Purpose: This research proposes an implementation model of Total Productive Maintenance (TPM) based on the analysis of criticality of machines in the sewing process in the Ecuadorian footwear industry and the identification of unproductive times caused by labor failures.Design/methodology/approach: The project uses field research, presents a quantitative approach, the data collection is done in a horizon of 8 months in which the information is condensed in data tables and takes as a case study one of the most successful companies in the Ecuadorian footwear industry for its initiative to innovate their processes and research new technologies that help increase their efficiency.Findings: The results allow to demonstrate the successful application of the proposed model in the industrial sector of footwear with an increase of average production standards of 5% and a reduction in the number of human errors of 72.2%.Practical implications: The model allows to execute several activities in four phases: preparatory, introduction, implementation and consolidation in order to develop TPM in sewing process.Originality/value: The paper describes a case study in a major shoe company with the aim of reducing the times for unscheduled stoppages and the number of failures.

This study analyses the integration of Generative Artificial Intelligence (GenAI) in agro-environmental higher education in Ecuador, focusing on its contribution to sustainable digital transformation aligned with Sustainable Development Goals (SDGs) 4 and 9. The research was conducted at the Faculty of Agricultural and Environmental Engineering (FICAYA) of Universidad Técnica del Norte (UTN) using a quantitative, cross-sectional, and analytical design. A validated digital survey grounded in established technology-acceptance frameworks—the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) was administered to 94% of the student population, showing satisfactory internal consistency (Cronbach’s α = 0.87). Data was analysed using descriptive statistics and multivariate techniques, including Principal Component Analysis (PCA) and k-means clustering. The results obtained in Microsoft Forms^® indicate that ChatGPT-5 is the most widely used GenAI tool (54.2%), followed by Gemini (11.9%). Students reported perceived improvements in academic performance (62.5%), conceptual understanding (74.6%), and task efficiency (69.1%). PCA explained 67% of the total variance, identifying three latent dimensions: effectiveness and satisfaction, institutional access and support, and ethical concerns versus operational benefits. Furthermore, k-means clustering (k = 2) segmented users into two distinct profiles Integrators, characterised by frequent use and positive perceptions, and Cautious Users, exhibiting lower usage and greater ethical or technical concerns. Overall, the findings highlight GenAI as a catalyst for sustainable education and underline the need for institutional and ethical frameworks to support its responsible integration in Latin American universities.

Building-Integrated and Building-Attached Photovoltaic (BIPV/BAPV) systems are increasingly being adopted in metropolitan areas worldwide, driven by international commitments to reduce greenhouse gas emissions and the declining cost of PV technology. A promising application involves the vertical integration of PV panels into building facades, which offers architectural and energy benefits, particularly in urban environments with limited roof space. This study experimentally evaluates the energy behavior of 12 vertically mounted 5 W PV panels (model SP005P) installed on university buildings in Ibarra, Ecuador, across four azimuth orientations (−135° SE, −45° NE, 45° NW, 135° SW). A continuous 8-month monitoring campaign was conducted using a custom-designed Arduino-based data logger, validated with multimeter measurements (error < 5%). The dataset was used to develop MATLAB version 2025b forecasting models based on Sum-of-Sine functions, achieving R² values between 0.83 and 0.98 and RMSE values between 0.024 and 0.082 W. The 45° (NW) orientation achieved the highest annual energy yield of 48% STC, reaching up to ≈440 kWh/kWp in the best-performing facade, while 135° (SW) also exhibited favorable performance compared with the northeast and southeast orientations. These findings provide significant evidence for facade-integrated PV design in equatorial latitudes, offering performance benchmarks and validated forecasting tools that can support architectural planning, BIPV feasibility analysis, and urban solar-energy strategies in regions with similar conditions.

