión de la predicción, se propone un algoritmo en conjunto basado en Aprendizaje Profundo (DL). Se consideran cinco arquitecturas DL distintas, generando múltiples aprendices individuales con hiperparámetros seleccionados aleatoriamente. La diversidad se garantiza entrenando cada modelo con conjuntos de datos ligeramente diferentes, obtenidos mediante muestreo aleatorio. Tres técnicas de fusión de información se utilizan para construir los modelos finales en conjunto. El enfoque propuesto ha sido evaluado con éxito en la predicción de incidencias diarias reales reportadas en líneas de distribución de dos provincias españolas, Valencia y Albacete, logrando una predicción precisa de los días con incidencias extremas, al tiempo que mantiene un buen rendimiento global y una baja tasa de falsas alarmas. Los modelos con mejor desempeño que emplean esta metodología alcanzan tasas de detección del 38 % y del 73 %, con tasas de falsas alarmas del 1 % y del 3 %, respectivamente. Este enfoque no solo mejora la precisión de la predicción en comparación con los aprendices individuales, sino que también incrementa la capacidad de generalización y la robustez de los modelos DL independientes. Además, reduce de manera efectiva el sobreajuste inherente a estos métodos, eliminando la necesidad de un proceso complejo de selección de hiperparámetros.Weather events are primarily contributors to electrical supply disruptions, prompting the need to accurately forecast these weather-related power outages. This paper focuses on predicting daily reported incidences in electrical grids within specific regions, leveraging weather conditions as specific predictive variables. An optimization-based feature selection approach has been considered for selecting the optimal Reanalysis node locations used as predictors. To overcome the data imbalance challenge and enhance prediction accuracy, we propose a Deep Learning-based (DL) ensemble algorithm. Five distinct DL architectures are considered, generating multiple individual learners with randomly selected hyperparameters. Diversity is ensured by training each model with slightly different randomly sampled data. Three information fusion techniques construct the final ensemble models. The proposed approach has been successfully evaluated in predicting real daily reported incidences in distribution lines across two Spanish provinces, Valencia and Albacete, achieving an accurate prediction of days with extreme incidences while maintaining a good overall performance and a low rate of false alarms. The top-performing models using this methodology achieve detection rates of 38% and 73%, with false alarm rates of 1% and 3%, respectively. This approach not only enhances prediction accuracy compared to individual learners but also improves the generalization ability and robustness of standalone DL models. Additionally, it effectively reduces the inherent overfitting of these methods, removing the necessity for a complex hyperparameter selection process.Agencia Estatal de Investigació
Micromotors for antimicrobial resistance bacteria inactivation in water systems: opportunities and challenges
Get PDFThe intensive use of antibiotics and the inadequate removal in water treatment plants have contributed to the phenomena of antimicrobial resistance. Bacterial colonies and biofilms present in water distribution and aquatic systems respond to the presence of antibiotics by the generation of resistance genes and other determinants transmitted through the environment. In this perspective, we identify the opportunities and challenges of self-propelled micromotors in the fight against antimicrobial resistance by the elimination of antibiotics and bacteria in water. Recent progress is contextualized in the current scenario in terms of bacteria and antibiotics found in real settings and current removal technologies. As illustrated in this perspective, the unique features of micromotors result in a high surface area to-mass ratio for enhanced degradation capabilities, for both antibiotic removal and bacteria biofilm inactivation, as compared with static current technologies. The autonomous movement of micromotors allows us to reach more volumes of water and even hard-to-access areas, offering great opportunities to reach hard-to-access pipelines, not accessible by current approaches. Yet, as envisioned in this perspective, micromotors are far away from real applications, hampered mainly by the main challenges of the treatment of high-water volumes. We also advocate scientists to include in the proof-of-concept studies real water and the evaluation of a major number of antibiotics and bacteria commonly found in real settings, as will be described in this perspective. Micromotors hold considerable promise as a holistic approach to fight antimicrobial resistance, but cross-discipline collaborations are a must to translate the recent progress into real practical applications.Ministerio de Ciencia, Innovación y Universidade