BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications...BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications,a lack of effective treatment strategies,and substantial socioeconomic burdens,it has become an urgent public health issue that requires management and resolution.Adolescent T2DM differs from adult T2DM.Despite a significant increase in our understanding of youth-onset T2DM over the past two decades,the related review and evidence-based content remain limited.AIM To visualize the hotspots and trends in pediatric and adolescent T2DM research and to forecast their future research themes.METHODS This study utilized the terms“children”,“adolescents”,and“type 2 diabetes”,retrieving relevant articles published between 1983 and 2023 from three citation databases within the Web of Science Core Collection(SCI,SSCI,ESCI).Utilizing CiteSpace and VoSviewer software,we analyze and visually represent the annual output of literature,countries involved,and participating institutions.This allows us to predict trends in this research field.Our analysis encompasses co-cited authors,journal overlays,citation overlays,time-zone views,keyword analysis,and reference analysis,etc.RESULTS A total of 9210 articles were included,and the annual publication volume in this field showed a steady growth trend.The United States had the highest number of publications and the highest H-index.The United States also had the most research institutions and the strongest research capacity.The global hot journals were primarily diabetes professional journals but also included journals related to nutrition,endocrinology,and metabolism.Keyword analysis showed that research related to endothelial dysfunction,exposure risk,cardiac metabolic risk,changes in gut microbiota,the impact on comorbidities and outcomes,etc.,were emerging keywords.They have maintained their popularity in this field,suggesting that these areas have garnered significant research interest in recent years.CONCLUSION Pediatric and adolescent T2DM is increasingly drawing global attention,with genes,behaviors,environmental factors,and multisystemic interventions potentially emerging as future research hot spots.展开更多
ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build...ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.展开更多
With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers ...With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.展开更多
As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynami...As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.展开更多
The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reac...The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.展开更多
Objective:Based on the CNKI database,this study analyzes the current research status and hotspots of the Timing it Right(TIR)Theory in China,providing insights and references for its further development in the field o...Objective:Based on the CNKI database,this study analyzes the current research status and hotspots of the Timing it Right(TIR)Theory in China,providing insights and references for its further development in the field of nursing.Methods:Using bibliometric methods and Citespace software,this study conducts a statistical and visual analysis of publications on TIR Theory from CNKI,focusing on annual publication volumes,author collaboration networks,high-frequency keywords,and emergent terms.Results:The study statistically analyzed the time distribution and research hotspots of 117 relevant papers.The annual publication volume shows a gradual upward trend,though the overall volume remains low.High-frequency keywords such as“family nursing,”“quality of life,”“acute myocardial infarction,”and“stroke”form the core research themes.Conclusion:Research on TIR Theory in China’s nursing field is still in the exploratory stage,and its attention and emphasis need to be enhanced.As it aligns with modern medical models,its application scope in nursing is expanding,promoting the high-quality,scientific,and diversified development of nursing services in China.展开更多
Objective:To systematically investigate the research status,research hotspots,and developmental trends of robotic techniques in stroke rehabilitation through bibliometric and visualization analysis.Methods:Literature ...Objective:To systematically investigate the research status,research hotspots,and developmental trends of robotic techniques in stroke rehabilitation through bibliometric and visualization analysis.Methods:Literature published in the Web of Science from 2004 to 2024 were screened.VOSviewer,CiteSpace,R Software,Microsoft Office Excel 2021,and“bibliometric.com”were employed to conduct bibliometric analysis and network visualization.Results:A total of 3,704 documents were retrieved.Northwestern University was the most productive institution.Krebs Hermano Igo was the most prolific author.The Journal of NeuroEngineering and Rehabilitation had the highest publication volume.The United States currently holds a leading position in various aspects,including the overall volume of publications,institutional contributions,author output,and funding support.Keywords such as“deep learning”“physical human-robot interaction”“wearable robotics”“mirror therapy”“telerehabilitation”“soft robotics”“augmented reality”“functional near-infrared spectroscopy,”and“impedance control”highlight the current research hotspots and frontiers.Conclusion:Rehabilitation robotics is a field with vigorous growth,progressively advancing toward intelligent,personalized,accessible,and efficient rehabilitation solutions with substantial future potential.展开更多
