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The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used to monitor and control different environments, such as fire, water, temperature, and movement, among others. These sensors detect anomalies in the input data to the system, allowing alerts to be generated for early risk detection. The advancement of artificial intelligence has led to improved sensor systems and networks, resulting in devices with better performance and more precise results by incorporating various features. The aim of this work is to conduct a bibliometric analysis using the PRISMA 2020 set to identify research trends in the development of machine learning applications in fiber optic sensors. This methodology facilitates the analysis of a dataset comprised of documents obtained from Scopus and Web of Science databases. It enables the evaluation of both the quantity and quality of publications in the study area based on specific criteria, such as trends, key concepts, and advances in concepts over time. The study found that deep learning techniques and fiber Bragg gratings have been extensively researched in infrastructure, with a focus on using fiber optic sensors for structural health monitoring in future research. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. This presents an opportunity for future studies.

In the field of art, machine learning models have been used to predict artistic styles in paintings. The foregoing is somewhat advantageous for analysts, as these tools can provide more valuable results and help reduce bias in the results and conclusions provided. Therefore, the objective of this research was to examine research trends in the use of machine learning to predict artistic styles from a bibliometric review based on the PRISMA methodology. From the search equations, 268 documents were found, out of which, following the application of inclusion and exclusion criteria, 128 documents were analyzed. Through quantitative analysis, a growing research interest in the subject is evident, progressing from user perception approaches to the utilization of tools like deep learning for art studies. Among the main results, it is possible to identify that one of the most used techniques in the field has been neural networks for pattern recognition. Also, a large part of the research focuses on the use of design software for image creation and manipulation. Finally, it is found that the number of studies focused on contemporary modern art is still limited, this is due to the fact that a large part of the investigations has focused on historical artistic styles.

This study aims to analyze the impact of social media on pre‑purchase decision‑making among both current and future professionals. For this analysis, information obtained from a previous bibliometric study was used. From this study, 6 research questions and 3 hypotheses were developed, driven by 8 variables. A 14‑question survey was administered to 214 students and graduates from various programs in Medellín, Colombia. Results indicated that 92.5% of participants actively used social media for information before making purchase decisions, with Instagram, YouTube, and Facebook as preferred platforms. Instagram was notably popular among those aged 18–25, while Facebook and YouTube had a more uniform appeal across age groups. Additionally, participants also considered reviews on platforms like Google Reviews, Amazon, and Mercado Libre. The findings suggest no significant age‑based differences in platform preferences, implying that personal factors beyond age influence social media choice. Furthermore, the use of social networks to research products or services is a common practice among students and professionals, regardless of their educational level. In conclusion, this study indeed offers valuable insights for organizations to refine their marketing strategies and captivate customers through the quality, impact, and dissemination of the content they post on social media.

Machine learning (ML) has revolutionized resource management in agriculture by analyzing vast amounts of data and creating precise predictive models. Precision agriculture improves agricultural productivity and profitability while reducing costs and environmental impact. However, ML implementation faces challenges such as managing large volumes of data and adequate infrastructure. Despite significant advances in ML applications in sustainable agriculture, there is still a lack of deep and systematic understanding in several areas. Challenges include integrating data sources and adapting models to local conditions. This research aims to identify research trends and key players associated with ML use in sustainable agriculture. A systematic review was conducted using the PRISMA methodology by a bibliometric analysis to capture relevant studies from the Scopus and Web of Science databases. The study analyzed the ML literature in sustainable agriculture between 2007 and 2025, identifying 124 articles that meet the criteria for certainty assessment. The findings show a quadratic polynomial growth in the publication of articles on ML in sustainable agriculture, with a notable increase of up to 91% per year. The most productive years were 2024, 2022, and 2023, demonstrating a growing interest in the field. The study highlights the importance of integrating data from multiple sources for improved decision making, soil health monitoring, and understanding the interaction between climate, topography, and soil properties with agricultural land use and crop patterns. Furthermore, ML in sustainable agriculture has evolved from understanding weather data to integrating advanced technologies like the Internet of Things, remote sensing, and smart farming. Finally, the research agenda highlights the need for the deepening and expansion of predominant concepts, such as deep learning and smart farming, to develop more detailed and specialized studies and explore new applications to maximize the benefits of ML in agricultural sustainability.

