Resultados de investigación

Este estudio examinó el efecto moderador de la cohesión familiar, la expresividad y el conflicto sobre las relaciones entre la inteligencia emocional, la satisfacción con la vida y la ideación suicida entre los adolescentes españoles. La muestra la formaron un total de 2.722 adolescentes de 12 a 18 años (Edad = 14,11, s.d. = 1,42; 52,8% chicas). Los efectos de la interacción fueron significativos: el conflicto familiar mitigó los efectos de la inteligencia emocional sobre la satisfacción con la vida, y la cohesión y expresividad familiar fortalecieron los efectos de la inteligencia emocional sobre la ideación suicida. Estos hallazgos proporcionan evidencia adicional del papel protector de la cohesión familiar y la expresividad en la ideación suicida de los adolescentes, y el papel dañino del conflicto familiar en el bienestar de los adolescentes. Los resultados implican que mejorar la cohesión familiar y la expresividad y reducir los conflictos familiares puede ser una forma prometedora de reforzar el vínculo entre la inteligencia emocional y la satisfacción con la vida y de prevenir la ideación suicida entre los adolescentes., Universidad de Málaga Grupo PAIDI Applied Positive Lab CTS-1048 (Junta de Andalucía) Proyecto I+D+i del Ministerio de Ciencia e Innovación de España (PID2020-117006RB-I00)

Problematic smartphone use (PSU) has been widely studied, and recent research has examined the affective and cognitive process risk factors that underlie its development and maintenance. Based on the Interaction of Person–Affect–Cognition–Execution model for problematic internet use, the present study analyzed the mediating role of cognitive emotion regulation strategies in the link between depressive symptomatology and PSU severity in adolescents. The sample consisted of 2,197 adolescents aged 12 to 19 years from southern Spain, who completed self-report questionnaires of depressive symptoms (Depression Anxiety Stress Scale–21), cognitive emotion regulation strategies (Cognitive Emotion Regulation Strategies Questionnaire), and PSU severity (Smartphone Addiction Scale–Short Version). We used the SPSS PROCESS macro to conduct parallel mediation analyses. The results demonstrated significant indirect/mediation effects from depressive symptoms to PSU severity through cognitive emotion regulation strategies, including other-blame, catastrophizing, rumination (i.e., maladaptive), and refocus on planning (i.e., adaptive). The implications of this study include that specific teaching about these strategies may help reduce PSU severity in adolescents., Universidad de Málaga (PPIT.UMA.A2.2019, PPIT.UMA.D2.2022) Grupo PAIDI Applied Positive Lab CTS-1048 (Junta de Andalucía) Proyecto I+D+i del Ministerio de Ciencia e Innovación de España (PID2020-117006RB-I00) Fondos FEDER/Junta de Andalucía (UMA 18-FEDERJA-147)

These data derived from the proyect PID2020-115954RB-I00: Interacción entre la virulencia de nodavirus y la respuesta inmune innata en dorada y lubina (INTERNODASS), and they have been published in: Moreno P, J Gemez-Mata, D Alvarez-Torres, E Garcia-Rosado, J Bejar, MC Alonso (2023) Genomic characterization and transcription analysis of European sea bass (Dicentrarchus labrax) rtp3 genes. Molecular Immunology, 163, 243-248. (doi: 10.1016/j.molimm.2023.10.009) Moreno P, D Alvarez-Torres, E Garcia-Rosado, J Bejar, MC Alonso (2026) Functional assessment of European sea bass RTP3 proteins and their effect on RGNNV replication. Fish and Shellfish Immunology, 168, 111002 (https://doi.org/10.1016/j.fsi.2025.111002), European sea bass rtp3 genes: in vivo transcriptional study and in vitro functional characterization

This dataset contains aerial images of cellular base stations captured using an Unmanned Aerial Vehicle (UAV). The images are used to train and evaluate YOLO-based object detection models for automatic identification of base station infrastructure.

- [The full description of the dataset can be found at: https://www.uma.es/robotics-and-mechatronics/info/124594/sar-datasets/ ] - Collection of multimodal raw data captured from a manned all-terrain vehicle in the course of two realistic outdoor search and rescue (SAR) exercises for actual emergency responders conducted in Málaga (Spain) in 2018 and 2019: the UMA-SAR dataset. The sensor suite, applicable to unmanned ground vehicles (UGVs), consisted of overlapping visible light (RGB) and thermal infrared (TIR) forward-looking monocular cameras, a Velodyne HDL-32 three-dimensional (3D) lidar, as well as an inertial measurement unit (IMU) and two global positioning system (GPS) receivers as ground truth. Our mission was to collect a wide range of data from the SAR domain, including persons, vehicles, debris, and SAR activity on unstructured terrain. In particular, four data sequences were collected following closed-loop routes during the exercises, with a total path length of 5.2 km and a total time of 77 min. In addition, we provide three more sequences of the empty site for comparison purposes (an extra 4.9 km and 46 min). Furthermore, the data is offered both in human-readable format and as rosbag files, and two specific software tools are provided for extracting and adapting this dataset to the users’ preference. The review of previously published disaster robotics repositories indicates that this dataset can contribute to fill a gap regarding visual and thermal datasets and can serve as a research tool for cross-cutting areas such as multispectral image fusion, machine learning for scene understanding, person and object detection, and localization and mapping in unstructured environments., This work has been performed in the frame of the project “TRUST-ROB: Towards Resilient UGV and UAV Manipulator Teams for Robotic Search and Rescue Tasks,” funded by the Spanish Government (grant number RTI2018-093421-B-I00) and project UMA18-FEDERJA-090 funded by the Andalusian Regional Government (Junta de Andalucía)

