High Centrality Research Articles

대학 비교과 교육과정 질 관리를 위한 환류 핵심이슈 도출

Objectives The purpose of this study is to derive key issues related to feedback in the extracurricular curriculum at the university level and suggest directions for system improvements. Methods Therefore, the literature review for this study encompassed 117 academic journal articles published in South Korea during the last decade (2014-2023). Details of each Introduction and Conclusion were extracted, keywords were refined, and the main keywords were identified through TF or TF-IDF. Additionally, a semantic network analysis was conducted to determine connections between keywords. A CONCOR analysis was performed to clarify associations between cooccurring keywords. The results were also visualized. Results First, the top 10 most frequent feedback-related core keywords in non-credit extracurricular programs follow: writing, learning community, core competencies, academic achievement,tutoring, university life, online, self-directed learning, thinking skills, and collaboration. Second, the top five keywords with high degree centrality in the semantic network analysis were learning community-academic achievement-university life-tutoring-collaboration. The top five keywords with closeness centrality were collaboration-creativity-problem solving-career-learning community. The top five keywords with eigenvector centrality were learning community-academic achievement-collaboration-self-directed learning-tutoring. The top five keywords with betweenness centrality were collaboration-creativity-problem-solving-career-learning community. Third, as a result of the CONCOR analysis of the main keywords, the following four clusters were found: demand and performance management, system improvement, content and method improvement, and response to environmental change. Conclusions Based on these findings, the following measures are emphasized: (1) the higher effectiveness of IR related to non-credit extracurricular programs, (2) the preparation of strategies to identify and support prospective transfer students, (3) the examination of management systems to improve the operation of non-credit extracurricular programs, and (4) efforts to ensure the continuity and consistency of policies.

Examining Anxiety and Insomnia in Internship Students and Their Association with Internet Gaming Disorder.

Background: Internships are a mandatory graduation requirement to help medical students transition to the work environment. Some individuals are prone to anxiety in an unfamiliar environment, which is a public concern among young adults. Here, we investigated the mechanism between internet gaming disorder and anxiety and insomnia among internship students. Methods: A convenient sample of 267 internship students was collected in a cross-sectional study module between 17 July and 27 December 2022. The survey contained a 7-item Generalized Anxiety Disorder (GAD-7), Athens Insomnia Scale (AIS), and Internet Gaming Disorder Scale-Short-Form (IGDS9-SF). The association was estimated using Pearson's correlations, and network analysis was performed to characterize these associations. Results: Our results indicate that about 60% of participants exhibited mild to severe anxiety and insomnia, while 2.28% showed symptoms of internet gaming disorder. Also, we found a moderate association between anxiety and insomnia. An item-level analysis indicated that GAD_1 "feeling anxious" and GAD_5 "unable to sit still" are essential for gaming, and that GAD_2 "uncontrollable worrying" is crucial for insomnia. This indicated an interplay between these items, supported by our centrality analysis, where we found that GAD_1 and GAD_2 depicted high centrality. Conclusions: We found high rates of anxiety and insomnia in internship students and the association between selected symptoms of anxiety and insomnia. At the same time, low rates of internet gaming disorder could be attributed to a lack of time for entertainment and an increased awareness of its risks. Given these findings, an awareness of anxiety and insomnia risk should be emphasized.

The spread of misinformation in networks with individual and social learning

The paper studies the spread of misinformation when agents have both individual and social learning. In the presence of sources of misinformation, the most vulnerable and harmful agents are those with poor individual learning and high centrality in the network. However, if opinions are polarized, providing some agents with better private information can backfire on other agents. Moreover, the incentives to spread misinformation have an inverted U-shaped relationship with the spreader’s influence; and, under certain conditions, an unaware spreader can be more harmful than a purposeful one. Overall, this paper warns that any policy that fails to consider both the precision of agents’ private information and the network structure runs the risk of backfiring.

Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology

Mental fitness is a construct that goes beyond a simple focus on subjective emotional wellbeing to encompass more broadly our ability to think, feel, and act to achieve what we want in our daily lives. The measurement and monitoring of multiple (often interacting) domains is crucial to gain a holistic and complete insight into an individual’s mental fitness. We aimed to demonstrate the capability of a new mobile app to characterise the mental fitness of a general population of Australians and to quantify the interrelationships among different domains of mental fitness. Cross-sectional data were collected from 4901 adults from the general population of Australians engaged in work or education who used a mobile app (Innowell) between September 2021 and November 2022. Individuals completed a baseline questionnaire comprised of 26 questions across seven domains of mental fitness (i.e., physical activity, sleep and circadian rhythms, nutrition, substance use, daily activities, social connection, psychological distress). Network analysis was applied at both a domain-level (e.g., 7 nodes representing each cluster of items) and an individual item-level (i.e., 26 nodes representing all questionnaire items). Only 612 people (12%) were functioning well across all domains. One quarter (n = 1204, 25%) had only one problem domain and most (n = 3085, 63%) had multiple problem domains. The two most problematic domains were physical activity (n = 2631, 54%) and social connection (n = 2151, 44%), followed closely by daily activity (n = 1914, 39%). At the domain-level, the strongest association emerged between psychological distress and daily activity (r = 0.301). Psychological distress was the most central node in the network (as measured by strength and expected influence), followed closely by daily activity, sleep and circadian rhythms and then social connection. The item-level network revealed that the nodes with the highest centrality in the network were: hopelessness, depression, functional impairment, effortfulness, subjective energy, worthlessness, and social connectedness. Social connection, sleep and circadian rhythms, and daily activities may be critical targets for intervention due to their widespread associations in the overall network. While psychological distress was not among the most common problems, its centrality may indicate its importance for indicated prevention and early intervention. We showcase the capability of a new mobile app to monitor mental fitness and identify the interrelationships among multiple domains, which may help people develop more personalised insights and approaches.

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023

BackgroundRecently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aimed to explore the research status and hotspots of the application of DL in cancer.MethodsWe retrieved all articles on the application of DL in cancer from the Web of Science database Core Collection database. Biblioshiny, VOSviewer and CiteSpace were used to perform the bibliometric analysis through analyzing the numbers, citations, countries, institutions, authors, journals, references, and keywords.ResultsWe found 6,016 original articles on the application of DL in cancer. The number of annual publications and total citations were uptrend in general. China published the greatest number of articles, USA had the highest total citations, and Saudi Arabia had the highest centrality. Chinese Academy of Sciences was the most productive institution. Tian, Jie published the greatest number of articles, while He Kaiming was the most co-cited author. IEEE Access was the most popular journal. The analysis of references and keywords showed that DL was mainly used for the prediction, detection, classification and diagnosis of breast cancer, lung cancer, and skin cancer.ConclusionsOverall, the number of articles on the application of DL in cancer is gradually increasing. In the future, further expanding and improving the application scope and accuracy of DL applications, and integrating DL with protein prediction, genomics and cancer research may be the research trends.

Mapping Theme Trends and Research Frontiers in Dexmedetomidine Over Past Decade: A Bibliometric Analysis.

Dexmedetomidine, an α2-adrenergic receptor (α2-AR) agonist, is extensively used in clinical and animal studies owing to its sedative, analgesic, and anxiolytic effects. The diverse range of research domains associated with dexmedetomidine poses challenges in defining pivotal research directions. Therefore, this study aimed to conduct a qualitative and quantitative bibliometric study in the field of dexmedetomidine over the past decade to establish current research trends and emerging frontiers. Relevant publications in the field of dexmedetomidine between 2014 and 2023 were extracted from the Web of Science Core Collection database. The bibliometric analysis, incorporating statistical and visual analyses, was conducted using CiteSpace (6.1.R6) and R (4.3.1). The present study encompassed a total of 5,482 publications, exhibiting a consistent upward trend over the past decade. The United States and its institutions had the highest centrality. Ji, Fuhai, and Ebert, Thomas J. were identified as the most productive author and the most cited author, respectively. As anticipated, the most cited journal was Anesthesiology. Moreover, cluster analysis of cited references and co-occurrence of keywords revealed that recent studies were primarily focused on sedation, delirium, and opioid-free anesthesia. Finally, a timeline view of keywords clusters and keywords burst demonstrated that primary research frontiers were stress response, neuroinflammation, delirium, opioid-free anesthesia, peripheral nerve block, and complications. Current research trends and directions are focused on sedation, delirium, and opioid-free anesthesia, as evidenced by our results. The frontier of future research is anticipated to encompass basic investigations into dexmedetomidine, including stress response and neuroinflammation, as well as clinical studies focusing on delirium, opioid-free anesthesia, peripheral nerve block, and associated complications.

