Characteristics and trends in global tea research: a Science Citation Index Expanded-based analysis

Trends of impact factor contributors to the Injury Journal: A bibliometric analysis

PURPOSE

This study aims to analyse papers concerning journal impact factors published in the Injury-International Journal of the Care of the Injured between 1997 and 2022. Through this analysis, the research offers valuable insights into the publication performance and contributors to the journal impact factor, encompassing papers, authors, institutions, and countries.

METHODS

Articles and reviews published in the Injury between 1995 and 2021 were examined using the Science Citation Index Expanded database. The study employed the journal impact factor contributing indicator to compare highly cited and high journal impact factor papers across various aspects, including papers, authors, institutions, and countries.

RESULTS

A notable correlation exists between prolific authors, institutions, and countries, alongside those who contribute to high journal impact factors. However, a less distinct connection was observed between highly cited papers/authors and high journal impact factor contributors. The Injury serves as a well-regarded international journal. Notably, editorial members of the journal play a substantial role, serving as model editors and contributing significantly to the journal's success. Out of the Top 25 IF contributing papers with the CN of 34 or more the following themes were noted to dominate: bone healing/tissue regeneration (40 %) of papers, covid-19 pandemic (24 %), polytrauma/coagulopathy (12 %) and infection (8 %).

CONCLUSIONS

Utilizing the journal impact factor to assess research performance at the individual, institutional, or national levels appears not to be the most appropriate method. The results show that highly cited authors did not hold the distinction of being the primary contributors to the IF. Analysis revealed a low significant relationship among the primary contributors to the IF, highly cited papers, and the most influential papers in 2022. A more effective indicator could involve considering the total number of citations a publication receives from its year of publication up to the end of the most recent year.

Dyslexia: A Bibliometric and Visualization Analysis

Dyslexia is a disorder characterized by an impaired ability to understand written and printed words or phrases. Epidemiological longitudinal data show that dyslexia is highly prevalent, affecting 10-20% of the population regardless of gender. This study aims to provide a detailed overview of research status and development characteristics of dyslexia from types of articles, years, countries, institutions, journals, authors, author keywords, and highly cited papers. A total of 9,166 publications have been retrieved from the Social Sciences Citation Index (SSCI) and Science Citation Index Expanded (SCI-E) from 2000 to 2021. The United States of America, United Kingdom, and Germany were the top three most productive countries in terms of the number of publications. China, Israel, and Japan led the Asia research on dyslexia. University of Oxford had the most publications and won first place in terms of h-index. Dyslexia was the most productive journal in this field and Psychology was the most used subject category. Keywords analysis indicated that "developmental dyslexia," "phonological awareness," children and fMRI were still the main research topics. "Literacy," "rapid automatized naming (RAN)," "assessment," "intervention," "meta-analysis," "Chinese," "executive function," "morphological awareness," "decoding," "dyscalculia," "EEG," "Eye tracking," "rhythm," "bilingualism," and "functional connectivity" might become the new research hotspots.

Effects of UAV-LiDAR and Photogrammetric Point Density on Tea Plucking Area Identification

High-cost data collection and processing are challenges for UAV LiDAR (light detection and ranging) mounted on unmanned aerial vehicles in crop monitoring. Reducing the point density can lower data collection costs and increase efficiency but may lead to a loss in mapping accuracy. It is necessary to determine the appropriate point cloud density for tea plucking area identification to maximize the cost–benefits. This study evaluated the performance of different LiDAR and photogrammetric point density data when mapping the tea plucking area in the Huashan Tea Garden, Wuhan City, China. The object-based metrics derived from UAV point clouds were used to classify tea plantations with the extreme learning machine (ELM) and random forest (RF) algorithms. The results indicated that the performance of different LiDAR point density data, from 0.25 (1%) to 25.44 pts/m2 (100%), changed obviously (overall classification accuracies: 90.65–94.39% for RF and 89.78–93.44% for ELM). For photogrammetric data, the point density was found to have little effect on the classification accuracy, with 10% of the initial point density (2.46 pts/m2), a similar accuracy level was obtained (difference of approximately 1%). LiDAR point cloud density had a significant influence on the DTM accuracy, with the RMSE for DTMs ranging from 0.060 to 2.253 m, while the photogrammetric point cloud density had a limited effect on the DTM accuracy, with the RMSE ranging from 0.256 to 0.477 m due to the high proportion of ground points in the photogrammetric point clouds. Moreover, important features for identifying the tea plucking area were summarized for the first time using a recursive feature elimination method and a novel hierarchical clustering-correlation method. The resultant architecture diagram can indicate the specific role of each feature/group in identifying the tea plucking area and could be used in other studies to prepare candidate features. This study demonstrates that low UAV point density data, such as 2.55 pts/m2 (10%), as used in this study, might be suitable for conducting finer-scale tea plucking area mapping without compromising the accuracy.

