Repositorio Universidad Internacional Iberoamericana
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Pupilometer efficacy in monitoring anxiety in undergraduate medical students during high-fidelity clinical simulation
No full textThe aim of the present work was to determine the correlation between the State-Trait Anxiety Inventory (STAI) score and pupillary diameter and whether this correlation exists to develop a predictive model of anxiety with the pupillary diameter of students exposed to high-fidelity clinical simulation. This was a randomized, blinded, simulation-based clinical trial. The study was conducted at the Advanced Clinical Simulation Center, Faculty of Medicine, Valladolid University (Spain), from February 1 to April 15, 2023, and involved volunteer sixth-year undergraduate medical students. The STAI score, vital signs (oxygen saturation, perfusion index, blood pressure, heart rate, and temperature), and pupillary response were assessed. The primary outcomes were the delta (pre/postsimulation) of the state STAI and the delta of the pupillary diameter. Sixty-one sixth-year students fulfilled the inclusion criteria. There was no difference regarding the clinical scenario. There was a statistically significant correlation between the state STAI score and pupillary diameter. The predictive model had an AUC of 0.876, with the delta diameter of the pupillary being the only statistically significant variable for anxiety prediction. Our results showed that both the pupillary response and the STAI score allowed the identification of students with disabling anxiety. These results could pave the way for appropriate protocol development that allows for personalized tutoring of students with elevated anxiety levels
Detection of cotton crops diseases using customized deep learning model
No full textThe agricultural industry is experiencing revolutionary changes through the latest advances in artificial intelligence and deep learning-based technologies. These powerful tools are being used for a variety of tasks including crop yield estimation, crop maturity assessment, and disease detection. The cotton crop is an essential source of revenue for many countries highlighting the need to protect it from deadly diseases that can drastically reduce yields. Early and accurate disease detection is quite crucial for preventing economic losses in the agricultural sector. Thanks to deep learning algorithms, researchers have developed innovative disease detection approaches that can help safeguard the cotton crop and promote economic growth. This study presents dissimilar state-of-the-art deep learning models for disease recognition including VGG16, DenseNet, EfficientNet, InceptionV3, MobileNet, NasNet, and ResNet models. For this purpose, real cotton disease data is collected from fields and preprocessed using different well-known techniques before using as input to deep learning models. Experimental analysis reveals that the ResNet152 model outperforms all other deep learning models, making it a practical and efficient approach for cotton disease recognition. By harnessing the power of deep learning and artificial intelligence, we can help protect the cotton crop and ensure a prosperous future for the agricultural sector
Percepción del Software GeoGebra en la Enseñanza- Aprendizaje de la Geometría en 4to Grado del Nivel Secundario
No full textEl estudio “Percepción del Software GeoGebra en la Enseñanza-Aprendizaje de la Geometría en 4to Grado del Nivel Secundario” analizó la percepción de los estudiantes sobre GeoGebra como herramienta para enseñar geometría en los politécnicos Juan Francisco Alfonseca y Miguel Ángel García Viloria, en Villa La Mata, República Dominicana. La investigación abordó la limitada efectividad de las metodologías tradicionales en la enseñanza de geometría, acentuada por la escasa integración de tecnologías educativas. Este enfoque ha generado desinterés en los estudiantes y evidenciado una falta de preparación docente en el uso de herramientas tecnológicas como GeoGebra. Así mismo, la insuficiencia de recursos tecnológicos en las escuelas fue un factor determinante que afectó los resultados. Metodológicamente, el estudio empleó un enfoque cuantitativo con diseño cuasi-experimental, utilizando observaciones, encuestas y cuestionarios diagnósticos y finales. La muestra incluyó estudiantes de 4to grado y docentes de los dos politécnicos. Los resultados evidenciaron que el uso de GeoGebra mejoró significativamente la percepción de los