Food Supply Chain Safety Research Trends From 1997 to 2020: A Bibliometric Analysis

Fault diagnosis of photovoltaic systems using artificial intelligence: A bibliometric approach

Conventional fault detection methods in photovoltaic systems face limitations when dealing with emerging monitoring systems that produce vast amounts of high-dimensional data across various domains. Accordingly, great interest appears within the international scientific community for the application of artificial intelligence methods, which are seen as a highly promising solution for effectively managing large datasets for detecting faults. In this review, more than 620 papers published since 2010 on artificial intelligence methods for detecting faults in photovoltaic systems are analyzed. To extract major research trends, in particular to detect most promising algorithms and approaches overcoming excessive time calculations, a conventional bibliographic survey would have been extremely difficult to complete. That is why this study proposes to carry out a review with an innovative approach based on a statistical method named Bibliometric and a Expert qualitative content analysis. This methodology consists of three stages. First, a collection of data from databases is carried out with all precautions to achieve a large, robust, high-quality database. Second, multiple bibliometric indicators are chosen based on the objectives to be achieved and analyzed to assess their real impact, such as the quantity and nature of publications, collaborative connections among organizations, researchers, and countries or most cited articles. Finally, the Expert qualitative content analysis carried out by experts identifies the current and emerging research topics that have the greatest impact on fault detection in photovoltaic systems using artificial intelligence.

Gut microbiota and autism spectrum disorders: where do we stand?

BACKGROUND

Children with autism spectrum disorder (ASD) often have digestive problems and microbial imbalances in their guts, suggesting that these conditions may play a role in the development of the disorder. Scopus-based research on the gut microbiota and ASD was examined in this bibliometric analysis to shed light on the current state of research and identify potential hotspots for future work in this area.

METHODS

We searched documents from the Scopus database and reference citation analysis to collect published data on the gut microbiota and ASD from 2003 to 2022. The downloaded document records were exported to VOSviewer v.1.6.19 to examine and visualize the collaboration between countries and determine the research hotspots.

RESULTS

The search yielded 958 articles specifically dedicated to gut microbiota and ASD. The number of publications in this field increased rapidly after 2013, with a peak in 2022. The United States (n = 267; 27.87%) was the most active country, followed by China (n = 171; 17.85%) and Italy (n = 96; 10.02). International collaboration was observed, with the USA playing a central role. University College Cork, Ireland, was the most productive institution (n = 24; 2.51%). The National Natural Science Foundation of China was the most active funding agency (n = 76; 7.93%). Nutrients journal had the highest number of publications (n = 28; 2.92%). The articles related to gut microbiota and ASD were highly cited, with an h-index of 108. The research themes identified focused on the modulation of gut microbiota as a potential therapy for children with ASD and gut-brain axis dysfunction in ASD.

CONCLUSIONS

In recent years, the study of gut microbiota and its association with ASD has garnered considerable interest as an emergent field of study. The results of this study substantially enhance our current understanding of the knowledge landscape in this field and illuminate potential avenues for future research. It is essential to emphasize the significance of devoting more resources to the newest and most promising research areas, such as investigating the potential therapeutic benefits of modulating the intestinal microbiota in children with ASD. This research has enormous potential and merits intensified focus and investigation.

Global research trends on the links between insulin resistance and obesity: a visualization analysis

Background

Obesity increases the chance of developing insulin resistance. Numerous inflammatory markers have been linked to an increased risk of insulin resistance in obese individuals. Therefore, we performed a bibliometric analysis to determine global research activity and current trends in the field of obesity and insulin resistance.

Methods

Scopus was used between 2002 and 2021 to retrieve publications related to terms related to obesity and insulin resistance. Data were exported to Microsoft Excel. Additionally, we use VOSviewer software to create visualization maps that describe international collaborations and research hotspots.

Results

We identified 6626 publications, including 5754 journal articles, 498 review articles, and 109 letters to the editor. The most productive countries were the United States (n = 995, 30.11%), followed by China (n = 650, 9.81%), Italy (n = 412, 6.22%) and Spain (n = 386, 5.83%). Previously to 2012, this field was mainly focused on ‘adipocyte dysfunctions that link obesity with insulin resistance”; and ‘relationship between obesity, insulin resistance, and risk of cardiovascular disease’. ‘Supplements improve insulin sensitivity‘, and ‘obesity-induced inflammation and insulin resistance’ were found more recently (after 2014), indicating that research in this field has acquired significant interest and emphasis in recent years.

Conclusions

This is the first bibliometric study to focus on publications related to insulin resistance and obesity at the global level. Our reporting of quantifiable knowledge in this field may be useful in providing evidence and direction for future research, clinical practice, and educational initiatives.