Producción Científica

 

 

Seawater intrusion is among the world’s leading causes of groundwater contamination, as salty water can affect potable water access, food production, and ecosystem functions. To explore such contamination sources, multivariate analysis supported by unsupervised learning tools has been used for decades to aid in water resource pattern recognition, clustering, and water quality data variability characterization. This study proposes a systematic review of these techniques applied for supporting seawater intrusion identification based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and subsequent bibliometric analysis of 102 coastal hydrogeological studies. The most relevant identified methods, including principal components analysis (PCA), hierarchical clustering analysis, K-means clustering, and self-organizing maps, are explained and applied to a case study. Although 74 % of the studies that applied dimensional reduction methods, such as PCA, associated most of the database variance with the salinization process, 77 % of the studies that applied clustering methods associated at least one water sample cluster with the influence of seawater intrusion. Based on the review and a practical demonstration using the open-source R software platform, recommendations are made regarding data preprocessing, research opportunities, and publishing information necessary to replicate and validate the studies.

 

 

Increasing manufacturing efficiency has been a constant challenge since the First Industrial Revolution. What started as mechanization and turned into electricity-driven operations has experienced the power of digitalization. Currently, the manufacturing industry is experiencing an exponential increase in data availability, but it is essential to deal with the complexity and dynamics involved to improve manufacturing indicators. The aim of this study is to identify and allow an understanding of the unfilled gaps and the opportunities regarding production scheduling using machine learning and data science processes. In order to accomplish these goals, the current study was based on the Knowledge Development Process-Constructivist (ProKnow-C) methodology. Firstly, selecting 30 articles from 3608 published articles across five databases between 2015 and 2019 created a bibliographic portfolio. Secondly, a bibliometric analysis, which generated comparative charts of the journals’ relevance regarding its impact factor, scientific recognition of the articles, publishing year, highlighted authors and keywords was carried out. Thirdly, the selected articles were read thoroughly through a systemic analysis in order to identify research problems, proposed solutions, and unfilled gaps. Then, research opportunities identified were: (i) Big data and associated analytics; (ii) Collaboration between different disciplines; (iii) Solution Customization; and (iv) Digital twin development.

 

 

Industrial parks have been used to promote the economic development of countries. However, its rapid growth has generated environmental problems related to the depletion of natural resources and pollution. Consequently, the network analysis and the bibliometric analysis applied in this research generated qualitative and quantitative information from a systemic perspective on the thematic and community evolution of research on industrial parks (IP) performed to improve its negative environmental impact and reach sustainability. This study used the Web of Science (WoS) database from 1996 – 2019. The main trends and critical research points were identified in four periods of 6-year each. Social network analysis (SNA) was used to identify the intellectual structure main and the academic collaboration networks established among countries/territories, institutions, and authors. The most productive country in articles is currently China (882), however, when we consider the frequency of articles per million inhabitants, it ranks seventh. The WoS database grouped 63.6 % of the articles published in the subjects of “Environmental Sciences & Ecology”, “Engineering”, and “Science & Technology – Other Topics”. Industrial Ecology (IE), Industrial Symbiosis (IS), and Circular Economy (CE) were the author keywords with the highest frequency, indicating that IP research has focused from these perspectives to promote the exchange of byproducts and to evaluate the performance and environmental impact of industrial areas through the use of methodologies such as carbon footprints, emergy analysis, and life cycle analysis (LCA). Finally, some themes were identified and proposed for future research based on analyzing research trends and hot spots from the literature review on industrial parks.

 

 

Bibliometric studies allow to collect, organize and process information that can be used to guide the development of research and innovation and to provide basis for decision-making. Paraffin/olefin separations constitute an important industrial issue because cryogenic separation methods are frequently needed in industrial sites and are very expensive. As a consequence, the use of membrane separation processes has been extensively encouraged and has become an attractive alternative for commercial separation processes, as this may lead to reduction of production costs, equipment size, energy consumption and waste generation. For these reasons, a bibliometric survey of paraffin/olefin membrane separation processes is carried out in the present study in order to evaluate the maturity of the technology for this specific application. Although different studies have proposed the use of distinct alternatives for olefin/paraffin separations, the present work makes clear that consensus has yet to be reached among researchers and technicians regarding the specific membranes and operation conditions that will make these processes scalable for large-scale commercial applications.

 

 

Background: In the face of numerous sustainability challenges within global logistics operations, smart logistics, or Logistics 4.0, has emerged as a rapidly evolving field over the past decade. Situated within the broader context of Industry 4.0, Logistics 4.0 serves as a critical pillar for ensuring business sustainability by leveraging innovative and disruptive technological solutions. This study offers a novel and comprehensive analysis of the role of Logistics 4.0 in fostering business sustainability, with a particular focus on the agro-industrial sector. Methods: Employing a bibliometric and content analysis approach, this research examines 56 publications from 2015 to 2021, sourced from Scopus, ScienceDirect, and Springer databases. The bibliometric research method incorporates joint keyword analysis using VOSviewer and is complemented by a content analysis of the selected articles. The bibliometric analysis uncovers a growing yet still nascent publication trend in this field. Results: The study reveals that Logistics 4.0 plays a significant role in enhancing the sustainability of firms across various sectors, particularly within the agro-industrial sector. By harnessing digital technologies and innovative business models, Logistics 4.0 paves the way for creating competitive advantages for agro-industrial firms. Conclusion: This research emphasizes the pivotal role of Logistics 4.0 in promoting sustainable and competitive growth in agribusiness, offering valuable insights for both academia and industry practitioners.

