Analysis and improvement of evaluation indexes for clustering results

Liver cancer (LC) is one of the most common malignancies. Currently, nanotechnology has made great progress in LC research, and many studies on LC nanotechnology have been published. This study aims to discuss the current status, hot spots, and research trends in this field through bibliometric analysis. The Web of Science Core Collection (WoSCC) database was searched for papers related to hepatocellular carcinoma (HCC) included from January 2000 to November 2022, and its research hotspots and trends were visualized and analyzed with the help of VOSviewer. In addition, a search was conducted to find LC papers related to nanotechnology. Then we used the visual analysis software VOSviewer and CiteSpace to evaluate the contributions of countries/regions, authors, and journals related to the topic and analyze keywords to understand the research priorities and hot spots in the field as well as the development direction. There are 1908 papers in the highly cited literature on LC, and its research hotspots are pathogenesis, risk factors, and survival rate. The literature on the application of nanotechnology in LC had 921 papers. Among them, China (n=560, 60.8%) and the United States (n=170, 18.5%) were the countries with the highest number of published papers. Wang Yan (n=11) and Llovet JM (n=131) were the first authors and co-cited authors, respectively. The International Journal of Nanomedicine was the most prolific academic journal (n=41). In addition to "hepatocellular carcinoma" and "nanoparticles", the most frequent keyword was "drug delivery". In recent years, "metastasis" and "diagnosis" appeared in the keyword bursts. This indicates that the application of nanoparticles in the early diagnosis and drug delivery of LC (including liver metastasis) has a good prospect. Nanotechnology has received more and more attention in the medical field in recent years. As nanoparticles are easily localized in organelles and cells, they can increase drug permeability in tumor tissues, improve drug delivery efficiency and reduce drug toxicity. Our research results were the first scientific evaluation of the application of nanotechnology in LC, providing scholars with research hotspots and development trends.

Intelligent education research has become a research hotspot in recent years. The Citespace software that operates a graph visualization function was used to clarify the current situation, hot spots, and evolutionary trends of intelligent education research development; the authors, institutions, and countries engaged in intelligent education research, as well as the basic knowledge structure, main keywords, citation clustering, dual-map overlay of journals and citation emergence of intelligent education research. The results show that the annual number of publications in the field has shown an upward trend since 2010, with strong communication among research institutions and countries, but weak communication among researchers. Among them, the United States is the center of the global collaborative network of intelligent education research. The basic knowledge structure of intelligence education research is mainly composed of Classroom Management, Evaluation Index, 5G Network, and Big Data Analytics. The dual-map overlay analysis of journals shows that the core areas of intelligence education are increasing, and the analysis of keywords and cited literature shows that Intelligence Tutoring System, AI system, Students and Education, Model, and System are high-frequency words with high-intensity burstness. In addition, research on intelligent education is characterized by multi-country, multi-field, and multi-disciplinary integration, and the adoption of Big Data, Distance Education Technology and Artificial Intelligence Technology to provide scientific support for teaching and learning will become the key research content in this field in the future.

The traditional H-K clustering algorithm can solve the randomness and apriority of the initial centers of K-means clustering algorithm. However, it will lead to a dimensional disaster problem when apply to high dimensional dataset clustering due to its high computational complexity. Clustering ensemble exerts ensemble learning technique to get a better clustering result through learning merged data set of multiple clustering results. The objective of this paper is to improve the performance of traditional H-K clustering algorithm in high dimensional datasets. Using ensemble learning, a new clustering algorithm is proposed named EPCAHK (Ensemble Principle Component Analysis Hierarchical K-means Clustering algorithm). In the EPCAHK algorithm, the high dimensional dataset is mapped into a low dimensional space using PCA method firstly. Subsequently, the clustering results of the hierarchical stage for obtaining initial information (e.g., the cluster number or the initial clustering centers) are integrated by using the min-transitive closure method. Finally, the final clustering result is achieved by using K-means clustering algorithm based on the ensemble clustering results above. The experimental results indicate that comparing to the traditional H-K clustering algorithm, the EPCAHK obtains a better clustering result. The average accuracy of the clustering results can reach up to 90% or above, and the stability for the large high dimensional dataset is also improved.

