Timeline Graph Research Articles

Research hotspots and frontiers in acral melanoma: A bibliometric analysis from 1999 to 2023

BackgroundAcral melanoma (AM), an aggressive subtype of melanoma with poor prognosis, has been increasingly studied. The present study aims to discuss the current status, hotspots and future directions of AM studies through visualized analysis with bibliometrics and knowledge graph. MethodPublications related to acral melanoma from January 1999 to May 2023 were searched and retrieved from the Web of Science. Data extraction and visualization of the top 10 publications by year of publication, journal, country and core author were performed using R Studio (Version 4.3.0) and Scimago Graphica (Version 1.0.34). Co-reference graphs regarding country/region, organization, author, and keywords, as well as reference collaborative network, co-occurrence network, and references were plotted using VOSviewer (Version 1.6.19) and CiteSpace (Version 6.2.R3). ResultsA total of 1387 articles related to AM published in English from 1999 to 2023 were included in the present study. A total of 7499 authors were from 2092 organizations in 50 countries. The articles were published in 356 journals, involving 4131 keywords and 28,200 references. The 1387 articles related to AM had been cited a total of 10,014 times by the time of this study. The result showed that Journal of the American Academy of Dermatology had the largest number of citations and citation rate, with a total of 60 publications having been cited 2191 times. Having the top three productivity institutions in the world, the US is the most productive country in this field, with a total of 361 publications. The authors with the highest number of publications were Guo Jun (n = 43) and Si Lu (n = 38) from Peking University. The keyword burstiness test found that “ipilimumab”, “open label”, “efficacy” and “nivolumab” appeared most frequently in recent years. The co-cited reference timeline graph showed that the clustering of “advanced melanoma” and “melanocytic lesion” has been a hotspot since 2016. ConclusionsThe number of AM-related studies has been increasing. The clinical characteristics and immunotherapy of AM are still key research directions, with the US playing a leading role in this field. This bibliometric analysis found up to 1387 publications, which not only comprehensively and quantitatively reflected the research trends and hotspots, but also provided a theoretical basis for future studies of AM. Researchers can benefit from choosing the right journals and finding potential collaborators or partner institutions.

PP110 Knowledge Transfer From Scoping Review Into Primary Research In The Context Of Clinical Practice Guidelines Update

IntroductionIn the development and update process of clinical practice guidelines (CPG) is necessary to focus research questions as much as possible to optimize the systematic reviews. We carried out a scoping review as a precursor to a systematic review to update the recommendation of a CPG for the Management of Patients with Autism Spectrum Disorders in Primary Care. To our knowledge, there is limited information in the existing literature on graphical options for visually presenting scales or other available instruments and classification in a timeline graph.MethodsWe conducted a systematic search to identify instruments for screening of neurodevelopmental disorders and early detection and diagnosis of autism spectrum disorder (ASD). All studies were analyzed to retrieve scales and other instruments used in the assessment of neurodevelopment in the preschool children, and detection of signs and symptoms of neurodevelopment disorder or ASD. We developed a timeline graphic to compile all of the instruments retrieved.ResultsThe information about the name of instrument, type, age of application, diagnostic accuracy, and context of validation was transferred to spreadsheet of the software program Microsoft Excel in tabular format. The instruments found were finally categorized according to the role of each of them in the diagnostic of autism, and age in which they are used. We developed a timeline graph for visually presenting classified instruments according to utility in the routine developmental surveillance, detection of specific signs and symptoms of ASD and diagnostics and evaluation of autism.ConclusionsThe proposed graphical timeline could assist methodologists and researchers in identifying gaps of evidence and lines of research related to use and validation in different contexts the scales and other instruments actually developed. The process of review of evidence can provide information useful for future research in the context of primary research. The relationship between groups of work of health technology assessment and primary research promote the knowledge transfer and optimization of research.

The Effect of Freight and Passenger Transportation and Energy Production on Economic Growth in the Framework of Macro-Economic Indicators: The Case of Kazakhstan

This study analyzes the impact of freight and passenger transport and energy production on the economic growth of Kazakhstan in the period 1996-2021 using the VAR model. The analysis also includes control variables such as energy production, economic growth, exchange rates, inflation, interest rates, foreign direct investment, and unemployment. The research uses data from the World Bank, the Central Bank of Kazakhstan, and the National Bureau of Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. The findings showed that freight transportation's current and one-term lagged value affects economic growth. After determining the significance of the effect, we examined its causality. The findings concluded that none of the independent variables had a causal effect on economic growth, whereas the model with all three independent variables has. The study chose a long study interval and determined the data frequency as annual. The data period may be chosen as monthly or quarterly, and the effects of fluctuations during the year may be examined separately. As the timeline graph shows, the Covid-19 period created a significant statistical disruption for passenger transport. Future researchers may analyze this effect using the series from the pandemic period.

