Scientometric Analysis of Safety Sign Research: 1990-2019

Knowledge mapping of research progress in blast-induced ground vibration from 1990 to 2022 using CiteSpace-based scientometric analysis

Blasting constitutes an essential component of the mining and construction industries. However, the associated nuisances, particularly blast vibration, have emerged as significant concerns that pose threats to operational stability and the safety of the surrounding areas. Given the increasing emphasis on sustainability, ecological responsibility, safety, and geo-environmental practices, the impact of blast vibration has garnered heightened attention and scrutiny. Nevertheless, the field still lacks comprehensive phase analysis studies. Therefore, it is imperative to elucidate the research progress on blast vibration and discern its current frontiers of investigation. To address this need, this study employs bibliometric methods and the CiteSpace 6.1.R2 software to analyze 3093 papers from the Web of Science database. Through this comprehensive analysis, the study aims to chronicle the developmental trajectory, assess the present research status, and identify future trends in the field of blast vibration. The findings of this study reveal that research on "blasting vibration" is advancing rapidly, with the number of citations exhibiting a J-shaped growth curve over time. China emerges as the leading contributor to this research, followed by India, and the foremost institution in this field is Central South University in China. Cluster analysis identifies the effects of ground vibration, numerical simulation, blast load, blasting vibration and rockburst hazard as the most prominent research areas presently. The primary research directions in this domain revolve around the rock fragmentation, compressive strength, particle swarm optimization, and ann. The emergence of these keywords underscores a dynamic shift towards a more holistic and multidisciplinary approach in the field of blasting-induced ground vibration. Furthermore, this study provides a concise overview of blast vibration, discusses prediction techniques, and proposes measures for its control. Additionally, the discussion delves into the social significance of intelligent blasting systems within the context of artificial intelligence, aiming to address the hazards associated with blast-induced ground vibrations.

A comparative investigation of machine learning algorithms for predicting safety signs comprehension based on socio-demographic factors and cognitive sign features

This study examines whether the socio-demographic factors and cognitive sign features can be used for envisaging safety signs comprehensibility using predictive machine learning (ML) techniques. This study will determine the role of different machine learning components such as feature selection and classification to determine suitable factors for safety construction signs comprehensibility. A total of 2310 participants were requested to guess the meaning of 20 construction safety signs (four items for each of the mandatory, prohibition, emergency, warning, and firefighting signs) using the open-ended method. Moreover, the participants were asked to rate the cognitive design features of each sign in terms of familiarity, concreteness, simplicity, meaningfulness, and semantic closeness on a 0-100 rating scale. Subsequently, all eight features (age, experience, education level, familiarity, concreteness, meaningfulness, semantic closeness, and simplicity) were used for classification. Furthermore, the 14 most popular supervised classifiers were implemented and evaluated for safety sign comprehensibility prediction using these eight features. Also, filter and wrapper methods were used as feature selection techniques. Results of feature selection techniques indicate that among the eight features considered in this study, familiarity, simplicity, and meaningfulness are found to be the most relevant and effective components in predicting the comprehensibility of selected safety signs. Further, when these three features are used for classification, the K-NN classifier achieves the highest classification accuracy of 94.369% followed by medium Gaussian SVM which achieves a classification accuracy of 76.075% under hold-out data division protocol. The machine learning (ML) technique was adopted as a promising approach to addressing the issue of comprehensibility, especially in terms of determining factors affecting the safety signs' comprehension. The cognitive sign features of familiarity, simplicity, and meaningfulness can provide useful information in terms of designing user-friendly safety signs.

Bibliometric and visual analysis of cerebral revascularization from 1999 to 2022

Background

Cerebral revascularization is a neurosurgical procedure used to restore the cerebral collateral circulation channel. This study examines the countries, institutions, authors, journals, keywords, and references related to the disease in the field of cerebral revascularization from 1999 to 2022 from a bibliometrics perspective, evaluates the changes of knowledge structure clustering and identifies the new hot spots and new research directions in this field.