빅데이터를 활용한 유보통합에 대한 사회적 인식 분석

The purpose of this study is to find out the social discourse of ECEC integration using big data. Big data related to ECEC integration from 2013 to 2023 were collected using Textorm. The collected raw data were refined, and among them 50 keywords were selected as a result of frequency analysis. The results of the study are as follows. First, the social discourse of ECEC integration showed high frequency in the order of ‘teacher’, ‘child care center’, ’kindergarten’, ‘child care’, and ‘qualification’. As a result of cluster analysis, social discourse was formed centering on three core discourses such as teacher qualification acquisition, policy direction, and consultation subject. Second, major keywords such as ‘child care center’, and ‘kindergarten’ have a higher degree of centrality, while word such as ‘policy’, and ‘Korea National Open University’ have a higher closeness centrality. Third, the ego network analysis was conducted on the main keywords with higher centrality and frequency, such as ‘teacher’ and ‘qualification’. In addition, the ego network analysis was performed and visualized the main keywords and visualized. Through this study, the social discourse was investigated and implications for approach of ECEC integration were discussed.

Unraveling symptom interplay: a network analysis of procrastination in gifted students

BackgroundThis study explores the intricate web of symptoms experienced by academically gifted high school students, focusing on procrastination, rumination, perfectionism, and cognitive flexibility. The well-being of these gifted adolescents remains a pivotal concern, and understanding the dynamics of these symptoms is vital.MethodsA diverse sample of 207 academically gifted high school students from Mashhad, Iran, participated in this study. Using convenience sampling, participants from grades 10, 11, and 12 were included, with detailed assessments conducted through questionnaires measuring the mentioned symptoms.ResultsOur network analysis uncovers compelling insights into the interplay of these symptoms: Procrastination, though moderately central, exerts significant influence within the network, underscoring its relevance. Cognitive flexibility, while centrally positioned, curiously exhibits a negative influence, potentially serving as a protective factor. Negative perfectionism emerges as the keystone symptom, with both high centrality and a positive influence. Rumination displays substantial centrality and a positive influence, indicating its role in symptom exacerbation. Positive perfectionism, moderately central, lacks direct influence on other symptoms.ConclusionThis network analysis provides a nuanced understanding of the relationships among procrastination, rumination, perfectionism, and cognitive flexibility in academically gifted adolescents. Negative perfectionism and cognitive flexibility emerge as critical factors deserving attention in interventions aimed at enhancing the well-being of this unique group. Further research should explore causal relationships to refine targeted interventions.

Bioinformatics Approach is Unraveling Potential Crosstalk between Cytomegalovirus and Epilepsy

Background: Cytomegalovirus (CMV) is a double-stranded DNA virus that is known to be associated with congenital disorders. Epilepsy is a neurological disorder that occurs due to the inception of neurotransmitters. It is suggested that cytomegalovirus can affect epilepsy since it can reach the brain. This study aimed to investigate the molecular crosstalk between epilepsy and Cytomegalovirus infection using a bioinformatics approach. Methods: We used gene expression datasets related to each condition retrieved from a public database. Differentially expressed gene analysis was performed for each dataset group separately. The common genes that were significantly expressed under both conditions were subjected to protein-to-protein network analysis and gene enrichment analysis. Results: A total of 192 common genes were identified across the two conditions. The three genes CCL2, CD44, and CCL3 were defined as hub genes in protein-to-protein interaction networks with the highest centrality. Discussion: This finding suggested the essential roles of these molecules in biological systems. Additionally, these genes are involved in inflammatory processing and the immune response. Conclusion: We suggest that inflammatory chemokine molecules may participate in molecular crosstalk between CMV and epilepsy. Therefore, additional investigations are required to demonstrate the role of each suggested molecule in this association.

The Complexity of Borderline Personality Disorder: Network Analysis of Personality Factors and Defense Styles in the Context of Borderline Personality Organization.

Borderline personality disorder (BPD) is known to share characteristics with a variety of personality disorders (PDs) and exhibits diverse patterns of defense mechanisms. To enhance our understanding of BPD, it's crucial to shift our focus from traditional categorical diagnostics to the dimensional traits shared with other PDs, as the borderline personality organization (BPO) model suggests. This approach illuminates the nuanced spectrum of BPD characteristics, offering deeper insights into its complexity. While studies have investigated the comorbidity of BPD with other PDs, research exploring the relationship between various personality factors and defense mechanisms within BPD itself has been scarce. The present study was undertaken to investigate the complex interrelationships between various personality factors and defense styles in individuals diagnosed with BPD. Using a network analysis approach, data from 227 patients diagnosed with BPD were examined using the Defense Style Questionnaire and Personality Disorder Questionnaire-4+ for assessment. Intricate connections were observed between personality factors and defense styles. Significant associations were identified between various personality factors and defense styles, with immature defense styles, such as maladaptive and image-distorting being particularly prominent in BPD in the centrality analysis. The maladaptive defense style had the highest expected influence centrality. Furthermore, the schizotypal, dependent, and narcissistic personality factors demonstrated relatively high centrality within the network. Network analysis can effectively delineate the complexity of various PDs and defense styles. These findings are expected to facilitate a deeper understanding of why BPD exhibits various levels of organization and presents with heterogeneous characteristics, consistent with the perspectives proposed by the BPO.

