Currently, health centers are being affected by various cyberattacks putting at risk the confidential information of their patients and the organization because they do not have a plan or tools to help them mitigate these cyberattacks, which is important to know what measures to take to protect the privacy of personal data. The present work was carried out under a systematic literature review, which aims to show the importance of cybersecurity in the health sector knowing which tools are the most used and efficient to prevent a cyberattack. A systematic review of 301 articles was carried out, 79 of which are aligned with the objective set, fulfilling the inclusion and exclusion criteria. The search for information was carried out in the Scopus and Dimensions databases. The analysis carried out has resulted in good information that was compiled for the development of this topic, being favorable thanks to the different research of different authors.

Agriculture currently faces multiple challenges associated with climate change, the reduction in arable land, and the need to produce food more efficiently in terms of water and nutrient use. This study evaluated an Internet of Things (IoT)-based hydroponic monitoring system with threshold-controlled recirculation for lettuce (Lactuca sativa) under open-field thermal stress conditions, comparing it with a conventional closed recirculating PVC pipe-based hydroponic system operated using fixed pump timing. The architecture integrated an ESP32 microcontroller, sensors for nutrient solution temperature, pH, total dissolved solids (TDS), turbidity voltage, dissolved oxygen (DO), and electrical conductivity (EC), Wi-Fi/HTTPS connectivity, a PHP–MySQL server, and a web interface for near-real-time monitoring. During the growing period, 241,797 readings were recorded between 21 January and 13 February 2026. The threshold-based logic activated the pump mainly according to nutrient solution temperature and DO, while pH, EC, TDS, and relative turbidity voltage were monitored as operational indicators. The sensor-instrumented system operated with pump activation during approximately 28.5% of the monitoring period, while temperature exhibited high variability and peaks of 40.19 °C. Visual crop monitoring showed greater canopy uniformity in the sensor-instrumented system, supporting the technical feasibility of low-cost IoT-based monitoring and threshold-controlled recirculation for open-field hydroponic production of lettuce.

El presente estudio se llevó a cabo con el objetivo de comprobar la relación entre dependencia funcional y depresión en el adulto mayor. La metodología que se empleó corresponde a un estudio de tipo aplicado, observacional; analítico de casos y controles, la muestra estuvo conformada por 180 adultos mayores que cumplieron con los criterios de selección, de los cuales 60 tuvieron dependencia funcional y depresión. Se utilizaron como instrumentos de evaluación la Escala Abreviada de Yesavage y el Índice de Katz. Como resultado el Odds ratio fue de 2,5 con un intervalo de confianza de 1,32 – 4,72 con un valor p de 0,004. Y de los adultos mayores con dependencia funcional el 60% presentaron depresión y 37,5% no presentaron. Se concluye que existe una relación directa entre dependencia funcional y depresión. Y que la proporción de dependencia funcional con depresión fue mayor en comparación con los que no presentaron depresión. Asimismo, la depresión si representa un factor de riesgo en los adultos mayores con dependencia funcional.

The measurement of urban development in Latin American cities has historically relied on one-dimensional models focused on GDP or density, which are insufficient to guide policies in heterogeneous and unequal contexts. This study designs and applies an empirical and comparative model with a socioeconomic approach to evaluate urban development in Lima, Medellín, and San Salvador in 2020–2024. Seventeen indicators that are comparable, objective, and publicly available in the three cities are integrated and normalized using min–max, and composite indices are estimated using three methods: equal weighting, CRITIC, and Entropy. It was found that Lima consistently shows the greatest relative progress (≈6–7%); Medellín consolidates high levels with moderate increases (≈2–4%); and San Salvador records the highest proportional growth under the Entropy method (≈11%). These findings are consistent with citizen perceptions obtained from a survey of 1170 participants (April–August 2025), according to which, on average, 60% recognize the existence of urban growth in the three cities. The proposed model is reproducible and transparent, contributing significantly to year-on-year monitoring and the prioritization of interventions by local and national governments by enabling short- and medium-term readings, in line with the Sustainable Development Goals (SDGs).

The growing sophistication of cyberattacks in Internet of Things (IoT) environments demands proactive and efficient solutions. We present an automated hyperparameter optimization (HPO) method for detecting cyberattacks in IoT that explicitly addresses class imbalance. The approach combines a Random Forest surrogate, a UCB acquisition function with controlled exploration, and an objective function that maximizes weighted F1 and MCC; it also integrates stratified validation and a compact selection of descriptors by metaheuristic consensus. Five models (RandomForest, AdaBoost, DecisionTree, XGBoost, and MLP) were evaluated on CICIoT2023 and CIC-DDoS2019. The results show systematic improvements over default configurations and competitiveness compared to Hyperopt and GridSearch. For RandomForest, marked increases were observed in CIC-DDoS2019 (F1-Score from 0.9469 to 0.9995; MCC from 0.9284 to 0.9986) and consistent improvements in CICIoT2023 (F1-Score from 0.9947 to 0.9954; MCC from 0.9885 to 0.9896), while maintaining low inference times. These results demonstrate that the proposed HPO offers a solid balance between performance, computational cost, and traceability, and constitutes a reproducible alternative for strengthening cybersecurity mechanisms in IoT environments with limited resources.

Urban sustainability assessments in Latin America have relied predominantly on institutional and technical indicators, leaving resident perceptions—a critical dimension of policy legitimacy—systematically underexplored. This study addresses that gap through a comparative analysis of how residents perceive sustainable urban development across three Latin American cities: Lima (Peru), Medellín (Colombia), and San Salvador (El Salvador). Drawing on 1209 structured surveys administered in 2025 (431 in San Salvador, 390 in Lima, 388 in Medellín), the study measures six dimensions of perceived urban sustainability: urban growth trends, strategic direction of development, visibility of sustainability initiatives, expectations of self‐sustainability, equity in the distribution of public space, and fairness of urban development policies. Internal consistency was confirmed across all three samples (Cronbach's α = 0.751–0.772). Findings reveal a consistent legitimacy gap: while majorities acknowledge ongoing urban growth (52.6%–74.0%), no city reaches majority endorsement of its development direction (30.0%–40.7%). Recognition of sustainable actions remains below 50% even in Medellín, and equity dimensions produce the most critical evaluations across all three cities with 49%–67% of residents disagreeing that public spaces and urban policies benefit all sectors equally. Self‐sustainability expectations converge aspirationally across cities despite stark institutional differences, suggesting that public optimism is fragile rather than performance‐based. The study concludes that territorial equity, participatory planning, and the visible decentralization of sustainability interventions are indispensable conditions for building the social legitimacy necessary to advance genuinely inclusive urban development in the Latin American region. These findings contribute an empirically grounded, resident‐centered perspective to the SDG 11 agenda.