Methods

The Web of Science Core Collection (WOSCC) database and the PICOS retrieval method were used to conduct a comprehensive search for articles and reviews pertaining to cerebral revascularization. The final filtered data were bibliometrically and visually drawn using Microsoft office 365, CiteSpace (v.6.1.R2), and VOSviewer (v.1.6.18).

Results

From 1999 to 2022, a total of 854 articles pertaining to cerebral revascularization, which originated from 46 nations, 482 institutions, and 686 researchers, were extracted from the WOSCC database, and the number of publications in this field of study was rising. The United States held the highest proportion in the ranking analysis of countries, institutions, authors, and journals. By analyzing co-citations, the scientific organization of this field and the development status of frontier fields were realized. Cerebral revascularization, moyamoya disease, extracranial intracranial bypass, and occlusion are the current research focal points in the field of cerebral revascularization. Hyperperfusion and vascular disorder may also become a new study focus in this discipline in the near future.

Conclusion

Using the method of bibliometrics, this study analyzed and reviewed the articles in the field of cerebral revascularization, which enabled scholars to better comprehend the dynamic process in this field and provided a foundation for future in-depth research.

A Bibliometric and Visualization Analysis of Intermittent Fasting

CiteSpace software was utilized to visually analyze the literature on intermittent fasting from Web of Science from 2000 to 2020 in order to reveal the current status, research hotspots and emerging trends of intermittent fasting. The results show that: (1) intermittent fasting research results are increasing year by year; (2) the United States is at the core of this field and has a high influence; (3) intermittent fasting research is mainly concentrated in the fields of nutrition, cell biology and kinesiology, which embodies interdisciplinary characteristics; (4) the literature of Sutton, Mattson and Trepanowski that were published in the same period have the highest co-citation frequencies, however, their research perspectives are quite different, reflecting that the research in this field is still in a state of continuous development; (5) from the perspective of citation bursts, the evolution of research hotspots in this field in the last 20 years can be divided into 3 stages; (6) the keyword timeline mapping shows that time restricted feeding is at the forefront of this research field. This study can help researchers explore the field for the first time to quickly grasp the frontiers and obtain more valuable data, thereby providing facilitation for the follow-up research.

Bibliometric Analysis of the Toxicity of Bisphenol A

Bisphenol A (BPA) is used worldwide and research on the toxicity of BPA has advanced rapidly in the last few decades. This study aimed to evaluate the global scientific output of toxicity of BPA and explore the hot spots and research trends. All available articles related to the toxicity of BPA until 2022 were retrieved from the Web of Science Core Collection database. The VOSviewer, a bibliometric analysis software, was used to analyze the information of included articles, including countries/institutions, international cooperation, journals, citations, and keywords. Among 1644 retrieved articles, 1611 eligible studies were identified for analysis, and the annual publications increased with time in the past three decades. China and the United States were the most active contributors in this field. Chinese Academy of Sciences and the Dow chemical company conducted relatively more research than others about BPA toxicity. The journal “Chemosphere” published the most studies on “BPA toxicity”. Before 2015, most research focused on estrogenic activity and the test system mainly utilized animal experiments. However, in recent years, research related to toxic mechanisms of BPA at the cellular level and the toxicity of its analogs have received widespread attention. Considering some critical research gaps, future research on BPA toxicology should probably focus on the molecular biology of toxic mechanism, mixture toxicity, and co-exposure of BPA substitutes. This study will help researchers understand past and current research trends, hot spots, and trends of toxicity studies of BPA and, thus, contribute to further research and risk management of BPA.

Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation

We live in a complex world characterised by complex people, complex times, and complex social, technological, economic, and ecological environments. The broad aim of our work is to investigate the use of ICT technologies for solving pressing problems in smart cities and societies. Specifically, in this paper, we introduce the concept of deep journalism, a data-driven deep learning-based approach, to discover and analyse cross-sectional multi-perspective information to enable better decision making and develop better instruments for academic, corporate, national, and international governance. We build three datasets (a newspaper, a technology magazine, and a Web of Science dataset) and discover the academic, industrial, public, governance, and political parameters for the transportation sector as a case study to introduce deep journalism and our tool, DeepJournal (Version 1.0), that implements our proposed approach. We elaborate on 89 transportation parameters and hundreds of dimensions, reviewing 400 technical, academic, and news articles. The findings related to the multi-perspective view of transportation reported in this paper show that there are many important problems that industry and academia seem to ignore. In contrast, academia produces much broader and deeper knowledge on subjects such as pollution that are not sufficiently explored in industry. Our deep journalism approach could find the gaps in information and highlight them to the public and other stakeholders.

The Effect of Safety Signs on the Monitoring of Conflict and Erroneous Response

The safety sign is important in our daily life and workplace to prevent potential safety issues. However, it remains undetermined whether the safety signs would influence the cognitive control ability of the people, which serves to guide the behaviors in a goal-directed manner. Therefore, this study aimed to examine the effect of safety signs on cognitive control by uncovering the behavioral performance and neural manifestations underlying the monitoring of conflict and error. The participants performed a flanker task after watching low- and high-hazard safety signs with the electroencephalogram (EEG) data recorded continually. The behavioral results indicated a classic congruency effect with higher accuracy rate and faster response time under a congruent condition compared to an incongruent condition. However, no hazard effect on behavioral performances was observed. The results of event-related potentials (ERPs) demonstrated a more negative N2 elicited by the incongruent trials and an increased (error-related negativity) ERN difference between the error and correct responses in the high-hazard condition compared to those in the low-hazard condition, implying that the monitoring of the conflict and error were both enhanced after watching the high-hazard safety signs. This study contributes to the understanding of the relationship between safety signs and cognitive control, and further expand the measurements that can be applied to assess the effectiveness of safety signs design.

Scientometric Analysis of Public Health Emergencies: 1994-2020

The purpose of this paper is to summarize the research hotspots and frontiers in the field of public health emergencies (PHE) between 1994–2020 through the scientometric analysis method. In total, 2247 literature works retrieved from the Web of Science core database were analyzed by CiteSpace software, and the results were displayed in knowledge mapping. The overall characteristics analysis showed that the number of publications and authors in the field of PHE kept an upward trend during the past decades, and the United States was in the leading position, followed by China and England. Switzerland has the highest central value and plays an important intermediary role in promoting the integration and exchange of international PHE research achievements. The keyword co-occurrence analysis indicated that COVID-19 was the most high-frequency keyword in this field, and there had been no new keywords for a long time until the outbreak of COVID-19 in 2019. The burst detection analysis showed that the top five burst keywords in terms of burst intensity were zika virus, Ebola, United States, emergency preparedness and microcephaly. The results indicated that the research theme of PHE is closely related to the major infectious diseases in a specific period. It will continue to develop with more attention paid to public health. The conclusions can provide help and reference for the PHE potential researchers.

A bibliometric analysis study of blood flow restriction using CiteSpace

[Purpose] To assess the current state-of-the-art and the prevailing trends regarding the global use of blood flow restriction (BFR) in the past 20 years. [Participants and Methods] We retrieved literature relating to BFR from 1999 to 2020 using Web of Science. We conducted a bibliometric analysis of countries/institutions, cited journals, authors/cited authors, cited references, and keywords using CiteSpace. An analysis of counts and centrality was used to examine publication output, countries/institutions, core journals, active authors, foundation references, hot topics, and frontiers. [Results] Seven hundred seventy five references were included and the total number of publications has been continually increasing over the investigated period. Representatives of important academic groups are the Japanese scholars from the University of Tokyo as represented by Takashi Abe. Jeremy Paul Loenneke’s article (centrality: 0.15) was the most representative and symbolic reference with the highest centrality. The three topics identified were intervention (intensity resistance exercise, IRE), physiology (ischemia and muscular function) and behavior (adaptation and increase). The four frontier topics were phosphorylation, reduction, low intensity and arterial occlusion. [Conclusion] This study provides an insight into BFR and offers valuable information for BFR researchers to identify new perspectives for potential cooperation with collaborators and their related cooperative institutions.

