Leticia del Carmen Ríos Rodríguez

Background: The aim of this study was to analyse whether narcissistic facets and indicators of the need for social validation predict behaviours related to ‘selfie’ addiction among students at the Autonomous University of Zacatecas (UAZ), Mexico, using a preliminary, adapted version of the NPI-40. Methods: An empirical, cross-sectional, non-experimental, correlational-predictive study was conducted with 255 students aged between 14 and 23, selected via convenience sampling. The adjusted NPI-40, the Psychometric Scale on Selfie Addiction, and six indicators of social validation and Instagram usage were employed. The data were analysed using exploratory factor analysis with a polychoric matrix and hierarchical linear regression. Results: The results revealed a preliminary structure comprising three factors and two observed composites of the adjusted NPI-40: authority, agentic grandiosity, exploitation, vanity, and exhibitionism. Behaviours related to selfie addiction were primarily associated with exhibitionism, exploitation, frequency of posting on Instagram and sensitivity to negative comments. The final model explained 29.5% of the variance. Conclusions: It is concluded that the relationship between narcissism, social validation and selfie addiction is not homogeneous and should therefore be analysed by facets.

Background: The relationship between selfie addiction and narcissism in students at the Universidad Autónoma de Zacatecas (UAZ, Autonomous University of Zacatecas), Mexico, was analysed. The aim of this study was to identify the narcissistic factors associated with students’ selfie taking addiction. Methods: To identify the relationship between narcissism and selfie addiction, the Narcissistic Personality Inventory (Adapted NPI-40) and the Psychometric Selfie Addiction Scale (PSAS) were used. A structural equation model (SEM) was employed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used for structural validation. EFA and CFA confirmed adequate fit and reliability indicators regarding the robust unidimensional structure of the PSAS. Results: The SEM results indicated significant associations between the latent dimensions of the narcissistic traits of superiority, authority, need for admiration, exhibitionism, and exploitation and selfie addiction. This research provides structural and psychometric evidence for the relationship between narcissism and selfie addiction in the Mexican student population, integrating Adapted NPI-40 and PSAS, as well as a parsimonious explanatory structural equation model that demonstrates the relationship between different narcissistic traits and social media practices. Conclusions: The results provide a basis for developing digital literacy interventions for young people and future cross-validations.

Artificial Intelligence in Education is expanding rapidly, yet the adaptation of chatbots to specific reading-comprehension levels remains underexplored. This mixed-methods study presents Lectobot, a conversational agent designed to provide personalized scaffolding across three levels of reading comprehension (literal, inferential, and critical). First, we conducted a diagnostic assessment with first-year undergraduates (N = 58) using validated instruments: COMPLECsec (reading comprehension), EMA (Academic Motivation Scale), and MARSI (Metacognitive Strategies). Non-parametric analyses (Kolmogorov–Smirnov; Mann–Whitney U with Benjamini–Hochberg adjustment) indicated wide heterogeneity in comprehension (median global accuracy ≈ 55%) and a predominance of extrinsic motivation, with selective use of problem-solving strategies. These findings informed design rules for Lectobot (text selection, adaptive task difficulty, and strategy prompts). In a five-week implementation with a focus group (n = 8), semi-structured interviews were transcribed and coded in MAXQDA, guided by the Technology Acceptance Model (perceived usefulness and ease of use). Students perceived Lectobot as useful for text understanding and synthesis and moderately easy to use; reported difficulties were mainly technical (access and session continuity), leading to actionable design improvements. We discuss ethical and practical implications for personalized scaffolding in higher education and outline avenues for larger-scale evaluations and broader grade levels.

Background: The relationship between the dimensions of selfie addiction and narcissism in students at the Universidad Autónoma de Zacatecas (UAZ, Autonomous University of Zacatecas), Mexico, was analysed. The aim of this study was to identify the factors of narcissism associated with students' addictive behaviour towards selfies. Methods: To identify the relationship between narcissism and selfie addiction, the NPI-40 Narcissistic Personality Inventory and the Psychometric Selfie Addiction Scale (PSAS) were used. This was done using a Structural Equation Modelling (SEM). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to carry out the structural validation process. EFA and CFA confirmed adequate fit and reliability indicators regarding the robust multidimensional structure of the Selfie Addiction Scale. Results: SEM indicated that narcissistic traits predict selfie addiction. It also indicated that there is body objectification and appearance comparison through social media. This research provides important findings on recent structural and psychometric evidence in the Mexican student population, as it integrates the NPI-40 and PSAS, as well as a parsimonious explanatory Structural Equation Modelling that demonstrates the relationship between narcissistic traits and social media practices. Conclusions: The results provide a basis for developing digital literacy interventions for young people and future cross-validations.

