The COVID-19 pandemic has affected the mental health of regular basic education teachers. Despite the fact that in recent months the number of infections has decreased significantly, the return to face-to-face classes is of great concern to teachers due to the adverse educational context they must face. In this sense, the objective of this study was to determine whether or not psychological distress is significantly related to burnout syndrome in regular basic education teachers upon their return to face-to-face classes. This research employed a quantitative approach, the design was non-experimental, and the type of study was descriptive–correlational and cross-sectional. In total, 184 teachers participated and responded using the Psychological Distress Scale and the Maslach Burnout Inventory, which are instruments with adequate psychometric properties. The results indicated that 40.7% of the teachers had a moderate level of psychological distress, and 45.1% also had a moderate level of burnout syndrome. Likewise, it was found that the Pearson’s r correlation coefficient between the variables psychological distress and burnout syndrome was 0.752, and the p-value was below the level of significance (p < 0.05). It was concluded that there is a direct and significant relationship between psychological distress and burnout syndrome in regular basic education teachers upon their return to face-to-face classes. For this reason, it is suggested that the Ministry of Education should design policies that allow a reassessment of the work that teachers have been carrying out and that promote the implementation of preventive and corrective programs to improve their mental health.

The magnetic field penetration depth poses challenges in communications, geophysical exploration, biomedical therapies, and superconducting device design. The objective of this systematic review was to identify, analyze, and understand the depth of magnetic field penetration in conductors, semiconductors, superconductors, insulators and natural materials, modelling applications in medicine, engineering, and basic sciences. An exhaustive search was carried out in databases such as Scopus, IEEE Xplore, ScienceDirect, and IOPSCIENCE using keywords such as depth and penetration and magnetic and field and materials. PRISMA was used as a method to define inclusion and exclusion criteria, ensuring quality, transparency, and methodological rigor, followed by a detailed statistical analysis. The results showed that the penetration depth varies according to the material, frequency, and application conditions. In human tissues, infrastructure, and agricultural applications, the penetration range is between 0.01 and 0.2 m, with the possibility of a range greater than one meter in specific applications. The higher the frequency, the lower the penetration depth is confirmed. In conclusion, the penetration of the magnetic field depends on material properties such as conductivity and magnetic permeability, frequency, and temperature. The developed models offer relevant information for future research and technological applications.

Crack formation and rehabilitation of concrete elements, such as slabs and columns, in buildings located in areas with temperatures above 25 °C, where accelerated water evaporation significantly reduces their structural strength, was addressed. To mitigate this effect, an intelligent automated monitoring and curing system was developed, using integrated sensors and embedded controllers. The study was applied, experimental and explanatory, based on the hypothetico-deductive method. Work was carried out with physical models (specimens, columns and solid slabs) with 1:2:3 dosage, in which thermal and humidity sensors were integrated, and a visualisation system with an LCD screen was designed in Proteus for data collection. Quantitative analysis, with 95 % confidence, revealed a moderate and significant correlation (r = 0.587; p = 0.001) between the environmental thermo-hygrometer and the embedded DS18B20 sensor, showing effective heat transfer. The low correlation with the HD-38 sensor (r = 0.143; p = 0.468) indicated little influence of ambient humidity on internal humidity. The system restored the initial screams, used 1680 litres of water in 28 days, reducing consumption by 20 % compared to traditional methods. Higher evaporation was identified between 11:00 and 16:00 hours (UTC-5), a critical phenomenon not reported in previous studies in tropical areas.

This study addresses the formation, detection, and repair of cracks in concrete elements exposed to temperatures above 25 °C, where accelerated evaporation compromises their structural strength. An automated intelligent curing system with embedded sensors (DS18B20, HD-38) and Arduino controllers was developed and applied to solid slabs, columns, and concrete test specimens (1:2:3.5 mix ratio). The electronic design was simulated in Proteus and validated experimentally under tropical conditions. Data with normal distribution (p > 0.05) showed a significant correlation between internal and ambient temperature (r = 0.587; p = 0.001) and a low correlation in humidity (r = 0.143; p = 0.468), indicating hygrometric independence. The system healed cracks of 0.01 mm observed two hours after pouring the mixture, associated with an evaporation rate of 1.097 mL/s in 4 m². For 28 days, automated irrigation cycles were applied every 30 to 60 min, with a total of 1680 L, achieving a 20% reduction in water consumption compared to traditional methods. The system maintained stable thermal conditions in the concrete despite ambient temperatures of up to 33.85 °C. A critical evaporation range was identified between 11:00 and 16:00 (UTC-5). The results demonstrate the effectiveness of the embedded system in optimizing curing, water efficiency, and concrete durability.

The continuous rise of artificial intelligence tools in educational settings highlights the importance of understanding how students position themselves in relation to these technologies. This study aims to analyze the attitudes toward ChatGPT among Peruvian university students, considering the cognitive, affective, and behavioral components, as well as the metric properties of the instrument. A quantitative approach was employed, with a descriptive-comparative and instrumental research design, involving 464 Peruvian students from different academic disciplines. The results indicated that, after performing confirmatory factor analysis, the final model consisted of 33 items assessing attitudes toward ChatGPT across cognitive, affective, and behavioral components, with slightly acceptable fit indices (χ²/df, p < 0.05, SRMR, RMSEA, TLI, CFI, and GFI) and adequate factor loadings (λ > 0.3). In addition, the instrument showed satisfactory reliability evidence (αordinal and Ωordinal > 0.7). Another finding revealed that engineering students exhibited a significantly more favorable affective attitude toward ChatGPT (p = 0.03) compared to students from the social and natural sciences. No significant differences (p > 0.05) were found in students’ attitudes based on sex or age. In conclusion, although future engineers display a more favorable affective attitude than students from other disciplines, overall attitudes toward ChatGPT do not show relevant differences across other sociodemographic factors. Moreover, the instrument proved to be valid and reliable with 33 items, thus representing a solid and less dense tool for future research.

Introduction: The study analyzes the relationship between strategic planning and governance in public procurement at a decentralized public university in Peru, considering its implications for efficiency, transparency, and regulatory compliance. Methods: A mixed descriptive-correlational approach was applied using a non-experimental cross-sectional design, evaluating 152 university employees using a validated questionnaire ( α > 0.71) and a review of normative documents. Results: The findings reveal a predominance of simplified awarding procedures (2019-2024) and a high incidence rate in the preparatory stage, identified as the main operational bottleneck, resulting in economic damages of up to 2,982,623.50 PEN and average delays of 71.6 days. The Regulatory Alignment Index (55%) indicates gaps with international standards. A significant positive correlation was found between governance and planning ( ρ = 0.566; p < 0.01), with moderate explanatory power ( R ² = 0.3295). Discussion: These results suggest that, despite acceptable operational performance, structural weaknesses persist in governance and strategic planning. The identified gaps highlight the need to incorporate sustainability, life-cycle approaches, and project management methodologies. An adaptive model integrating public value, efficiency, transparency, and sustainability is proposed to strengthen governance and align university procurement with global best practices.