Electrochemical Sensors and Biosensors for the Analysis of Tea Components: A Bibliometric Review

Tea is a popular beverage all around the world. Tea composition, quality monitoring, and tea identification have all been the subject of extensive research due to concerns about the nutritional value and safety of tea intake. In the last 2 decades, research into tea employing electrochemical biosensing technologies has received a lot of interest. Despite the fact that electrochemical biosensing is not yet the most widely utilized approach for tea analysis, it has emerged as a promising technology due to its high sensitivity, speed, and low cost. Through bibliometric analysis, we give a systematic survey of the literature on electrochemical analysis of tea from 1994 to 2021 in this study. Electrochemical analysis in the study of tea can be split into three distinct stages, according to the bibliometric analysis. After chromatographic separation of materials, electrochemical techniques were initially used only as a detection tool. Many key components of tea, including as tea polyphenols, gallic acid, caffeic acid, and others, have electrochemical activity, and their electrochemical behavior is being investigated. High-performance electrochemical sensors have steadily become a hot research issue as materials science, particularly nanomaterials, and has progressed. This review not only highlights these processes, but also analyzes and contrasts the relevant literature. This evaluation also provides future views in this area based on the bibliometric findings.

Dietary natural products as a potential inhibitor towards advanced glycation end products and hyperglycemic complications: A phytotherapy approaches

Natural products exist in various natural foods such as plants, herbs, fruits, and vegetables. Furthermore, marine life offers potential natural products with significant biological activity. The biochemical reaction is known as advanced glycation end products (AGEs) occurs in the human body. On the other hand, foods are capable of a wide range of processing conditions resulting in the generation of exogenous AGEs adducts. Protein glycation and the formation of advanced glycation end products both contribute to the pathogenesis of hyperglycemic complications. AGEs also play a pivotal role in microvascular and macrovascular complications progression by receptors for advanced glycation end products (RAGE). RAGE activate by AGEs leads to up-regulation of transcriptional factor NF-kB and inflammatory genes. Around the globe, researchers are working in various approaches for therapeutical implications on controlling AGEs mediated disease complications. In this regard, one of the potential promising agents observed with a wide range of AGEs inhibition by food-derived natural products. Current biotechnological tools have been turned to natural products or phytochemicals to manufacture the molecules without compromising their functionality. Metabolic engineering and bioinformatics perspectives have recently enabled the generation of a few potent metabolites with anti-diabetic activity. As the primary focus, this review article will also discuss multidisciplinary approaches that emphasize current advances in anti-diabetic therapeutic action and future perspectives of natural products.

Reply to Comment on Chen, J., Su, Y., Si, H., Chen, J. Managerial Areas of Construction and Demolition Waste: A Scientometric Review. Int. J. Environ. Res. Public Health 2018, 15 (11), 2350, doi:10.3390/ijerph15112350

Thank you for the comments made by Ho; it is a great honor that our article has attracted attention. We would like to provide feedback to the comment, which focuses on the following fiveissues[...].

Global performance and development on sustainable city based on natural science and social science research: A bibliometric analysis

Sustainable city has been a global concern in recent years, involving natural science and social science research. However, few studies have attempted to map the global research of sustainable city. This study aimed to reveal the global performance and development of sustainable city research during 1992 to 2016, using a bibliometric analysis based on Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) on Web of Science. Research performance, research emphases and trends were illustrated by bibliometric indicators and newly developed visualization tools, like Science of Science (Sci2), Gephi, and alluvial diagram. Sustainable city research in natural science and social science were well-matched in quantity, and had similar and different characteristics in terms of different investigated aspects. China ranked first in natural science research, while the USA was the leading country in social science research. More categories and clusters were involved in sustainable city field, indicating more interdisciplinary integration was undergoing. Energy and fuels in natural science field, and interdisciplinary applications mathematics in social science field started to attract more attention. Statistical analysis of words in title, author keywords, and KeyWords Plus has been investigated to monitor the development of sustainable city research. Finally, three critical issues in sustainable city research based on the clues by the analysis of these keywords were reviewed and discussed.