Visualization Software Research Articles

Global research hotspots and trends in constraint-induced movement therapy in rehabilitation over the past 30 years: a bibliometric and visualization study.

Stroke is a cerebrovascular disease with high prevalence and mortality, and upper limb hemiparesis is a major factor limiting functional recovery in stroke patients. Improvement of motor function in stroke patients through various forms of constraint-induced movement therapy (CITM) has been recognized as safe and effective in recent years. This research field lacks a comprehensive systematic and clear vein combing analysis, analyzing the literature research of CIMT in the field of rehabilitation in the past three decades, summarizing the research hotspots and cutting-edge trends in this field, in an effort to offer ideas and references for subsequent researchers. Relevant literature on CIMT in rehabilitation was collected from 1996 to 2024 within the Web of Science database's core dataset by using CiteSpace6.1, VOSviewer1.6.18, R-bibliometrix4.6.1, Pajek5.16, Scimago Graphica 1.0.26 software for visualization and analysis. There were 970 papers in all United States was ranked first with 401 papers. Alabama Univ was ranked first for institutions with 53 papers. Neurorehabilitation and Neural Repair was ranked first for journals with 78 papers, and Taub E was ranked first for author publications with 64 papers. Research keywords were CIMT, stroke rehabilitation, upper extremity function, lower extremity gait balance, randomized controlled trials, physical therapy techniques (transcranial magnetic stimulation and sensory amplitude electrical stimulation), primary motor cortex plasticity, lateral dominance (spatial behaviors), cerebral vascular accidents, activities of daily living, hand function, disability, functional restoration, bimanual training, aphasia, acquired invalidity, type A Botulinum toxin and joystick riding toys. The current state of research shows that CIMT still has a vast potential for development in the field of rehabilitation research. The research hotspots are the clinical efficacy of CIMT combined with other therapies (botulinum toxin type A, transcranial direct current stimulation, virtual reality, mirror therapy, robotic-assisted) to enhance the functionality of upper limb hemiparesis in stroke patients, the mechanism of CIMT to improve the plasticity of the motor cortex through electrophysiological and imaging methods, and improvement of lower limb gait balance function in stroke patients and aphasia applications, the optimal intervention time and dose, and exploration of CIMT in new settings such as robot-assisted, telemedicine, and home rehabilitation.

Digitally driven surgical guide planning.

To investigate the role of a fully digital process in the surgical treatment of mandibular fractures in children. We analyzed a complete dataset from 22 children with mandibular fractures treated with digital surgical assistance. The patient's treatment process included preoperative thin layer CT (Computed Tomography) scanning, computer-aided design (3D reconstruction, virtual reduction, and internal fixation device determination and shaping), and 3D printing (jaw model, bite plate). We used occlusal and shaping plates during surgery to assist in fracture reduction and fixation. During the follow-up, we observed the occurrence of fracture healing, occlusal relationships, opening degrees, and complications in pediatric patients after surgery. Next, we used the 3D overlay function of MIMICS software to compare the preoperative surgical design with postoperative jaw imaging data to evaluate the overall surgical effect. The postoperative imaging data showed good fracture healing, normal occlusion during follow-up, and significant improvement in opening degrees. The mean preoperative opening degree was 23.59 ± 2.89 mm, and the mean postoperative opening degree was 29.82 ± 1.79 mm; there was a significant difference between these two parameters (p < 0.05). There were no complications such as tooth germ injury, nerve injury or fracture block displacement. The postoperative mandibular imaging data was imported into MIMICS software for 3D overlay visualization, and the postoperative mandibular morphology recovery was well-matched with the preoperative design. We measured the average upper deviation (0.65 ± 0.09) mm and the average lower deviation (-0.57 ± 0.14) mm. The fully digital process has a precise, minimally invasive, and safe effect in the surgical treatment of mandibular fractures in children, and the clinical effect is satisfactory.

Comparative evaluation of volumetric changes between two pediatric rotary files (Kedo-S plus, Kedo-SG blue) and manual files (hand K-files) during canal preparation of primary mandibular molars: an in-vitro nano-CT analysis.

