Producción Científica

 

 

This research focused on identifying various types of faults occurring on 330kV transmission lines through the use of artificial neural networks (ANN). A MATLAB model for the Gwagwalada-Katampe 330kV transmission line in Nigeria was implemented to generate fault datasets. Voltage and current fault parameters were utilized to train and simulate the ANN network architecture selected for each stage of fault detection. Four types of faults were considered, along with a fifth condition representing no fault. The results illustrated the success of the developed model in identifying various fault conditions and system parameters on the Gwagwalada-Katampe 330kV transmission line, modelled using MATLAB Simulink.

 

 

Purpose: This study aims to analyze and compare selected physical fitness, physiological, and psychological variables among boys from government, government- aided, and private schools in the Chennai district. The purpose is to understand how different school environments impact these variables and to provide insights that can inform policy and practice in physical education and health promotion. Methodology: A sample of 300 boys aged 12-15 years was selected through stratified random sampling, with 100 boys from each school type (government, government-aided, and private schools). Physical fitness was measured using the Fitness Gram test battery, physiological variables such as BMI, resting heart rate, and blood pressure were assessed using standard clinical procedures, and psychological variables were evaluated using the Rosenberg Self- Esteem Scale and the Perceived Stress Scale. Data were analyzed using ANOVA to compare the means across the three school types, with post-hoc tests conducted to identify specific group differences. Conclusion: The study found significant differences in physical fitness, physiological health, and psychological well-being among boys from different types of schools. Boys from private schools exhibited better physical fitness and lower stress levels compared to their peers in government and government-aided schools. These findings highlight the influence of socio-economic factors and access to resources on students’ health and suggest the need for targeted interventions in government and government- aided schools to improve physical and psychological well- being among students.

 

 

A study was conducted at General Hospital Ijebu Igbo antenatal section to investigate the prevalence of intestinal parasitic infection and anemia in pregnant women. A questionnaire was administered to 42 pregnant women who attended the antenatal section of the clinic during the study period. Out of these 42 pregnant women, 18 (42.9%) provided both fecal and blood samples for parasitological and hematological analysis. 50% of the respondents fall within 16-25years age group, while those within 36-45years have the lowest percentage (22.2%). 50% have the knowledge of the helminth infection, out of the 9(50%) that have the knowledge, only 7(77.8%) have the knowledge of how the infection is being transmitted. Of 18 respondents, 13(72%) have the knowledge of anemia, and 5(28%) of them had no prior knowledge of it. The parasitological analysis revealed three intestinal parasite which are Ascaris lumbricoides (22.2%), Enterobius vermicularis (11.11%) and Entamoeba histolytica (5.56%). There were no reported cases of severe anaemic condition in this hospital based study. This suggests that the awareness level of anemia and parasitic infection is moderately high. Therefore, screening for intestinal parasites and deworming of infected pregnant women should be included in antenatal care.

 

 

PT. Electronics Components Indonesia manufactures capacitors and focuses on enhancing productivity and operational efficiency of the frame welding machines through effective maintenance. This study employs a quantitative method to analyze the Overall Equipment Effectiveness (OEE) values, including availability, performance efficiency, and rate of quality, as well as conducting a Six Big Losses analysis. The results indicate that the average availability reached 97.83%, with a significant decrease in August due to downtime. Performance efficiency remained consistently above 90%, although higher product output tended to reduce efficiency. The rate of quality was stable and high, reflecting improvements in production processes and quality control. The average OEE value reached 88%, exceeding the global standard of 85%. To further enhance the effectiveness of the frame welding machines, suggested improvements include operator training, regular performance evaluations, attention to operator well-being, selection of high-quality raw materials, updating SOPs, regular preventive maintenance, improving workplace safety, and investing in backup energy systems. In conclusion, the improvements implemented successfully enhanced the performance and operational quality of the frame welding machines.

 

 

In the contemporary business landscape, effective supply chain management (SCM) is paramount for organizations seeking to thrive amidst evolving market dynamics and heightened customer expectations. This research paper presents a pioneering approach to SCM that harnesses cutting-edge technologies, namely Kafka and Akka, to revolutionize data integration and decision-making processes. By leveraging Kafka as a robust distributed event streaming platform and Akka as a versatile toolkit for developing concurrent and distributed applications, our system facilitates seamless communication and coordination across diverse nodes within the supply chain network. This paper elucidates the intricacies of the proposed architecture, detailing the implementation methodology and performance evaluation metrics. Through a comprehensive examination, we demonstrate how our solution enhances supply chain visibility, fosters operational agility, and enables real-time responsiveness to market fluctuations and customer demands. Moreover, practical use cases exemplify the transformative impact of our approach on inventory management optimization, order fulfillment efficiency, and logistics optimization. Furthermore, we delve into the challenges encountered during implementation and deployment, offering insights into potential mitigative strategies. Finally, we outline avenues for future research, exploring emerging trends and opportunities in the realm of SCM empowered by Kafka and Akka technologies.

