Precise temperature control in high-temperature furnaces is challenged by nonlinearities, parameter drift, and high thermal inertia. This study proposes an adaptive control strategy combining a classical PID loop with real-time gain updates from a feed-forward artificial neural network (ANN). Implemented on an 18 kW retrofitted Blue-M furnace, the system was characterized by second-order transfer functions for heating and forced convection cooling. A dataset of 9702 samples was built from eight fixed PID configurations tested under a multi-ramp thermal profile. The selected 3-64-64-32-2 ANN, executed in Python and interfaced with LabVIEW, computes optimal gains in 0.054 ms while preserving real-time monitoring capabilities. Experimental results show that the ANN-assisted PID reduces the mean absolute error to 5.08 °C, limits overshoot to 41% (from 53%), and shortens settling time by 20% compared to the best fixed-gain loop. It also outperforms a fuzzy controller and remains stable under ±5% signal noise. Notably, gain reversals during cooling prevent temperature spikes, improving transient response. Relying on commodity hardware and open-source tools, this approach offers a cost-effective solution for legacy furnace upgrades and provides a replicable model for adaptive control in high-temperature, safety-critical environments like metal processing, battery cycling, and nuclear systems.

STEM (Science, Technology, Engineering and Mathematics) careers are fundamental to technological, economic and social development worldwide, which is why the demand for professionals trained in these areas has increased significantly in the last decade. This study analyzes the evolution of undergraduate enrollment in general and in STEM careers in face-to-face mode in Ecuador from 2015 to 2023. Variables such as type of financing, geographic distribution, field of study and enrollment by sex are considered, both in general and by STEM careers. For this purpose, data from the Secretariat of Higher Education, Science, Technology and Innovation (SENESCYT) were used. In addition, future enrollment in STEM careers by sex is projected for students from the country's Polytechnic Schools. In addition, the study analyzes the impact of the type of financing on enrollment. It is observed that public institutions concentrate the largest number of students in STEM careers, while private institutions have a lower participation in these areas. This suggests that opportunities for access to STEM education depend largely on government funding and support policies. One of the most relevant findings is the constant growth of engineering enrollment, which has remained between 15% and 16% of total students since 2016. On the other hand, enrollment in mathematics has experienced a considerable drop, going from 13.84% in 2015 to only 2.92% in 2023. In contrast, ICT degrees have shown significant growth, reflecting increasing digitalization and labor market demand in areas such as cybersecurity, artificial intelligence, and data analysis. Analysis by sex shows a persistent gender gap in STEM degrees, with a higher proportion of men in engineering and ICT, while in Mathematics the difference is smaller.

Potato cultivation in the Ecuadorian Andes is largely manual and relies on intensive agrochemical inputs. We introduce a reproducible workflow that couples life cycle assessment (LCA) with a neural-network surrogate to enable rapid multi-impact screening of two potato management scenarios in Ecuador: (i) conventional manual management and (ii) Unmanned aerial vehicle (UAV)-based field monitoring to identify hotspots for targeted ground-based input application. Multi-category impacts are computed in OpenLCA using the environmental footprint method (EF 3.0) per kilogram of potatoes and scaled to annual national totals using reported national production data. UAV operation is parameterized as 0.51 kg CO₂ eq·h⁻¹, equivalent to 0.225 kg CO₂ eq·ha⁻¹ at a coverage rate of 2.27 ha·h⁻¹. For 2024, the UAV-informed scenario reduces climate change from 4.29 × 10⁷ to 3.75 × 10⁷ kg CO₂ eq (−12.7%), resource use, fossils from 5.09 × 10⁸ to 4.54 × 10⁸ MJ (−10.7%), and freshwater eutrophication from 3.33 × 10⁴ to 2.83 × 10⁴ kg P eq (−15.0%), while land use remains nearly unchanged at ~4.73 × 10⁹ Pt (−0.1%). To avoid repeated LCA recalculations, a multi-output artificial neural network (ANN) surrogate (29 outputs) was trained in Python (TensorFlow/Keras) and evaluated using leave-one-year-out (LOYO) cross-validation (2015–2024), showing strong agreement with the LCA results. This framework enables scalable what-if analysis and efficient evaluation of UAV-enabled precision monitoring strategies in resource-constrained settings.

The study analyzes the implementation of Open Educational Resources (OER) and Information and Communication Technologies (ICT) in the teaching of General Chemistry at the National Polytechnic School (EPN) and its impact on the academic performance of first-semester engineering students. The research follows a quantitative and quasi-experimental approach, comparing control groups and two intervention groups (I1 and I2) over four academic periods (2022B-2024A). The results show an increase in the passing rate in the intervention groups, reaching up to 83% in 2024A, in contrast to the control group which started with only 25.5% in 2022B. However, despite this improvement, final grades did not increase proportionally. Statistical analyses, including chi-square and ANOVA tests, reveal significant differences in some periods, especially in group I2. Several key factors were identified: the incorporation of virtual laboratories, interactive simulations and bimonthly projects facilitated learning, but their impact focused on reducing failure rather than improving overall performance. The adaptation of the control group to intervention strategies in the last academic periods also leveled the differences. The study concludes that the use of OER and ICT is effective in increasing the pass rate, but new pedagogical strategies are required to improve overall grades and not just avoid failure.

One of the Sustainable Development objectives proposed by UNESCO in its 2030 agenda is to achieve gender equity in the entire educational system, emphasizing the teaching of science, technology, engineering and mathematics (STEM) for girls and the women. Worldwide, 30% of STEM students are women and the remaining 70% are men. Studies on academic performance at the secondary level such as the PISA tests establish a gap between performance in mathematics between women and men, these being The latter are those with better academic performance. This factor may explain the low rate of women in STEM careers at the university level. This paper analyzes the impact of the study modality, the sex of the student and the teacher, on the final grade, considered as an indicator of the academic performance of university students in the subject of probability and statistics at the Polytechnic School. National, from 2019 to 2023. In this case, for the final grade, a weighted value is considered, including exams, homework, class participation and projects. When comparing the final grade with the study modality using the Wilcoxon hypothesis test, the null hypothesis is rejected, with a pvalue less than 0.01, that is, the grades are not the same in all study modalities. To confirm these results, we used a Kruskal-Wallis hypothesis test similar to the Wilcoxon hypothesis test, obtaining the same result. To analyze the final grade with the sex of the student, a Mann-Whitney hypothesis test was carried out by which it is verified. that the final grade is not significantly different if it is compared between groups of students by sex. To analyze the impact of the study modality and the sex of the teacher, after rejecting the hypothesis of group equality using the Kruskal-Wallis test, a logistic regression model was built taking these as covariates and approval or approval as the response variable. not of the course. It was determined that the probability of passing the course depends significantly on the study modality and the sex of the assigned teacher.