Pediatric endodontics has become popular due to advancements in cleaning, shaping and irrigation systems, resulting in faster and effective removal of infected pulp, saving time, and creating a pathogen-free environment. The patented rotary file system, Kedo-S, designed for primary teeth, introduced a single file generation for efficient pulp therapy. However, there are currently no studies assessing canal preparation in primary mandibular molars using nano-CT (computed Tomography). To evaluate the volumetric changes of two recently introduced pediatric rotary file systems in comparison with conventional hand file systems in primary mandibular molar using an ultra-high resolution nano-CT. This in-vitro study was performed in extracted primary mandibular molar based on certain inclusion and exclusion criteria. Samples were prepared and working length was determined before the pre-operative scan using a high resolution nano-CT device (SkyScan 2214, Bruker, Kontich, Belgium). A single well-experienced pediatric dentist prepared the canals using three file systems: Kedo-S plus, Kedo-SG blue and Hand K-files. A post-operative scan was performed similar to pre-operative scan. Image reconstruction was performed with NRecon software for 3D volumetric visualization and analysis of the root canals. Kedo-SG blue file systems had the highest mean difference in the canal volume (8.85%). Hand K-files had the least difference at (1.24%) of canal volume. Kedo-S plus file system had a mean canal volume difference (6.14%) which is closer to hand K-files. Rotary file systems resulted in a significant enlargement of canals compared to hand files.

Enabling Product Carbon Footprint Management in the Material Extrusion Process

The environmental impact of new products and production processes is one of the most important indicators of the current time. Many methods exist to estimate ecological metrics, such as the Product Carbon Footprint (PCF) in the individual product development phases with stand-alone software. However, methods to integrate the PCF in the entire process chain with the possibility to interact in the process are missing. This paper presents a new approach to measuring the ecological impact of an Additive Manufacturing production process, exemplified by the Material Extrusion (MEX) process. The novelty of the approach lies in implementing a single software for machine control, processing, and visualization of sensor signals, parameter variation, and reporting functions to enable comprehensive PCF management. The workflow includes a model-based prediction of the PCF based on the G-code, live monitoring during the production phase, and a subsequent automated evaluation at a central interface. Critical points can be identified, and approaches for optimizing the MEX process can be designed. Uncertainty evaluation of the PCF based on the combination of uncertainty of the sensors and the Life Cycle Assessment is included in the method. The developed prototype software can be used in the design phase for prediction and in the process phase for optimization, enabling seamless PCF management for the MEX process.

Изучение возможности применения фульвовой кислоты для флотационного извлечения ванадия на основе расчёта молекулярных дескрипторов

The relevance of the work lies in the need to process acidic productive solutions containing the valuable component vanadium in the form of vanadyl cations. The object of study in this work is fulvic acid (FulvAc), and the subject is the possibility of its use as a flotation reagent-collector of vanadyl cations. The purpose of the work is to study the possibility of flotation extraction of vanadium from acidic productive solutions. To achieve the goal, the following tasks are set: selection of a selectively acting collecting reagent in relation to a valuable component based on the "structure-property / activity-property" principle; carrying out molecular calculations, including structural, physicochemical and quantum chemical parameters of a new reagent of natural origin - fulvic acids; application of a software package for modeling and visualization of "substrate-reagent" systems; studying the mechanism of interaction between FulvAc molecules and the substrate [VO(H2O)4]2+; implementation of laboratory flotation testing of the collecting reagent. The following special research methods are used in the work: chemical modeling and analysis using The Cambridge Crystallographic Data Center (CCDC) and Avogadro software systems. Calculations of molecular descriptors of flotation activity of a new organic reagent FulvAc in relation to the extractable valuable component vanadium (metal substrate), which quantitatively allow to evaluate the possibility of using FulvAc for flotation extraction of vanadium substrate from solutions based on the principle of "structure-property/activity-property", are presented. The calculation of molecular descriptors carried out in this work has showed that FulvAc due to phenolic, hydroxyl, carbonyl and carboxyl groups are able to form chelate complexes with vanadium cations, oxygen heteroatoms cause chemisorption centers. Vanadium in acidic productive solutions is in the form of vanadyl cations (VO)2+ and aquavanadylcations [VO(H2O)4]2+, which show the properties of complexing agents. Modeling of flotosystems "substrate-reagent" formation with the use of The Cambridge Crystallographic Data Center software is carried out. The possibility of formation of stable substrate-reagent flotation system "(VO)2+ / [VO(H2O)4]2+– FulvAc" by charge-controlled mechanism has been proved.

Neural Network Circuits for Bionic Associative Memory and Temporal Order Memory Based on DNA Strand Displacement.