Background: Metal-organic frameworks (MOFs) are hybrid materials composed of metal ions or clusters and organic ligands that spontaneously assemble via coordination bonds to create intramolecular pores, which have recently been widely used in biomedicine due to their porosity, structural, and functional diversity. They are used in biomedical applications, including biosensing, drug delivery, bioimaging, and antimicrobial activities. Our study aims to provide scholars with a comprehensive overview of the research situations, trends, and hotspots in biomedical applications of MOFs through a bibliometric analysis of publications from 2002 to 2022. Methods: On 19 January 2023, the Web of Science Core Collection was searched to review and analyze MOFs applications in the biomedical field. A total of 3,408 studies published between 2002 and 2022 were retrieved and examined, with information such as publication year, country/region, institution, author, journal, references, and keywords. Research hotspots were extracted and analyzed using the Bibliometrix R-package, VOSviewer, and CiteSpace. Results: We showed that researchers from 72 countries published articles on MOFs in biomedical applications, with China producing the most publications. The Chinese Academy of Science was the most prolific contributor to these publications among 2,209 institutions that made contributions. Reference co-citation analysis classifies references into 8 clusters: synergistic cancer therapy, efficient photodynamic therapy, metal-organic framework encapsulation, selective fluorescence, luminescent probes, drug delivery, enhanced photodynamic therapy, and metal-organic framework-based nanozymes. Keyword co-occurrence analysis divided keywords into 6 clusters: biosensors, photodynamic therapy, drug delivery, cancer therapy and bioimaging, nanoparticles, and antibacterial applications. Research frontier keywords were represented by chemodynamic therapy (2020-2022) and hydrogen peroxide (2020-2022). Conclusion: Using bibliometric methods and manual review, this review provides a systematic overview of research on MOFs in biomedical applications, filling an existing gap. The burst keyword analysis revealed that chemodynamic therapy and hydrogen peroxide are the prominent research frontiers and hot spots. MOFs can catalyze Fenton or Fenton-like reactions to generate hydroxyl radicals, making them promising materials for chemodynamic therapy. MOF-based biosensors can detect hydrogen peroxide in various biological samples for diagnosing diseases. MOFs have a wide range of research prospects for biomedical applications.

Objective To explore the articles sources coming form nursing journals of statistic source published in 2010-2014, to analyze research hot spot and explore national research and clinical practice hot spots of nursing field. Methods We selected Wanfang Database as data source to retrieve articles form 12 statistical source of nursing core journal, and utilized self-compiled computer program to count the frequency of key words and construct high frequency key words matrix, and then the SPSS 18.0 software was used for cluster analysis. Results The results of research presented that there were 8 research hot spots of nursing core journals in 5 years including scale, psychological nursing, nursing education, improving nursing quality, application of evidence based nursing on critical patients, child perioperative nursing, rehabilitation nursing of apoplexy patients and chronic disease patient′s nursing. Conclusions The research hot spot of nursing core journals′ articles reflect the key point work on clinical nursing and teaching and research of nursing field, and research hot spots of nursing core journals in 5 years can summarize as scale, psychological nursing, nursing education, improving nursing quality and so on 8 research topics. Key words: Nursing; Research hot spot; Co-word analysis; Cluster analysis; Journals of statistic source

Social Frailty is a significant public health concern affecting the elderly, particularly with the global population aging rapidly. Older adults with social frailty are at significantly higher risk of adverse outcomes such as disability, cognitive impairment, depression, and even death. In recent years, there have been more and more studies on social frailty, but no bibliometrics has been used to analyze and understand the general situation in this field. Therefore, by using CiteSpace, VOSviewer, and Bilioshiny software programs, this study aims to analyze the general situation of the research on social frailties of the older adults and determine the research trends and hot spots. A bibliometric analysis was conducted by searching relevant literature on the social frailty of the older adults from 2003 to 2022 in the Web of Science core database, using visualization software to map publication volume, country and author cooperation networks, keyword co-occurrences, and word emergence. We analyzed 415 articles from 2003 to 2022. Brazil has the highest number of articles in the field of social frailty of the older adults, and the United States has the highest number of cooperative publications. Andrew MK, from Canada, is the most published and co-cited author, with primary research interests in geriatric assessment, epidemiology, and public health. "Social Vulnerability," "Health," "Frailty," "Mortality," and "Older Adult" are among the research hotspots in this field. "Dementia," "Alzheimer's disease," "Population," and "Covid-19" are emerging research trends in social frailty among the older adults. This scientometric study maps the research hotspots and trends for the past 20 years in social frailty among the older adults. Our findings will enable researchers to better understand trends in this field and find suitable directions and partners for future research.