estudiantes hacia las tecnologías aplicadas al aprendizaje de geometría, incrementando su interés y comprensión de conceptos geométricos. Sin embargo, la resistencia al cambio en las metodologías y la falta de formación docente limitaron el impacto total de los resultados. Se concluyó que, GeoGebra se presenta como una herramienta prometedora para innovar en la enseñanza de la geometría, al promover un aprendizaje significativo y motivar a los estudiantes. No obstante, persisten retos como la carencia de infraestructura tecnológica y la insuficiente capacitación docente, los cuales dificultan su integración efectiva en el aula. Se recomienda invertir en tecnología, implementar programas de formación continua para docentes y promover políticas educativas que impulsen la innovación en los métodos de enseñanza
Eficiência Operacional e Financeira na Educação Básica Privada nas Regiões Norte e Nordeste do Brasil
No full textA pesquisa tem como objetivo conhecer as motivações das instituições de ensino privadas no Brasil de como obtêm melhorias contínuas de produtos e serviços para garantir a sua eficiência operacional e financeira. Considerando os inúmeros avanços tecnológicos e as diversas metodologias comerciais praticadas no mercado nacional e internacional, é vital investigar as melhores práticas de como atrair, fidelizar e reter estudantes em um cenário progressista e inovador. Outro ponto a ser considerado é observar a trilha de sobrevivência das empresas frente às transformações rápidas, planejadas, concisas, inovadoras, a ser integrada na era moderna. A decisão de investir em empreendedorismo e inovação é acreditar em mudanças, pelas quais fortalecem as relações com a sociedade, bem como produz soluções através do ensino e qualificação dos estudantes para o mercado de trabalho em uma sociedade que cada dia a régua de inteligência e habilidades aumentam nas exigências de pessoas capacitadas. Observar a disseminação dos direcionadores estratégicos com relação ao trabalho e as pessoas, do topo da pirâmide até a base operacional, bem como a governança e estratégia de sustentabilidade capaz de gerar valor ao cliente. Os procedimentos metodológicos serão fundamentados através de uma pesquisa de campo, a ser realizada em quinze instituições de ensino na Educação Básica localizadas na Região Geográfica do Nordeste no Estado do Ceará e Norte no Estado do Pará, considerando que as empresas possuem uma rede de ensino ativa nestas localidades. Almeja-se com a referida pesquisa proporcionar alternativas de gestão corporativa que possibilitem suprir as lacunas identificadas no desempenho operacional e financeiro das instituições de educação privadas. Pretende-se que essa pesquisa possa beneficiar outras Instituições educacionais, nos aspectos de captação, retenção e fidelização de alunos, potencializando o setor educacional
Methodology and content for the design of basketball coach education programs: a systematic review
No full textBackground: The increasing complexity of basketball and the need for optimal decision-making in order to maximize competitive performance highlight the necessity of specialized training for basketball coaches. This systematic review aims to compile, synthesize, and integrate international research published in specialized journals on the training of basketball coaches and students, examining their characteristics and needs. Specifically, it analyzes the content, technical-tactical actions, and methodologies used in practice and education programs to determine which essential parameters for their technical and tactical development.
Methods: A structured search was carried out following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA®) guidelines and the PICOS® model until January 30, 2025, in the MEDLINE/PubMed, Web of Science (WOS), ScienceDirect, Cochrane Library, SciELO, EMBASE, SPORTDiscus, and Scopus databases. The risk of bias was assessed and the PEDro scale was used to analyze methodological quality.
Results: A total of 14,090 articles were obtained in the initial search. After inclusion and exclusion criteria, the final sample was 23 articles. These studies maintained a high standard of quality. This revealed data on the technical-tactical actions addressed in different categories; the profiles, characteristics, and influence of coaches on player development; and the approaches, teaching methods, and evaluation methodologies used in acquiring knowledge and competencies for the professional development of basketball coaches.
