Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Introduction: The main cause of disruptions in the energy service is generated in the distribution grids. The faults need repairs before restoring the service, which requires their rapid location, since this process influences the duration and frequency of the disruptions. Many companies assess power service quality solely by measuring the equivalent interruption frequency and duration (DES and FES), as they lack the resources to invest time and money in strategies to improve system reliability. Objective: Determine the location of the fault zone in medium voltage power distribution systems. Method: The clustering methods of k-means and the Gaussian Mixture Model (GMM) based on the expectation-maximization algorithm were implemented, to create groups based on their characteristics, thus defining the probability of belonging to each one. Results: A methodology for the detection of failures efficiently was obtained, which serves as support for planning processes and execution of action plans, facilitating the taking of corrective measures related to the continuity of the service and decreasing the system restoration time. Conclusions: The application of the k-means and GMM algorithms allows identifying possible fault zones according to the test data. Although it does not show a single fault zone, since it makes estimates according to the data, it is a tool to make decisions based on the estimates obtained.

Multimodal data fusion is a research field that combines information from various sources, each with its own modalities. One of the prominent challenges in data fusion is addressing adverse conditions that arise when dealing with real-world implementations. This article presents a review of data fusion, conducting a comparative analysis through a literature search across various application domains that tackle the challenges of data heterogeneity and adverse conditions. The focus of this paper is centered on establishing a robust foundation to enable the development of future research in this field. This review reveals that almost half of the analyzed documents describe adverse conditions, but only a minority conduct analyses on how their techniques address noise or benefit from considering these conditions. The number of modalities used in the research is generally low, with most studies employing static data in 1D dimensions. Finally, it is crucial for researchers to continue working on an interdisciplinary vocabulary and consider applications in real-world environments with adverse conditions to advance in this field. It is also important to explore applications with higher-dimensional data and more modalities, which could provide valuable insights for addressing specific challenges in data fusion.

The analysis of sustainability in Cyber-Physical Systems (CPS) and its connection to non-functional requirements has become a highly critical aspect today. The diversity of contexts, concepts, design criteria, and perspectives among designers and researchers can lead to ambiguities and make determining or measuring system sustainability challenging. To address this issue, this articledescribes a proposed methodological tool with the primary objective of representing sustainability through the NFR Framework and elucidating the attributes contributing to its future operationalization. Through the identification and analysis of non-functional requirements, a series of inquiries are suggested in order to identify central aspects within the sustainability framework. Resolving these inquiries facilitates the assessment of these aspects on relevance scales defined according to the context. Designers and their teams could employ this model to establish metrics that highlight the relationships and contribution levels of each non-functional requirement in support of sustainability. While the final weighting remains within the purview of the designer and team, the proposed model enables the documentation, standardization, and detailed definition of the undertaken process and the applied valuation scale.

Introduction: Hemophilia A in pediatrics is a topic of interest due to the catastrophic, out-of-pocket, and health costs it generates, in addition to the disease burden it causes. Recently, the need to identify novel therapies has been emphasized. Objective: To evaluate the characteristics of research on pharmacological interventions for the management of hemophilia A in pediatrics. Method: Bibliometric study. A semi-structured search was conducted in the Scopus database. Results:  A total of 363 articles were included. The first publication was in 1964. Predominantly, the scientific output consisted of original articles (87.32%; n=317), followed by reviews (6.1%; n=22). International collaboration was 7.98%. The University Medical Center Utrecht (Netherlands) was the most prolific and impactful institution, while the United States was the most prolific and impactful country. The most frequently used keywords were blood coagulation factor 8, intravenous drug administration, and hemarthrosis. The co-occurrence network revealed three research niches related to therapy, age groups, and specific outcomes. Conclusions: A modest growth in research on pharmacological interventions for the management of hemophilia A in pediatrics was identified. The research has been based on primary data, led by Dutch institutions and in Japan, despite the United States being the most prolific country. The most frequently studied topics are related to pathophysiology, coagulation factor VIII, complications, and hemarthrosis.

Introduction: Microsurgery in plastic surgery has experienced significant growth since 1976, particularly in fields such as breast reconstruction and the management of surgical flaps. However, inequalities persist in scientific output and global access to this technology. Objective: This bibliometric study analyzed global trends in productivity, innovation, collaboration and gaps in microsurgery applied to plastic surgery. Method: A bibliometric analysis was conducted on publications indexed in Scopus, utilizing terms related to microsurgery and plastic surgery. Scientific mapping techniques and bibliometric analyses were applied to evaluate global output, international collaborations, and research themes. Results:  A total of 282 documents were identified, with the United States leading in scientific production and impact (h-index of 24). Microsurgery emerged as the most prolific journal, while Plastic and Reconstructive Surgery stood out for its impact. Key thematic areas included breast reconstruction and surgical flaps. Since 2012, a notable increase in scientific output has been observed. International collaboration networks are predominantly composed of countries with high or upper-middle incomes. Conclusions: This analysis provides a comprehensive overview of global trends in microsurgery applied to plastic surgery, highlighting the central role of international collaborations and emerging thematic areas. The findings carry significant implications for evidence-based decision-making and the design of policies that promote equity in research and specialized surgical care.

