Introducción: La inteligencia artificial (IA) en el sector salud promete grandes impactos, que permitan enfrentar desafíos como la detección temprana de enfermedades, diagnósticos precisos, personalización de tratamientos, y optimización de procesos en las entidades prestadoras del servicio de salud. Objetivo: Examinar la literatura reciente sobre las implicaciones del uso de IA en la gestión de la salud, explorando tanto sus beneficios como las preocupaciones asociadas. Metodología: La investigación es descriptiva basada en análisis documental de artículos publicados entre 01/01/2018 y 30/06/2024, en inglés y español, en bases de datos como Scopus y Web of Science. Resultados: Dentro de los principales hallazgos muestran el potencial para mejorar la precisión en diagnósticos, una mayor personalización en el tratamiento y reducir errores médicos, actuando como un asistente cognitivo y de apoyo en procesos clínicos. Sin embargo, se identifican retos como referentes a la ética, privacidad, seguridad de datos y regulación de su uso. Conclusiones: Si bien la IA presenta una oportunidad importante de transformación digital para mejorar la gestión de la salud en las personas y en las entidades prestadoras de la salud, su implementación responsable demanda marcos regulatorios claros y estrategias centradas en las personas (paciente y profesional de la salud). De este modo, se busca aprovechar sus beneficios, mitigando riesgos y promoviendo una atención médica confiable, equitativa y eficiente. Por lo tanto, esta revisión es importante para conocer diversas posturas, y continuar con la valoración de los impactos e investigación en temas específicos.

Introduction: Secondary-data studies (clinical, administrative or sensor records) embed selection, measurement and missing-data processes that are often treated as “preprocessing”, leaving key causal assumptions implicit and hard to audit. Objective: To propose a reproducible protocol that makes causal assumptions explicit in secondary-data studies using layered directed acyclic graphs. Methodology: The protocol separates a material causal system (exposure→outcome) and three additional layers: (i) selection/observability, (ii) operationalisation and measurement (constructs vs. recorded proxies) and (iii) missing-data mechanisms. It includes estimand and time alignment, extraction rules and cohort construction, plus quality control based on graph source code and figure traceability. Results: Outputs include a reporting checklist (Table 1), a decision→threat→graph-signature mapping with conditional mitigations (Table 2), a related-work gap synthesis (Table 3), layered DAG examples (Figs. 1–9) and reproducible evaluations quantifying typical biases and sensitivity to missingness (Tables 4–7). Conclusions: The layered approach makes selection, measurement and missingness assumptions explicit; improves reproducibility through code–figure–text traceability; and operationalises alignment between design/analysis choices and the estimand, limiting claims that exceed the available evidence. A minimal applied case shows that observation/missingness decisions can materially shift the estimand, motivating explicit sensitivity reporting (Δ) and denominators.

Introduction: The connection between green innovation and firm performance on the industrial sector of Pakistan is explored by this study, which implements the versatile explainable artificial intelligence (XAI) approaches to reveal the knowledge path with transparent explanations of complex decisions. Objective: It adopts a comparative approach to SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) model in explaining green innovation endeavors into an elucidation of practical business gains guaranteed. Method: On a large scale, study access a comprehensive dataset of 284 manufacturing companies of diverse industries within Pakistan and develop a machine learning model to forecast the firm indicators of performance whilst being interpretable using XAI methods. Results: Research has found that green innovation has a positive impact that is statistically significant on firm performance and the drivers which have been identified are described as environmental compliance, resource efficiency and sustainable product development. The above comparative analysis of SHAP and LIME shows that both methods, in their turn, yield good insights, but SHAP shows more consistent global explanations whereas LIME is better at explaining individual instances. Conclusions: By having the contribution in the growing literature on sustainable business practices in emerging markets, this research is practical in giving the right directions to policymakers and business leaders in Pakistan. Suggestions are given to the policy makers and the firms in Pakistan indicating that strategic investments need to be made in process innovation and regulatory frameworks. This study highlights the promise of XAI to help in de-mystifying the complex nature of relationships in sustainability-related performance.