BACKGROUND Colorectal cancer(CRC)is the third-most prevalent cancer and the cancer with the second-highest mortality rate worldwide,representing a high public health burden.Deep learning(DL)offers advantages in the di...BACKGROUND Colorectal cancer(CRC)is the third-most prevalent cancer and the cancer with the second-highest mortality rate worldwide,representing a high public health burden.Deep learning(DL)offers advantages in the diagnosis,identification,localization,classification and prognosis of CRC patients.However,few bibliometric analyses of research hotspots and trends in the field have been performed.AIM To use bibliometric approaches to analyze and visualize the current research state and development trend of DL in CRC as well as to anticipate future research directions and hotspots.METHODS Datasets were retrieved from the Web of Science Core Collection for the period January 2011 to December 2023.Scimago Graphica(1.0.45),VOSviewer(1.6.20)and CiteSpace(6.3.1)were used to analyze and visualize the nation,institution,journal,author,reference and keyword indicators.Origin(2022)was utilized for plotting,and Excel(2021)was used to construct the tables.RESULTS A total of 1275 publications in 538 journals from 74 countries and 2267 institutions were collected.The number of annual publications has increased over time.China(371,29.1%),the United States(265,20.8%)and Japan(155,12.2%)contributed significantly to the number of articles published,accounting for 62.1%of the total publications.The United States had the strongest ties to other nations.Sun Yat-sen University in China had the highest number of publications(32).The journal with the most publications was Scientific Reports(34,Q2),whereas Gastrointestinal Endoscopy had the most co-citations(1053,Q1).Kather JN,was the author with the most articles(12)and co-citations(287).The most frequently cited reference was Deep Residual Learning for Image Recognition.Keywords were divided into six clusters,with“colorectal cancer”(12.34)having the highest outbreak intensity.CONCLUSION This study highlights the current status and most active directions of the use of DL in CRC.This approach has important applications in the identification,diagnosis,localization,classification and prognosis of the disease and will remain a central focus in the future.展开更多
Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhib...Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhibit significant limitations in representing attributes of complex networks at various scales,particularly failing to provide advanced visual representations of specific nodes and edges,community affiliation attribution,and global scalability.These limitations substantially impede the intuitive analysis and interpretation of complex network patterns through visual representation.To address these limitations,we propose SFFSlib,a multi-scale network visualization framework incorporating novel methods to highlight attribute representation in diverse network scenarios and optimize structural feature visualization.Notably,we have enhanced the visualization of pivotal details at different scales across diverse network scenarios.The visualization algorithms proposed within SFFSlib were applied to real-world datasets and benchmarked against conventional layout algorithms.The experimental results reveal that SFFSlib significantly enhances the clarity of visualizations across different scales,offering a practical solution for the advancement of network attribute representation and the overall enhancement of visualization quality.展开更多
The hybrid CO_(2) thermal technique has achieved considerable success globally in extracting residual heavy oil from reserves following a long-term steam stimulation process.Using microscopic visualization experiments...The hybrid CO_(2) thermal technique has achieved considerable success globally in extracting residual heavy oil from reserves following a long-term steam stimulation process.Using microscopic visualization experiments and molecular dynamics(MD)simulations,this study investigates the microscopic enhanced oil recovery(EOR)mechanisms underlying residual oil removal using hybrid CO_(2) thermal systems.Based on the experimental models for the occurrence of heavy oil,this study evaluates the performance of hybrid CO_(2) thermal systems under various conditions using MD simulations.The results demonstrate that introducing CO_(2) molecules into heavy oil can effectively penetrate and decompose dense aggregates that are originally formed on hydrophobic surfaces.A stable miscible hybrid CO_(2) thermal system,with a high effective distribution ratio of CO_(2),proficiently reduces the interaction energies between heavy oil and rock surfaces,as well as within heavy oil.A visualization analysis of the interactions reveals that strong van der Waals(vdW)attractions occur between CO_(2) and heavy oil molecules,effectively promoting the decomposition and swelling of heavy oil.This unlocks the residual oil on the hydrophobic surfaces.Considering the impacts of temperature and CO_(2) concentration,an optimal gas-to-steam injection ratio(here,the CO_(2):steam ratio)ranging between 1:6 and 1:9 is recommended.This study examines the microscopic mechanisms underlying the hybrid CO_(2) thermal technique at a molecular scale,providing a significant theoretical guide for its expanded application in EOR.展开更多
Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of s...Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of surgical failure.Therefore,it is necessary to design a visualization system for closed thoracic drainage.Augmented reality(AR)technology can assist in visualizing the internal anatomical structure and determining the insertion point on the body surface.The structure of the currently used steel-needle-guided chest tube was modified by integrating it with an ultrafine diameter camera to provide real-time visualization of the puncture process.After simulation experiments,the overall registration error of the AR method was measured to be within(3.59±0.53)mm,indicating its potential for clinical application.The ultrafine diameter camera module and improved steel-needle-guided chest tube can timely reflect the position of the needle tip in the human body.A comparative experiment showed that video guidance could improve the safety of the puncture process compared to the traditional method.Finally,a qualitative evaluation of the usability of the system was conducted through a questionnaire.This system facilitates the visualization of closed thoracic drainage puncture procedure and pro-vides an implementation scheme to enhance the accuracy and safety of the operative step,which is conducive to reducing the learning curve and improving the proficiency of the doctors.展开更多
Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately c...Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately controlling the blasting energy and achieving the directional fracture of a rock mass have become common problems in the field.A two-dimensional blasting(2D blasting)technique was proposed that utilizes the characteristic that the tensile strength of a rock mass is significantly lower than its compressive strength.After blasting,only a 2D crack surface is generated along the predetermined direction,eliminating the damage to the reserved rock mass caused by conventional blasting.However,the interior of a natural rock mass is a"black box",and the process of crack propagation is difficult to capture,resulting in an unclear 2D blasting mechanism.To this end,a single-hole polymethyl methacrylate(PMMA)test piece was used to conduct a 2D blasting experiment with the help of a high-speed camera to capture the dynamic crack propagation process and the digital image correlation(DIC)method to analyze the evolution law of surface strain on the test piece.On this basis,a three-dimensional(3D)finite element model was established based on the progressive failure theory to simulate the stress,strain,damage,and displacement evolution process of the model under 2D blasting.The simulation results were consistent with the experimental results.The research results reveal the 2D blasting mechanism and provide theoretical support for the application of 2D blasting technology in the field of rock excavation.展开更多
A new visualization method for studying the damage to gel structure caused by high salinity ions is explored by using the characteristics of suppression image signal of Mn^(2+) and nuclear magnetic resonance(NMR) imag...A new visualization method for studying the damage to gel structure caused by high salinity ions is explored by using the characteristics of suppression image signal of Mn^(2+) and nuclear magnetic resonance(NMR) imaging technique. The diffusion and distribution characteristics of Mn^(2+) in porous media-gel system were studied based on manganese chloride static diffusion and gel flooding experiments, and the gel's nuclear magnetic image and displacement pressure were tested. The results show that the diffusion of Mn^(2+)conforms to the Fick diffusion law in porous media-gel system, and the diffusion speed of Mn^(2+) increases and the area of gel image decreases gradually with the increase of concentration, and the image of gel decreases faster and the pressure drop of water drive is larger in flooding experiment of manganese chloride with higher concentration. Reaction-diffusion model with the reaction of Mn^(2+) with gel was established to study the concentration distribution characteristics of Mn^(2+). The model is validated by comparing the results with magnetic resonance imaging(MRI) experiments and the diffusion coefficient of Mn^(2+) equals 1.6 mm^2/h, and the minimum concentration of Mn^(2+) to impact gel NMR image signals is 2.5 g/L. The above results show that the diffusion of Mn^(2+) into the gel in the rock core inhibits the imaging signal of the gel and damages its strength, and the greater the concentration is, the greater the influence. Increase of adsorption amount of gel and reaction rate, reduction of diffusion time, and addition of ion adsorption isolator all can reduce the impact of Mn^(2+) on the gel.展开更多
In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML...In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.展开更多
Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginn...Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginners to grasp the intricate composition rules of formulas.To address this gap,we introduce Formula-S,a situated visualization method for TCM formula learning in augmented reality(AR)and evaluate its performance.This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization.Methods Formula-S is an interactive AR tool designed for TCM formula learning,featuring three modes(3D,Web,and Table).The dataset included TCM formulas and herb properties extracted from authoritative references,including textbook and the SymMap database.In Formula-S,the hierarchical visualization of the formulas as herbal medicine compositions,is linked to the multidimensional herb attribute visualization and embedded in the real world,where real herb samples are presented.To evaluate its effectiveness,a controlled study(n=30)was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification,formula composition,and recognition.In the study,participants interacted with the AR tool through HoloLens 2.Data were collected on both task performance(accuracy and response time)and user experience,with a focus on task efficiency,accuracy,and user preference across the different learning modes.Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks.Regarding user experience,our new approach demonstrated the highest system usability and lowest task load,effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency.Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment,suggesting this approach offers usability advantages for TCM education.Conclusions The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods.Additionally,it provides superior contextual understanding of TCM formulas,making it a promising new solution for TCM learning.展开更多
