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
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
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
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
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
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
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
Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.Th...Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.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
Applying the Public-Private Partnership(PPP)model is indispensable in creating new economic growth points in the public service sector.However,there is still a lack of research on mapping the application of the PPP mo...Applying the Public-Private Partnership(PPP)model is indispensable in creating new economic growth points in the public service sector.However,there is still a lack of research on mapping the application of the PPP model in the new era and context.Therefore,based on reviewing the characteristics and development concepts of the PPP model,this paper uses CiteSpace software to analyze the sample authors,journals,and regions in the Scopus database.This paper aims to explore the current development status,research paradigms,and research gap as well as future trends of the PPP model.The results show that(1)The focus of PPP research has shifted from traditional models such as Build-Operate-Transfer(BOT)and Private Finance Initiatives(PFI)to contemporary themes such as risk management,policy analysis,and project governance.Subsequent research(2014-2018)has emphasized the importance of governance and regulatory frameworks to improve PPP outcomes.(2)The growing academic interest in PPP development in China accounts for 28.78%of the total publications.This surge reflects China's rapid economic growth and highlights the interplay between government regulation and private financing.Key research themes include risk management,performance evaluation,contractual flexibility,and financing mechanisms,particularly concerning the BOT model.(3)Effective risk management,relationship dynamics,and innovative financing strategies are key components of a strong PPP knowledge framework.Collaborative risk sharing and strong relationships between public and private entities are key to project success,and strategic financing partnerships are necessary to cope with the complexity of large infrastructure projects.展开更多
Objective:To analyze the current status,hotspot and trend of mental health research in patients with chronic kidney disease at home and abroad.Methods:China National Knowledge Infrastructure,WanFang,VIP,China Biology ...Objective:To analyze the current status,hotspot and trend of mental health research in patients with chronic kidney disease at home and abroad.Methods:China National Knowledge Infrastructure,WanFang,VIP,China Biology Medicine database,PubMed,and Web of Science core collection database were used as search sources from January 2004 to December 2024,and CiteSpace software was used for visual analysis and knowledge mapping.Results:A total of 2059 Chinese and 1678 foreign literatures were included.The number of publications showed a fluctuating upward trend,but the collaboration among authors was relatively loose.Negative psychology,such as depression and anxiety,as well as the quality of life of chronic kidney disease patients,were the main research hotspots.Conclusion:In the future,it is necessary to enhance cooperation and communication among researchers,continue to explore the mechanism of mental health,optimize research designs,innovate psychological nursing intervention measures,and focus on improving the psychological resilience and social support levels of patients.展开更多
The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and managem...The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and management tool that integrates digitization and visualization,has demonstrated considerable advantages in enhancing project quality,reducing costs,and improving collaborative efficiency.This study aims to systematically investigate the application and developmental trends of BIM visualization technology within the field of landscape engineering.Through an analysis of technological advancements and industry dynamics over the past decade,it has been observed that BIM visualization technology is intricately linked with green building practices,sustainable construction methods,and the development of smart cities within the context of landscape engineering projects.The technology also possesses significant potential for application in the planning and design of landscape engineering,construction management,and project maintenance.The convenience of visualization enhances the expressive capacity of the design scheme,improves communication efficiency between the involved parties,and mitigates the costs and time inefficiencies associated with design modifications.By drawing on the successful experiences of other industries and integrating them with the unique characteristics of landscape engineering,BIM visualization technology is poised to assume a more significant role within this field.This integration is expected to advance the entire industry towards greater intelligence and informatization,while simultaneously enhancing the efficiency and quality of design,construction,and maintenance processes.展开更多
The advent of the big data era has made data visualization a crucial tool for enhancing the efficiency and insights of data analysis. This theoretical research delves into the current applications and potential future...The advent of the big data era has made data visualization a crucial tool for enhancing the efficiency and insights of data analysis. This theoretical research delves into the current applications and potential future trends of data visualization in big data analysis. The article first systematically reviews the theoretical foundations and technological evolution of data visualization, and thoroughly analyzes the challenges faced by visualization in the big data environment, such as massive data processing, real-time visualization requirements, and multi-dimensional data display. Through extensive literature research, it explores innovative application cases and theoretical models of data visualization in multiple fields including business intelligence, scientific research, and public decision-making. The study reveals that interactive visualization, real-time visualization, and immersive visualization technologies may become the main directions for future development and analyzes the potential of these technologies in enhancing user experience and data comprehension. The paper also delves into the theoretical potential of artificial intelligence technology in enhancing data visualization capabilities, such as automated chart generation, intelligent recommendation of visualization schemes, and adaptive visualization interfaces. The research also focuses on the role of data visualization in promoting interdisciplinary collaboration and data democratization. Finally, the paper proposes theoretical suggestions for promoting data visualization technology innovation and application popularization, including strengthening visualization literacy education, developing standardized visualization frameworks, and promoting open-source sharing of visualization tools. This study provides a comprehensive theoretical perspective for understanding the importance of data visualization in the big data era and its future development directions.展开更多