 

 

Comprehensive clinical documentation is crucial for effective healthcare delivery, yet it poses a significant burden on healthcare professionals, leading to burnout, increased medical errors, and compromised patient safety. This paper explores the potential of generative AI (Artificial Intelligence) to streamline the clinical documentation process, specifically focusing on generating SOAP (Subjective, Objective, Assessment, Plan) and BIRP (Behavior, Intervention, Response, Plan) notes. We present a case study demonstrating the application of natural language processing (NLP) and automatic speech recognition (ASR) technologies to transcribe patient-clinician interactions, coupled with advanced prompting techniques to generate draft clinical notes using large language models (LLMs). The study highlights the benefits of this approach, including time savings, improved documentation quality, and enhanced patient-centered care. Additionally, we discuss ethical considerations, such as maintaining patient confidentiality and addressing model biases, underscoring the need for responsible deployment of generative AI in healthcare settings. The findings suggest that generative AI has the potential to revolutionize clinical documentation practices, alleviating administrative burdens and enabling healthcare professionals to focus more on direct patient care.

 

 

Epilepsy, a complex global neurological disorder, has spurred extensive research efforts focused on enhancing diagnostic and therapeutic strategies, with a growing emphasis on the identification of biomarkers. This bibliometric study examines 1,774 publications from 2000 to 2023, revealing a notable increase in research activity, particularly in the past decade. The US, China, and the UK lead contributions, with Asian countries exhibiting growing potential. Keyword co-occurrence analysis reveals a shift towards investigations of neuroinflammatory and genetic biomarkers, as well as emerging areas such as artificial intelligence and epigenetics. Content analysis links specific epilepsy aetiologies to biomarkers, offering promising possibilities for personalised diagnostics and treatments. These findings yield valuable insights into current trends, guiding future research and informing the development of targeted approaches for the diagnosis and treatment of epilepsy.

 

 

The Vehicle Routing Problem (VRP) not only poses a fundamental challenge in logistics and operations management but also plays a crucial role in mitigating environmental impact through the optimization of efficient and sustainable routes. The scientometric development proceeded in two stages: scientific mapping and network construction. In the first stage, a bibliometric analysis of publications indexed in Scopus from 2000 to March 2024 was conducted using the PRISMA and Tree of Sciences (TOS) methodology, selecting 364 relevant documents on “sustainable” and “Vehicle Routing Problem”. Recommended bibliometric procedures were applied, and Bibliometrix tools were utilized to integrate bibliographic information. In the second stage, a citation network was constructed using graph theory to identify key documents and research trends, analyzing indicators such as Indegree, Betweenness, and Outdegree. The results indicated a significant increase in publications on VRP and sustainability since 2013, highlighting international collaboration and the leadership of China and the United States. Key authors and journals in the field were also identified. Finally, research clusters were developed on electric vehicle routing optimization, optimization methods, routing problems, and logistical challenges, underscoring the cooperation between enterprises and sustainable logistics as key areas for future research.

 

 

Hybrid modeling in bioprocess engineering has emerged as a promising approach to strengthen process system engineering applications. However, understanding evolution of the field structure is a challenge. To address this gap, we conducted a comprehensive bibliometric analysis of the field. This study aims to assess publications metadata quantitatively and qualitatively to map the research landscape. Through a systematic review of Scopus and Web of Science databases, 360 contributions have been identified within chemical or biochemical engineering. Using Bibliometrix®, Tree of Science®, VantagePoint®, VOSViewer®, and Python, metadata was analyzed and visualized, revealing “hybrid model” and “neural networks” are the central keywords on the field, with notable contributions from countries like Portugal and the United States of America. Thematic analysis unveiled three clusters: one dealing with control applications and other two that combine machine learning terminology with bioprocesses concepts. Furthermore, the field exhibits a high level of collaboration, with leading researchers such as Rui Oliveira and Moritz von Stosch making significant contributions. Based on these findings, insights into the research trends and future directions are presented.

 

 

This study investigated the conversion of sugars into furan derivatives, specifically 2,5-dimethylfuran, through catalytic processes using bibliographic analysis. This method evaluates scientific outcomes and impact within a specific field by analyzing data such as publication trends, references, collaborative models, leading authors, and institutions. The study utilized data from the reliable Scopus database and conducted analysis using the visualization of similarity (VOS) viewer program to gain in-depth insights into the current state of research on this topic. The findings revealed that “5 hydroxymethyl furfural” was the most used keyword, followed by “biomass” and “catalysis.” The research trend remained stable and popular from 2006 to 2022, with a decline beginning in 2023. The growing number of publications indicates increasing interest and importance of these topics. Notably, China led in the number of publications, with 80% more than the second-ranked United States, followed closely by India in the third place. The study also highlighted citation linkages between authors and countries, providing a comprehensive overview of research on converting sugars to furan derivatives, particularly 2,5-dimethylfuran, through catalytic processes.