In this article, we present a three-dimensional visualization technique that has been developed in order to establish an interactive immersive environment to visualize the particles in granular materials and dislocati...In this article, we present a three-dimensional visualization technique that has been developed in order to establish an interactive immersive environment to visualize the particles in granular materials and dislocations in crystals. Simple elementary objects often exhibit complex collective behavior. Understanding of such behaviors and developments of coarse-scale theories, often requires insight into collective behavior that can only be obtained through immersive visualization. By displaying the computational results in a virtual environment with three-dimensional perception, one can immerse inside the model and analyze the intricate and very complex behavior of individual particles and dislocations. We built the stereographic images of the models using OpenGL rendering technique and then combine with the Virtual Reality technology in order to immerse in the three-dimensional model. A head mounted display has been used to allow the user to immerse inside the models and a flock of birds tracking device that allows the movements around and within the immersive environment.展开更多
In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string an...In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string and split into individual characters using regular expression. This will be followed by separating the token grammar using best first search (BFS) algorithm to determine node having lowest value, lastly followed by graph presentation of intermediate representation achieved with the help of graph visualization software (GraphViz) while former is implemented using python programming language version 3. The efficacy of our approach is used in analyzing C++ code and yielded a satisfactory result.展开更多
Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in powe...Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in power systems, especially in Smart Grid are still in infancy stage. Besides, while there were a lot of researches working on visualizing data in transmission power system, the study on displaying distribution power system data was limited. Therefore, in this paper, author proposed some techniques to visualize the Smart Grid data at distribution. They are classified in three categories, which are low dimensional techniques, multivariate high dimensional techniques and Geographical Information System (GIS) techniques.展开更多
In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytic...In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.展开更多
Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challe...Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challenging.Herein,wepropose visual rehabilitation training system including iontronic meta-fabrics withskin-friendly and large matrix features,as well as high-resolution image modules fordistribution of human muscle tension.Attributed to the dynamic connection and dissociationof the meta-fabric,the fabric exhibits outstanding tactile sensing properties,such as wide tactile sensing range(0~300 kPa)and high-resolution tactile perception(50 Pa or 0.058%).Meanwhile,thanks to the differential capillary effect,the meta-fabric exhibits a“hitting three birds with one stone”property(dryness wearing experience,long working time and cooling sensing).Based on this,the fabrics can be integrated with garmentsand advanced data analysis systems to manufacture a series of large matrix structure(40×40,1600 sensing units)training devices.Significantly,the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allowthis visualization training strategy extendable to various common disease monitoring.Therefore,we believe that our study overcomes theconstraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.展开更多
基金Supported by the National Natural Science Foundation of China,No.82105018 and No.81903950.
文摘BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications,a lack of effective treatment strategies,and substantial socioeconomic burdens,it has become an urgent public health issue that requires management and resolution.Adolescent T2DM differs from adult T2DM.Despite a significant increase in our understanding of youth-onset T2DM over the past two decades,the related review and evidence-based content remain limited.AIM To visualize the hotspots and trends in pediatric and adolescent T2DM research and to forecast their future research themes.METHODS This study utilized the terms“children”,“adolescents”,and“type 2 diabetes”,retrieving relevant articles published between 1983 and 2023 from three citation databases within the Web of Science Core Collection(SCI,SSCI,ESCI).Utilizing CiteSpace and VoSviewer software,we analyze and visually represent the annual output of literature,countries involved,and participating institutions.This allows us to predict trends in this research field.Our analysis encompasses co-cited authors,journal overlays,citation overlays,time-zone views,keyword analysis,and reference analysis,etc.RESULTS A total of 9210 articles were included,and the annual publication volume in this field showed a steady growth trend.The United States had the highest number of publications and the highest H-index.The United States also had the most research institutions and the strongest research capacity.The global hot journals were primarily diabetes professional journals but also included journals related to nutrition,endocrinology,and metabolism.Keyword analysis showed that research related to endothelial dysfunction,exposure risk,cardiac metabolic risk,changes in gut microbiota,the impact on comorbidities and outcomes,etc.,were emerging keywords.They have maintained their popularity in this field,suggesting that these areas have garnered significant research interest in recent years.CONCLUSION Pediatric and adolescent T2DM is increasingly drawing global attention,with genes,behaviors,environmental factors,and multisystemic interventions potentially emerging as future research hot spots.