Влияние загрязнённой радионуклидами среды на сердечный ритм детей в современных условиях

The main aim was to study the characteristics of heart rate variability in 8- and 10-year boys and girls that permanently reside in areas with an increased level of radioactive contamination. The body functions are formed by close interaction of the body and the environment. The adaptive responses of the developing organism are improved at each ontogenetic stage as its contact with the environment become more complex. We found that features of heart rate regulation depend on the area of residence. The contribution of the autonomous circuit of heart rate regulation is increased for 8- and 10-year-old girls from radio-ecologically safe areas (RESA). Based on the principle of functional antagonism this leads to a weakening of the central circuit of regulation. The shift gradient of indicators is higher for 8-year-old girls from radio-ecologically unfavorable areas (REUA) compared to 10-year-old girls. This reflects the greater sensitivity of their organism to adverse factors. The dominance of the autonomous circuit of regulation was marked for 8- and 10-year-old boys from the RESA. In contrast an imbalance in the operation of regulatory mechanisms with an increase in the central regulatory circuit was found for boys from the REUA. High centralization of cardiac control indicates that adaptation mechanisms are in a state of pronounced tension. The increase in the shift gradient for boys from REUA falls at the age of 10 years. The results of the study revealed gender differences in the regulation of heart rhythm. The obtained data is important diagnostic aspects of morphofunctional maturation of the organism for subsequent ontogenetic stages depending on environmental living conditions.

Structural characteristics and spatiotemporal changes of a reticular river network based on complex network theory

eticular river networks, characterized by a dense pattern of rivers and loop structures, are primarily found in lower river delta plains and are being modified due to rapid population growth and urbanization. This change impacts the distribution of water resources and could result in more frequent and severe floods. Therefore, accurately characterizing the structure of river networks is crucial. In this study, the structure and its changes of a typical plain reticular river network in the Lixia River hinterland area (LRHA), China, were evaluated in the 1960s, 1970s, 1980s, 2009, and 2016 using complex network theory tools at global and local scales. First, we constructed a complex network model by generalizing river sources, outlets, and confluences as nodes and channels as edges. By comparing with the equivalent random networks, it is found that the river networks of LRHA have large clustering coefficients and short characteristic path lengths. These characteristics classify it as a small-world network within complex networks, which is notably efficient for water and material transportation. Second, at the global scale, the global efficiency in complex network theory considers the interconnectivity between nodes and assesses the potential paths between them, effectively reflecting the connectivity status of the river network. At the local scale, the betweenness centrality of a complex network can reflect the control ability of water and material transportation at river nodes. After the 1970s, constructing several new mainstem rivers gradually shifted nodes with high betweenness centrality towards the north–south flowing rivers. In addition, we used Moran’s I to quantify the spatial clustering of the network’s indicators and found that degree and betweenness centrality exhibited higher spatial clustering, with mean Moran’s I values of 0.398 and 0.300, respectively. Finally, we compared the structure of river networks in urban versus rural areas and the mainstem versus tributary streams. We found that urban river networks and mainstem rivers exhibit a higher degree of betweenness centrality, resulting in a greater capacity to regulate water and material cycles within the river network. According to the research findings, complex network theory has been proven to effectively evaluate the structure of reticular river networks at various scales. It enhances our comprehension of the river network’s structure and assists managers in gaining a deeper understanding of how the river network structure influences the distribution of water resources.

