King Juan Carlos University
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Asistente de Inteligencia Artificial "GamifIcA Edu"
No full textGamifIcA Edu es un asistente de Inteligencia Artificial que asesora al docente en la creación de actividades gamificadas y Juegos Serios, adaptándose a los requerimientos marcados por el/la docente para la actividad. Dispone de una amplia base de conocimiento consistente en libros académicos de referencia y guías sobre creación de actividades gamificadas y Juegos Serios.
El uso de inteligencia artificial generativa (IAG) ha abierto nuevas oportunidades en educación. Sin embargo, la falta de competencias digitales puede ser un obstáculo para su adopción. En este estudio, presentamos "GamifIcA Edu", un asistente basado en GPT diseñado para ayudar a los docentes a implementar gamificación y juegos serios sin necesidad de conocimientos avanzados de ingeniería de prompts. Hemos evaluamos su efectividad mediante una rúbrica aplicada a cinco escenarios educativos distintos.
Se presentan dos casos de uso en los que el usuario define la actividad gamificada que desea desarrollar, y GamifIcA Edu crea de forma completa la actividad ajustándose a los requerimientos del docente.
Se puede acceder de forma gratuita al uso del asistente GamifIcA Edu a través de este enlace: https://chatgpt.com/g/g-X5nOmZeVg-gamifica-ed
Developing Digital Competencies in the Social Science Classroom Through Storymaps and Digital Narratives
No full textThe publication focuses on geolocated digital narratives related to the school curriculum of Social Sciences and their practical application by future teachers of Primary and Secondary Education. In the academic year 2023- 2024, as part of an educational innovation project, it has been proposed to carry out an activity with university students to develop digital skills and learn the corresponding curriculum content, using ArcGIS StoryMaps. The activity proposal is presented, and its implementation is analyzed, also providing reflections from university teachers
who have implemented it in university classrooms and students’ opinions, aiming to consider potential future changes and improvements in the development of the innovation project
Digitalization intensity and its impact on financial performance: The role of scalable platforms
No full textThis research investigates the impact of digital platforms on financial and economic outcomes, emphasizing EBITDA, market capitalization, and the capacity for debt financing. The research illustrates that digital platforms enhance revenue streams while simultaneously decreasing operational expenditures, thereby leading to an overall enhancement in financial performance. Utilizing a dynamic panel data methodology, the results demonstrate the temporal impacts of digital platforms on key financial indicators. Furthermore, it explores the complex interplay between digital intensity and marginal benefits, offering practical ideas for companies seeking to enhance both scalability and funding opportunities. By analyzing differing levels of digital intensity, we illustrate how scalability influences financial margins and market capitalization. The results imply that organizations adopting digital platforms are more inclined to secure long-term economic viability and financing capability through improved efficiencies in data processing and strategic decision-making. However, investing in digitalization has an optimal point from where it shows diminishing returns
Immunological characterization of the rainbow trout bursa
No full textThe bursa of Fabricius is an immune organ, located in the caudo-dorsal surface of the cloaca, responsible for the development and maturation of avian B cells. A few years ago, a lymphoepithelial tissue placed caudal to the urogenital papilla of the cloaca analogous to the bursa was identified for the first time in Atlantic salmon (Salmo salar). The salmon bursa was demonstrated to involute around sexual maturation, as in birds. However, no primary lymphoid functions were identified in this tissue. In the current study, we have identified a homologous immune organ in rainbow trout (Oncorhynchus mykiss), a different salmonid species. This lymphoepithelium covering a blind sac, caudal to the anus, was identified in rainbow trout at different stages of development and it also experienced regression in an age-dependent way. It contained abundant IgM+ B cells and CD3+ cells and especially numerous was the number of MHC II-expressing cells. In contrast to Atlantic salmon, in rainbow trout, the bursa epithelium contained quite a few IgT+ B cells but very few IgD+ B cells. Thus, by flow cytometry, we could determine that the IgM+ B cells identified in the trout bursa had lost surface IgD expression. Interestingly, although an immunization of rainbow trout by bath barely had effects on the bursa at a transcriptional level, when fish were immunized anally with a model antigen, there were significant changes in the levels of transcription of immune genes in this tissue. These included secreted igm, secreted and membrane igd, bcma and prdm1-a2. Altogether these results evidence the existence of a bursa-like immune structure in another teleost species and provide novel information to understand the immune role of this tissue in fish, pointing to a relation to gut immune responses
Inteligencia artificial como respaldo a la aplicación de metodogías activas en Grados de Ingeniería y Arquitectura
No full textEl proyecto persiste el uso de las posibilidades de la Inteligencia Artificial (IA) generativa de texto para respaldar las acciones de gamificación desarrolladas en el marco del GID. En este sentido se ha hecho uso de estas posibilidades tecnológicas para generar material que posteriormente se ha usado en metodologías de gamificación, que ha tenido una muy buena acogida. Además, se ha fomentado un uso critico de estas tecnología
Transfer learning for a tabular-to-image approach: A case study for cardiovascular disease prediction
No full textObjective:
Machine learning (ML) models have been extensively used for tabular data classification but recent works have been developed to transform tabular data into images, aiming to leverage the predictive performance of convolutional neural networks (CNNs). However, most of these approaches fail to convert data with a low number of samples and mixed-type features. This study aims: to evaluate the performance of the tabular-to-image method named low mixed-image generator for tabular data (LM-IGTD); and to assess the effectiveness of transfer learning and fine-tuning for improving predictions on tabular data.