Objetivo: El objetivo de la investigación es desarrollar un convertidor electrónico de potencia aplicando la tecnología multinivel que cumpla con los requerimientos de seguridad, eficiencia y calidad de generación de energía para interconexión a la red eléctrica. Marco Teórico: El Marco Teórico se basa en un análisis del estado del arte del tema de investigación para conocer los resultados científicos actuales de las diferentes tendencias en el desarrollo de inversores multinivel para sistemas interconectados a la Red Eléctrica. Método: La metodología adoptada para esta investigación fue el hipotético deductivo. Como hipótesis consideramos que es posible mejorar la eficiencia y calidad de la energía eléctrica en inversores multinivel utilizando la técnica de control por eliminación selectiva de armónicos (SHE), para reducir la distorsión armónica total (THD) durante la interconexión a la red. Resultados y Discusión: Los pruebas y resultados obtenidos a lo largo del desarrollo del proyecto bajo diferentes condiciones de cargas, permitieron conocer el comportamiento del prototipo de inversor multinivel desarrollado en condiciones reales usando arreglos de paneles fotovoltaicos para la interconexión a la Red Eléctrica. Implicaciones de la investigación: Se analizaron diferentes topologias de inversores multinivel para definir cual es la que mejor se adapta a las especificaciones del caso de estúdio. Originalidad/Valor: La relevancia y valor de esta investigación se evidencia en el desarrollo e implementación de un prototipo de inversor multinivel interconectado a la Red Eléctrica de gran valor para la docencia y para el sector industrial, el cual satisface los requerimientos, prescindiendo de importaciones costosas.

Objectives: This study aims to identify a reliable prediction model for Mexico's wholesale electricity market to prevent supply-demand imbalances by analyzing three machine learning models with conformal prediction techniques. Theoretical Framework: Electricity demand forecasting traditionally uses SARIMAX models or artificial neural networks (ANN)/deep learning (DL). However, SARIMAX models are sensitive to data perturbations, while ANN/DL models face interpretability and computational challenges. Decision tree-based models (LGBM and CatBoost) have emerged as alternatives, offering potential advantages for time series prediction. Method: The study analyzed electricity demand data from CENACE (2018-2022), using four years for training and one for validation. Model performance was evaluated using MAPE, MAE, MSE, RMSE, and R² metrics, along with Conformal Prediction metrics for uncertainty quantification. Results and Discussion: CatBoost demonstrated superior performance (MAPE: 1.85%, R²: 0.9) compared to LGBM and SARIMAX models. SARIMAX showed significant limitations in prediction accuracy, particularly during seasonal variations. LGBM achieved intermediate performance with acceptable accuracy (R²: 0.89). Research Implications: The LGBM and CatBoost models achieved MAPE values within the literature's benchmark range (0.4-3%) while requiring fewer computational resources than complex DL models, making them practical alternatives for electricity demand forecasting. Originality/Value: This research pioneers the application of three prediction models with conformal prediction techniques in the Mexican electricity market context, offering probabilistic guarantees for prediction validity instead of traditional point predictions.

Objective: Reflect on the actions of the entrepreneur and the actions of the knowledge worker as functions of the educational researcher according to the current historical epoch. Theoretical Framework: Both functions have as main support the theory 'Knowledge Society'. They are also implicit in the theories 'Post-industrial society' and 'Information society'. Method: The content of the work is part of the results of the qualitative research 'The educational researcher in the knowledge and information societies'. Based on the sources of consultation is theoretical, interpretative analysis, descriptive approach and oriented to the professional practices of the educational researcher. Results and Discussion: The main result revolves around the differences on the functions specified in the contract and employment appointment whose characteristic is that they are carried out within the contracting institution, in relation to acting as an entrepreneur and knowledge worker, which, in addition to being freely chosen, are developed by conviction, professional ethics and social commitment, without omitting that they develop outside the labor institution. Implications of the research: The professional practices of the educational researcher are not reduced or restricted to the functions specified in the contract and employment appointment. For this reason, acting as an entrepreneur and knowledge worker are functions that must, have and can be developed by the educational researcher and by other educational actors of the Mexican educational system. Regardless of the fact that few researchers carry out both functions, the results benefit the educational researcher, the formation of human capital, the labor institution and society. Most of the obstacles to developing them are found in the regulations of the administrative bureaucracy. Originality/Value: This work contributes to the literature on the educational researcher and aims to invite the educational and institutional authorities, educational actors and mainly the educational researcher to incorporate the functions as part of the professional practices that correspond to them because both are in accordance with the current historical era and the benefits and advantages they offer to society.