BackgroundOptic atrophy (OA) is primarily caused by damage to the retinal pathway system, including widespread degeneration of retinal ganglion cells and axons, leading to visual impairment and blindness. Despite its clinical significance and diverse etiological factors, there is currently a lack of comprehensive bibliometric analyses exploring research trends and hotspots within this field.MethodThis study retrieved relevant literature on OA published between 2003 and 2023 from the Web of Science Core Collection database. We conducted a bibliometric analysis using tools such as CiteSpace, VOSviewer, and SCImago Graphica to examine annual publication trends, co-occurrence patterns, collaborative networks among countries and institutions, and the evolution of research hotspots of OA.ResultsA total of 5,274 publications were included in the bibliometric analysis, comprising 4,561 research articles and 713 review articles. The United States emerged as the leading country in OA research, followed by Germany and China. Over the past two decades, the primary research hotspots focused on “mitochondrial dysfunction,” “hereditary optic neuropathy,” “ocular hypertension” and “diagnostic techniques.” Future research trends are likely to revolve around “molecular mechanisms” and “therapeutic targets.”ConclusionThis bibliometric analysis provides an overview of research developments in OA over the past 20 years, highlighting the emphasis on the pathological basis of OA and advancements in diagnostic and therapeutic approaches. Future studies should continue to explore the molecular basis of mitochondrial dysfunction to identify potential gene therapy targets for treating OA.

To analyze the research status, research hotspots and frontier trends of traditional Chinese medicine (TCM) in the treatment of influenza in the past 20 years through the knowledge graph, so as to provide reference basis for further research. The related literatures of TCM in the treatment of influenza were collected in China National Knowledge Infrastructure (CNKI) from 2000 to 2019. The relevant graphs of authors, research institutions and key words were drawn by CiteSpace 5.6, the distribution and cooperation of main research forces in this field were analyzed, and the research frontiers and hot spot information in this field were discussed. A total of 3 048 related literatures were obtained, involving 949 authors and 242 research institutions. The analysis of the number of articles showed that the volume of articles related to the treatment of influenza with TCM fluctuated greatly in the past 20 years, which was obviously affected by the sudden hot spots around 2010, but showed an overall upward trend, with an average annual volume of about 152 articles. The analysis of the author's cooperation map showed that a total of 77 core authors had published more than 5 articles, accounting for only 8.1% of all authors, and 5 authors had published more than 30 articles. Five major teams had been formed with Gu Ligang, Liu Qingquan, Lu Fangguo, Cui Xiaolan and Zhang Fengxue as the core. The analysis of the cooperation map of research institutions showed that the cooperation among institutions was not good, and only the scientific research institutes in Beijing and Guangzhou had formed a closely related cooperation network. The keyword co-occurrence map showed that 8 keywords appeared more than 100 times, especially ultra-high-frequency keywords, influenza virus ranked first (n = 518). There were 14 key nodes, such as influenza virus, TCM treatment, viral pneumonia and so on, which supported the current research field of TCM in the treatment of influenza. Fourteen clusters were formed to classify the current research hotspots, including the nomenclature of influenza, virus type, TCM treatment, western medicine knowledge, etc., and the map showed that the clustering was reasonable and the structure was significant. Timeline graph showed that parainfluenza virus, virus disease, pharmacodynamics, heat-clearing and detoxifying drugs, bacteriostasis and experimental research had all been studied for more than 8 years, revealing the research hotspots and trends of TCM in the treatment of influenza. The overall research related to the treatment of influenza with TCM is relatively perfect. In the future, the close cooperation among authors and institutions should be strengthened. The molecular mechanism research, clinical and animal trials of TCM should be further studied, so as to improve the research system of TCM treatment of influenza.

In recent years, the rise of big data, artificial intelligence and other technologies has triggered a surge in data volume and information explosion, which has a huge impact on the research and practice of knowledge management. By combing the current situation, hot spots and future research trends of knowledge management research, we can provide reference for the innovation and breakthrough of follow-up research. This paper combs the literature on knowledge management in China from 1998 to 2018, studies the status quo, hot spots and trends of knowledge management research by using data statistics, knowledge mapping and key literature interpretation methods, and finds that China's knowledge management research has entered a relatively mature development stage; the research hot spots are mainly reflected in the following five aspects: knowledge sharing and knowledge transfer The future research trends are summarized as knowledge management under artificial intelligence, knowledge sharing under sharing economy and knowledge service under data drive.