基金Under the auspices of President Foundation of the Chinese Academy of Sciences(1999).
文摘ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.
基金supported by the Natural Science Foundation of Henan Province(Grant No.242300420297)awarded to Yi Sun.
文摘With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.
基金supported in part by the National Key Research and Development Plan Project(2022YFB3304700)in part by the Xinliao Talent Program of Liaoning Province(XLYC2202002).
文摘As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.
基金supported by the National Natural Science Foundation of China(Nos.12175321,11975021,and 11675275)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)。
文摘The Taishan Antineutrino Observatory(TAO)is a satellite experiment of the Jiangmen Underground Neutrino Observatory,located near the Taishan nuclear power plant(NPP).The TAO aims to measure the energy spectrum of reactor antineutrinos with unprecedented precision,which would benefit both reactor neutrino physics and the nuclear database.A detector geometry and event visualization system was developed for the TAO.The software was based on ROOT packages and embedded in the TAO offline software framework.This provided an intuitive tool for visualizing the detector geometry,tuning the reconstruction algorithm,understanding neutrino physics,and monitoring the operation of reactors at NPP.Further applications of the visualization system in the experimental operation of TAO and its future development are discussed.
文摘Objective:Based on the CNKI database,this study analyzes the current research status and hotspots of the Timing it Right(TIR)Theory in China,providing insights and references for its further development in the field of nursing.Methods:Using bibliometric methods and Citespace software,this study conducts a statistical and visual analysis of publications on TIR Theory from CNKI,focusing on annual publication volumes,author collaboration networks,high-frequency keywords,and emergent terms.Results:The study statistically analyzed the time distribution and research hotspots of 117 relevant papers.The annual publication volume shows a gradual upward trend,though the overall volume remains low.High-frequency keywords such as“family nursing,”“quality of life,”“acute myocardial infarction,”and“stroke”form the core research themes.Conclusion:Research on TIR Theory in China’s nursing field is still in the exploratory stage,and its attention and emphasis need to be enhanced.As it aligns with modern medical models,its application scope in nursing is expanding,promoting the high-quality,scientific,and diversified development of nursing services in China.
文摘Objective:To systematically investigate the research status,research hotspots,and developmental trends of robotic techniques in stroke rehabilitation through bibliometric and visualization analysis.Methods:Literature published in the Web of Science from 2004 to 2024 were screened.VOSviewer,CiteSpace,R Software,Microsoft Office Excel 2021,and“bibliometric.com”were employed to conduct bibliometric analysis and network visualization.Results:A total of 3,704 documents were retrieved.Northwestern University was the most productive institution.Krebs Hermano Igo was the most prolific author.The Journal of NeuroEngineering and Rehabilitation had the highest publication volume.The United States currently holds a leading position in various aspects,including the overall volume of publications,institutional contributions,author output,and funding support.Keywords such as“deep learning”“physical human-robot interaction”“wearable robotics”“mirror therapy”“telerehabilitation”“soft robotics”“augmented reality”“functional near-infrared spectroscopy,”and“impedance control”highlight the current research hotspots and frontiers.Conclusion:Rehabilitation robotics is a field with vigorous growth,progressively advancing toward intelligent,personalized,accessible,and efficient rehabilitation solutions with substantial future potential.
基金Supported by Science and Technology Project of Huzhou City,Zhejiang Province,No.2023GY33.
