Producción Científica

 

 

Objective: To present a global overview of the current research landscape and emerging trends in mechanical thrombectomy for acute ischemic stroke (AIS) over the past decade. Methods: A thorough search was conducted on the Web of Science on May 20, 2024, focusing on original articles and reviews in English. Bibliometric tools were employed to make a network analysis and visual representation. Additionally, data on disability-adjusted life years, prevalence, and incidence of ischemic strokes were extracted from the Global Burden of Disease database. Results: A total of 7776 papers were included, indicating a steady increase from 169 to 1311 between 2014 and 2023. The United States led in core publications with 2887 papers. The incidence and disability-adjusted life years of ischemic stroke have continued to rise in Asia but have recently declined in North America and European countries. The University of Calgary emerged as the leading institution and Mayank Goyal was the most prolific author. Neurointerventional Surgery was the top contributing journal with 790 articles. The analysis identified 6332 keywords forming 5 clusters, with “mechanical thrombectomy” serving as the largest cluster, focusing mainly on interventional thrombectomy techniques for AIS. The term “tissue plasminogen activator” exhibited strong burst strength of 46.58. Keywords such as “injury”, “diagnosis”, “posterior circulation”, and “severity” burst in 2020 and lasted until 2024. Conclusions: Interest in mechanical thrombectomy for AIS was progressively increasing. Future research directions may include minimizing intraoperative injuries, refining diagnostic techniques, investigating interventions for posterior circulation, and tailoring thrombectomy strategies based on stroke severity and large vessel occlusion etiology.

 

 

Nature-based solutions (NBS) are increasingly proposed as a response to the growing vulnerability of coastal areas to the risks of coastal erosion and flooding. These solutions rely on the functioning of ecosystems to mitigate the effects of coastal hazards. However, the ability of ecosystems to act as buffer zones is being compromised due to increasing urbanization in coastal areas. The implementation of NBS in urbanized coastal areas is becoming a major challenge for our societies, as coastal cities densely concentrate populations and valuable assets. This study has two main objectives: (1) to provide a structured overview of current NBS research and (2) to explore whether and how NBS are utilized in urban coastal risk management. A critical review of the literature serves as a foundation for understanding how NBS is conceptualized, identifies the factors contributing to the ambiguity of the term, and proposes five key elements for defining NBS. A systematic review of 3384 publications from Scopus shows that coastal issues represent a secondary focus in NBS research (14%). Coastal NBS studies primarily address coastal erosion and flooding exacerbated by sea level rise through natural coastal ecosystems. While urban issues related to climate change are at the heart of NBS research, the urban dimension has very little connection with coastal NBS. This article highlights the need for a multifaceted response to manage coastal risks in coastal cities, combining hard and soft engineering (hybrid solutions), inshore and offshore NBS, coastal and stormwater NBS, and regulating urbanization in flood-prone areas. The application of NBS in coastal risk management calls for incorporating natural coastline dynamics into land-use planning and rethinking our fixed modes of coastal occupation. This article provides keys to understanding the concept of NBS to facilitate its integration into coastal risk management plans.

 

 

Background: Hydroxychloroquine and Chloroquine (CQ) and Hydroxychloroquine (HCQ) are antimalarial drugs with well-known anti-inflammatory and antiviral effects used to treat various diseases, with few side effects. After COVID-19 emergence, numerous researches from around the world have examined the potential of using CQ or HCQ as potential treatment of COVID-19. However, conflicting outcomes have been found in COVID-19 clinical trials after treatment with CQ or HCQ. This study aims to evaluate research on CQ and HCQ for COVID-19 treatment and prophylaxis control using bibliometric methods. Methods: We analyzed bibliometric data on HCQ and COVID-19 (HCQ-C19) quantitatively and semantically (2020–2023) using the Scopus database VOSviewer, Bibliometrix, and MS Excel. Results: Analyses of 7471 original and conference articles revealed that the total number of publications has continually increased. The country producing the most articles in this field was the United States, followed by Italy, India, and Spain. The top-productive authors on HCQ-C19 are Mussini, C., and Raoult, D. (Italy) with 23 and 21 articles, respectively. The top-impactful organization is IHU Méditerranée Infection, France. A Bibliometrix’s network analysis based on the co-occurrence of keywords revealed the following themes HCQ-C19, including “clinical research/practice,” “COVID-19,” “thrombosis,” “HCQ,” “epidemiology,” and “infectious disease.” Conclusion: In conclusion, the analysis reveals a growing interest in HCQ-C19 research. Prominent contributions come from the United States, Italy, India, and Spain. Key themes include clinical research/practice, COVID-19, thrombosis, HCQ, epidemiology, and infectious disease. Future recommendations include conducting well-designed clinical trials and fostering collaborative interdisciplinary efforts.