Research on Influencing Factors of Cost Control of Centralized Photovoltaic Power Generation Project Based on DEMATEL-ISM

The high cost of centralized photovoltaic power generation projects is an important problem affecting industrial development, which needs to be solved urgently. It is particularly important to explore the influencing factors of cost control and the interaction between them. This paper takes a centralized photovoltaic power generation project as the research object, and determines the index system of influencing factors of cost control from the perspective of the life cycle. Secondly, the logical relationship between influencing factors is judged by the method of combining DEMATEL (decision-making trial and evaluation laboratory) and ISM (interpretive structural modelling). Finally, the multi-order recursive interpretation structure model is obtained, and the action mechanism between various factors is obtained. The results show that national policies and standards are the most profound influencing factors, and their cause degree reaches 2.155; the reason degree of market changes is the second, which is 1.586; bidding and contract management are the factors with the highest centrality, which is 7.120; and transmission and the storage of electricity and equipment repair and maintenance are the most direct factors affecting cost control. Finally, some suggestions are put forward for different types of influencing factors. The research results can better help photovoltaic power generation enterprises solve the problem of cost control.

Social media sensors as early signals of influenza outbreaks at scale

Detecting early signals of an outbreak in a viral process is challenging due to its exponential nature, yet crucial given the benefits to public health it can provide. If available, the network structure where infection happens can provide rich information about the very early stages of viral outbreaks. For example, more central nodes have been used as social network sensors in biological or informational diffusion processes to detect early contagious outbreaks. We aim to combine both approaches to detect early signals of a biological viral process (influenza-like illness, ILI), using its informational epidemic coverage in public social media. We use a large social media dataset covering three years in a country. We demonstrate that it is possible to use highly central users on social media, more precisely high out-degree users from Twitter, as sensors to detect the early signals of ILI outbreaks in the physical world without monitoring the whole population. We also investigate other behavioral and content features that distinguish those early sensors in social media beyond centrality. While high centrality on Twitter is the most distinctive feature of sensors, they are more likely to talk about local news, language, politics, or government than the rest of the users. Our new approach could detect a better and smaller set of social sensors for epidemic outbreaks and is more operationally efficient and privacy respectful than previous ones, not requiring the collection of vast amounts of data.

Robustness of space information networks based on coverage centrality

This study aims to explore cost-effective strategies for efficiently dismantling global complex networks into mutually isolated connected components, particularly in the context of a space information network (SIN). We introduce a novel metric called the coverage centrality, which comprehensively considers the centrality of nodes and links within a satellite coverage area, which integrates the topological and geographical structural information about the network. Through numerical experiments on real-world networks, we demonstrate that the proposed indicator significantly outperforms traditional methods in terms of both effectiveness and efficiency, which tends to select nodes close to the average betweenness of the network for removal rather than solely focusing on nodes with higher centrality, providing a new perspective for us to deeply understand the disintegration behavior of complex networks. The current work not only offers potential application in areas such as anti-terrorist measures and epidemic prevention or control, but also provides new tools to analyze the characteristics of SIN models.

Direct and indirect effects of degree of interdisciplinarity on firms' innovation performance: The moderating role of firms' capabilities

AbstractCombinations of heterogeneous knowledge from different scientific domains may drive highly innovative outcomes. Our study investigates whether firms can benefit from interdisciplinary research and development (R&D) activities by also reflecting on the potential negative consequences of increasing complexity of outcome validation activities at later stages of innovation processes. We explore which resources and organizational capabilities may influence the efficacy of interdisciplinary R&D activities. We examine whether the available financial slack, collaborations with universities, and a high betweenness centrality in scientific networks may promote the flexibility, scope, and efficiency of knowledge integration, and thus moderate the direct and mediated relationships between the degree of interdisciplinarity (DoI) of a firm's R&D activities and innovation performance. To test our hypotheses, we performed an analysis of medical technology firms that are highly dependent on interdisciplinary R&D. We collected a panel dataset of R&D activities and successful market launches of new products from 79 large medical technology firms between 1997 and 2021. The measurement of a firm's DoI is based on a novel approach involving neural networks in a bibliographic data graph. Our results suggest that firms can improve their innovation performance if they conduct interdisciplinary R&D activities. However, higher levels of DoI also increase the complexity of the required outcome validation, which reduces a firm's innovation performance. We also found that high levels of financial slack help to overcome barriers of implementing interdisciplinary R&D activities. Collaborations with universities, and good access to knowledge in scientific networks, further foster interdisciplinary knowledge application in new product development.