文摘BACKGROUND Colorectal cancer(CRC)is the third-most prevalent cancer and the cancer with the second-highest mortality rate worldwide,representing a high public health burden.Deep learning(DL)offers advantages in the diagnosis,identification,localization,classification and prognosis of CRC patients.However,few bibliometric analyses of research hotspots and trends in the field have been performed.AIM To use bibliometric approaches to analyze and visualize the current research state and development trend of DL in CRC as well as to anticipate future research directions and hotspots.METHODS Datasets were retrieved from the Web of Science Core Collection for the period January 2011 to December 2023.Scimago Graphica(1.0.45),VOSviewer(1.6.20)and CiteSpace(6.3.1)were used to analyze and visualize the nation,institution,journal,author,reference and keyword indicators.Origin(2022)was utilized for plotting,and Excel(2021)was used to construct the tables.RESULTS A total of 1275 publications in 538 journals from 74 countries and 2267 institutions were collected.The number of annual publications has increased over time.China(371,29.1%),the United States(265,20.8%)and Japan(155,12.2%)contributed significantly to the number of articles published,accounting for 62.1%of the total publications.The United States had the strongest ties to other nations.Sun Yat-sen University in China had the highest number of publications(32).The journal with the most publications was Scientific Reports(34,Q2),whereas Gastrointestinal Endoscopy had the most co-citations(1053,Q1).Kather JN,was the author with the most articles(12)and co-citations(287).The most frequently cited reference was Deep Residual Learning for Image Recognition.Keywords were divided into six clusters,with“colorectal cancer”(12.34)having the highest outbreak intensity.CONCLUSION This study highlights the current status and most active directions of the use of DL in CRC.This approach has important applications in the identification,diagnosis,localization,classification and prognosis of the disease and will remain a central focus in the future.
基金supported by the National Natural Science Foundation of China(Grant Nos.61773091 and 62476045)the LiaoNing Revitalization Talents Program(Grant No.XLYC1807106)the Program for the Outstanding Innovative Teams of Higher Learning Institutions of Liaoning(Grant No.LR2016070).
文摘Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhibit significant limitations in representing attributes of complex networks at various scales,particularly failing to provide advanced visual representations of specific nodes and edges,community affiliation attribution,and global scalability.These limitations substantially impede the intuitive analysis and interpretation of complex network patterns through visual representation.To address these limitations,we propose SFFSlib,a multi-scale network visualization framework incorporating novel methods to highlight attribute representation in diverse network scenarios and optimize structural feature visualization.Notably,we have enhanced the visualization of pivotal details at different scales across diverse network scenarios.The visualization algorithms proposed within SFFSlib were applied to real-world datasets and benchmarked against conventional layout algorithms.The experimental results reveal that SFFSlib significantly enhances the clarity of visualizations across different scales,offering a practical solution for the advancement of network attribute representation and the overall enhancement of visualization quality.
基金financially supported by the National Natural Science Foundation of China(No.U20B6003)the China Scholarship Council(No.202306440015)a project of the China Petroleum&Chemical Corporation(No.P22174)。
文摘The hybrid CO_(2) thermal technique has achieved considerable success globally in extracting residual heavy oil from reserves following a long-term steam stimulation process.Using microscopic visualization experiments and molecular dynamics(MD)simulations,this study investigates the microscopic enhanced oil recovery(EOR)mechanisms underlying residual oil removal using hybrid CO_(2) thermal systems.Based on the experimental models for the occurrence of heavy oil,this study evaluates the performance of hybrid CO_(2) thermal systems under various conditions using MD simulations.The results demonstrate that introducing CO_(2) molecules into heavy oil can effectively penetrate and decompose dense aggregates that are originally formed on hydrophobic surfaces.A stable miscible hybrid CO_(2) thermal system,with a high effective distribution ratio of CO_(2),proficiently reduces the interaction energies between heavy oil and rock surfaces,as well as within heavy oil.A visualization analysis of the interactions reveals that strong van der Waals(vdW)attractions occur between CO_(2) and heavy oil molecules,effectively promoting the decomposition and swelling of heavy oil.This unlocks the residual oil on the hydrophobic surfaces.Considering the impacts of temperature and CO_(2) concentration,an optimal gas-to-steam injection ratio(here,the CO_(2):steam ratio)ranging between 1:6 and 1:9 is recommended.This study examines the microscopic mechanisms underlying the hybrid CO_(2) thermal technique at a molecular scale,providing a significant theoretical guide for its expanded application in EOR.