Conclusions: Adequate theoretical and practical training for basketball coaches is essential for player development. Therefore, training programs for basketball coaches must integrate technical-tactical, physical, and psychological knowledge with the acquisition of skills and competencies that are refined through practice. This training should be continuous, more specialized, and comprehensive, focusing on understanding and constructing knowledge that supports the professional growth of basketballers. Additionally, training should incorporate digital tools and informal learning opportunities, with blended learning emerging as the most effective methodology for this purpose
Image-Based Dietary Energy and Macronutrients Estimation with ChatGPT-5: Cross-Source Evaluation Across Escalating Context Scenarios
No full textBackground/Objectives: Estimating energy and macronutrients from food images is clinically relevant yet challenging, and rigorous evaluation requires transparent accuracy metrics with uncertainty and clear acknowledgement of reference data limitations across heterogeneous sources. This study assessed ChatGPT-5, a general-purpose vision-language model, across four scenarios differing in the amount and type of contextual information provided, using a composite dataset to quantify accuracy for calories and macronutrients. Methods: A total of 195 dishes were evaluated, sourced from Allrecipes.com, the SNAPMe dataset, and Home-prepared, weighed meals. Each dish was evaluated under Case 1 (image only), Case 2 (image plus standardized non-visual descriptors), Case 3 (image plus ingredient lists with amounts), and Case 4 (replicates Case 3 but excluding the image). The primary endpoint was kcal Mean Absolute Error (MAE); secondary endpoints included Median Absolute Error (MedAE) and Root Mean Square Error (RMSE) for kcal and macronutrients (protein, carbohydrates, and lipids), all reported with 95% Confidence Intervals (CIs) via dish-level bootstrap resampling and accompanied by absolute differences (Δ) between scenarios. Inference settings were standardized to support reproducibility and variance estimation. Source stratified analyses and quartile summaries were conducted to examine heterogeneity by curation level and nutrient ranges, with additional robustness checks for error complexity relationships. Results and Discussion: Accuracy improved from Case 1 to Case 2 and further in Case 3 for energy and all macronutrients when summarized by MAE, MedAE, and RMSE with 95% CIs, with absolute reductions (Δ) indicating material gains as contextual information increased. In contrast to Case 3, estimation accuracy declined in Case 4, underscoring the contribution of visual cues. Gains were largest in the Home-prepared dietitian-weighed subset and smaller yet consistent for Allrecipes.com and SNAPMe, reflecting differences in reference curation and measurement fidelity across sources. Scenario-level trends were concordant across sources, and stratified and quartile analyses showed coherent patterns of decreasing absolute errors with the provision of structured non-visual information and detailed ingredient data. Conclusions: ChatGPT-5 can deliver practically useful calorie and macronutrient estimates from food images, particularly when augmented with standardized nonvisual descriptors and detailed ingredients, as evidenced by reductions in MAE, MedAE, and RMSE with 95% CIs across scenarios. The decline in accuracy observed when the image was omitted, despite providing detailed ingredient information, indicates that visual cues contribute meaningfully to estimation performance and that improvements are not solely attributable to arithmetic from ingredient lists. Finally, to promote generalizability, it is recommended that future studies include repeated evaluations across diverse datasets, ensure public availability of prompts and outputs, and incorporate systematic comparisons with non-artificial-intelligence baselines
Estrategia pedagógica para la incorporación de la educación artística como eje transversal en la formación inicial docente que ofrece la Universidad Pedagógica Nacional Francisco Morazán de Honduras
No full textLa educación artística es un tema que actualmente toma fuerza en el discurso educativo mundial, especialmente en Latinoamérica, por su demostrada influencia en el desarrollo integral de las personas, lo que se manifiesta en el aprendizaje, porque entre otros factores estimula la motivación, atención, memoria, imaginación, creatividad e ingenio. Al ser integrada con otras asignaturas potencializa el fomento de la curiosidad, sentimientos de sorpresa, la investigación, el pensamiento reflexivo, expresión y comunicación. Existe evidencia científica que respalda la idea de que la educación artística, según Herrera (2022) es una herramienta neuro-educativa, que puede ser integrada en estrategias que ponen en práctica los docentes en procesos educativos de las diferentes áreas del conocimiento con muy buenos resultados. El estudio se enmarca en el paradigma pragmático, con un enfoque mixto, y diseño explicativo secuencial, transversal. Los resultados generaron datos empíricos que indican que la educación artística está presente en catorce planes de estudio de la universidad, en nueve de manera electiva y en otros cinco de manera obligatoria, pero no se declara el uso del arte como línea transversal ni se visualizan estrategias para fortalecerla. Los resultados estadísticos revelan una percepción positiva de los directivos, docentes y estudiantes de la UPNFM integrantes de la muestra, respecto a la importancia que estos le dan a la educación artística, lo que constituye un área de oportunidad para el desarrollo de la estrategia pedagógica y aunque el grupo focal expresó que históricamente no se ha dado formalidad e importancia a esta área, se detectó la existencia de algunos profesores que están utilizando elementos de la educación artística en las materias que imparten. Estas iniciativas individuales que se han desarrollado, se consideran positivas, y se han incorporado a la estrategia pedagógica que se presenta para darle un carácter más interdisciplinar a la educación artística en el diseño curricular de la universidad
Factores que influyen en la implementación de metodologías estandarizadas de gestión de proyectos en las empresas privadas de la ciudad de Santiago, República Dominicana.