Pixels and perception: Mapping the association between digital media and psychotic-like experiences in adolescents

IntroductionPsychotic-like experiences (PLEs) during adolescence can lead to psychotic disorders. Digital media usage has been suggested to link to PLEs, but research is limited on how different types of screen exposure may differentially relate to PLEs over time. This study aimed to examine longitudinal associations between screen usage patterns and PLEs in adolescents. MethodsParticipants comprised 11,876 adolescents assessed annually from ages 9–12 years as part of the Adolescent Brain Cognitive Development study (ABCD). Screen usage (TV, video games, online video, social media, texting, video chat) and PLEs were assessed via self-report. Longitudinal network analysis models were estimated to examine connections between screen usage types and PLEs across three time points. ResultsTwo clusters were formed, including digital media for socializing (e.g., social media/texting/video chat) and digital media for entertainment (e.g., online video/video games/TV). Texting and online video(s) had the highest centrality at each time point, suggesting importance in the network. PLE symptoms of hallucinations and concentration difficulties exhibited higher centrality than other symptoms. Online video and TV were influential bridges between screen usage and PLEs. Network structure significantly differed between ages 9–10 and 10–12 years, but global strength was unchanged over time. DiscussionResults highlight the importance of understanding the associations between specific screen usage types and PLE symptoms. Texting and online video usage appear most influential in the development of adolescent PLEs over time. Findings can inform targeted interventions to promote healthy screen habits and reduce PLEs in at-risk youth.

Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

Research Trends on Living Donors for Liver Transplantation: A Text Network Analysis and Topic Modeling

Purpose: This study aimed to identify research topics and trends on living liver donors over time through text network analysis and topic modeling.Methods: Five electronic databases (PubMed, CINAHL, Embase, Web of Science, and PsycINFO) were reviewed for studies published through September 2023, and 392 studies were included. Text network analysis was used to identify the basic characteristics and centrality of the network. The topics were named after extracting meaningful topics through topic modeling using latent Dirichlet allocation.Results: A total of 1,111 keywords were extracted from the abstracts of 392 selected studies, among which “length of stay,” “morbidity,” “mortality,” “pain,” and “quality of life” showed high frequency and centrality. Through topic modeling analysis, the following four topics were derived: objective health indicators (topic 1), subjective health indicators (topic 2), hepatobiliary-related indicators (topic 3), and early health indicators (topic 4). An analysis of trends in these topics over time showed that the proportion of topics 1, 3, and 4 increased or remained stable. In contrast, there was no significant change in topic 2, representing subjective health indicators.Conclusion: This study explored research trends on living liver donors using text network analysis and topic modeling. Based on the main topics derived, research on postoperative outcomes for living liver donors has focused on objective health indicators, hepatobiliary-related indicators, and early health indicators compared to subjective health indicators. We suggest that future studies utilize integrated indicators of physical and psychosocial aspects.

Bibliometric Analysis of Trends and Future Directions of Research and Development of Seed Orchards

Seed orchards are important seed resources for producing improved tree crops for future plantations, forest restoration, and forestry practices (i.e., gene conservation) and for transmitting current gene diversity to future generations. Seed orchards are a major sub-division in forest science. The establishment and management of a seed orchard involves many steps, from the selection of superior trees to the harvesting of a seed crop. Studying the trends and future directions of seed orchards using different analysis methods is critically important, especially to establish resistant forests via the production of climate-smart, biotic/abiotic-stress-resistant seedling materials. Published papers related to seed orchards should be analyzed to determine the current trends in this field and to contribute to its future directions. Bibliometric analysis has been used for different purposes in various scientific fields. However, it has not been performed for publications in seed orchards. This study was carried out to analyze the current trends of research on seed orchards and to determine the future directions of these orchards based on published papers. For these purposes, 1018 published papers were obtained from the Science Citation Index, Science Citation Index Expanded, and citation index databases of “Web of Science” using the keyword “seed orchard”. The papers were published between 1980 and 2022 and were subjected to bibliometric analysis based on the most prolific contributors, references, countries, and keywords. CiteSpace software 6.1 R6 was applied to visualize information about seed orchard research. The average number of citations per publication was 13.05, and the 4 H-Index of the publication set was 48. The most prolific contributors with the strongest citation bursts, the highest centrality, and the greatest numbers of published papers were from Canada, Sweden, South Korea, Finland, and Czech Republic, while Canada (186 published articles), the USA (140), and Sweden (115), together with China, Brazil, and Germany, were active countries, especially based on citations from recent years. The “keywords” of the papers were the core of the research. “Mating pattern”, “Swedish forestry”, “fertility variation”, “Hymenoscyphus fraxineus”, “threatened Pacific sandalwood”, “outbreeding depression”, “climate change”, “management”, and “growth”, together with others such as “genetic improvement” and “effective size”, were active study areas and keywords, based on results of the analysis. They also guided the literature search and inventory and classification of early studies and served as predictors for future studies. The results of this study are discussed based on the trends and future directions of the research and development of seed orchards.