Scientometric Analysis of Disaster Risk Perception: 2000-2020

This paper used 1526 works from the literature on disaster risk perception from 2000 to 2020 in the Web of Science core collection database as the research subject. The CiteSpace knowledge graph analysis tool was used to visual analyze the country, author, institution, discipline distribution, keywords, and keyword clustering mapping. The paper drew the following conclusions. Firstly, disaster risk perception research has experienced three stages of steady development, undulating growth, and rapid growth. Secondly, the field of disaster risk perception was mainly concentrated in the disciplines of engineering, natural science, and management science. Thirdly, meteorological disasters, earthquakes, nuclear radiation, and epidemics were the main disasters in the field of disaster risk perception. Residents and adolescents were the main subjects of research in the field of disaster risk perception. Fourthly, research on human risk behavior and risk psychology and research on disaster risk control and emergency management were two major research hotspots in the field of disaster risk perception. Finally, the research field of disaster risk perception is constantly expanding. There is a trend from theory to application and multi-perspective combination, and future research on disaster risk perception will be presented more systematically. The conclusion can provide a reference for disaster risk perception research, as well as directions for future research.

Analysis of EEG Characteristics of Drivers and Driving Safety in Undersea Tunnel

To study the influence of the driving environment of an undersea tunnel on driver EEG (electroencephalography) characteristics and driving safety, a real vehicle experiment was performed in the Qingdao Jiaozhou Bay Tunnel. The experimental data of the drivers’ real vehicle experiment were collected using an illuminance meter, EEG instrument, video recorder and other experimental equipment. The undersea tunnel is divided into different areas, and the distribution law of driving environment characteristics, EEG characteristics and vehicle speed characteristics is analyzed. The correlations between the driving environment characteristics, EEG characteristics and vehicle speed characteristics model the variables that pass the correlation test. The driving safety evaluation model of an undersea tunnel is established, and the driving safety in different areas of the undersea tunnel is evaluated. The results show that there are obvious differences in illumination, EEG power change rate, vehicle speed and other variables in different areas of the undersea tunnel. The driving environment characteristics are highly correlated with the β wave power change rate. The driving safety of different areas of the undersea tunnel from high to low is: upslope area, downslope area, exit area and entrance area. The study will provide a theoretical basis for the safe operation of the undersea tunnel.

Science Mapping: A Scientometric Review on Resource Curses, Dutch Diseases, and Conflict Resources during 1993–2020

Over the past few decades, the wealth of Africa has not made African wealthy. There is a voicing that Africa is cursed, whether richly poor or poorly rich. Sub-Saharan Africa is commonplace for political turbulence, as well as humanitarian and economic misery. In such a catastrophic situa-tion, political economics studies have focused on the Resource Curses, Dutch Diseases, and Con-flict Resources in this area. A systematic scientometric analysis of this field would be beneficial but is currently lacking in the academic literature. Using VOSviewer and CiteSpace, this review fills the void by analyzing the 1783 articles published in the WoS SSCI Collection between 1993 and 2020 on the “Resource Curses”, “Dutch Diseases”, and “Conflict Resources”. The author dis-cusses recent papers with disruptive potential, references with the most robust citation explora-tions, and cooperation networks between authors and institutes. Three hotspots were detected: the causes and effects of the Resource curses; the interaction among the Resource Curses, Dutch Diseases, and Conflict Resources; the factors that affect rent collection and regime resilience. While the literature on the “Resource curse” and “Dutch Disease” has been around longer, studies on “Conflict Resources” are picking up quickly. Conflict Resources were characterized by active citation exploration keywords and multiple active co-citation clusters, including possibly groundbreaking articles. There is a massive overlap between the three strings of literature, but each one has its emphasis.