Due to the rapid and constant changes in the market, organizations are increasingly forced to develop innovative products or services with added value. In Colombia, a large percentage of information and communications technology (ICT) firms concentrate in the city of Medellín. For these organizations, developing and implementing innovation capabilities (ICs) is considered strategic and essential to strengthen their competitiveness and the economic contribution of the ICT sector to the city and the country, which is reflected in the national GDP. Therefore, the purpose of this paper is to analyze the variables that lead to the identification and incorporation of ICs by firms in the ict sector through a systematic literature review (SLR) in the 6 most relevant bibliographic databases. The results obtained were used for the analysis of the ICT sector in Medellín. According to our findings, firms must possess the necessary innovation capabilities and competencies to develop skills and knowledge oriented to research and development and to be competitive in the market, considering the transformations of the industry. In addition, identifying and incorporating ics into their organizational structures allow them to improve decision-making and create strategies that contribute to strengthening their innovation activity and competitive advantage. como respuesta a cambios rápidos y constantes en el mercado, las organizaciones se ven cada vez más en la necesidad de generar productos o servicios innovadores y con valor agregado. Frente a este escenario, para que las organizaciones puedan generar resultados innovadores, estas deben contar con competencias y capacidades de innovación (CI) que posibiliten la consolidación de habilidades y conocimientos orientados a la investigación y el desarrollo y les permitan además ser competitivas. En la ciudad de Medellín se concentra un gran porcentaje de las empresas del sector de las tecnologías de la información y la comunicación (TIC) en Colombia, para las cuales desarrollar CI es estratégico y de vital importancia para el fortalecimiento de su competitividad, dadas las transformaciones que involucran a esta industria y el aporte económico que el sector TIC representa para la ciudad y el país, que se ve reflejado en el PIB nacional. Por lo anterior, el objetivo de esta investigación es analizar las variables que conducen a la identificación e incorporación de CI en las empresas del sector TIC, para lo cual se acudió a una revisión sistemática de literatura (RSL) en las 6 bases de datos bibliográficas más relevantes para la academia. Los resultados obtenidos fueron utilizados para analizar el sector TIC de Medellín, permitiendo concluir que la identificación e incorporación de las CI dentro de las estructuras organizativas hacen posible mejorar la toma de decisiones, generando con ello estrategias que contribuyen al fortalecimiento de la innovación y las ventajas competitivas. como resposta a mudanças rápidas e constantes no mercado, as organizações se veem cada vez mais na necessidade de gerar produtos ou serviços inovadores que lhes permitam outorgar valor agregado. Para gerar resultados inovadores, as organizações devem contar com competências e capacidades de inovação (CI) que lhes possibilitem desenvolver habilidades e conhecimentos orientados para a pesquisa e o desenvolvimento, e além de serem competitivas. Na cidade de Medellín, Colômbia, concentra-se grande porcentagem das organizações do setor das tecnologias da informação e da comunicação (TIC) do país para as quais desenvolver CI é considerado estratégico e de vital importância para fortalecer sua competitividade, tendo em vista as transformações que envolvem essa indústria e a contribuição econômica que o setor de TIC representa para a cidade e o país, o que se vê refletido no pib nacional. Nesse sentido, o objetivo deste artigo é analisar as variáveis que conduzem à identificação e à incorporação de CI nas empresas do setor das TIC; para isso, recorreu-se a uma revisão sistemática da literatura nas seis bases de dados bibliográficas mais relevantes na academia. Os resultados foram utilizados para analisar o setor das TIC em Medellín. Pode-se concluir que a identificação e a incorporação das CI dentro das estruturas organizacionais tornam possível que elas possam melhorar a tomada de decisões, gerando, com isso, estratégias que contribuam para o fortalecimento da inovação e das vantagens competitivas. En réponse aux évolutions rapides et constantes du marché, les organisations ont de plus en plus besoin de générer des produits ou services innovants leur permettant d'apporter une valeur ajoutée. Pour générer des résultats innovants, les organisations doivent disposer de compétences et de capacités d'innovation (CI) qui leur permettent de développer des compétences et des connaissances orientées vers la recherche et le développement, tout en étant compétitives. Un grand pourcentage d'organisations du secteur des technologies de l'information et de la communication (TIC) en Colombie sont concentrées dans la ville de Medellín, pour lesquelles le développement de CI se considère comme stratégique et d'une importance vitale pour renforcer leur compétitivité, compte tenu des transformations qui impliquent cette industrie et de la contribution économique que le secteur des TIC représente pour la ville et le pays, qui se reflète dans le PIB national. Par conséquent, l'objectif de cet article est d'analyser les variables qui conduisent à l'identification et à l'incorporation de l'IC dans les entreprises du secteur des tIC, pour lesquelles on a mené une revue systématique de la littérature (RSL) dans les six bases de données bibliographiques les plus pertinentes de l'académie. On a utilisé les résultats obtenus pour analyser le secteur des TIC à Medellin. On a pu conclure que l'identification et l'incorporation des CI dans les structures organisationnelles rend possible d'améliorer la prise de décision, en gé­nérant ainsi des stratégies qui contribuent au renforcement de l'innovation et des avantages concurrentiels.

In recent years, the rapidly changing landscape of society and the economy has compelled organizations to adapt and innovate. Information and communication technologies (ICTs) have seen significant advancements in hardware and software. However, many companies within the ICT sector often overlook the need to infuse innovation into areas beyond ICT development and infrastructure. This study evaluates the innovation capabilities of medium-sized enterprises providing Information Technology Service Management (ITSM) in Medellín, Colombia. Utilizing a structural equation model, the study examined causal variables related to competitiveness and innovation capacity. Of the 42 variables considered, seven, including corporate branding evaluation, sustainable development, and improvisation capability, showed results below the normal threshold. The ICT sector, focused on the development and provision of technological and Industry 4.0-related services, continuously evolves. This model contributes to assessing and achieving that objective.