Pavlovian associative memory plays an important role in our daily life and work. The realization of Pavlovian associative memory at the deoxyribonucleic acid (DNA) molecular level will promote the development of biological computing and broaden the application scenarios of neural networks. In this article, bionic associative memory and temporal order memory circuits are constructed by DNA strand displacement (DSD) reactions. First, a temporal logic gate is constructed on the basis of DSD circuit and extended to a three-input temporal logic gate. The output of temporal logic gate is used for the weight species of associative memory. Second, the forgetting module and output module based on the DSD circuit are constructed to realize some functions of associative memory, including associative memory with simultaneous stimulus, associative memory with interstimulus interval effect, and the facilitation by intermittent stimulus. In addition, the coding, storage, and retrieval modules are designed based on the analysis and memory capabilities of temporal logic gate for temporal information. The temporal order memory circuit is constructed, demonstrating the temporal order memory ability of DNA circuit. Finally, the reliability of the circuit is verified through Visual DSD software simulation. Our work provides ideas and inspiration to construct more complex DNA bionic circuits and intelligent circuits by using DSD technology.

The Analysis of Natural Lighting-based Visual Comfort for Classrooms Building by Using Velux Daylight Visualizer

This study aims to determine the level of natural lighting at a school building carried out with the use of the Velux Daylight Visualizer (VDV) software. VDV is a software for analysing natural lighting on building model. The output is Daylight Factor (DF) or Daylight Natural Lighting Factor and Illumination (E). E value is the main indicator of the level lighting and visual comfort in the room by referring to simulation results referring Indonesian’s Standard of SNI 03-2396-2001 for visual comfort. Results shown the existing conditions in the classroom have a low level of lighting with majority measurement points having average lighting level below 250 lux. To improve the natural lighting quality in the classrooms, variations of walls-to-windows ratio (WWR) applied the model. The variation of WWR is conduct an experiment to substitute its value in regression equation. With the increasing size of the opening at WWR 30%, the distribution of DF values at measurement distance 1 meter and 2 meters increases compared to WWR 20%. Trend also continues to occur at WWR 40% to WWR 60%, the DF value has increased quite significantly, especially at several points blocked by walls or meeting points between light from 2 adjacent windows.

Research on cooperation network and theme evolution of education Digital transformation based on CiteSpace

Using CiteSpace6.2.6 visual analysis software and literature statistical analysis method, this paper selects 424 academic journal literature data from CNKNO.cn database to systematically organize and analyse the current literature related to education digital transformation in China, taking cooperation network and theme evolution of education digital transformation as the research object. First, through the construction of literature knowledge map, it reveals the cooperation network structure and key nodes in the field of education digital transformation. Secondly, through the theme evolution analysis, the paper discusses the development context and hot topics of education digital transformation research. It is found that in the field of digital transformation of education, the density and tightness of cooperation network are increasing, and the cooperation relationship between domestic research institutions is getting closer and closer. At the same time, the evolution of the theme shows a trend of transferring from basic theoretical exploration to applied practice, and the content covered is gradually rich and diverse. This study provides an important reference for in-depth understanding of the development trend and key issues of education digital transformation, and also provides useful enlightenment for future research directions.

Uncertainty Visualization of Critical Points of 2D Scalar Fields for Parametric and Nonparametric Probabilistic Models.

This paper presents a novel end-to-end framework for closed-form computation and visualization of critical point uncertainty in 2D uncertain scalar fields. Critical points are fundamental topological descriptors used in the visualization and analysis of scalar fields. The uncertainty inherent in data (e.g., observational and experimental data, approximations in simulations, and compression), however, creates uncertainty regarding critical point positions. Uncertainty in critical point positions, therefore, cannot be ignored, given their impact on downstream data analysis tasks. In this work, we study uncertainty in critical points as a function of uncertainty in data modeled with probability distributions. Although Monte Carlo (MC) sampling techniques have been used in prior studies to quantify critical point uncertainty, they are often expensive and are infrequently used in production-quality visualization software. We, therefore, propose a new end-to-end framework to address these challenges that comprises a threefold contribution. First, we derive the critical point uncertainty in closed form, which is more accurate and efficient than the conventional MC sampling methods. Specifically, we provide the closed-form and semianalytical (a mix of closed-form and MC methods) solutions for parametric (e.g., uniform, Epanechnikov) and nonparametric models (e.g., histograms) with finite support. Second, we accelerate critical point probability computations using a parallel implementation with the VTK-m library, which is platform portable. Finally, we demonstrate the integration of our implementation with the ParaView software system to demonstrate near-real-time results for real datasets.