18F]sodium fluoride positron emission tomography: a systematic bibliometric review from 2008 to 2022.

As a noninvasive diagnostic tool, fluorine-18-labelled sodium fluoride positron emission tomography ([18F]NaF PET) has been increasingly applied in clinical practice due to its excellent imaging performance, attracting more attention from clinical practitioners. However, with the continuous development of technology and growth of knowledge, the field of [18F]NaF PET is changing. Nevertheless, few studies have conducted quantitative analyses of the literature in this field. Therefore, in this study, we used bibliometric methods to analyze the trends, content distribution, and frontiers of this field from multiple perspectives, including social and international structure, conceptual structure, and intellectual structure. This study used the Web of Science (WOS) core database as the data source and retrieved literature related to [18F]NaF PET between 2008 and 2022. CiteSpace and VOSviewer software were then employed for bibliometric analysis. This study performed co-occurrence analysis and citation analysis to investigate the characteristics of [18F]NaF PET in 3 aspects. A total of 682 articles related to [18F]NaF PET were collected during the period from 2008 to 2022. The author, Alavi, had the highest number of publications (67 articles). In terms of institutions, the University of Edinburgh had the highest number of publications (64 articles). The United States (300 articles) was the country with the highest number of published articles. Keyword co-occurrence analysis revealed that [18F]NaF PET-related technologies, bone metastasis (prostate cancer and breast cancer), and atherosclerosis were prominent research directions in this field. In terms of highly cited authors, Even-Sapir had the highest citation count (188 citations). Regarding highly cited journals, the Journal of Nuclear Medicine ranked as the most highly cited journal. The literature co-citation clustering and timeline graph showed that atherosclerotic plaques, bone metastasis, and the clinical applications of [18F]NaF PET were topics of active research in this field. There has been an increase in the literature published in the field of [18F]NaF PET from 2008 to 2022. The United States holds a prominent position in the field of [18F]NaF PET. Arteriosclerosis and bone metastasis are the main topics in this field and at the forefront of research.

Twitter Data Analysis Using Hadoop and ‘R’ and Emotional Analysis Using Optimized SVNN

Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints. A parallel computational environment provided by Apache Hadoop can distribute and process the data over different destination systems. In this paper, the Hadoop cluster with four nodes integrated with RHadoop, Flume, and Hive is created to analyze the tweets gathered from the Twitter stream. Twitter stream data is collected relevant to an event/topic like IPL- 2015, cricket, Royal Challengers Bangalore, Kohli, Modi, from May 24 to 30, 2016 using Flume. Hive is used as a data warehouse to store the streamed tweets. Twitter analytics like maximum number of tweets by users, the average number of followers, and maximum number of friends are obtained using Hive. The network graph is constructed with the user’s unique screen name and mentions using ‘R’. A timeline graph of individual users is generated using ‘R’. Also, the proposed solution analyses the emotions of cricket fans by classifying their Twitter messages into appropriate emotional categories using the optimized support vector neural network (OSVNN) classification model. To attain better classification accuracy, the performance of SVNN is enhanced using a chimp optimization algorithm (ChOA). Extracting the users’ emotions toward an event is beneficial for prediction, but when coupled with visualizations, it becomes more powerful. Bar-chart and wordcloud are generated to visualize the emotional analysis results.

A Descriptive Study of the Achievement Timeline of Volleyball Athletes at State University of Malang

This research aims to describe the career path of achievement of volleyball student-athletes from the State University of Malang based on the chronological timeline of achievements in the volleyball championship. This research uses visual research methods (VRM), where data is processed into visual form, namely a timeline graph of achievements. The participants are men's and women's volleyball athletes from the State University of Malang class of 2018-2020 from various faculties with active student status. The achievement data were collected using a questionnaire and given to athletes digitally through Google Forms, then their answers were visualized in timeline graphs. The timeline graphs show the record of athlete achievements chronologically from high school (or equivalent) to college. The graphs were produced and then analyzed using qualitative content analysis. The results showed three patterns in the timeline of athlete achievements: 1) progressive/increase pattern, 2) descending patterns, and 3) stagnation patterns. Implications of this study are: 1) beneficial to understand what factors affect changes in athlete achievements, 2) as reminders for athletes to keep tracking their achievements and develop strategies to improve them; 3) as input for coaches to develop future training programs to improve student-athlete achievement.