BackgroundGroundwater pollution has become an important factor restricting regional economic development and environmental protection. The prevention and control of groundwater pollution has always been the focus of water resources management scholars. The purpose of this study is to systematically evaluate the knowledge system of groundwater pollution prevention and control from 1981 to 2021, and to explore the research trend and hot spots of groundwater pollution prevention and control knowledge system. And the emotional and behavioral changes of water conservancy workers.Topics and MethodsIn the field of groundwater environment from 1981 to 2021, taking “science network” (WOS) as the literature source database, the literature system and bibliometric characteristics were studied by means of bibliometrics, knowledge atlas and collaborative research. Occurrence analysis. This paper attempts to evaluate and sort out the similarities and differences between frontier hotspots and evolution trends in the field of groundwater environment. At the same time, the emotional behavior of water conservancy workers in various places was investigated. In order to investigate the regulation of psychological expectation on the emotional arousal effect of negative stimulation and its corresponding neural mechanism when excluding any cognitive strategy involvement in the emotional expectation stage. It is intended to mainly manipulate the predictability (predictable / unpredictable) and potency (negative / neutral) of the target stimulus. The experimental task is the expected stage from the emergence of the negative cue to the presentation of the negative target. The subjects are required to only pay attention to the fixation point in the center of the screen after watching the negative cue and do not take any coping strategies for the subsequent negative stimulus. In order to eliminate the fatigue effect, the experiment is divided into four sections. At the end of each section, the subjects took a proper rest, and then tested the success degree of the subjects following the experimental guidance requirement of “only pay attention to the fixation point from the presentation of the cord stimulus to the appearance of the target stimulus”, and scored with a 5-point scale (1 = very unsuccessful, 5 = very successful) to evaluate the success degree of non cognitive manipulation. 36 healthy subjects, 18 men and 18 women, were recruited to rule out possible gender differences in the process of emotional expectation (Galli et al., 2011). All subjects filled in the state trait anxiety questionnaire and Beck depression questionnaire before participating in the experiment to eliminate the possibility of anxiety disorder or depressive tendency. The experiment intends to simultaneously record the activity level of peripheral physiological indexes such as event-related brain potential (ERP), skin electricity, heart rate and skin temperature and frowning electromyography (electromyography index directly related to the negative expression of subjects under negative stimulation), so as to comprehensively reveal how the EEG, peripheral physiological activity level and electromyography activity level related to negative emotion change with expected factors.ResultsGroundwater pollution prevention and control is a general theory in the field of environmental risk of groundwater at home and abroad. There are many core trends in groundwater pollution prevention and control. This paper gives the evolution track, development stage and dynamic change of the research topic.ConclusionIn recent 40 years, the research on the change law of hot spot migration can be divided into three stages. 2009 is a watershed, and the problem has undergone earth shaking changes. Through the visual analysis of knowledge base system, 12 research hotspots are summarized. Explore the change law of topics in the form of dynamic knowledge map, observe the migration of research hotspots, and provide evidence and discussion for research trends and recent hotspots.AcknowledgementsSupported by a project grant from Key R&D Program of Shaanxi Province (Grant No. D5140200023) and Xi 'an Geological Survey, China Geological Survey (Grant No.211527180141).

Focusing on the development trend of maize breeding technology, this paper uses the methods of bibliometric analysis, co-word network analysis, visual analysis and content analysis to retrieve the papers and patents in CNKI literature database and incopat patent database, uses Excel, network analysis integration software, visual analysis system to from the aspects of article load, high-frequency authors, research hotspots, core journals, patent layout, Carry out in-depth mining and visual analysis of research situation in this field, and prospects for the future research. The results show that the number of literatures on maize breeding technology has increased year by year since 1957, and researchers' attention to this field has gradually increased. Under the strategy of fighting a turnaround in the seed industry, it will continue to receive attention. Relevant research is mainly focused on crop disciplines, and the fund support obtained is relatively diversified, basic and applied basic research institutes account for the largest proportion, and more than 50% of the literature is mainly published in professional journals, Patent applications are mainly applied by scientific research institutions and enterprises, supplemented by colleges and universities. Research hotspots mainly focus on maize genetic breeding, biological breeding, waxy maize, sweet maize, breeding technology, disease resistance breeding. In the future, it will be a research hotspot in the aspects of ‘machine harvest + transgenic’, industrialization of biological breeding and digitization of maize production.

There are two types of cell death-apoptosis and necrosis. Apoptosis is cell death regulated by cell signaling pathways, while necrosis has until recently been considered a passive mechanism of cell death caused by environmental pressures. However, recent studies show that necrosis can also be regulated by specific cell signaling pathways. This mode of death, termed necroptosis, has been found to be related to the occurrence and development of many diseases. We used bibliometrics to analyze the global output of literature on necroptosis in the field of neuroscience published in the period 2007-2019 to identify research hotspots and prospects. We included 145 necroptosis-related publications and 2239 references published in the Web of Science during 2007-2019. Visualization analysis revealed that the number of publications related to necroptosis has increased year by year, reaching a peak in 2019. China is the country with the largest number of publications. Key word and literature analyses demonstrated that mitochondrial function change, stroke, ischemia/reperfusion and neuroinflammation are likely the research hotspots and future directions of necroptosis research in the nervous system. The relationship between immune response-related factors, damage-associated molecular patterns, pathogen-associated molecular patterns and necroptosis may become a potential research hotspot in the future. Taken together, our findings suggest that although the inherent limitations of bibliometrics may affect the accuracy of the literature-based prediction of research hotspots, the results obtained from the included publications can provide a reference for the study of necroptosis in the field of neuroscience.

