Los nuevos retos de la universidad en la sociedad de la información requieren un cambio importante en sus canales de formación rígidos. Los formatos de inteligencia artificial prometen una importante mejora en el aprendizaje a todos los niveles de formas cualitativas incomparables: permiten al docente personalizar la educación de acuerdo con las necesidades del alumno, así como integrar las diversas formas de interacción humana y IA. en el nuevo milenio. En que el director de la nueva universidad tiene el reto de planificar, diseñar, desarrollar y aplicar urgentemente habilidades digitales para formar unos profesionales que sean capaces de comprender y desarrollar el entorno tecnológico según sus necesidades.

Background and Objectives: Brain Tumor Fusion-based Segments and Classification-Non-enhancing tumor (BTFSC-Net) is a hybrid system for classifying brain tumors that combine medical image fusion, segmentation, feature extraction, and classification procedures. Materials and Methods: to reduce noise from medical images, the hybrid probabilistic wiener filter (HPWF) is first applied as a preprocessing step. Then, to combine robust edge analysis (REA) properties in magnetic resonance imaging (MRI) and computed tomography (CT) medical images, a fusion network based on deep learning convolutional neural networks (DLCNN) is developed. Here, the brain images’ slopes and borders are detected using REA. To separate the sick region from the color image, adaptive fuzzy c-means integrated k-means (HFCMIK) clustering is then implemented. To extract hybrid features from the fused image, low-level features based on the redundant discrete wavelet transform (RDWT), empirical color features, and texture characteristics based on the gray-level cooccurrence matrix (GLCM) are also used. Finally, to distinguish between benign and malignant tumors, a deep learning probabilistic neural network (DLPNN) is deployed. Results: according to the findings, the suggested BTFSC-Net model performed better than more traditional preprocessing, fusion, segmentation, and classification techniques. Additionally, 99.21% segmentation accuracy and 99.46% classification accuracy were reached using the proposed BTFSC-Net model. Conclusions: earlier approaches have not performed as well as our presented method for image fusion, segmentation, feature extraction, classification operations, and brain tumor classification. These results illustrate that the designed approach performed more effectively in terms of enhanced quantitative evaluation with better accuracy as well as visual performance.

En la actualidad, en donde se vive una crisis mundial de salud a causa de un virus llamado Covid-19, presentando un gran reto para el campo de la medicina y un cambio drástico en las vidas de las personas, se debe idear un modo diferente de poder llevar el duelo porque el virus sigue vigente en el entorno, además de haber perdido muchas vidas, no se permite realizar un duelo con el respeto y costumbre que se tiene en distintas culturas. A lo largo de la pandemia, se muestran momentos de angustia, dolor, depresión y caos; debiendo superar de manera drástica y resiliente. La presente investigación es de tipo mixta, exploratoria- descriptiva, cuyos resultados se realizan para el contexto académico mediante un muestreo aleatorio simple, en base al cálculo de la muestra y la predisposición de los encuestados de participar en forma voluntaria, teniendo como muestra a 261 personas entre jóvenes y adultos de 20 a más de 60 años. En conclusión, la resiliencia post pandemia se puede advertir en los encuestados que se encuentran proclives a un estado de depresión y ansiedad, el mismo que debe ser atendido por los especialistas brindando un apoyo psicosocial.

The field of energy harvesting is expanding to power various devices, including electric vehicles, with energy derived from their surrounding environments. The unique mechanical and electrical qualities of composite materials make them ideal for energy harvesting applications, and they have shown tremendous promise in this area. Yet additional studies are needed to fully grasp the promise of composite materials for energy harvesting in electric vehicles. This article reviews composite materials used for energy harvesting in electric vehicles, discussing mechanical characteristics, electrical conductivity, thermal stability, and cost-effectiveness. As a bonus, it delves into using composites in piezoelectric, electromagnetic, and thermoelectric energy harvesters. The high strength-to-weight ratio provided by composite materials is a major benefit for energy harvesting. Especially important in electric vehicles, where saving weight means saving money at the pump and driving farther between charges, this quality is a boon to the field. Many composite materials and their possible uses in energy harvesting systems are discussed in the article. These composites include polymer-based composites, metal-based composites, bio-waste-based hybrid composites and cement-based composites. In addition to describing the promising applications of composite materials for energy harvesting in electric vehicles, the article delves into the obstacles that must be overcome before the technology can reach its full potential. Energy harvesting devices could be more effective and reliable if composite materials were cheaper and less prone to damage. Further study is also required to determine the durability and dependability of composite materials for use in energy harvesting. However, composite materials show promise for energy harvesting in E.V.s. Further study and development are required before their full potential can be realized. This article discusses the significant challenges and potential for future research and development in composite materials for energy harvesting in electric vehicles. It thoroughly evaluates the latest advances and trends in this field.

El uso de inteligencia artificial ha superado el enfoque académico, y transciende por sus beneficios, que están orientados al desarrollo de la gestión pública. La presente investigación se realizó con el propósito de analizar la inteligencia artificial en la gestión pública en tiempos de Covid-19, específicamente se abordó la relevancia de las oportunidades, evaluación del impacto y el gran potencial ofrecido por la inteligencia artificial. La metodología que se utilizó refiere a una revisión documental en las siguientes bases científicas Scopus, Taylor & Francis, Wos, Ebsco y Scielo, lo cual proporciona un amplio e importante panorama general de la inteligencia artificial y su impacto sobre la gestión pública en tiempos de pandemia. Los resultados marcan ciertas claves para diseñar políticas y estrategias de uso de la inteligencia artificial en diferentes contextos de la gestión pública, mostrando las bondades y desafíos. Se concluye que la llegada de avances tecnológicos devela el alcance de la tecnología a la gestión pública, una diversidad de medios o instrumentos para su eficiencia e impacto colocan en funcionamiento, dando apoyo en el desarrollo de sistemas de control que otorgan legalidad y generan procesos democratizadores para la dirección pública.

Objective: This article, of a theoretical nature, was oriented to the contextual analysis referred to digital government, its origin, aspects, and trends; mainly, the way in which it was implemented and developed in some Latin American countries was emphasized, in addition to the reflections on the implications related to digital government in the current situation, as well as the challenges it has been facing and future challenges. Theoretical framework: The universe of more contemporary aspects regarding electronic government was explored from the perspective of state management, as well as the foundations on which it has been consolidating and the changes it has undergone and at the same time generated in its wide spectrum of applications. Design/Methodology/Approach: A descriptive systematic review has been implemented with the collection of various definitions, approaches and strategies in relation to electronic government. Based on the qualitative approach, the analysis and extraction of various articles with relevant information from various databases such as Scopus, Ebsco, ProQuest and Scielo was carried out; taking into account those of the last four years. Findings: The acceptance of electronic government processes was based on the characteristics of citizens and their attitude towards technology; public bodies continue to show a series of problems, among which a marked inability to resolve the duties effectively and efficiently in charge despite having the appropriate technological tools and implements stands out. Research, practical and social implications: Future efforts that seek not only electronic government, but also a scaffolding that supports the development of administration processes through TIC and new platforms based on artificial intelligence. Implications/Originality/Value: The real implementation of an electronic government requires, urges and forces cultural changes in society due to the use of TIC and cutting-edge technological resources.