La cuarta revolución industrial ha promovido de manera significativa la Inteligencia Artificial (IA) donde cada día se hace uso del Machine Learning (ML), conferiéndole un papel fundamental en la solución de desafíos inherentes a la fabricación, como el mejoramiento, optimización de la calidad de los procesos. El presente trabajo se ha concebido con la finalidad de subrayar la importancia y la utilidad del ML como una herramienta clave en este contexto, dividiendo el estudio en dos partes: el estado presente del ML y las principales técnicas empleadas. Se examinaron detalladamente 54 casos en los cuales se aplicaron algoritmos de ML referidos a la ingeniería industrial. Los estudios revelan que la implementación de técnicas de ML arrojan resultados notables en términos de precisión y confiabilidad, especialmente en áreas críticas como el análisis de fallos, predicción de defectos y la optimización de sistemas. Estas técnicas han demostrado ser sumamente eficaces para abordar estos desafíos, destacando así la relevancia y el potencial del ML en la industria contemporánea.

Background: The usability of electronic health records influences patient safety, clinical efficiency, and the sustainable digital transformation of health care. While tools such as the System Usability Scale exist, few are based on structured software quality models or align with local regulatory frameworks, particularly in low- and middle-income countries. Objective: This study aims to develop and psychometrically validate an instrument to assess electronic health record usability, based on the ISO 25010 (International Organization for Standardization) quality model, and in accordance with the Peruvian Technical Health Standard (Norma Técnica de Salud [NTS]). Methods: A 3-stage methodological study was conducted following COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) guidelines. First, a 23-item instrument was developed, grouped into 7 usability dimensions based on ISO 25010. Second, content validity was assessed using a modified Delphi method with 10 experts, using Aiken’s V coefficient. Third, structural validity and reliability were evaluated in 115 participants (physicians, nurses, and administrative staff) using confirmatory factor analysis and Cronbach α. Additionally, the module’s functional compliance with the NTS was verified. Results: The instrument demonstrated excellent psychometric properties among 115 participants (53 physicians, 48 nurses, and 14 administrative staff); high content validity (Aiken’s V=0.95; 95% CI 0.84‐0.98), excellent internal consistency ( α =.968), and optimal factor fit (Comparative Fit Index=1.000; Tucker-Lewis Index=1.001). Overall usability was perceived as very high by 94 of 115 users (81.7%), and high by 21 of 115 users (18.3%), with no perceptions at lower levels. The module met 28 of 35 requirements (80%) of the Peruvian Technical Health Standard. Administrative staff reported higher satisfaction (13/14, 93% rated it as very high) compared with clinical professionals (81/101, 80% rated it as very high), particularly in the dimensions of error protection and operability. Conclusions: This study provides the first fully psychometrically validated instrument in Spanish based on ISO 25010, System Usability Scale, and other theoretical foundations for evaluating the usability of information systems. The results highlight the importance of considering both international standards and local regulatory requirements (NTS) in the design of digital health systems. The instrument is applicable in Spanish-speaking contexts and can serve as a reference for future usability evaluations in the region as well as in low- and middle-income countries.

The aim of this study was to rigorously quantify and analyse the concentrations of atmospheric pollutants (PM₁₀, PM_2.5, SO₂, NO₂, CO, H₂S, and O₃) emitted by artisanal brick kilns in Juliaca City, Peru. The AERMOD dispersion model and a network of low-cost sensors (LCSs) were employed to characterise air quality at specific receptor sites. A georeferenced inventory of kiln operations was created to determine their parameters and operational intensity, providing a foundation for estimating emission factors and rates. Data were obtained from the United States Environmental Protection Agency (EPA) and supplemented with locally gathered meteorological records, which were processed for integration into the AERMOD model. The findings revealed that brick kilns are a principal source of atmospheric pollution in the region, with carbon monoxide (CO) emissions being especially pronounced. The LCSs facilitated the identification of pollutant concentrations at various locations and enabled the quantification of the specific contribution of brick production to ambient aerosol levels. Comparative assessments determined that these sources account for approximately 85% of CO emissions within the study area, underscoring a significant adverse impact on air quality and public health. Background pollutant levels, emission rates, spatial distributions, and concentration patterns were analysed within the assessment zones, resulting in solid model performance. These results provide a sound scientific basis for the formulation and implementation of targeted environmental mitigation policies in urban areas and the outskirts of Juliaca.

