This paper introduces a new method of compressing digital images by using the Difference Transform applied in medical imaging. The Difference Transform algorithm performs the decorrelation process of image data, and in this way improves the encoding process, achieving a file with a smaller size than the original. The proposed method proves to be competitive and in many cases better than the standards used for medical images such as TIFF or PNG. In addition, the Difference Transform can replace other transforms like Cosine or Wavelet.

This article presents the comprehensive design and evaluation of a digital storytelling system tailored forchildren aged 4 to 6 in Latin America. This system is based on generative artificial intelligence.Tests were conducted encompassing the system’s functionality, content diversity, generation times,voice evaluation, intonation, speed, and pronunciation quality. The results confirm the system’s correctoperation and intuitive nature. The generated stories exhibit a high degree of diversity, as evidenced bythe calculation of Jaccard indices, with a maximum value of 0.2 observed in the evaluations of 30 analyzedstories. As anticipated, generation times increase with the length of the stories. It was determined thatthe voice best suited for storytelling is Onyx from OpenAI’s TTS. However, pronunciation errors werenoted in all TTS model voices. According to the conducted analysis, the system produces diverse stories that promote values among Spanish-speaking children, thus emphasizing the importance of inclusivity for individuals with different abilities. It is noteworthy that no inappropriate content for children was found in any of the stories

Introducción. Las estrategias didácticas utilizadas para la enseñanza y el aprendizaje de la programación de software son complejas porque se debe adquirir, codificar y recuperar información con base en el pensamiento lógico-matemático para diseñar instrucciones que serán ejecutadas por un ordenador con el fin de resolver problemas de diversa naturaleza. Esto justifica por qué estos contenidos tienen alta demanda en la educación superior de la actualidad, a pesar de que los índices de titulación sean, por el contrario, muy bajos. Objetivo. Proponer y evaluar estrategias didácticas generales y específicas para la enseñanza y aprendizaje de programación en software con el fin de crear una alternativa para disminuir los registros de bajo rendimiento y la deserción en las carreras que incluyan temas de la mencionada área. Método. Diseño cuasiexperiemtal, análisis cuantitativo no paramétrico, longitudinal (cuatro evaluaciones), con una muestra de 78 estudiantes de la carrera de ingeniería en Computación, con distribución al azar en dos grupos experimentales y dos grupos de control en escenarios de aulas inteligentes. Material. Programas de software con lenguajes C y C++ en plataforma educativa, así como uso de Autogradr y del Inventario de estrategias metacognitivas. Resultados. Se empleó una prueba de Kruskal-Wallis debido a que se tuvo una muestra sin distribución normal y con escala por jerarquías. Se observó la aceptación de la hipótesis nula en ambas pruebas: 1) H = 0.04, en rendimiento académico superior en los grupos experimentales, la interdependencia en conocimientos es regular alta 0.657, con diferencia de 1.7 en rendimiento promedio, y 2) H = 0.24, en estrategias metacognitivas superior en los grupos experimentales, la interdependencia en estrategias metacognitivas es baja 0.342. Se resalta el área de planificación como fase elemental para la solución de problemas. Conclusiones. Se demostró que la estrategia didáctica expuesta en tres bloques específicos de enseñanza y aprendizaje elevó el rendimiento académico y la metacognición de los estudiantes.

Raceway bioreactors are widely employed for microalgal production owing to their low construction and operational costs, in addition to their scalability benefits. Nonetheless, limited hydrodynamic studies are corroborated by computer models that have been experimentally validated. This paper delineates the methodology and validation of a computational fluid dynamics (CFD) model for a 10 L laboratory-scale Raceway bioreactor operating under abiotic conditions. In ANSYS Fluent, a multiphase technique was used with the RNG k–ε turbulence model, which is good for simulating flows that are curved or rotating in open-channels. Experimental validation was performed using Particle Image Velocimetry (PIV) at paddlewheel velocities of 20, 25, and 30 rpm. The CFD predictions showed a strong match with the experimental data, with a mean relative error of less than 8%. The examination of the flow field revealed the formation and subsequent reduction of low-velocity zones, depending on the intensity of agitation. Based on study on velocity distribution and Reynolds number, it was suggested that the design be changed so that the paddlewheel be moved to improve flow homogeneity without increasing energy use. The validated CFD model provides a reliable basis for improving the hydrodynamics, design, and operation of Raceway bioreactors. Additionally, it serves as a foundation for future research on biomass cultivation and expansion, facilitating the development of more efficient and sustainable microalgal production technologies.