In recent years, machine and deep learning models have attracted significant attention for electricity price forecast in global wholesale electricity markets. Yet, a predominant focus on point forecast in most parts of literature limits the practical application of these models due to the absence of uncertainty quantification. In this study, we first perform an analysis of the electricity price trends in the Mexican wholesale electricity market to determine the influence of key variables. Using independent component analysis and wavelet coherence analysis, we were able to identify primary determinants influencing locational marginal electricity prices. Subsequently, we applied four different models covering the most important algorithms proposed in the literature for electricity price forecast. Our findings revealed that the most accurate forecasting results were achieved using a deep learning‐based method with a decision tree‐based model trailing closely. Finally, we incorporate conformal prediction for uncertainty quantification by calculating the prediction intervals with a target coverage level of 95%. The conformal prediction intervals provide a more comprehensive view of the possible future scenarios, enhancing economic efficiency, risk management, and decision‐making processes. This is particularly important because of the dynamic nature of electricity markets, where prices are strongly influenced by multiple factors.

In this article, a prototype of a low power wind turbine interconnected to the NETWORK and the controlled electronic converter for the rectification of the generated voltage was designed, which is used for the conditioning of the electrical power generated by low power wind systems for the Connection to the electric grid. Using different electronic components and free hardware development boards, the construction of a controlled three-phase rectifier prototype was carried out, divided into 3 modules, the first one in charge of obtaining a reference signal and synchronization of the voltage to be rectified, the second is the control circuit, which performs the time calculations for the activation of the third module, in charge of rectifying the triphasic voltage using thyristors (SCR), in which the moment of activation of the semiconductors can be controlled. Finally, tests of the prototype connected to a wind turbine built by teachers and students of the Technological University of Campeche were carried out, verifying its correct operation in the rectification of the voltage delivered by this generator. En este artículo se diseñó un prototipo de aerogenerador de baja potencia interconectado a la RED y el convertidor electrónico controlado para la rectificación del voltaje generado, el cual se utiliza para el acondicionamiento de la energía eléctrica generada por sistemas eólicos de baja potencia para la conexión. a la red eléctrica. Utilizando diferentes componentes electrónicos y placas de desarrollo de hardware libre se realizó la construcción de un prototipo de rectificador trifásico controlado, dividido en 3 módulos, el primero encargado de obtener una señal de referencia y sincronización del voltaje a rectificar, el segundo es el circuito de control, que realiza los cálculos de tiempo para la activación del tercer módulo, encargado de rectificar la tensión trifásica mediante tiristores (SCR), en el cual se puede controlar el momento de activación de los semiconductores. Finalmente, se realizaron pruebas del prototipo conectado a un aerogenerador construido por docentes y estudiantes de la Universidad Tecnológica de Campeche, verificando su correcto funcionamiento en la rectificación del voltaje entregado por este generador. Neste artigo foi projetado um protótipo de turbina eólica de baixa potência interligada à REDE e o conversor eletrônico controlado para a retificação da tensão gerada, que é utilizado para o condicionamento da energia elétrica gerada por sistemas eólicos de baixa potência para a Conexão à rede elétrica. Utilizando diferentes componentes eletrônicos e placas de desenvolvimento de hardware livre, foi realizada a construção de um protótipo de retificador trifásico controlado, dividido em 3 módulos, sendo o primeiro responsável pela obtenção do sinal de referência e sincronização da tensão a ser retificada, o segundo é o circuito de controle, que realiza os cálculos de tempo para acionamento do terceiro módulo, encarregado de retificar a tensão trifásica através de tiristores (SCR), nos quais pode ser controlado o momento de acionamento dos semicondutores. Por fim, foram realizados testes do protótipo conectado a um aerogerador construído por professores e alunos da Universidade Tecnológica do Campeche, verificando seu correto funcionamento na retificação da tensão entregue por este gerador.

This article analyzes different architectures with which a neural network can be developed using computer vision with the objective of detecting traffic accidents. For the development of the software, the Java Script programming language was used, reaching the conclusion that the best architecture to use is a Convolutional Neural Network since it has the capabilities of detecting features within the images. At the same time, a database was developed with the necessary characteristics for the functioning of the neural network. Este artículo analiza diferentes arquitecturas con las que se puede desarrollar una red neuronal mediante visión por ordenador con el objetivo de detectar accidentes de tráfico. Para el desarrollo del software se utilizó el lenguaje de programación Java Script, llegando a la conclusión que la mejor arquitectura a utilizar es una Red Neural Convolucional ya que tiene la capacidad de detectar características dentro de las imágenes. Paralelamente se desarrolló una base de datos con las características necesarias para el funcionamiento de la red neuronal. Este artigo analisa diferentes arquiteturas com as quais uma rede neural pode ser desenvolvida utilizando visão computacional com o objetivo de detectar acidentes de trânsito. Para o desenvolvimento do software foi utilizada a linguagem de programação Java Script, chegando-se à conclusão de que a melhor arquitetura a ser utilizada é uma Rede Neural Convolucional, pois possui capacidade de detectar características dentro das imagens. Paralelamente, foi desenvolvida uma base de dados com as características necessárias ao funcionamento da rede neural.