 

 

Objective: Oxidative stress is an important factor mediating the pathologic progression of many diseases. In recent years, the antioxidant effects of acupuncture have been gradually confirmed. However, bibliometric analysis in this field, which is still lacking. This study aimed to explore the current state of research and recent trends in the regulating of oxidative stress by acupuncture using bibliometric methods. Methods: Articles pertaining to the acupuncture antioxidant effects were systematically retrieved from the Web of Science Core Collection database, encompassing the temporal scope from inception to September 6, 2024. Countries, publications, authors, co-citations, and keywords were visualized and analyzed using CiteSpace, VOSviewer, and R software. Results: A total of 438 articles have been published in the field, with the number increasing yearly. Chinese scholars constitute a significant force in the domain of research pertaining to this field. Beijing University of Traditional Chinese Medicine is the institution with the highest number of publications. Cunzhi Liu (17) is the author with the highest number of publications. The journals with the most publications (39) and citations (652) are EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE. Basic research is the main type of research. Both co-cited literature analysis and keyword examination have indicated neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and stroke, as prominent research domains. Electroacupuncture is the most common intervention. Pain and inflammation may be a trend in research in this area. Conclusion: This bibliometric analysis summarises the disease mapping and some of the mechanisms of acupuncture’s antioxidant effects. Neurological disorders such as Parkinson’s disease, vascular dementia, and stroke are major research areas in this field. Pain and inflammation may be a direction for future research.

 

 

Topic modelling (TM) is a significant natural language processing (NLP) task and is becoming more popular, especially, in the context of literature synthesis and analysis. Despite the growing volume of studies on the use of and versatility of TM, the knowledge of TM development, especially from the perspective of bibliometrics analysis is limited. To this end, this study evaluated TM research using two techniques namely, bibliometrics analysis and TM itself to provide the current status and the pathway for future studies in the TM field. For this purpose, this study used 16,941 documents collected from Scopus database from 2004 to 2023. Results indicate that the publications on TM have increased over the years, however, the citation impact has declined. Furthermore, the scientific production on TM is concentrated in two countries namely, China and the USA. Our findings showed there are several applications of TM that are understudied, for example, TM for image segmentation and classification. This paper highlighted the future research directions, most importantly, calls for increased multidisciplinary research approaches to fully deploy TM algorithms optimally and thus, increase usage in non-computer science subject areas.

 

 

The rapid industrialization and urbanization in China require a high level of safety management and thus urge the development of safety risk assessment in China. In the past two decades, many safety risk assessment research findings have been published in international journals by Chinese scholars, while it is not clear the development progress and China’s contributions to the world in this research field. Therefore, a systematic and thorough literature review is conducted to investigate risk assessment research in China. Firstly, the research publications authored by Chinese scholars are searched from the well-known literature database Web of Science to support the analysis of risk assessment research in China. Secondly, a bibliometric analysis is conducted for the obtained literature related to risk assessment research in China to find out publication trends, research organizations, research authors, research topics, and research methods. Then, a thorough analysis of research topics and research methods is carried out to present the research progress. Finally, possible future research issues in the risk assessment research domain are discussed based on this literature review. According to the discussion, more attention in China should be paid to the risk of digital or autonomous systems, the risk related to extreme events, and the risk in large cities.

 

 