No full textLa gestión de proyectos es fundamental en la administración de empresas, ya que permite planificar, ejecutar y controlar proyectos de manera eficiente. Aunque la implementación de metodologías estandarizadas de gestión de proyectos es una práctica consolidada a nivel mundial, en la ciudad de Santiago, República Dominicana, su adopción ha sido limitada. A pesar de los beneficios que estas metodologías aportan, como la mejora en la eficiencia, calidad y rentabilidad de los proyectos, diversas barreras han impedido su plena implementación en las empresas privadas de la región. Esta investigación se centró en identificar y analizar los factores que obstaculizan la adopción de metodologías estandarizadas de gestión de proyectos en las empresas privadas de Santiago. A través de un estudio mixto, utilizando entrevistas y cuestionarios aplicados a empresarios y gerentes de proyectos de 57 empresas, se han identificado las principales barreras: falta de liderazgo comprometido, resistencia al cambio y deficiencias en la formación especializada del personal. Estas barreras limitan la adopción efectiva de las metodologías en muchos casos. Los resultados también revelaron que un porcentaje significativo de las empresas, especialmente las grandes, están comenzando a implementar estas metodologías, pero enfrentan desafíos organizacionales y culturales importantes. Asimismo, se han propuesto mejores prácticas para superar estos desafíos, las cuales se consideran soluciones potenciales a futuro, dado que su implementación completa requeriría más tiempo para validar su viabilidad. Los hallazgos de esta investigación proporcionan una comprensión más clara de los obstáculos a los que se enfrentan las empresas locales, ofreciendo una base sólida para futuras investigaciones que puedan medir la efectividad de las soluciones propuestas. Se espera que este estudio aporte valor a las empresas de Santiago y contribuya al conocimiento sobre la implementación de metodologías estandarizadas en contextos empresariales similares, facilitando su aplicación en otras regiones y sectores
Edge-Based Autonomous Fire and Smoke Detection Using MobileNetV2
No full textForest fires pose significant threats to ecosystems, human life, and the global climate, necessitating rapid and reliable detection systems. Traditional fire detection approaches, including sensor networks, satellite monitoring, and centralized image analysis, often suffer from delayed response, high false positives, and limited deployment in remote areas. Recent deep learning-based methods offer high classification accuracy but are typically computationally intensive and unsuitable for low-power, real-time edge devices. This study presents an autonomous, edge-based forest fire and smoke detection system using a lightweight MobileNetV2 convolutional neural network. The model is trained on a balanced dataset of fire, smoke, and non-fire images and optimized for deployment on resource-constrained edge devices. The system performs near real-time inference, achieving a test accuracy of 97.98% with an average end-to-end prediction latency of 0.77 s per frame (approximately 1.3 FPS) on the Raspberry Pi 5 edge device. Predictions include the class label, confidence score, and timestamp, all generated locally without reliance on cloud connectivity, thereby enhancing security and robustness against potential cyber threats. Experimental results demonstrate that the proposed solution maintains high predictive performance comparable to state-of-the-art methods while providing efficient, offline operation suitable for real-world environmental monitoring and early wildfire mitigation. This approach enables cost-effective, scalable deployment in remote forest regions, combining accuracy, speed, and autonomous edge processing for timely fire and smoke detection
Nut Consumption Is Associated with Cognitive Status in Southern Italian Adults
No full textBackground: Nut consumption has been considered a potential protective factor against cognitive decline. The aim of this study was to test whether higher total and specific nut intake was associated with better cognitive status in a sample of older Italian adults. Methods: A cross-sectional analysis on 883 older adults (>50 y) was conducted. A 110-item food frequency questionnaire was used to collect information on the consumption of various types of nuts. The Short Portable Mental Status Questionnaire was used to assess cognitive status. Multivariate logistic regression analyses were performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between nut intake and cognitive status after adjusting for potential confounding factors. Results: The median intake of total nuts was 11.7 g/day and served as a cut-off to categorize low and high consumers (mean intake 4.3 g/day vs. 39.7 g/day, respectively). Higher total nut intake was significantly associated with a lower prevalence of impaired cognitive status among older individuals (OR = 0.35, CI 95%: 0.15, 0.84) after adjusting for potential confounding factors. Notably, this association remained significant after additional adjustment for adherence to the Mediterranean dietary pattern as an indicator of diet quality, (OR = 0.32, CI 95%: 0.13, 0.77). No significant associations were found between cognitive status and specific types of nuts. Conclusions: Habitual nut intake is associated with better cognitive status in older adults