Global solar radiation is a fundamental component of the Earth's energy balance and plays a critical role in integrating renewable energy into electrical systems. However, its pronounced variability, particularly in high-altitude regions, constrains energy stability and complicates planning processes. This study evaluated regression-based and machine-learning models for 1-day-ahead prediction of global horizontal irradiance (GHI) in Juliaca, Peru (>3,800 m.a.s.l.), using 11 years (2010–2020) of daily NASA POWER data ( n = 4,000 observations after cleaning; 80/20 chronological train/test split: training from 2010 to 2018 and testing from 2018 to 2020). During data auditing, we identified that the same-day clearness index ( K _T ) is algebraically related to the same-day GHI through the extraterrestrial radiation term, which would otherwise inflate the apparent predictive accuracy. Therefore, we restricted same-day predictors to cyclical solar geometry terms and used lagged specific humidity, clearness index, and irradiance values from the previous 1–3 days as legitimate autoregressive information. Under this leakage-free design, Linear Regression achieved the best performance ( R ² = 0.390, MAE = 0.677 kWh m ⁻² d ⁻¹ , and RMSE = 0.896 kWh m ⁻² d ⁻¹ ), narrowly outperforming gradient boosting ( R ² = 0.384) and polynomial regression ( R ² = 0.381). Random Forest and shallow neural networks followed closely, with all six models exhibiting remarkably comparable performance. Feature-importance and SHAP analyses for the Random Forest model showed that previous-day irradiance and previous-day (lag-1) humidity were the dominant predictors. This pattern may be consistent with short-persistence cloud processes; however, cloud observations are required to verify this interpretation directly. The modest but realistic explanatory power obtained here, together with the diagnostic procedure used to achieve it, offers a template for detecting and avoiding under-reported leakage risk in solar radiation forecasting studies that use clearness-index-derived predictors.

BACKGROUND The usability of electronic health record (EHR) systems is crucial for patient safety and clinical efficiency, particularly in developing countries such as Peru, where challenges in implementing these technologies persist. OBJECTIVE To develop and validate an instrument based on the ISO 25010 standard to evaluate the usability of the EHR module, integrated with the requirements of the Peruvian Technical Health Standard (NTS). METHODS A methodological study was conducted in three phases: (1) Development of the instrument by integrating 23 items organized into seven usability dimensions; (2) Content validation with 10 experts using Aiken's V coefficient; and (3) Psychometric validation with 115 users using confirmatory factor analysis and reliability calculation. The study evaluated a HCE module implemented in a Peruvian health institution. RESULTS The instrument demonstrated excellent psychometric properties: content validity (V=0.95), model fit (CFI=1.000, TLI=1.001), and high reliability (α=0.968). Overall usability was perceived as "very high" (81.7%) and "high" (18.3%). The module met 80% of the NTS requirements. Certain differences were identified, but they were not significant between clinical and administrative professionals in terms of perceived usability. CONCLUSIONS This study provides the first validated instrument in Spanish for evaluating the usability of information systems that integrates ISO 25010, SUS, and other theoretical foundations. The results highlight the importance of considering both international standards and local regulatory requirements (NTS) in the design of digital health systems. The instrument is applicable in Spanish-speaking contexts and can serve as a reference for future usability evaluations in the region.

El objetivo principal de un enfoque de desarrollo humano es priorizar el bienestar y el empoderamiento de las personas, independientemente de sus antecedentes o circunstancias. El quinto Informe Nacional de Desarrollo Humano (INDH) de 2011 se centró en la Colombia rural y reconoció que, si bien el país había logrado avances en desarrollo humano, existían importantes disparidades regionales en las condiciones de vida y el bienestar. El informe reconocía que el modelo rural existente no promovía el desarrollo humano y, por el contrario, hacía a la población rural más vulnerable debido a obstáculos estructurales como la desigualdad, los conflictos por la tierra y la exclusión de las oportunidades de crecimiento y desarrollo. También identificó que el modelo de desarrollo imperante era inequitativo y excluyente, impidiendo a campesinos, indígenas y afrocolombianos acceder y beneficiarse de los recursos del territorio. El informe recomendó al Estado y a la sociedad colombiana concentrar sus esfuerzos en mejorar la productividad del sector, la educación y la inversión productiva, así como desarrollar mercados de tierras para promover el desarrollo y el crecimiento humano. La sexta INDH para Colombia se basa en estas preocupaciones y se centra en las persistentes desigualdades y los bajos niveles de productividad económica en el país. Profundiza en cuatro temas estratégicos: la educación y su conexión con la inclusión económica, el acceso efectivo a la justicia, abordar los problemas que enfrentan las personas y abordar las barreras a la igualdad de género. La investigación ilustra el comportamiento de indicadores significativos que han experimentado cambios sustanciales o marcados puntos de inflexión en su trayectoria. Cabe señalar que este no es un diagnóstico exhaustivo de cada tema, ni profundiza en las causas detalladas de cada resultado. Más bien, presenta tendencias que invitan a la reflexión sobre estos indicadores, destaca hitos notables de la última década, como legislación reciente, políticas públicas o eventos significativos que se consideran relevantes en el contexto del desarrollo humano en Colombia.