The result of one clustering algorithm can be very different from that of another for the same input dataset as the other input parameters of an algorithm can substantially affect the behavior and execution of the algorithm. Cluster validity indices measure the goodness of a clustering solution. Cluster validation is very important issue in clustering analysis because the result of clustering needs to be validated in most applications. In most clustering algorithms, the number of clusters is set as a user parameter. There are a number of approaches to find the best number of clusters. Validity measures can be used to find the partitioning that best fits the underlying data (to find how good the clustering is). This chapter describes an application (CLUSTER) developed in the Matlab/GUI environment that represents an interface between the user and the results of various clustering algorithms. The user selects algorithm, internal validity index, external validity index, number of clusters, number of iterations etc. from the active windows. In this Package we compare the results of k-means, fuzzy c-means, hierarchical clustering and multiobjective clustering with support vector machine (MocSvm). This chapter presents a MATLAB Graphical User Interface (GUI) that allows the user to easily “find” the goodness of a clustering solution and immediately see the difference of those algorithms graphically. Matlab (R2008a) Graphical User Interface is used to implement this application package.

ObjectiveThe popularity of minimally invasive surgery for lumbar spinal stenosis (LSS) has been steadily increasing worldwide. This study aims to conduct a comprehensive bibliometric analysis to identify global trends and hotspots in the research related to this surgical approach.MethodsSelect articles related to the field that were retrieved from the Web of Science Core Collection (WoSCC) between January 1, 1993 and December 31, 2022. Visualization of networks and in-depth bibliometric analyses, including the number of publications, countries/regions, institutions, journals, authors, keywords, and references, were conducted using VOSviewer and CiteSpace software.ResultsA total of 1197 papers were identified over a three-decade period, with the highest production year being 2022, which saw 171 papers published. The most prolific countries/regions were the United States (279) and Harvard Medical School (59). Among journals, Spine (3289 citations) was the most cited, while World Neurosurgery (98 publications) had the highest number of publications. Lewandrowski, Kai-Uwe (29 publications) wrote the most articles, and Ahn, Y (239 citations) ranked first among cited authors. The most frequently used keyword was “discectomy”, but recent years have shown a strong emergence of keywords such as “microendoscopic decompressive laminotomy”, “foraminotomy” and “classification”.ConclusionThe United States and China have emerged as leaders in the field of minimally invasive surgery for LSS. Endoscopic spinal surgery is recognized as a critical approach, with ongoing research focused on indications, potential complications, minimally invasive anatomical approaches, and outcomes. Furthermore, there is a strong emphasis on optimizing the surgical process, which has become a trending and hot spot in current research. The improvement of surgical techniques is at the forefront of advancements in this field.

The year 2022 marks the 50th anniversary of the signing of the Convention Concerning the Protection of World Cultural and Natural Heritage. Heritage building information modeling (HBIM), which is a digital method of conserving architectural heritage, has recently received a great deal of attention from researchers, planners, and policy-makers in related fields around the world. However, there is not yet a complete analysis of the hot spots and trends in this area of research, nor has a complete workflow based on the practical application of HBIM been developed. In this article, we analyzed the research progress, hot spots, and trends in HBIM since 2010. We used the CiteSpace scientometric analysis tool to analyze 372 documents with high relevance to HBIM from the Web of Science core database using literature co-citation analysis, keyword co-occurrence analysis, cluster analysis, and keyword emergence detection. The findings show that research in the field of HBIM was still in the conceptualization stage during 2010–2017, and with the continuous development of various technologies, attention to HBIM has gradually accelerated since 2017 by expanding its uses to multidisciplinary fields such as artificial intelligence. In the cluster analysis of literature co-citations, 14 clusters were generated, and four clusters, semiautomatic 3D modeling, heritage information system, pilot study, and virtual reality, which have high rates of citation, are discussed in this paper. These clusters reflect the hot spots and frontiers of research in HBIM to a certain extent. In the “Discussion” section, a systematic and complete workflow of HBIM application to heritage architecture is proposed for three levels: modeling, data exchange, and auxiliary management. On this basis, the development of the field of heritage building conservation and sustainable development is analyzed to provide valuable theoretical and practical references to propose future research directions.