Resultados de investigación

Datos extraídos a partir de un formulario de google.forms, [ES]Los datos corresponden a las respuestas de 80 participantes, estudiantes universitarios, a una tarea de asociación léxica y definición de 56 neologismos derivados organizados por sufijos y con distintos grados de transparencia morfológica y frecuencia de uso. Para cada palabra presentada, los participantes llevaron a cabo una doble tarea: 1) Escribir palabras relacionadas con el derivado proporcionado, ya fuera por compartir lexema o sufijo. 2) Definir el significado del neologismo con sus propias palabras y sin consultar el diccionario., Esta investigación forma parte del proyecto GRAMADÍS, con referencia PID2023-149351NB-I00, financiado por el Ministerio de Ciencia, Innovación y Universidades, la Agencia Estatal de Investigación y el Fondo Europeo de Desarrollo Regional (MCIU /AEI /10.13039/501100011033 / FEDER, UE) dentro del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023.

The dataset consists of a single relational database organized into a set of core tables, catalog tables and a metadata table. The database implements a normalized schema designed to represent spatially explicit forest inventory, climatic and satellite-derived information for the Spanish territory. This dataset integrates and derives from multiple third-party open-access datasets. The authors have performed original data curation, harmonization, and derivation, resulting in a new, value-added dataset. The original data sources listed below, in accordance with their respective attribution requirements. Spanish National Forest Inventory (IFN) Ministerio para la Transición Ecológica y el Reto Demográfico (MITECO) (2025). Spanish National Forest Inventory (Inventario Forestal Nacional). Government of Spain. Available at: https://www.miteco.gob.es/es/biodiversidad/temas/inventarios-nacionales/inventario-forestal-nacional.html NASADEM Merged Digital Elevation Model (Global 1 arc second V001) Provided by NASA JPL and archived at the NASA Land Processes Distributed Active Archive Center (LP DAAC). Elevation data were accessed and processed via Google Earth Engine. https://doi.org/10.5067/MEaSUREs/NASADEM/NASADEM_HGT.001 ERA5-Land climate data (Copernicus / ECMWF) Muñoz Sabater, J. (2019). ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store. https://doi.org/10.24381/cds.e2161bac Landsat 5 U.S. Geological Survey (USGS). Landsat 5 Thematic Mapper Level-2, Collection 2, Tier 1. Accessed via Google Earth Engine. Available at: https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LT05_C02_T1_L2 Landsat 7 U.S. Geological Survey (USGS). Landsat 7 Enhanced Thematic Mapper Plus Level-2, Collection 2, Tier 1. Accessed via Google Earth Engine. Available at: https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LE07_C02_T1_L2, [EN]This dataset contains an integrated forest, climate and satellite-derived database for Spain based on Spanish National Forest Inventory, Copernicus and NASA data. It characterizes the evolution of Spanish forests through plots distributed across the national territory that have been inventoried on four occasions from 1986 to the present., This work was supported by the International Chair Project on Trustworthy Artificial Intelligence and the Demographic Challenge within the framework of the National Artificial Intelligence Strategy (ENIA). Reference: TSI-100933-2023-0001. Funded by the Secretary of State for Digitalization and Artificial Intelligence and by the European Union (NextGenerationEU)., This dataset contains an integrated forest, climate and satellite-derived database for Spain based on Spanish National Forest Inventory, Copernicus and NASA data. It characterizes the evolution of Spanish forests through plots distributed across the national territory that have been inventoried on four occasions from 1986 to the present.

Approved by CEIm Hospital Universitario y Politécnico La Fe (protocol #2024-0422-1), [EN]Objectives This study aims to assess the prognostic value of routinely available haematological inflammatory indices—neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and platelet-to-lymphocyte ratio (PLR)—for predicting 90-day functional outcome measured by the modified Rankin Scale (mRS) in patients with acute ischaemic stroke treated with reperfusion/recanalisation therapies. A further objective is to integrate these biomarkers with relevant clinical, laboratory and imaging covariates to develop predictive models and to explore whether associations remain consistent across clinically meaningful subgroups (e.g., stroke aetiology, occlusion site and reperfusion success). Conclusions Overall, LMR emerges as a reliable and readily accessible predictor of post-stroke functional outcome following reperfusion-treated ischaemic stroke, with higher LMR values associated with a greater likelihood of a favourable 90-day outcome. By contrast, NLR and PLR show less consistent prognostic performance. Incorporating LMR into multivariable prognostic models may improve risk stratification and support more personalised post-acute care decisions., PID2021-125211OB-I00 (Ministerio de Ciencia e Innovación, España) RD21/0006/0014 (ISCIII – RICORS-ICTUS, España) SA2117P23 (Junta de Castilla y León, España), PREDICTUS.xlsx PREDICTUS_processed_full.csv PREDICTUS_processed_models.csv PREDICTUS_data_dictionary.csv README_PREDICTUS.txt