This article presents the design of an optical antenna with a square spiral geometry formed by five rings. The antenna uses graphene as a conductive material, taking advantage of its absorption properties. The graphene layer has a thickness of 0.0175 mm, a relative permittivity of 12, and a loss tangent of 0.03. In addition, Pyrex glass is used as the substrate, with a thickness of 1 mm, a relative permittivity of 4.82, and a loss tangent of 0.0054. The total size of the substrate is 6.60 × 6.60 mm, and the design was simulated using CST Studio Suite. Rectangular slots were incorporated into the structure to modify the current surface distribution surrounding the radiating patch. According to the results, the proposed design achieved a gain of 8.2 dB at a resonance frequency of 50.4 GHz, with a bandwidth of 967 MHz. The simulated antenna operates within the V‐band frequency range (40–75 GHz), making it suitable for the electromagnetic spectrum, which is widely used in millimeter‐wave radar systems and high‐speed wireless communication networks. Due to its ability to support gigabit data transfer speeds, the V band is also used for point‐to‐point radio links and wireless backhaul applications. Furthermore, since this frequency range does not require the payment of license fees, the proposed antenna offers a cost‐effective solution for this type of band due to the ability of the antenna to concentrate signal power in a specific direction.

The uncertainty that the COVID-19 pandemic has brought demonstrates that income redistribution and traditional debt relief mechanisms are insufficient to meet public spending needs, mitigate external debt, and comply with the UN’s Sustainable Development Goals (SDGs), which aim to reduce multilateral debt to sustainable levels. Also, West African countries have focused their attention on the long-term fight against poverty and inequality and strengthening their social programs, especially in primary health care and macroeconomic stability. However, for more than a decade, the developing and least developed countries of West Africa have faced rapidly weakening macroeconomic conditions, combining several interrelated crises such as the sharp decline in oil prices, volatile financial markets and tourism disruptions, a global recession, the crisis of climate change, and shortages of food and energy, along with the economic contraction of COVID-19. Data from these countries show that health spending increases economic growth, minimizes infant mortality rates, and reduces debt. Furthermore, increasing government spending efficiency reduces the total debt and improves the health sector, in particular.

The distributed structure of traditional networks often fails to promptly and accurately provide the computational power required for artificial intelligence (AI), hindering its practical application and implementation. Consequently, this research aims to analyze the use of AI in software-defined networks (SDNs). To achieve this goal, a systematic literature review (SLR) is conducted based on the PRISMA 2020 statement. Through this review, it is found that, bottom-up, from the perspective of the data plane, control plane, and application plane of SDNs, the integration of various network planes with AI is feasible, giving rise to Intelligent Software Defined Networking (ISDN). As a primary conclusion, it was found that the application of AI-related algorithms in SDNs is extensive and faces numerous challenges. Nonetheless, these challenges are propelling the development of SDNs in a more promising direction through the adoption of novel methods and tools such as route optimization, software-defined routing, intelligent methods for network security, and AI-based traffic engineering, among others.

Understanding why people adopt or ignore vector-borne disease (VBD) preventive measures is key to better risk assessment and control. However, little is known about why some households adopt preventive practices while others do not, which is particularly striking in this era of One Health’s attention to human, environmental, and animal health. We examined what household factors are linked to practices that may reduce exposure to disease vectors, with a focus on Chagas disease (CD) and American Cutaneous Leishmaniasis (ACL) vectors. We surveyed 204 households in 12 rural communities in Coclé Province, Republic of Panama, between March 2022 and December 2023. We used logistic regression models to explore the association between household contextual elements, such as respondents’ sex, wealth (consumer goods and agricultural), knowledge about ACL and CD, feelings about insects, and perceptions of control over health outcomes, and personal (use of repellents, and hand protection before touching a CD vector) and property-based behaviors (use of insecticides in the house, use of windows/doors screens, and cleaning peridomestic debris) that may reduce exposure to disease vectors. We found mixed associations between protective behaviors and the contextual household elements . Participants who reported feeling bothered by insects were more likely to use repellents (Odds Ratio [OR]: 2.97 95% Confidence Interval [95%CI]: 1.47-6.20), whereas those who reported being in control of their health were less likely to use protection before touching a CD vector (OR = 0.8, CI: 0.67-0.95). Window/door screens were associated with more household consumer goods wealth (OR: 1.44; CI: 1.23-1.71), while households with a history of ACL cases were more likely to have peridomestic debris accumulation (OR: 2.33; CI: 1.17-4.75). Additionally, householders bothered by insects were less likely to have peridomestic debris (OR: 0.42; CI: 0.20-0.84), as well as those who believe health outcomes happen by chance (OR: 0.89; CI: 0.82-0.98). Our findings emphasize the importance of considering a more comprehensive household background and attention to cultural values to foster context-sensitive strategies for vector-borne pathogen prevention and control.