Radiographic Evaluation of Distal Radius Fracture Healing by Time: Orthopedist versus Qualitative Assessment of Image Processing

Distal radius fractures are among the most prevalent long-bone fractures in the body. Fracture healing assessment is based on clinical evaluation and radiological examinations. A lack of consensus exists regarding the radiographic criteria for fracture union. Our work examined the commonly used criteria for the assessment of fracture healing. Thirty-two patients, conservatively treated for distal radius fracture, participated in a prospective study. Enrolled patients followed protocol for 26 weeks. Four orthopedic surgeons with similar ranks were asked to evaluate three parameters of radiographic measurements for each set of radiographs, including callus formation, the presence of a fracture line, and bridging of fracture sites or sites of fracture edges in 70 radiographs. Ten patients were eligible for the study. The degree of agreement among surgeons was “good” (Cronbach’s alpha): callus formation—0.8, bridging of fracture sites—0.775, blurring of fracture line gap—0.795. A timeline based on the specific week and grading system was made. Radiographic detection of callus formation was seen after the second film, between 6 and 9 weeks, and an agreement among surgeons was achieved for more than half of the patients for the blurring of the fracture gap. The radiographic healing progression of the distal radius can be detected after 6 and 9 weeks in all three parameters with good agreement between different surgeons. A timeline graph such as the one that was made in this model can be used for the follow-up of patients’ fracture healing or early detection of non-union.

Force-Directed Timelines: Visualizing & Exploring Temporal Patterns

Visualization has shown to be a valuable tool in the analysis of large and complex temporal datasets, aided by the emergence of new models such as Time Curves, which distorts timelines to position time points based on their similarity with each other, reflecting changes in the data over time. In this paper, we further explore time-series functionally and aesthetically by presenting an interactive and parameter-based implementation of the Time Curves model, complemented with the addition of supporting visualizations and data analysis methods. In our implementation we introduce Time Paths, a force-directed layout that can dynamically transform the original model to not only smoothen the transitions between time points, but also reduce visual noise in favor of portraying overall patterns. The proposed addition of visual elements to the model includes temporal glyphs and a supporting timeline graph which help discover and better understand temporal patterns across complex datasets. Through interactive exploration, we demonstrate how these methods can be used to analyze and identify the main agents at the source of significant instances in three biological datasets. These methods are presented within CroP, a data visualization tool with coordinated multiple views aimed at the analysis of biological datasets.

Visual analysis of influenza treated by traditional Chinese medicine based on CiteSpace

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.

Bibliometrics and Visualization of the Mechanisms of Parkinson's Diseases Based on Animal Models.

Energy metabolism disorder is one of the causes of Parkinson's disease (PD). Rodents, such as rats and mice are often used to establish animal models of PD. This paper used a bibliometric method to analyze the studies of rat and mouse PD models published between 2009 and 2018 in the Web of Science (WOS) database using CiteSpace V software. In addition, we conducted a literature review on the development status and research hotspots in this field in the past ten years. The related articles on rat and mouse PD models were retrieved from the WOS database, and an analysis of the keywords in these articles was conducted using CiteSpace V. A timeline graph was developed by the software in order to show the focus of researchers in the PD field. A total of 8,636 articles were obtained. Results of the cluster analysis in the PD field such as neuroinflammation, oxidative stress, and autophagy, contributed to the systematic review about the pathogenesis of PD. At the same time, based on the property of the model drug, this review has summarized and compared different administration techniques and mechanisms of 6-hydroxydopamine (6- OHDA), 1-methyl-4-phenyl-1, 2, 4, 5-tetrahydropyridine (MPTP), paraquat and rotenone. According to the bibliometric analysis, studies on PD were focused on the mechanisms of oxidative stress, neuroinflammation, and autophagy. Activated microglia releases inflammatory cytokines; mitochondrial dysfunction is caused by oxidative damage of mitochondrial protein; abnormal autophagy-lysosome pathway can lead to abnormal protein deposition in dopaminergic neurons. In addition, although many animal models of PD have been established, there are some limitations of such models. Therefore, it is necessary to develop models that accurately mimic human PD.