Background and objectives: This article analyzes the comprehensive assessment and enhancement of the sustainable management of Agricultural Production Units (APUs) in the departments of Atlántico, César, and Magdalena in the Caribbean region of Colombia. The main objective is to identify challenges and opportunities for enhancing agricultural sustainability and propose appropriate strategies within a local context. Methods: The research employed a mixed methodological approach, incorporating APU diagnosis; strengths, weaknesses, opportunities, and threats analysis; and structured surveys administered to agricultural producers in each department. Moreover, secondary sources were employed to assess sustainable agricultural practices and key environmental variables. Findings: APUs in the Caribbean region face significant challenges, including limited access to technology, inefficient soil management, and scarce water resources. In Atlántico, 40% of producers lack education in soil studies. In Cesar, 30% of soils are degraded. In Magdalena, 70% are affected by salinization. These results emphasize the need to adopt agroecological technologies and strategies adjusted to the local context to ensure agricultural sustainability and resilience. Conclusion: This study highlights the urgency of implementing comprehensive strategies that consider regional specific

Introducción: Los puentes son estructuras que demandan grandes inversiones y son vitales para el desarrollo económico de cualquier país, su adecuado desempeño, durante y después de un sismo de magnitud considerable, es clave para atender emergencias derivadas del evento y garantizar una rápida recuperación económica de las zonas afectadas. En el contexto nacional, los apoyos elastómeros reforzados son los elementos de conexión más usados entre la superestructura y la subestructura, debido a su bajo costo en comparación con otros sistemas disponibles, no obstante, los requerimientos actualmente vigentes en la normativa colombiana consideran exclusivamente cargas muertas y vivas verticales en estado de servicio, sin que se presenten requerimientos adicionales de evaluación del desempeño sísmico de este tipo de apoyos. Objetivo: Se busca comparar la norma de diseño de puentes Colombiana y el Eurocodigo para el diseño de apoyos elastoméricos, con el fin de determinar la normativa que produce elastómeros con mejor desempeño durante eventos sísmicos. Metodología: Se desarrollaron modelos computacionales de puentes tipo viga cajón (representativo de Colombia). Los puentes modelados con longitudes constantes, presentan variaciones en la posición y altura de las columnas de los apoyos intermedios y además en la curvatura horizontal del puente. Los modelos incluyen los efectos de la rigidez de cada tipología de elastómero diseñado asociado a cada normativa, de los análisis se obtienen y comparan los desempeños de los dispositivos ante eventos sísmicos considerando análisis tiempo historia. Resultados: Se determinó el proceso de diseño y por ende la normativa que produce elementos de conexión tipo apoyos elastómeros con mejor comportamiento ante eventos sísmicos en términos de desplazamientos. Conclusiones: Se evidencian menores desplazamientos y por ende mejor comportamiento sísmico para las dimensiones de los elementos diseñados por el Eurocódigo.

Introduction: Mono, di, tri acetyl glycerols were obtained by esterification of technical grade glycerin with acetic acid in the presence of ion exchange resin on a laboratory scale. Toluene was used as a trawling agent. The mixture of acetyl glycerols was added with zinc oxide nanoparticles by applying ultrasound dispersion; concentrations equivalent to 0.05 were tested; 0.1;0.15; 0.2% by weight. The dispersions were subjected to four-ball tribological tests. The lubricating behavior under low load conditions was assessed through the Preventive Wear test, with measurement of the footprint diameter and the friction coefficient. The morphology of the prints was analyzed using scanning electron microscopy. The performance of the dispersions under Extreme Pressure lubrication conditions was evaluated by quantifying the welding point. The results obtained from the experimentation indicate that mono, di, tri acetyl glycerols require the addition of metal nanoparticles to improve their tribological performance with the purpose of using them in biolubricant formulations. Objective: study the behavior of mono, di, tri acetyl glycerols MDTAG in terms of tribology, mixing it with nanoparticles to improve the lubricating power. Method: The dispersions were subjected to four-ball tribology tests. The lubricating behavior was evaluated under low load conditions by applying the Preventive Wear test, the footprint diameter and the friction coefficient were measured. Results: The results obtained from the experimentation indicate that mono, di, tri acetyl glycerols require the addition of metal nanoparticles to improve their tribological performance with the purpose of using them in biolubricant formulations. Conclusions: The mixture of mono, di, tri acetyl glycerols with the addition of zinc oxide nanoparticles allows them to possibly be used as additives in biolubricant bases.