Bibliometric Analysis of Straw Return to Field Research on Soil Nutrients Based on CiteSpace

Soil nutrients are one of the important factors affecting crop growth, and straw return to field is an effective method to improve the soil nutrient composition in agricultural ecosystems. To optimize agricultural production and enhance the resource utilization efficiency of agricultural waste, this paper conducts a comprehensive analysis of annual publication volume, collaborating authors, journal analysis, research institutions, and the frequency and centrality of keywords based on the research papers related to straw return to field and soil nutrients collected in the China National Knowledge Infrastructure (CNKI) database from 2004 to 2024. With the aid of CiteSpace visualization software and bibliometrics, the results show that the number of Chinese-related articles has generally shown an upward trend since 2009. The main authors include Huancheng Pang, etc. The primary publishing journals are mainly “Jiangsu Journal of Agricultural Sciences,” among others. The main institutions include the Institute of Agricultural Resources and Regional Planning, etc. The research hotspots are unfolded from two aspects of straw return to field and soil nutrients, and related soil enzyme activity, and crop yield may become future research hotspots, which also provide reference significance for further leveraging the resource utilization of straw return to field.

DiffFit: Visually-Guided Differentiable Fitting of Molecule Structures to a Cryo-EM Map.

We introduce DiffFit, a differentiable algorithm for fitting protein atomistic structures into an experimental reconstructed Cryo-Electron Microscopy (cryo-EM) volume map. In structural biology, this process is necessary to semi-automatically composite large mesoscale models of complex protein assemblies and complete cellular structures that are based on measured cryo-EM data. The current approaches require manual fitting in three dimensions to start, resulting in approximately aligned structures followed by an automated fine-tuning of the alignment. The DiffFit approach enables domain scientists to fit new structures automatically and visualize the results for inspection and interactive revision. The fitting begins with differentiable three-dimensional (3D) rigid transformations of the protein atom coordinates followed by sampling the density values at the atom coordinates from the target cryo-EM volume. To ensure a meaningful correlation between the sampled densities and the protein structure, we proposed a novel loss function based on a multi-resolution volume-array approach and the exploitation of the negative space. This loss function serves as a critical metric for assessing the fitting quality, ensuring the fitting accuracy and an improved visualization of the results. We assessed the placement quality of DiffFit with several large, realistic datasets and found it to be superior to that of previous methods. We further evaluated our method in two use cases: automating the integration of known composite structures into larger protein complexes and facilitating the fitting of predicted protein domains into volume densities to aid researchers in identifying unknown proteins. We implemented our algorithm as an open-source plugin (github.com/nanovis/DiffFit) in ChimeraX, a leading visualization software in the field. All supplemental materials are available at osf.io/5tx4q.

Bibliometric analysis of sports management competencies in women’s semi-professional sport: A comprehensive analysis at the literature with data visualization software

The participation of women in sports and the management of women’s sports teams have gained significant attention in recent years, underscoring the need to understand the dynamics and organizational aspects of women’s sports. However, there is a noticeable lack of comprehensive bibliometric analyses in this domain, hindering a thorough exploration of the existing literature and the identification of key trends and knowledge gaps. This study aims to address this gap by conducting a rigorous bibliometric analysis of sports management competencies in women’s semi-professional teams in Europe. Using the VOSviewer software, advanced data analysis techniques, including citation and co-citation analysis, were employed to gain insights into the research landscape, influential authors, seminal papers, and key research trends. The results of the analysis revealed clusters of research topics related to women’s semi-professional sports, including performance, gender, football, and sports. The findings of this analysis will contribute to the advancement and success of women’s semi-professional teams by informing the development of tailored training programs, educational curricula, and professional initiatives for sports management roles. Ultimately, this study aims to enhance the understanding of sports management competencies in women’s semi-professional teams and guide future research endeavors in this area.

A Method for Extracting BPMN Models from Textual Descriptions Using Natural Language Processing

Business Process Model and Notation (BPMN) is a standard for formally modeling complex business processes. Manual creation of BPMN models can be time-consuming and error-prone, prompting a need for automation. Existing approaches, such as rule-based methods, machine learning, and machine translation, have progressed but face accuracy and real-world applicability challenges. In this research paper, we propose a novel method for automated extraction of BPMN models from textual descriptions using natural language processing (NLP) tools and deep learning models, including the spaCy library for text processing, a fine-tuned BERT model, and state-of-the-art large language models like GPT-3.5-Turbo and GPT-4. We utilize Graphviz, an open-source graph visualization software, to visualize the extracted processes. Our method supports representing tasks, exclusive gateways, parallel gateways, and start and end events in the generated BPMN models. The evaluation of 31 textual descriptions shows that our method generates process models with 96% accuracy using GPT-4 and 80% accuracy using GPT-3.5-Turbo large language models. Although subject to certain limitations, such as occasional inaccuracies in model outputs and reliance on well-formed input text, our approach offers a valuable contribution to the growing body of research on automating BPMN model generation.