Embedded Weather Station Data Distribution in a DataSocket Client-Server Network on the LabVIEW Platform

The article presents a model of a weather receiving station comprising a microcontroller system and LabVIEW application. The microcontroller system is equipped with a receiving radio modem and is intended to decode the frames of data transmitted by a weather station used to monitor weather sensors. The decoded stream of data is sent to a PC computer via a serial interface. The data is distributed over the Ethernet via a LabVIEW DataSocket application, based on the TCP protocol. The data is saved to a text file associated with the local DataSocket server. The DataSocket server allows access to the data by DataSocket clients connecting over the local network. The DataSocket client application enables presentation of current and historical data on a timeline graph.

Intra-abdominal pressure during endoscopic full-thickness resection comparing manual and automatic control insufflation: a block-randomized porcine study.

An automatic carbon dioxide (CO2) insufflating system (SPACE) was developed to stabilize intra-lumenal pressure (ILP) during endoscopic interventions. This study investigated whether SPACE could improve the control and monitoring of extra-lumenal intra-abdominal pressure (IAP) after establishing a perforation during endoscopic full-thickness resection (EFTR) of the gastric wall in porcine models. After first establishing the optimal preset pressure for gastric EFTR in four pigs, we compared IAP dynamics during EFTR between manual insufflation and SPACE using a block-randomized study (n = 10). IAP was percutaneously monitored and plotted on a timeline graph every 5s. The maximal IAP and the area under the IAP curve exceeding 10mmHg (AUC≥10mmHg) were compared between groups, with the agreement between IAP and endolumenally monitored ILP also analyzed for animals in the SPACE group. In the first study, 8mmHg was identified as the most preferable preset pressure after establishment of the perforation. In the randomized study, the mean maximal IAP in the SPACE group was significantly lower than that in the manual insufflation group (11.0 ± 2.0mmHg vs. 17.0 ± 3.5mmHg; P = 0.03). The mean AUC≥10mmHg was also significantly smaller in the SPACE group. Bland-Altman analysis demonstrated agreement between IAP and ILP within a range of ± 1.0mmHg. SPACE could be used to control and safely monitor IAP during gastric EFTR by measuring ILP during perforation of the gastric wall.

Metacognitive Inference Activity Support by Visualizing Eye-Movement Graph During Critical Reading

Although writing activities present a good opportunity to develop metacognitive skills, it is difficult for novice learners to be aware of logical inconsistencies or a lack of perspective, even in their own documents. To promote such learners’ metacognitive activities, a novel eye-movement visualization system is proposed that activates learners’ metacognitive inference activities by expanding a previously proposed framework. The system intuitively visualizes all reading processes of the expert, who critically reads the learner’s document, as a timeline graph. In addition, it has several support functions that provide information on the expert’s characteristic reading behaviors and the logical structure of documents. The initial experiment showed that the proposed graph visualization system has the potential to activate learners’ metacognitive inference activities, even after verifying the previously proposed eye-movement visualization tools. It was also confirmed that learners can generate the correction points by themselves, even in documents that they had already checked critically before submission.

Technical report: an ePRO patient reported outcome program for the evaluation of patients with irritable bowel syndrome

Patient reported outcome (PRO) is an important healthcare concept that describes patient's participation in their care by self-evaluation, usually in the form of questionnaires. This report describes an unique computerized technique, electronic PRO (ePRO), for following the progress of patients with irritable bowel syndrome (IBS). Patients first completed a series of questionnaires, including questions about their illness history, symptom severity, and, in this application, psychological and relationship issues. The symptom severity and psychological questionnaires were then completed at intervals by the patients on their own computers. The ePRO was constructed to allow scores to be automatically summed and placed on a time-line graph for review at the time of the next office visit. Of the 32 patients who completed the initial set of questionnaires, 20 maintained participation in the program for a 6-month period. Of those 20 patients, median number of submissions was 7.0; median interval between questionnaire submissions was 3.0 weeks, whereas median interval between office visits was 5.9 weeks. On average, questionnaire completion took less than 5 min and was positively experienced by the patients. The ePRO program proved to be technically feasible, clinically useful, and positively experienced by the patients. It provides a focus on a collaborative conversation between physician and patient. It has significant potential as a technique for evaluating outcome in response to various therapies.