基金the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant(No.20172005)。
文摘Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of surgical failure.Therefore,it is necessary to design a visualization system for closed thoracic drainage.Augmented reality(AR)technology can assist in visualizing the internal anatomical structure and determining the insertion point on the body surface.The structure of the currently used steel-needle-guided chest tube was modified by integrating it with an ultrafine diameter camera to provide real-time visualization of the puncture process.After simulation experiments,the overall registration error of the AR method was measured to be within(3.59±0.53)mm,indicating its potential for clinical application.The ultrafine diameter camera module and improved steel-needle-guided chest tube can timely reflect the position of the needle tip in the human body.A comparative experiment showed that video guidance could improve the safety of the puncture process compared to the traditional method.Finally,a qualitative evaluation of the usability of the system was conducted through a questionnaire.This system facilitates the visualization of closed thoracic drainage puncture procedure and pro-vides an implementation scheme to enhance the accuracy and safety of the operative step,which is conducive to reducing the learning curve and improving the proficiency of the doctors.
基金supported by the National Natural Science Foundation of China(Grant Nos.52404155 and 52304111)State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining&Technology,Beijing(Grant No.XD2024006).
文摘Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately controlling the blasting energy and achieving the directional fracture of a rock mass have become common problems in the field.A two-dimensional blasting(2D blasting)technique was proposed that utilizes the characteristic that the tensile strength of a rock mass is significantly lower than its compressive strength.After blasting,only a 2D crack surface is generated along the predetermined direction,eliminating the damage to the reserved rock mass caused by conventional blasting.However,the interior of a natural rock mass is a"black box",and the process of crack propagation is difficult to capture,resulting in an unclear 2D blasting mechanism.To this end,a single-hole polymethyl methacrylate(PMMA)test piece was used to conduct a 2D blasting experiment with the help of a high-speed camera to capture the dynamic crack propagation process and the digital image correlation(DIC)method to analyze the evolution law of surface strain on the test piece.On this basis,a three-dimensional(3D)finite element model was established based on the progressive failure theory to simulate the stress,strain,damage,and displacement evolution process of the model under 2D blasting.The simulation results were consistent with the experimental results.The research results reveal the 2D blasting mechanism and provide theoretical support for the application of 2D blasting technology in the field of rock excavation.
基金Supported by the National Natural Science Foundation of China(51274136 51704190)
文摘A new visualization method for studying the damage to gel structure caused by high salinity ions is explored by using the characteristics of suppression image signal of Mn^(2+) and nuclear magnetic resonance(NMR) imaging technique. The diffusion and distribution characteristics of Mn^(2+) in porous media-gel system were studied based on manganese chloride static diffusion and gel flooding experiments, and the gel's nuclear magnetic image and displacement pressure were tested. The results show that the diffusion of Mn^(2+)conforms to the Fick diffusion law in porous media-gel system, and the diffusion speed of Mn^(2+) increases and the area of gel image decreases gradually with the increase of concentration, and the image of gel decreases faster and the pressure drop of water drive is larger in flooding experiment of manganese chloride with higher concentration. Reaction-diffusion model with the reaction of Mn^(2+) with gel was established to study the concentration distribution characteristics of Mn^(2+). The model is validated by comparing the results with magnetic resonance imaging(MRI) experiments and the diffusion coefficient of Mn^(2+) equals 1.6 mm^2/h, and the minimum concentration of Mn^(2+) to impact gel NMR image signals is 2.5 g/L. The above results show that the diffusion of Mn^(2+) into the gel in the rock core inhibits the imaging signal of the gel and damages its strength, and the greater the concentration is, the greater the influence. Increase of adsorption amount of gel and reaction rate, reduction of diffusion time, and addition of ion adsorption isolator all can reduce the impact of Mn^(2+) on the gel.
文摘In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.
文摘Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginners to grasp the intricate composition rules of formulas.To address this gap,we introduce Formula-S,a situated visualization method for TCM formula learning in augmented reality(AR)and evaluate its performance.This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization.Methods Formula-S is an interactive AR tool designed for TCM formula learning,featuring three modes(3D,Web,and Table).The dataset included TCM formulas and herb properties extracted from authoritative references,including textbook and the SymMap database.In Formula-S,the hierarchical visualization of the formulas as herbal medicine compositions,is linked to the multidimensional herb attribute visualization and embedded in the real world,where real herb samples are presented.To evaluate its effectiveness,a controlled study(n=30)was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification,formula composition,and recognition.In the study,participants interacted with the AR tool through HoloLens 2.Data were collected on both task performance(accuracy and response time)and user experience,with a focus on task efficiency,accuracy,and user preference across the different learning modes.Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks.Regarding user experience,our new approach demonstrated the highest system usability and lowest task load,effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency.Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment,suggesting this approach offers usability advantages for TCM education.Conclusions The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods.Additionally,it provides superior contextual understanding of TCM formulas,making it a promising new solution for TCM learning.