Global mental health has emerged as a critical area of concern in the 21st century, driven by the increasing prevalence of mental health disorders, the impact of globalization, and the growing recognition of mental health as a cornerstone of overall well-being. The World Health Organization estimates that one in four people will be affected by mental or neurological disorders at some point in their lives, underscoring the urgency of addressing this issue. Despite this, mental health remains underprioritized in many healthcare systems, particularly in low- and middle-income countries, where resources are scarce and stigma persists. Current needs in global mental health include the integration of mental health services into primary care, the development of culturally sensitive interventions, and the training of healthcare professionals equipped to address these challenges. Promoting academic and scientific thinking among future healthcare professionals is a strategic approach to addressing these needs. By fostering a deep understanding of the social, cultural, and biological determinants of mental health, as well as the latest evidence-based practices, future professionals can be better prepared to design and implement innovative solutions. This approach not only enhances their ability to respond to the diverse and complex demands of global mental health but also encourages a proactive mindset toward research and policy development. Ultimately, investing in the academic and scientific training of healthcare professionals can lead to more effective mental health interventions, reduced disparities, and improved outcomes for populations worldwide, aligning with the contemporary needs of a rapidly evolving global landscape.     

Introduction: The generation of a work permit involves the management of specialized documentation that reflects the employee's qualifications for a certain task, a process that is usually costly. Objective: Create an integrated platform that allows user companies to intelligently and efficiently manage the processes of generating work permits for high-risk tasks. Methodology: The characterization of the sector is addressed by raising requirements for high-risk companies. The design involves the use of technologies such as DigitalOcean®, Rails®, PHP®, Ubuntu®, MySQL® and Power BI. The platform follows a comprehensive process of data extraction, transformation and loading, supported by a Data Warehouse. Results: The prevalence of manual methods in permit management stands out, justifying the relevance of Victoria 4.0 to streamline processes and guarantee the reliability of the data. User interaction is detailed, highlighting its intuitive interaction, and specific improvements in certain functionalities are described. In addition, the commercial prospects of Victoria 4.0 are discussed, comparing it with other market options and highlighting its adaptability to local regulations. Conclusions: Victoria 4.0 is not only a valuable alternative for companies that have the obligation to manage work permits for their employees, but it also has significant growth prospects in a market estimated at more than 2 billion dollars.    

Introduction: Many studies have been developed using techniques to remove pollutants in water bodies. Among these techniques is adsorption, a surface technique that uses an adsorbent based on agricultural residues to remove pollutants such as heavy metals. However, these studies have mostly been conducted at a laboratory scale, and few investigations have sought to anticipate the effectiveness of the adsorbent at an industrial scale. Objective: To simulate the removal of Cr(VI) in solution by a packed column at industrial scale using Theobroma cacao L. biomass as adsorbent. Method: A modeling and simulation type method was used where the computer tool Aspen Adsorption was employed to simulate the adsorption column using different configurations combined with a parametric evaluation. Results:  From the findings it was obtained that, using the Langmuir and Linear Driving Force (LDF) mathematical models, adsorption process efficiencies of up to 97% Cr (VI) removal were presented. In addition, the best parametric values were a column height of 5m, a flow rate of 100 m3/day and an initial concentration of 3500 mg/L. Conclusions: These findings allow presenting this study as a novel way in the engineering field of how computational tools have the ability to predict the possible behavior of adsorption columns packed with organic waste-based biomasses.

Morphological research serves as a fundamental pillar in the advancement of anatomical and medical knowledge, with broad applications in education, surgery, pathology, and forensic medicine. However, ethical considerations in this field remain largely overlooked and insufficiently regulated. Historically, the use of cadavers in anatomical studies has posed significant ethical challenges, ranging from the acquisition of bodies without consent to the present-day lack of specific regulatory frameworks. This article explores the existing gaps in applied ethics within morphological research, highlighting the urgent need for well-defined regulations and strict adherence to universal bioethical principles.

Introduction: Project formulation requires defining objectives, alternatives, resources, and evaluation criteria in increasingly complex contexts. In Colombia, despite the support of the Adjusted General Methodology (MGA), technical and operational barriers persist. Generative Artificial Intelligence, particularly large language models (LLMs), has emerged to support writing, synthesis, and planning, but its use in project formulation still lacks consolidated evidence. Objective: To identify and classify how LLMs have been applied to project formulation, their benefits and limitations, the evaluation methods used, application domains, and the existence of LLM or GenAI tools that support the MGA. Method: Systematic mapping following Petersen. Research questions were defined with PICOC, together with search strings and inclusion and exclusion criteria. IEEE Xplore, Scopus, ScienceDirect, Web of Science, and Taylor & Francis were queried from 2020 to 2025. A PRISMA diagram summarized identification, screening, and selection. Of 372 records, 33 studies met the criteria. Results:  GPT-3.5 and GPT-4 predominate. The most evidenced tasks include effort and time estimation, plan and schedule generation, ideation and design, and early risk management. Support was also observed for requirements, work breakdown, and resource allocation. Evaluation combined human comparisons, expert review, automatic metrics with other LLMs, surveys or interviews, and objective measures. No reports were found of LLM or GenAI tools to support the MGA. Conclusions: LLMs speed up cognitive tasks and improve clarity and creativity, but they require human validation, better contextualization, explainability, data protection, and technical integration. Trends point to hybrid approaches with retrieval augmented generation (RAG), multitask agents, and multimodal capabilities. The absence of reported experiences for the MGA reveals a strategic opportunity for research and development.