The rapid evolution of the mechanical industry necessitates reliable and innovative materials. Metal matrix composites (MMCs) have emerged as a leading contender for performing vital roles in this field. Carbon nanostructures, such as graphene and carbon nanotubes (CNTs), are particularly well-suited as reinforcement materials in MMCs. It has been found by recent experimental studies that incorporating CNTs and graphene as reinforcements into metal matrix composites, such as aluminum, magnesium, titanium, nickel, and copper matrices, can significantly enhance the mechanical, thermal, and tribological properties of these materials. This is achieved through various mechanisms, including the restriction of grain growth, hindrance of dislocations, load transfer at interfaces, and mitigation of thermal expansion mismatch. The precise reinforcement and optimization of fabrication techniques have opened up new avenues for achieving uniform nanostructure dispersion and strong interfacial bonding, leading to substantial improvements in quantitative properties. Such advancements in material science hold great promise for the development of high-performance materials with enhanced properties that are vital for various applications, including aerospace, automotive, biomedical, and beyond. The addition of low-carbon nanostructures to polymer matrix, ceramic, and biocomposite systems has also been observed to elicit noteworthy multifunctional improvements. Reinforcing collagen with CNT fibers leads to better mechanical and electrical performance compared to using collagen alone. This critical review provides an insightful and data-driven analysis of the current state of carbon nanostructure (CNTs/graphene)-reinforced metal matrix and biocomposites based on an extensive literature evaluation. The review includes an in-depth examination of the optimized synthesis and processing techniques for CNTs and graphene MMCs, highlighting the impact of reinforcement on their mechanical, thermal conductivity, electrical conductivity, and functional properties. Continued work refining fabrication methods fully leverages their potent multi-functional enhancement capabilities.

 

 

In the digital era, Business Intelligence (BI) and data analytics have become essential for optimizing academic management in higher education institutions. This bibliometric study analyzed 755 Scopus-indexed publications (2019–2023) using RStudio, Biblioshiny, and Microsoft Excel to elucidate key themes, influential authors, and emerging research trends. Learning analytics, educational data mining, and BI applications such as dropout prediction systems, tailored distance education strategies, and machine learning models for institutional performance predominate in the field. High-impact journals, including the British Journal of Educational Technology and the Journal of Learning Analytics, play crucial roles with contributions from scholars such as Christothea Herodotou and Bart Rienties. Thematic analysis revealed ten clusters emphasizing predictive modeling, educational innovation, and online learning. Geographic trends highlight the predominance of research in the United States and Europe, underscoring the necessity for greater inclusivity in underrepresented regions such as Africa and South America. While quantitative methodologies prevail, this study emphasizes the significance of qualitative approaches to capture nuanced impacts and ethical considerations, including privacy, equity, and bias mitigation. Future research must adopt interdisciplinary methodologies to address systemic challenges, foster context-sensitive, equitable BI solutions that drive innovation, and enhance decision making across diverse educational environments.

 

 

Recent advancement of technology in the analytics of big data has sparked a transformative revolution in smart agriculture, enabling farmers to make informed decisions, optimize resources, and enhance productivity and sustainability. Tracking developmental progress is crucial to understanding how big data applications in smart farming are rapidly evolving with ongoing technological advancements. We conducted a bibliometric analysis of academic publications and documents published in Scopus-indexed peer-reviewed journals. A total of 2,154 publications, including journal articles (45 %), conference proceedings (30 %), book series (16 %), and books (9 %), were retrieved, with 96 % of the documents in the English language and two-thirds of the documents published within the last four years of this research study. The reviewed publications were predominantly focused on the disciplines of computer science (64 %), engineering (36 %), and agriculture and biological science (22 %). The contributions of authors from India, China, and the United States were the highest, accounting for half of the publications when combined. As an outcome of the bibliometric analysis, five research domains of big data, i.e., data-driven decision-making, sustainability and supply chain management, technology and innovation, data management and governance, and digital transformation were identified, suggesting positive development in this field. As an implication of this work, we have identified a need for greater global collaboration to achieve big data advancement and technology adaptation. We also discussed the implications of this work for research, practice, and policy. Despite the opportunities that big data brings for smart farming, economics, data governance, and data sharing and reliability remain prevalent issues. These issues need to be addressed for fully effective utilisation of big data in smart farming.

 

 

Metaverse, a virtual space created as a digital version of the real world, is currently under development. Over the past two years, there has been a significant rise in scientific research on the metaverse. However, prior research necessitates a methodical examination of the literature on developing the metaverse environment, particularly with regard to payment ecology. To bridge this gap, we reviewed 40 journal articles related to the metaverse digital payment ecosystem and offer recommendations for future research. We refer to the Scientific Procedures and Rationales for Systematic Literature Reviews” (“SPAR-4-SLR”) procedure for carrying out a thorough review of the literature. Bibliometric analysis was also performed for the thematic observations. The results reveal five clusters in the Metaverse digital payment ecosystem: (1) metaverse reality, (2) technology, (3) data analytics, (4) blockchain, (5) non-fungible tokens (NFTs), and other tokens. Metaverse digital payment ecosystem research is still somewhat scattered and has no significant theme. Furthermore, this study provides a path for future research on the stability of the payment ecosystem and the metaverse regulatory framework.