Introduction: This study investigates the energy performance, carbon emissions, and thermal comfort implications of proposed building modifications for the London Business School E-Wing building. With the increasing demand for sustainable building practices, understanding the impact of various modifications is crucial. Objective: The primary aim is to evaluate the potential for reducing energy consumption, mitigating carbon emissions, and enhancing indoor environmental quality in educational institutions through strategic building upgrades. Methodology: A detailed building energy model was developed using the IES-VE software to model both existing and proposed E-Wing building scenarios. The model considers factors such as heating and cooling systems efficiency, lighting, and window characteristics. Results: The analysis revealed significant opportunities for energy savings, with proposed modifications demonstrating a potential reduction of 17.4% in energy consumption compared to the existing building. Further enhancements, such as window upgrades, could lead to a 25.8% decrease in energy usage from the baseline. Carbon emissions analysis indicated an estimated 8.2% potential reduction in emissions for the proposed building, underscoring the environmental benefits of sustainable building practices. Thermal comfort assessments showed a 13% potential increase in acceptable comfort levels and a 5% decrease in unacceptable thermal comfort hours during occupied times, particularly in lecture and seminar rooms. Conclusions: The study concludes that even when dealing with old buildings with certain restrictions, strategic modifications can significantly improve energy efficiency, reduce carbon emissions, and enhance thermal comfort in educational buildings, even when increasing the cooling load.

This study explores an innovative focus for optimizing clusters in the LEACH-C protocol via applying the P-Median model. Using a fixed number of sensors, the method is centered on improving energy efficiency for Wireless Sensor Networks (WSN). Applying the P-Median model managed to delay the death of the first node, reducing both the number of clusters and the number of packets sent to the cluster heads, increasing packets sent to the sink, and increasing average network energy. These advances represent a significant improvement in energy efficiency, a central aspect of WSN, also contributing to long-term sustainability and lowering operating and maintenance costs. The relevance of this study reaches beyond improvements in energy efficiency, presenting the potential to revolutionize resource and infrastructure management, especially in remote areas. The results of this study open a promising path towards optimization in the field of WSN and highlight the usefulness of the P-Median model in improving performance and energy efficiency within these networks.

Introducción— El consumo de sustancias psicoactivas ilícitas es una problemática que se vive a diario, donde personas de diferentes edades se han visto implicadas, resaltando que muchas de estas sustancias generan trastornos tales como, por ejemplo: la Marihuana o cannabis: su consumo afecta la función cerebral de manera directa, y particularmente las partes del cerebro responsables de la memoria, el aprendizaje, la atención, la toma de decisiones. El Bazuco: es una sustancia tóxica, cuyos principales riesgos de consumirla se reflejan en el deterioro neurológico y en el organismo, y es muy rápida su disolución en el torrente sanguíneo, aspecto que hace que sea muy adictiva. La Cocaína: su consumo afecta directamente el sistema nervioso y el resto del organismo de forma inmediata, en estas afectaciones se encuentran vasoconstricción, midriasis, hipertermia, taquicardia e hipertensión. La Heroína: es una sustancia altamente adictiva, inicialmente, sus efectos son muy placenteros, lo que propicia una conducta de consumo continuada y repetitiva, además, produce sensaciones de sequedad en la boca, enrojecimiento y acaloramiento de la piel, pesadez en brazos y piernas, náuseas y vómitos, comezón intensa y enturbiamiento de las facultades mentales. Objetivo— Esta problemática es algo que resalta mucho y de gran impacto en los jóvenes de acuerdo al contexto en el que se encuentren ya que hoy en dia hay mucha facilidad para obtener este tipo de sustancias, por ende, se han planteado una serie de trabajos que abordan desde la inteligencia artificial esa problemática. Metodología— El presente estudio realiza una revisión de 50 publicaciones relacionadas con el uso de métodos y técnicas de ML aplicadas al consumo de sustancias psicoactivas ilícitas. Resultados— De las publicaciones incluidas se hallaron temáticas en común por lo que se hace un resumen de los artículos seleccionados por cada temática y se describen brevemente los métodos adoptados, así como también una comparativa entre ellos, anotando los métodos usados, sus resultados y demás factores importantes de la aplicación o modelo en distintas áreas y se concluye con una serie de propuestas sobre las líneas que a futuro podrían encaminar la investigación en este campo.

Introduction— Doubly Fed Induction Motor (DFIM) is a popular machine used in variable speed drives, and its ruggedness, reliability and simplicity of speed control make it a suitable candidate for use in smart irrigation systems. Objective— This paper studies and evaluates the performance of DFIM at different operating conditions and shows that it can be viewed as a variable speed synchronous motor. Methodology— A mathematical model has been developed to optimize the performance of the DFIM in smart irrigation systems, taking into account the specific conditions of the application. In addition, an experimental setup was built and tested to enhance the theoretical results, which showed good correlation between the theoretical and experimental results. Results— The research results reveal that DFIM can be used to control the flow rate of water in irrigation systems, by adjusting the speed of the motor to match the desired flow rate. Conclusions— The results of this research demonstrate the potential of using the DFIM in smart irrigation systems to improve the performance and efficiency of irrigation and to provide better control and lower costs.