Methods:
We employed two public tabular datasets with patients diagnosed with cardiovascular diseases (CVDs): Framingham and Steno. First, both datasets were transformed into images using LM-IGTD. Then, Framingham, which contains a larger set of samples than Steno, is used to train CNN-based models. Finally, we performed transfer learning and fine-tuning using the pre-trained CNN on the Steno dataset to predict CVD risk.
Results:
The CNN-based model with transfer learning achieved the highest AUCORC in Steno (0.855), outperforming ML models such as decision trees, K-nearest neighbors, least absolute shrinkage and selection operator (LASSO) support vector machine and TabPFN. This approach improved accuracy by 2% over the best-performing traditional model, TabPFN.
Conclusion:
To the best of our knowledge, this is the first study that evaluates the effectiveness of applying transfer learning and fine-tuning to tabular data using tabular-to-image approaches. Through the use of CNNs’ predictive capabilities, our work also advances the diagnosis of CVD by providing a framework for early clinical intervention and decision-making support
Guía de Estudio Asignatura análisis de Balances
No full textGuía de estudio para las asignaturas en abierto de Análisis de Balance
Material docente: Práctica Voltámetro de Hoffman
No full textNueva Práctica de Laboratorio para poner en uso la correlación entre gas desprendido durante una hidrólisis del agua y la corriente que circula por un circuito, aplicando la primera Ley de Faraday, las cantidades de sustancias transformadas en la reacción de electrólisis del agua al aplicarle una corriente. Todo con el fin de estimar de la constante de Faraday
La medicina en televisión: implicaciones para la traducción. El caso del doblaje de las series sobre médicos
No full textEl presente estudio parte de la concepción de la traducción de productos audiovisuales médicos como un fenómeno comunicativo y social de masas con implicaciones directas en la labor traductora. Esta traducción médica audiovisual vendría caracterizada por una triple dimensión: terminológica, social y audiovisual. Emprendemos, pues, un estudio mediante el cual evaluamos la precisión y calidad de la versión doblada al español de una serie médica de habla inglesa. Para ello, sometemos un capítulo de la serie a un doble análisis: traductológico, comparando las réplicas de ambas versiones mediante las técnicas de traducción empleadas, y facultativo, mediante la elaboración de un cuestionario diseñado para conocer la valoración médica. Los datos obtenidos revelan un número importante de casos en los que se incumplen los parámetros de calidad terminológica y comunicativa, lo que resulta en un cierto grado de desacuerdo por parte de los facultativos respecto a la versión doblada
Hybrid silica materials functionalized with chloroxine-based metal complexes: Exploring synergistic antibacterial activity
No full textWe gratefully acknowledge financial support from the Ministerio de Universidades de España and the Resilience Funds Next Generation of the European Union (Margarita Salas Grant for A.A.G.-V.). We would also like to thank funding from Agencia Estatal de Investigación and Ministerio de Ciencia, Innovación y Universidades of Spain for the research project PID2022-136417NB-I00 financed by MCIU/AEI/10.13039/501100011033/and “ERDF A way of making Europe”, and from the Research Thematic Network RED2022-134091-T financed by MCIU/AEI/10.13039/501100011033. We would also like to acknowledge financial support from Gobierno Vasco/Eusko Jaurlaritza (IT1755-22).This study presents a novel strategy for developing advanced antibacterial materials by integrating coordination compounds with silica nanoparticles. Two new coordination compounds based on chloroxine, namely, {[Ni(chloroxine)2(H2O)2]·H2O} (1) and {[Zn(chloroxine)2(H2O)]·H2O} (2), were synthesized and subsequently used to functionalize mesoporous silica (SBA-15 and MSN) to create hybrid materials: SBA-(1)-Ni, SBA-(2)-Zn, MSN-(1)-Ni, and MSN-(2)-Zn. The Zn-based hybrids exhibited exceptional luminescence, while the Ni-based counterparts displayed the expected temperature-dependent magnetic susceptibility according to the loaded Ni amount. Antibacterial assessments against Escherichia coli and Staphylococcus aureus demonstrated a remarkable enhancement—up to 200% greater efficacy than free chloroxine, while MSN-(2)-Zn achieved the most potent minimum inhibitory concentration (MIC) of 3.96 μg/mL, demonstrating their multifunctional potential. These hybrid materials not only enhance antibacterial performance at lower drug concentrations but also offer a promising approach to combat bacterial resistance by enhancing the synergistic properties of silica and coordination compounds. This work encourages further investigation of the next generation of multifunctional antimicrobial materials based on nanomaterials and metallodrugs, with superior applications in biomedicine and nanotechnology