A proposed model of a visual interaction analysis graph for studying educational interactions and their impact on learning within a technology enhanced learning environment

Enhancing educational interactions in collaborative learning within Technology Enhanced Learning Environments (TELE) is a popular approach to engage students in active learning within the Higher education sector globally. These entail providing educational interaction episodes at various time points of a teaching/learning session. Analyses of interactions can explore whether improving student collaborations and interactions do indeed have an impact on learning. Few empirical studies on interaction analyses have been conducted in the context of Technology Enhanced classrooms in Higher education. Tools used currently for analyses of video data of educational interactions yield reports that are either too technical or do not, in themselves, give feedback on the impact of student interactions on learning. In this project, while studying collaborative learning within a Technology Enhanced practical lab, a simple model of an "Interaction Timeline Graph" was developed to sequentially analyse educational interactions over time, so that teachers and students alike might understand these. Content analyses of widely-used video analysis software applications was done. This led to some elements of these software applications to be incorporated in this new model. To further analyze educational impacts of these interactions, elements of a learning framework applied specifically to Technology Enhanced Learning lab have been coded and then incorporated into a further innovative detailed model of the "Visual Interaction and Learning Sequence Graph". Such a model of "Visual Interaction and Learning Sequence Graph" includes three critical segments of colour coded educational interactions in a sequential timeline as well as their representative snapshots along with each of its learning element. While studying learning in a technology enhanced classroom setting, it has much potential in its use, as interactions can be directly related to learning outcomes and summative grades. As this "Visual Interaction and Learning Sequence Graph" is simple and graphic, it can be used as a feedback tool for both the learner as well for facilitators on the effectiveness of interactions. When compared with grades, this model could also be used to expand academic analytics in identifying types of interaction that successful students engage in and those that may influence increased learning effectiveness and higher student performance.

A Study of the Temporal Course of Phenomenology of Alcohol Dependence

The natural history of alcoholism was first charted out in 1946 by Jellinek, whose original results have been replicated by multiple research groups. They have verified a general progression of alcohol dependence through a series of identifiable phases. The study investigated the sequence of events in the course of alcohol dependence and its deviations from randomness. The study consisted of 36 patients with alcohol dependence, subjected to a structured questionnaire containing 34 items describing the phenomenology of alcohol dependence, based on the lines of SCID. The items experienced by each patient were identified and then plotted on a timeline graph according to an important life event, the items being represented on cards given to the patients randomly. The subjects were re-interviewed after one week and asked to rank their symptoms again to analyze test-retest reliability. The analysis of the item ordering was determined by null hypothesis of randomness. The ordering showed three phases. The early phase was characterized by features of increased tolerance loss of flexibility, and salience. The middle phase consisted mainly of the need for alcohol, and the late phase was predominated by features of physiological withdrawal, tremors, nausea, panics, and hallucinations. There is a characteristic ordering of new events and symptoms, which suggests a developmental process of alcoholism, but this is apparent only if attention is confined to a limited part of the broad spectrum. This process is obscured by consideration of the social concomitants of alcohol dependence. The study of the natural history of alcohol dependence is essential in recognizing and treating the problem and determining whether an intervention appears to be working.

Alcohol dependency and affective illness among women of childbearing age

The objectives of the study were to identify variables that predicted duration of an episode of alcoholism among women and to examine risk factors for women having comorbid alcoholism with affective illness when compared to women who had an affective disorder only. We selected a cohort of women of childbearing age (n = 231) from computerized medical records. The women were contacted five years after their initial emergency visit and asked to participate in a follow-up study. Each RDC episode of illness and its duration were plotted on a longitudinal time-line graph. The only multivariate predictor of duration of an episode of alcoholism was comorbidity with a mood disorder. We compared women who had alcoholism comorbid with affective illness to women with affective illness only. Women with both disorders were 36 times more likely to have a history of illness with their first psychiatric episode before the age of 15 compared to women with an affective disorder only. The findings suggest a dual liability for alcoholism and an affective illness among women with young children.

Processes in Pollution Management: An Australian Model

/ This paper describes a model of the social and institutional processes involved in the solution of major pollution problems from the time they are first identified until they are resolved. The model is empirically demonstrated using four case studies of water and air pollution problems from Sydney, New South Wales, Australia. Each process of the model is quantified by the use of an indicator, e.g., number of articles in newspapers to measure the process "publicconcern," number of pages of text devoted to parliamentary debates to measure the process "political action." The case study data are presented on a time-line graph that shows the duration and magnitude of each process. The paper illustrates three aspects of the solution of major pollution problems: the long time frames involved, the importance of public opinion in initiating the solution process, and the partial nature of solutions-problems may be politically resolved but often a complete solution is not achieved. An understanding of social and institutional processes and time frames will enable planners and policy makers to communicate to the public and politicians the consequences of delay in acting to solve pollution and to direct attention to critical areas to expedite solutions.KEY WORDS: Pollution problems; Management process model; Performance indicators; Air pollution; Water pollution