 

 

The prevalence of Diabetes Mellitus and, particularly, type 2 diabetes (T2D) is increasing every year worldwide. Therefore, changed glucose homeostasis is associated with altered gut microbiota and with the development of type 2 diabetes mellitus (T2DM) and related complications. Among other concerns, an important aspect within this issue is the reversion of dysbiosis reported to be present in T2D patients, in which diet plays a key role, and particularly dietary fiber has shown a promising position. β-glucans are heterogeneous non-starch polysaccharides, constituted by D-glucose monomers linked through different β-glycosidic bonds, and changes in their structure or molecular weight affect the expressed biological properties. They appear in certain cereals, yeasts, or mushrooms and are widely known by their hypocholesterolemia effect. This study explored the current knowledge on the potential of β-glucans to modulate glucose homeostasis due to their prebiotic action, by performing a bibliometric analysis using the VOSviewer software and a narrative review. The bibliometric analysis showed that, despite the high number of references dealing with β-glucan and diabetes, there are few articles on glucans, diabetes, and intestinal dysbiosis. The detailed study on preclinical studies and clinical trials conducted during the last decade showed an improvement in glucose homeostasis due to β-glucan supplementation, studies on biochemical markers, and gut microbiota, and β-glucan are scarce. Nevertheless, existing data showed, both in animals and humans, a tendency towards an increase in beneficial bacteria and in the production of short-chain fat acids (SCFAs), particularly butyric acid. These aspects should be confirmed in the years to come to establish clear recommendations for β-glucan as a prebiotic coadjutant in the management of Diabetes Mellitus.

 

 

ChatGPT adds to the list of artificial intelligence-based systems designed to perform specific tasks and answer questions by interacting with users (Apple’s Siri, Amazon’s Alexa, Google’s Assistant and Bard, Microsoft’s Cortana, IBM’s Watson, Bixby from Samsung, among others). ChatGPT works using OpenAI’s GPT (Generative Pretrained Transformer) language model and is capable of learning from users’ preferences and behavior patterns to customize its response. ChatGPT has the potential to be applied in different fields, including education, journalism, scientific writing, communication, cell biology, and biotechnology, where there is already evidence. The aim of this work was to analyze the possible applications of ChatGPT in the agricultural and livestock industry. First, a scientometric analysis was performed with VosViewer and Bibliometrix (Bliblioshiny). 3 clusters were identified: (a) Main characteristics; (b) learning systems you use; and (c) applications. To the question: What are the main applications in which ChatGTP will revolutionize agriculture (or livestock) in the world? ChatGPT responded: (a) in the agricultural field: improvement of agricultural decision-making, optimization of agricultural production, detection and prevention of plant diseases, climate management, and supply chain management; and (b) in the livestock field: improvement of animal health and welfare, optimization of animal production, supply chain management, detection and prevention of zoonotic diseases, and climate management for animal production. ChatGPT does not scientifically support its answer, but from the analysis carried out, we find that there is enough scientific evidence to conclude, in this case, that its answers were correct. While ChatGPT does not necessarily scientifically substantiate its answers, users should. There is a lack of studies on the use of Artificial Intelligence and its relationship with ethics.

 

 

This research aimed to show how scientific production has developed on age generations at work, the scientific production that was used was indexed in the Scopus and Web of Science databases. The methodology used was bibliometric with data from 2000 to April 2021, using the Bibliometrix program for the analysis of 485 documents, distributed in journals, articles, papers, editorial, letters, notes, reviews and short interviews. The analyzes carried out were to the annual scientific production, the sources, the authors and the documents. It could be concluded that scientific production is very low, even though it has been increasing over time, the sources that have contributed more studies on the subject are related to the health area, most of the authors work together and the most relevant documents are published in both databases.

 

 

The fungus Fusarium oxysporum f. sp. cubense tropical race 4 (syn. Fusarium odoratissimum) (Foc TR4) causes vascular wilt in Musaceae plants and is considered the most lethal for these crops. In Latin America and the Caribbean (LAC), it was reported for the first time in Colombia (2019), later in Peru (2021), and recently declared in Venezuela (2023). This work aimed to analyze the evolution of Foc TR4 in Musaceae in LAC between 2018 and 2022. This perspective contains a selection of topics related to Foc TR4 in LAC that address and describe (i) the threat of Foc TR4 in LAC, (ii) a bibliometric analysis of the scientific production of Foc TR4 in LAC, (iii) the current situation of Foc TR4 in Colombia, Peru, and Venezuela, (iv) medium-term prospects in LAC member countries, and (v) export trade and local food security. In this study, the presence of Foc TR4 in Venezuela and the possible consequences of the production of Musaceae in the long term were reported for the first time. In conclusion, TR4 is a major threat to banana production in Latin America and the world, and it is important to take measures to control the spread of the fungus and minimize its impact on the banana industry. It is important to keep working on the control of Foc TR4, which requires the participation of the local and international industry, researchers, and consumers, among others, to prevent the disappearance of bananas.

 

 

The objective of this study is to identify and analyze the most relevant scientific work being undertaken in HR analytics. Additionally, it is to understand the evolution of the conceptual, intellectual, and social structure of this topic in a way that allows the expansion of empirical and conceptual knowledge. Bibliometric analysis was performed using Bibliometrix and Biblioshiny software packages on academic articles indexed on the Scopus and Web of Science (WoS) databases. Search criteria were applied, initially resulting in a total of 331 articles in the period 2008–2022. Finally, after applying exclusion criteria, a total of 218 articles of interest were obtained. The results of this research present the relevant notable topics in HR analytics, providing a quantitative analysis that gives an overview of HR analytics featuring tables, graphs, and maps, as well as identifying the main performance indicators for the production of articles and their citations. The scientific literature on HR analytics is a novel, adaptive area that provides the option to transform traditional HR practices. Through the use of technology, HR analytics can improve HR strategies and organisational performance, as well as people’s experiences.