Trends in research related to ophthalmic microperimetry from 1992 to 2022: A bibliometric analysis and knowledge graph study

A bibliometric analysis of the research hotspots and frontiers related to cell death in spinal cord injury

Background

Spinal cord injury (SCI) is a severe central nervous trauma that can cause serious consequences. Cell death is emerging as a common pathogenesis after SCI. In the last two decades, numerous studies have been published in the field of cell death after SCI. However, it is still rare to find relevant bibliometric analyses. This bibliometric study aims to visually represent global research trends in the field of cell death after SCI.

Methods

Bibliometric data were sourced from the Web of Science Core Collection (WoSCC) database. VOSviewer, CiteSpace, and R software ("bibliometrix" package) were used to analyze and visualize bibliometric data. Annual scientific production, countries/regions, institutions, authors, journals, highly cited papers, keywords, and literature co-citation were evaluated to determine research performance.

Results

An analysis of 5,078 publications extracted from the WoSCC database revealed a fluctuating yet persistent growth in the field of cell death after SCI over the past 23 years. China and the United States, contributing 69% of the total publications, were the main driving force in this field. The Wenzhou Medical University from China contributed to the most papers. In terms of authors, Salvatore Cuzzocrea from the University of Messina had the highest number of publications. The "Journal of Neurotrauma" was the top journal in terms of the number of publications, however, the "Journal of Neuroscience" was the top journal in terms of the number of citations. The theme of the highly cited articles mainly focused on the mechanism of cell death after SCI. The keyword and literature co-citation analysis mainly focused on the mode of cell death, mechanism research of cell death, and functional recovery after SCI.

Conclusion

This study analyzes the research hotspots, frontiers, and development trends in the field of cell death after SCI, which is important for future studies.

Research on distribution network fault processing technology based on knowledge of graph

Safety and reliability are the basis of the development of a distribution network. To analyze the risk transmission process in the distribution network and ensure the safe and reliable operation of the power system, this paper intends to use the knowledge graph method to realize the risk analysis of the distribution network information system. Firstly, the knowledge graph method is used to extract and integrate the risk knowledge of the multi-dimensional information collected by the distribution network. Secondly, the knowledge graph model of distribution network risk analysis is constructed, and the multi-dimensional distribution network fault handling and knowledge graph construction oriented to the feeder and platform area are designed. The distribution line parameters of the low-voltage distribution network model, neutral point grounding mode, and different fault types are analyzed, and the non-planned island is searched based on the knowledge graph adjacency matrix. Finally, combined with the simulation experiment, it is verified that the proposed method can effectively depict the information risk process of the distribution network. The structure of this paper starts from the multi-node complex distribution network, combined with a knowledge graph and deep learning method, which can solve the distribution network fault more quickly.