文摘In this article, we present a three-dimensional visualization technique that has been developed in order to establish an interactive immersive environment to visualize the particles in granular materials and dislocations in crystals. Simple elementary objects often exhibit complex collective behavior. Understanding of such behaviors and developments of coarse-scale theories, often requires insight into collective behavior that can only be obtained through immersive visualization. By displaying the computational results in a virtual environment with three-dimensional perception, one can immerse inside the model and analyze the intricate and very complex behavior of individual particles and dislocations. We built the stereographic images of the models using OpenGL rendering technique and then combine with the Virtual Reality technology in order to immerse in the three-dimensional model. A head mounted display has been used to allow the user to immerse inside the models and a flock of birds tracking device that allows the movements around and within the immersive environment.
文摘In this paper, a method to initiate, develop and visualize an abstract syntax tree (AST) in C++ source code is presented. The approach is in chronological order starting with collection of program codes as a string and split into individual characters using regular expression. This will be followed by separating the token grammar using best first search (BFS) algorithm to determine node having lowest value, lastly followed by graph presentation of intermediate representation achieved with the help of graph visualization software (GraphViz) while former is implemented using python programming language version 3. The efficacy of our approach is used in analyzing C++ code and yielded a satisfactory result.
文摘Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in power systems, especially in Smart Grid are still in infancy stage. Besides, while there were a lot of researches working on visualizing data in transmission power system, the study on displaying distribution power system data was limited. Therefore, in this paper, author proposed some techniques to visualize the Smart Grid data at distribution. They are classified in three categories, which are low dimensional techniques, multivariate high dimensional techniques and Geographical Information System (GIS) techniques.
文摘In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.
基金supported by the National Key Research and Development Program(2022YFB3805800)National Natural Science Foundation of China(52473307,22208178,62301290)+9 种基金Taishan Scholar Program of Shandong Province in China(tsqn202211116)Shandong Provincial Universities Youth Innovation Technology Plan Team(2023KJ223)Natural Science Foundation of Shandong Province of China(ZR2023YQ037,ZR2020QE074,ZR2023QE043,ZR2022QE174)Shandong Province Science and Technology Small and Medium sized Enterprise Innovation Ability Enhancement Project(2023TSGC0344,2023TSGC1006)Natural Science Foundation of Qingdao(23-2-1-249-zyyd-jch,24-4-4-zrjj-56-jch)Anhui Province Postdoctoral Researcher Research Activity Funding Project(2023B706)Qingdao Key Technology Research and Industrialization Demonstration Projects(23-1-7-zdfn-2-hz)Qingdao Shinan District Science and Technology Plan Project(2022-3-005-DZ)Suqian Key Research and Development Plan(H202310)Jinan City-School Integration Development Strategy Project for the Year 2023 under Grant(JNSX2023088).
文摘Rehabilitation training is believed to be an effectual strategy that canreduce the risk of dysfunction caused by spasticity.However,achieving visualizationrehabilitation training for patients remains clinically challenging.Herein,wepropose visual rehabilitation training system including iontronic meta-fabrics withskin-friendly and large matrix features,as well as high-resolution image modules fordistribution of human muscle tension.Attributed to the dynamic connection and dissociationof the meta-fabric,the fabric exhibits outstanding tactile sensing properties,such as wide tactile sensing range(0~300 kPa)and high-resolution tactile perception(50 Pa or 0.058%).Meanwhile,thanks to the differential capillary effect,the meta-fabric exhibits a“hitting three birds with one stone”property(dryness wearing experience,long working time and cooling sensing).Based on this,the fabrics can be integrated with garmentsand advanced data analysis systems to manufacture a series of large matrix structure(40×40,1600 sensing units)training devices.Significantly,the tunability of piezo-ionic dynamics of the meta-fabric and the programmability of high-resolution imaging modules allowthis visualization training strategy extendable to various common disease monitoring.Therefore,we believe that our study overcomes theconstraint of standard spasticity rehabilitation training devices in terms of visual display and paves the way for future smart healthcare.
