https://athenea.autanabooks.com/index.php/revista/issue/feed Athenea Engineering sciences journal 2026-11-04T03:32:46+00:00 Franyelit Suárez editorial@autanabooks.com Open Journal Systems <p>The <strong>Athenea Journal</strong> is published in collaboration with Venezuela and Ecuador, highlighting the multicultural values of our lands and showcasing Latin America’s scientific contributions to the world, where science becomes a universal language without borders. It is a space where the brightest minds from our nations come together to contribute to global knowledge, showing that in science there are neither limits nor barriers—only the shared desire to advance together. Athenea is not just a journal but a bridge connecting hearts and talents, proving that when we work together, borders fade away, and the future fills with infinite possibilities.</p> <p><strong>Athenea </strong>is a scientific journal oriented to Engineering Sciences. It is published by AutanaBooks SAS, with the institutional support of the Universidad Experimental "Antonio José de Sucre" (UNEXPO), vice-rectorate Puerto Ordaz, Venezuela. Its main administrative office is located in Venezuela, and its editor is PhD Franyelit Suárez.<br>The journal Athenea focuses on Engineering Sciences and aims to publish academic and scientific material of high research level and quality, produced by scientists and researchers in Latin America and the world to disseminate the work of teaching and research.</p> https://athenea.autanabooks.com/index.php/revista/article/view/153 Modeling and simulation through system dynamics of the interaction between academic load, teacher well-being and educational quality in universities 2026-11-04T03:32:46+00:00 Manuel Cardenas Herrera mcardenash@unsa.edu.pe Edgar Hilario Barreda Coaquira ebarreda@unsa.edu.pe James Josmell Ojeda Portugal jojedap@unsa.edu.pe <p>The aim of this study was to analyze, through system dynamics, the interaction among academic workload, faculty well-being, and educational quality under different university management scenarios. An external computational simulation dataset published in Zenodo was used, comprising 520,000 records generated from 1,000 paired Monte Carlo parameterizations, five scenarios, and 104 simulation weeks. Baseline conditions, administrative workload reduction, teaching workload reduction, institutional support, and a combined intervention were compared. Results showed that reducing work demands decreased faculty strain and improved simulated well-being and educational quality. The combined intervention produced the most favorable overall behavior, whereas institutional support alone generated compensatory effects due to the additional time costs incorporated into the model. Sensitivity analysis confirmed the relevance of teaching workload, institutional pressure, and recovery capacity. The findings represent exclusively the behavior of the computational model and should not be interpreted as empirical evidence from real universities or faculty members</p> 2026-10-26T00:00:00+00:00 Copyright (c) 2026 Manuel Cardenas Herrera, Edgar Hilario Barreda Coaquira, James Josmell Ojeda Portugal https://athenea.autanabooks.com/index.php/revista/article/view/154 Mathematical Modeling and Prediction of Heatwaves Using Time Series and Satellite Data 2026-11-04T03:32:36+00:00 Joan Patricio Cobena Cevallos joanpa13.cc@gmail.com Vicente Marlon Villa Villa mvilla@unach.edu.ec Marco Vinicio Parra Chavez marcov.parra@espoch.edu.ec Ana Carol Flores Mancheno acmancheno@espoch.edu.ec <p>Urban heatwaves require methods capable of capturing seasonality, persistence, and extreme temperature events. A retrospective modeling framework was developed for Guayaquil using reanalysis-based air temperature, oceanic anomalies, and satellite-derived land surface temperature. Temporal dynamics were represented using dynamic harmonic regression with autoregressive integrated moving average (ARIMA) errors and compared against a persistence baseline through independent chronological validation. A probabilistic forecasting approach and an alternative heatwave definition were also evaluated. Temporal modeling reduced the forecasting error for ERA5-Land maximum temperature relative to the naive baseline, whereas oceanic anomalies provided only marginal improvements for maximum temperature and degraded minimum temperature predictions. Probabilistic forecasting improved heatwave event detection, although it also increased the frequency of false alarms. MODIS observations revealed greater nighttime land surface temperature anomalies during events meeting the more stringent heatwave criterion. These findings explicitly distinguish temperature forecasting accuracy, extreme event detection, and complementary satellite-based evidence.</p> 2026-10-27T00:00:00+00:00 Copyright (c) 2026 Joan Patricio Cobena Cevallos, Vicente Marlon Villa Villa, Marco Vinicio Parra Chavez, Ana Carol Flores Mancheno https://athenea.autanabooks.com/index.php/revista/article/view/155 Mathematical Modeling of Educational Technology Adoption by University Faculty Using Differential Equations and Scenario Simulation 2026-11-04T03:32:27+00:00 Ana Rosario Miaury-Vilca amiaury@unsa.edu.pe Jorge Rolando Paredes Rondon jparedesr@unsa.edu.pe David Frank Molina Nunez dmolina@continental.edu.pe <p>This study analyzed educational technology adoption dynamics among university faculty using a four-state compartmental model formulated with ordinary differential equations and computational simulation. Six institutional scenarios were examined over 36 months using reproducible EduAdopt-4D research resources. Deterministic solutions were compared with computationally generated trajectories and 960 Monte Carlo replications; parameter sensitivity and numerical convergence analyses were also performed. At month 36, estimated adoption reached 66.29\% under the integrated intervention scenario, compared with 54.52\% in the baseline scenario and 43.71\% under digital overload. The analyses highlighted the influence of fatigue and recovery mechanisms on sustained adoption. The findings indicate that the proposed approach enables quantitative exploration of faculty technology-adoption transitions and comparison of institutional strategies under explicit assumptions. It offers a reproducible framework for subsequent applications and calibration studies in university settings.</p> 2026-10-27T22:00:31+00:00 Copyright (c) 2026 Ana Rosario Miaury-Vilca, Jorge Rolando Paredes Rondon, David Frank Molina Nunez