EFFECTIVE BIOMEDICAL SYSTEM FOR DETECTING, TRACKING, AND PREVENTING ASYMPTOMATIC COVID-19 PATIENTS NON-INVASIVELY USING IoT AND MIXED REALITY

This article proposes a novel biomedical system integrating internet of things (IoT) and mixed reality (MR) technologies for detecting, tracking, and preventing asymptomatic corona virus disease (COVID) patients from entering into public places which prevents the further spread of COVID-19 infection. Asymptomatic patients are the very active carriers for virus transmission, and the most challenging conditions in mitigating the virus transmission are contact tracking and contact tracing of asymptomatic patients. The proposed system can be implemented in public places such as theaters, malls, railway stations, airport, markets, conferences, and other gatherings for screening people to detect asymptomatic COVID patients and restrict them from entry. The arrest or decrease in spread of COVID infection during pandemic situation is the most challenging factor around the globe. However, with the proposed system, detection and prevention of asymptomatic COVID patients will result in drastic decrease in the spread of COVID infection during pandemic situation. The proposed system comprises an IoT-based sensing system to get the current sensor values and an MR vision software system to retrieve the pre-saved sensor values from the server. The MR vision system compares the present sensor values and the server values of the human and displays accurately with green MR images for permitted persons and red MR images for restricted asymptomatic COVID patients.

Non-contact computer vision enables analysis of the dynamic performance of naphthalene diimide electrochromic films

Non-contact multi modal analysis of naphthalene diimide chromic films using Kineticolor computer vision software.

Effectiveness of visual package on cervical cancer screening among menopausal women

Effectiveness of visual package on cervical cancer screening among menopausal women

SIMULATION OF GROUNDWATER POLLUTION IN A FACTORY BASED ON VISUAL MODFLOW

The groundwater pollution situation of an industrial park in Mengzhou City, Henan province was simulated to provide reference for groundwater pollution migration and prevention. Through various experiments and hydrogeological surveys to obtain basic parameters for simulation work, this paper uses Visual Modflow software to establish groundwater numerical model in the study area, and on this basis, MT3DMS module is used to simulate solute transport of leaked pollutants COD and NH3-N. In this paper, solute transport is simulated under two working conditions: under abnormal working conditions, the influence range and maximum transport distance of pollutants in sewage transport pipeline leakage without seepage prevention measures; Sewage transport pipeline leakage but seepage prevention measures in the case of pollutant diffusion.

Development of the Northeast China Logistics Network: A Bibliometric Analysis from the Perspectives of South Korea and China

Purpose - This study aims to disclose latest progress in the field of logistics networks in Northeast China through bibliometric analysis to uncover research topics from 2002 to 2022, and explore future research trends through bibliometric research.&#x0D; Design/Methodology/Approach - In this study, 230 CSSCI and 95 KCI articles were selected through a screening process using the PRISMA guidelines flowchart, eliminating research-irrelevant articles and duplicate articles. Citespace and Vosviewer visualization software were used to conduct bibliometric analysis on articles with search terms of “Northeast China” and “Logistics” from 2002 to 2022. It mainly discussed the following issues: (1) the salient conceptual dimensions using keywords analysis; (2) research hot spots using cluster analysis; and (3) likely future research trends.&#x0D; Findings - Based on the KCI and CSSCI databases (articles published from 2002 to 2022), this paper found that logistics development in Northeast China is expected to be accompanied by a number of experiments. Therefore, we firstly need to improve the level and efficiency of logistics activities. Border cities in Northeast China must ensure a smooth process of distribution. Further, it is also necessary to form a multinational logistics cooperation system by activating exchanges with neighboring countries.&#x0D; Research Implications - This study will help establish the status of individual research study in the future, promote the development of the logistics industry in Northeast China, and boost the construction of international cities. It will explore the direction of future research in relevant research fields of South Korea and China.