Aunque investigaciones previas han indicado que las habilidades emocionales afectan sustancialmente al bienestar ocupacional y la motivación del profesorado, los estudios que examinan las posibles vías por las cuales la inteligencia emocional se relaciona con la satisfacción laboral y con la intención de abandono son escasos. El presente estudio ha examinado un modelo de mediación serial incluyendo un recurso personal, i.e., inteligencia emocional, como un predictor de los recursos laborales (i.e., apoyo percibido de colegas y supervisores), satisfacción laboral e intención de abandono. Un total de 1.079 profesionales de la enseñanza (651 mujeres, Medad = 44.07 años) ha participado en este estudio. Los niveles de enseñanza del profesorado incluyen: preescolar, primaria y secundaria. Se ha analizado un modelo de mediación serial mediante la macro PROCESS de SPSS (modelo 80). Los resultados han apoyado un modelo que muestra que mayores niveles de inteligencia emocional se asocian con una menor intención de abandono docente a través de dos vías indirectas: (a) una mayor satisfacción laboral y (b) un mayor apoyo percibido de supervisores seguido de una mayor satisfacción laboral. Este estudio contribuye a la comprensión de cómo los recursos personales y contextuales pueden permitir que el profesorado se sienta satisfecho en el trabajo y menos propenso a considerar el abandono., Universidad de Málaga Grupo PAIDI Applied Positive Lab CTS-1048 (Junta de Andalucía) Proyecto I+D+i del Ministerio de Ciencia e Innovación de España (PID2020-117006RB-I00) Fondos FEDER/Junta de Andalucía (UMA 18-FEDERJA-147) Ayudas postdoctorales “Juan de la Cierva-Formación” del Ministerio de Ciencia, Innovación y Universidades de España (FJC2019- 038942-I/AEI/10.13039/501100011033)

All data are own production except for ieee118.raw, Transient Stability Constrained Optimal Power Flow (TSCOPF) is a nonlinear optimization problem used to perform economic dispatches while ensuring transient stability. This paper proposes a multi-contingency TSCOPF model that retains the dynamics of all generators and includes a transient synchronous generator dq-axis model. Program write_tscopf.py automatically reads the system data from standard PSSE raw files, builds the TSCOPF model tscopf.gms on high-level modelling system GAMS and solves it using a non-heuristic Interior Point algorithm. This approach facilitates the application of the model to a variety of systems and scenarios. Data for the New England 39 Bus System and the IEEE 118 Bus system are included.

The database consists of FIR images collected from a vehicle driven in outdoors urban scenarios. Images were acquired with an Indigo Omega imager, with a resolution of 164x129 pixels, a grey-level scale of 14 bits, and focal length of 318 pixels. The camera was mounted on the exterior of the vehicle, to avoid infrared filtering of the windshield. Recorded images were manually annotated, where each pedestrian is labelled as a bounding box. To prevent bias introduced by border artifacts their height is subsequently upscaled by 5%. The pedestrians appear in an up-right position., The dataset is divided in two: (i) Classification dataset: positives and randomly sampled negatives with a fixed height-width ratio of (1/2) and rescaled to 64x32 pixels, and (ii) Detection Dataset: Original positive and negative images with annotations., The classification Database is divided in a Train and a Test subset. The Train set contains 10208 positives and 43390 negatives, while the Test set contains 5944 positives and 22050 negatives. The annotated bounding boxes are resized to a constant aspect ratio (w/h) = 0.5 by changing their width appropriately. Any bounding box below 10 pixels in height is ignored. The remaining bounding boxes are resized to 64x32 pixels using bilinear interpolation. The negative samples were randomly selected from images not containing pedestrians.

Dataset of the paper: Carretero-Gómez, A., Piedra-Muñoz, L., 2021. Sustainability of non-renewable resources: The case of marble in Macael (Spain), Extractive Industries and Society, 8: 100876, doi: 10.1016/j.exis.2021.01.011. Link: https://www.sciencedirect.com/science/article/abs/pii/S2214790X21000113. 2214-790X