So far, about 770.1 million confirmed cases of COVID-19 have been counted by August 2023, and around 7 million deaths have been reported from these cases to the World Health Organization. In Ecuador, the first confirmed COVID-19 case was registered on 19 February 2020, and the country’s mortality rate reached 0.43% with 12986 deaths, suggesting the need to establish a mechanism to show the virus spread in advance. This study aims to build a dynamic model adapted to health and socio-environmental variables as a multivariate model to understand the virus expansion among the population. The model is based on Susceptible-Infected-Recovered (SIR), which is a standard model in which the population is divided into six groups with parameters such as susceptible S(t), transit stage E(t), infected I(t), recovered R(t), deceased Me(t), infected asymptomatic Ia(t), infected symptomatic Is(t) and deceased by other causes M(t) to be considered and adapted. The model was validated by using consistent data from Chile and run by inconsistent data from Ecuador. The forecast error was analyzed based on the mean absolute error between real data and model forecast, showing errors within a range from 6.33% to 8.41% for Chile, with confidence a interval of 6.17%, then 3.87% to 4.70% range for Ecuador with a confidence interval of 2.59% until 23rd December 2020 of the database. The model forecasts exponential variations in biosecurity measures, exposed population, and vaccination.

Understanding microclimatic variability at the land–atmosphere interface is essential for improving knowledge of atmospheric moisture dynamics in heterogeneous mountainous ecosystems. This study analyzes atmospheric relative humidity and soil moisture variability in an experimental Juglans neotropica Diels plantation located in the Ecuadorian Andes under real field conditions. An autonomous photovoltaic-powered monitoring system equipped with low-cost environmental sensors was deployed continuously for 60 days, generating more than 86,000 environmental measurements of atmospheric relative humidity above and below the canopy, together with soil moisture observations. The results revealed persistent vertical humidity stratification associated with canopy structure, characterized by systematically higher atmospheric humidity beneath the canopy compared to the upper atmospheric layer (ΔRH ≈ −36%). Strong intersensor coherence was observed between canopy levels (r = 0.8535), indicating stable temporal consistency in atmospheric variability patterns throughout the monitoring period. Soil moisture exhibited comparatively more stable temporal dynamics than atmospheric humidity, suggesting partial microclimatic decoupling between atmospheric and edaphic layers. The observed humidity gradients remained temporally stable during both daytime and nighttime conditions, supporting the interpretation of canopy-mediated atmospheric buffering processes within the plantation environment. From an ecological perspective, the results indicate that vegetation structure contributes to localized moisture retention, attenuation of short-term atmospheric fluctuations, and regulation of near-surface microclimatic conditions under heterogeneous Andean environmental conditions. Rather than focusing on instrumentation performance, the study provides empirical evidence of persistent canopy-related atmospheric regulation and moisture stratification in a native Andean forest species under continuous field monitoring conditions. These findings contribute to the understanding of land–atmosphere interactions, ecohydrological dynamics, and vegetation-mediated microclimatic regulation in mountainous ecosystems.

La enfermedad por COVID-19 prolongado es una manifestación clínica generalizada que aparece después de varias semanas de haber contraído la enfermedad. Objetivo: Investigar aspectos epidemiológicos y clínicos por COVID-19 prolongado en la provincia de Sucumbíos. Metodología: Estudio descriptivo, cuantitativo no experimental, retrospectivo y de cohorte transversal en una población de 57.727 habitantes, con 475 casos confirmados, muestra aleatoria de 235 personas con 95 % de confiabilidad y 5 % de error, se aplicó una encuesta estructurada diseñada y validada por expertos. Resultados: Prevalencia 8,22 en habitantes de casos confirmados, aspectos sociodemográficos: 57,02% tienen 25 a 49 años, 54,89% mujeres,56,17% estudios superiores, 88,51% mestizos,78,30% viven en zona urbana, 4,68% requirieron hospitalización, 2,55% unidad de terapia intensiva, 92,77% no requirió hospitalización. En el 46,30% el cuadro agudo duró de 3 a 5 días, el 19,57% tuvieron persistencia de sintomatología de 1 a 3 meses, 2,55% de 7 a 9 meses, 2,55% de 10 a 12 meses, 9,36% mayor a 1 año. Conclusiones: La mayor parte de personas no presentan afectación por covid prolongado, pero existe un porcentaje a considerar que siguen persistiendo hasta un año después con problemas de salud que puede impactar en la calidad de vida de los pacientes.