How foresight has evolved since 1999? Understanding its themes, scope and focus

PurposeForesight J's journey started in 1999, and in 2022, it marked the conclusion of its 24 years of publication. This paper aims to provide an overall overview of important research trends published in Foresight J between 1999 and 2022 by conducting a quantitative analysis of the journal’s literature. The overarching goal is to provide valuable insights into the dynamics of scholarly communication, aiding researchers, institutions and policymakers in assessing the significance and influence of academic work, guiding future research directions and academic evaluation.Design/methodology/approachThe two bibliometrics methodologies that make up the methodology of this article are scientific mapping and performance analysis. Authors have explained the development and composition of the Foresight J using these methods. The SCOPUS database is being used in current research to analyse several dimensions, such as the evolution of publications by year, the most cited papers, core authors and researchers, leading countries and prolific institutions. Moreover, the conceptual structure, scope, burst detection and co-occurrence analysis of the journal are mapped using network visualization software such as VOSviewer, CiteSpace and RStudio.FindingsWith a strong track record of output over the years, Foresight J has continued to develop in terms of publications. It is determined that “Saritas” is the author with the greatest overall impact. However, according to SCOPUS bibliometric data, “Blackman” and “Richardson” are the authors with the greatest relevance in terms of the quantity of articles. In addition, it becomes apparent that the USA, Australia and the UK are very productive nations in terms of publications. The most popular fields of the journal have always been forecasting, foresight, scenario planning, strategic planning, decision-making, technology and sustainable development. These are also the author keywords that appear the most frequently. In contrast, new study themes in the Foresight J include digital technologies, innovation, sustainability, blockchain, artificial intelligence and sustainability.Research limitations/implicationsSeveral noteworthy research implications are provided by the bibliometric study of Foresight J. “Saritas” is the author with the most overall impact, indicating that the precise contributions and influence of this researcher in the fields of forecasting, foresight and related fields. Given that “Blackman” and “Richardson” are well-known writers, it is also critical to examine the scope and complexity of their contributions to potentially identify recurring themes or patterns in their writing. The geographic productivity results, which show that the USA, Australia and the UK are the top three countries for Foresight J publications, may encourage more research into regional differences, patterns of collaboration and the worldwide distribution of research endeavours in the context of forecasting and foresight. Popular fields including scenario planning, forecasting, foresight and sustainable development are consistent, indicating persistent research interests. Examining the causes of these subjects’ ongoing relevance can reveal information about the consistency and development of scholarly interests over time.Practical implicationsForesight J’s bibliometric analysis has real-world applications for many stakeholders. It helps editors and publishers make strategic decisions about outreach and content by providing insights regarding the journal’s influence. Assessing organizational and author productivity helps institutions allocate resources more effectively. Policymakers acquire an instrument to evaluate research patterns and distribute funds efficiently. In general, bibliometric study of a journal helps decisionmakers in academic publishing make well-informed choices that maximize the potential of options for authors, editors, institutions and policymakers.Social implicationsThe societal ramifications of bibliometrically analysing Foresight J from 1999 and 2022 are substantial. This analysis highlights, over the past 24 years, research trends, technological developments and societal priorities have changed by methodically looking through the journal’s articles. Gaining knowledge about the academic environment covered by the journal can help raise public awareness of important topics and promote critical thinking. In addition, the analysis can support evidence-based decision-making by alerting decision makers to the influential research that was published in Foresight J. This could have an impact on the course of policies pertaining to innovation, technology and societal development.Originality/valueThis study presents a first comprehensive article that provides a general overview of the main trends and patterns of the research over the Foresight J’s history since its inception. Also, the paper will help the scientific community to know the value and impact of Foresight J.

Analysis of New Trends In the Field of Japanese Cultural Content Research in China

In China, research on Japanese popular culture (including cultural content) began growing gradually in the 1980s and it increased significantly from 2007. It peaked in 2010, declined in 2011 and 2012, and reached its second peak in 2016. It has been gradually declining since then, partly due to the coronavirus pandemic, leading to the current situation.&lt;/br&gt;This paper uses the academic resources of China National Knowledge Infrastructure (CNKI), a comprehensive Chinese academic information database, as well as quantitative analysis visualization software called “cite space”, to perform knowledge mapping (visualization graphs), which involves using computational methods such as keyword clusters. Knowledge mapping is performed to analyze the chronological changes in Japanese popular culture research in China, issues researchers are interested in, current research topics, the distribution of research content, and future research trends.&lt;/br&gt;Today, it has become increasingly difficult to assimilate all of the intellectual achievements related to Japanese cultural research which has exploded in China in a short period of time. It is hoped that research tools such as big data and quantitative analysis visualization software will facilitate cross-cultural intellectual and cultural exchange more quickly and smoothly in the future.