[EN]This paper develops an actionable interdisci-plinary model that quantifies and assesses uncertainties in water resource allocation under climate change. To achieve this objective, we develop an innovative socio-ecological grand ensemble that combines climate, hydrological, and mi-croeconomic ensemble experiments with a widely used deci-sion support system for water resource planning and manage-ment. Each system is populated with multiple models (multi-model), which we use to evaluate the impacts of multiple cli-mate scenarios and policies (multi-scenario, multi-forcing) across systems so as to identify plausible futures where wa-ter management policies meet or miss their objectives and to explore potential tipping points. The application of the meth-ods is exemplified by a study conducted in the Douro River basin (DRB), an agricultural basin located in central Spain. Our results show how marginal climate changes can trigger non-linear water allocation changes in the decision support systems (DSSs) and/or non-linear adaptive responses of ir-rigators to water shortages. For example, while some irriga-tors barely experience economic losses (average profit and employment fall by < 0.5 %) under mild water allocation re-ductions of 5 % or lower, profit and employment fall by up to 12 % (∼ 24 ×) when water allocation is reduced by 10 %or less (∼ 2×). This substantiates the relevance of informing the potential natural and socio-economic impacts of adapta-tion strategies and related uncertainties for identifying robust decisions.

[EN]This dataset contains primary data collected from a sample of 1,006 university students at the University of Salamanca (Spain) during the post-pandemic recovery period. The data collection focused on gathering information regarding self-perceived health, lifestyle habits, and psychological well-being in the higher education context. The dataset includes the following groups of variables: Socio-demographic data: Gender, age, and academic field. Health-related lifestyle habits: Dietary patterns, sleep quality, tobacco and alcohol consumption, and physical activity levels. Psychological and health perception: Self-perceived depression, changes in mental health during the pandemic, suicidal ideation, and use of sleep medication. Help-seeking indicators: Perceived need for psychological help, whether the student considered using university support services, and history of attendance at general therapy. All data has been fully anonymized to ensure the privacy and confidentiality of the participants. The structure of the data allows for the study of associations between behavioral patterns and mental health outcomes in the university population.

[ES]La influencia del aprendizaje autorregulado sobre el rendimiento académico se ha estudiado desde diferentes perspectivas y contextos. Sin embargo, pocos estudios han abordado su influencia sobre la satisfacción del alumnado en contextos de aprendizaje relacionados con la divulgación científica. Analizamos la influencia del aprendizaje autorregulado (motivación y estrategias de aprendizaje) en la satisfacción de estudiantes universitarios con la preparación de un artículo de divulgación científica en grupo. Participaron 83 estudiantes universitarios que completaron un cuestionario de aprendizaje autorregulado (MSLQ) y dos cuestionarios ad hoc que evaluaban la satisfacción con el trabajo de divulgación (interacción grupo y contenido). Los resultados mostraron niveles altos de satisfacción con la interacción y el contenido del trabajo de divulgación, mostrando valores promedio superiores a ocho sobre diez. Además, respecto a las dimensiones de aprendizaje autorregulado analizadas, se observó que la motivación influyó en la satisfacción con el contenido del trabajo en los estudiantes con un menor uso de estrategias de aprendizaje. Se discuten las implicaciones de los resultados en el contexto educativo.

[EN]Este dataset recopila de forma exhaustiva los nombres propios de persona y de lugar presentes en la obra poética de Kim Chunsu (김춘수), así como los sustantivos vinculados a accidentes geográficos, edificaciones, espacios domésticos, nociones de posición y dirección, el cuerpo humano y el tiempo. La recogida y categorización de los datos se ha realizado con el objetivo de analizar la construcción del espacio poético y el valor simbólico del uso de los topónimos como recurso poético. Estos datos han servido como base empírica para la investigación doctoral 김춘수 시의 공간 인식과 지명(地名)의 의미 연구 (2020), dirigida por el Dr. Shin Bumsoon, y para estudios posteriores como Pungto of Sense, Pungto of Poetry – Focusing on the Pungto Imagery of Kim Chunsu (Chunwon Research Journal, vol. 16) y Lugares del recuerdo en la poesía tardía de Kim Chunsu (ACTIO NOVA, núm. 6). El dataset se presenta como una sólida base para investigaciones que indaguen en las conexiones sistemáticas que se establecen entre lenguaje, espacio, tiempo y memoria en la poesía de Kim Chunsu o en la literatura en general., KGSP (Korean Government Scholarship Program), Datos 데이터 Lugares concretos 장소 (지명) Personajes 인물

Este conjunto de datos (en formato SPSS .sav) contiene los resultados de un estudio de casos y controles retrospectivo de 10 años (2002-2011). Incluye datos sociodemográficos, puntuaciones del Test de Memoria Conductual Rivermead (RBMT) y medidas de quejas de memoria pre y post-entrenamiento de 145 participantes mayores de 60 años., [ES]Objetivos: El objetivo principal de la investigación fue evaluar si un programa integral de entrenamiento de memoria, diseñado originalmente para personas mayores sanas, es igualmente efectivo en individuos con deterioro de memoria grave. Específicamente, se buscó analizar cambios en la memoria cotidiana mediante pruebas objetivas y medidas subjetivas de quejas de memoria. Conclusiones: Los resultados indican que tanto el grupo con deterioro como el grupo de control mejoraron significativamente su rendimiento en tareas de memoria cotidiana y redujeron sus quejas subjetivas tras el entrenamiento. Se destaca que el grupo con deterioro mostró una mejoría superior en tareas de memoria prospectiva en comparación con el grupo sano. En conclusión, estos programas son herramientas eficaces para personas mayores con pérdidas de memoria severas, Ayuntamiento de Salamanca (organizador y patrocinador de los talleres de memoria)., Dataset del estudio incluyendo nombre y datos de las variables recogidas en el estudio.

Here is the English version of the abstract, optimized for international repositories (like Zenodo, IEEE Dataport, or Kaggle) using standard terminology in Digital Pathology and Computer Vision: 📝 Dataset Abstract Title Suggestion: Automated Cervical Cytology Screening: A Labeled WSI Patch Dataset for Deep Learning-Based Object Detection. Abstract: The automated detection of cellular structures using Deep Learning models represents a key strategy to optimize cervical cancer screening by reducing clinical workload and inter-observer variability. However, analyzing Whole Slide Images (WSI) presents critical challenges, including the scarcity of high-quality annotations, high morphological complexity, and significant class imbalance. This dataset addresses these limitations by providing a collection of 640×640px image patches extracted from conventional Papanicolaou (Pap) tests from a Colombian clinical cohort. The data was processed through a semi-automated pipeline integrating manual annotation in QuPath, automated patch extraction, and YOLO label generation via Groovy and Python scripts. To ensure high diagnostic reliability, a web-based expert validation interface was implemented for final label verification. This resource supports the development of robust computer vision models aimed at enhancing precision and efficiency in digital cytological diagnosis., [EN]This dataset contains labeled image patches extracted from Colombian Whole Slide Images (WSIs) of conventional Papanicolaou (Pap) tests. It supports the training and validation of object detection models (e.g., YOLO) in automated cervical cytology diagnosis. The patches (640×640px JPGs) were extracted and labeled using a semi-automated pipeline combining manual annotation in QuPath and automated patch extraction and YOLO label generation via Groovy and Python scripts. A web-based expert validation interface was used to ensure label accuracy., This work was supported by the Secretaría Distrital de Salud de Bogotá (Colombia) and the ATENEA Agency (grant number 368-2022), in collaboration with the Spanish Ministry for Digital Transformation and Civil Service through the University-Enterprise Chair Call (Cátedras ENIA 2022) (Grant TSI-100933-2023-1), co-funded by the European Union NextGenerationEU/PRTR., 1. File List: ✓ JPG patches (640x640) ✓ YOLO-format labels (.txt) ✓ Visual validated patches (.jpg with bounding boxes) ✓ Metadata snapshots (.csv) ✓ Logs of processed annotations (.txt) 2. Relationship between files, if important: Each patch corresponds to a label file. Patches and labels are grouped by class. Visual validated images are derived from the patch-label pair. 3. File format: ✓ Images: .jpg ✓ Labels: .txt (YOLO format) ✓ Logs/Snapshots: .csv, .txt

https://www.sciencedirect.com/journal/studies-in-educational-evaluation, [ENG]This code contains the complete R analysis code used to produce all results, tables, and figures reported in the associated publication. The code implements sample construction, achievement growth and mobility analysis, Matthew-effect regression models with CR2 cluster-robust standard errors, and quasi-binomial logistic regression for SES gradients in upward mobility. Analyses use publicly available data from the TIMSS 2023 Longitudinal International Database (Grade 4–5 component, nine education systems).