BACKGROUND Biliary stone disease is a highly prevalent condition and a leading cause of hospitalization worldwide.Hepatolithiasis with associated strictures has high residual and recurrence rates after traditional mul...BACKGROUND Biliary stone disease is a highly prevalent condition and a leading cause of hospitalization worldwide.Hepatolithiasis with associated strictures has high residual and recurrence rates after traditional multisession percutaneous transhepatic cholangioscopic lithotripsy(PTCSL).AIM To study one-step PTCSL using the percutaneous transhepatic one-step biliary fistulation(PTOBF)technique guided by three-dimensional(3D)visualization.METHODS This was a retrospective,single-center study analyzing,140 patients who,between October 2016 and October 2023,underwent one-step PTCSL for hepatolithiasis.The patients were divided into two groups:The 3D-PTOBF group and the PTOBF group.Stone clearance on choledochoscopy,complications,and long-term clearance and recurrence rates were assessed.RESULTS Age,total bilirubin,direct bilirubin,Child-Pugh class,and stone location were similar between the 2 groups,but there was a significant difference in bile duct strictures,with biliary strictures more common in the 3D-PTOBF group(P=0.001).The median follow-up time was 55.0(55.0,512.0)days.The immediate stone clearance ratio(88.6%vs 27.1%,P=0.000)and stricture resolution ratio(97.1%vs 78.6%,P=0.001)in the 3D-PTOBF group were significantly greater than those in the PTOBF group.Postoperative complication(8.6%vs 41.4%,P=0.000)and stone recurrence rates(7.1%vs 38.6%,P=0.000)were significantly lower in the 3D-PTOBF group.CONCLUSION Three-dimensional visualization helps make one-step PTCSL a safe,effective,and promising treatment for patients with complicated primary hepatolithiasis.The perioperative and long-term outcomes are satisfactory for patients with complicated primary hepatolithiasis.This minimally invasive method has the potential to be used as a substitute for hepatobiliary surgery.展开更多
High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of disloc...High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.展开更多
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.
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 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.
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 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.
基金supported by the Central Government’s Guidance Fund for Local Science and Technology Development(2024ZY-CGZY-19)。
文摘Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.
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 following projects:Philosophy and Social Sciences Planning Leading Group of Guangdong Province(Project No.GD21CGL31)Research Projects of Department of Education of Guangdong Province(Project No.2023WCXTD037).
文摘Applying the Public-Private Partnership(PPP)model is indispensable in creating new economic growth points in the public service sector.However,there is still a lack of research on mapping the application of the PPP model in the new era and context.Therefore,based on reviewing the characteristics and development concepts of the PPP model,this paper uses CiteSpace software to analyze the sample authors,journals,and regions in the Scopus database.This paper aims to explore the current development status,research paradigms,and research gap as well as future trends of the PPP model.The results show that(1)The focus of PPP research has shifted from traditional models such as Build-Operate-Transfer(BOT)and Private Finance Initiatives(PFI)to contemporary themes such as risk management,policy analysis,and project governance.Subsequent research(2014-2018)has emphasized the importance of governance and regulatory frameworks to improve PPP outcomes.(2)The growing academic interest in PPP development in China accounts for 28.78%of the total publications.This surge reflects China's rapid economic growth and highlights the interplay between government regulation and private financing.Key research themes include risk management,performance evaluation,contractual flexibility,and financing mechanisms,particularly concerning the BOT model.(3)Effective risk management,relationship dynamics,and innovative financing strategies are key components of a strong PPP knowledge framework.Collaborative risk sharing and strong relationships between public and private entities are key to project success,and strategic financing partnerships are necessary to cope with the complexity of large infrastructure projects.
基金Tianjin Medical Key Discipline Construction Project(Project No.:TJYXZDXK-071C)。
文摘Objective:To analyze the current status,hotspot and trend of mental health research in patients with chronic kidney disease at home and abroad.Methods:China National Knowledge Infrastructure,WanFang,VIP,China Biology Medicine database,PubMed,and Web of Science core collection database were used as search sources from January 2004 to December 2024,and CiteSpace software was used for visual analysis and knowledge mapping.Results:A total of 2059 Chinese and 1678 foreign literatures were included.The number of publications showed a fluctuating upward trend,but the collaboration among authors was relatively loose.Negative psychology,such as depression and anxiety,as well as the quality of life of chronic kidney disease patients,were the main research hotspots.Conclusion:In the future,it is necessary to enhance cooperation and communication among researchers,continue to explore the mechanism of mental health,optimize research designs,innovate psychological nursing intervention measures,and focus on improving the psychological resilience and social support levels of patients.
基金Sponsored by Building Structure Key Laboratory Project of Colleges and Universities in Anhui Province(KLBSZD202105)Key Projects of Scientific Research Programs(Natural Science)of Higher Education Institutions in Anhui Province(2022AH051861)Research Team Program of Anhui Xinhua University(kytd202202).
文摘The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and management tool that integrates digitization and visualization,has demonstrated considerable advantages in enhancing project quality,reducing costs,and improving collaborative efficiency.This study aims to systematically investigate the application and developmental trends of BIM visualization technology within the field of landscape engineering.Through an analysis of technological advancements and industry dynamics over the past decade,it has been observed that BIM visualization technology is intricately linked with green building practices,sustainable construction methods,and the development of smart cities within the context of landscape engineering projects.The technology also possesses significant potential for application in the planning and design of landscape engineering,construction management,and project maintenance.The convenience of visualization enhances the expressive capacity of the design scheme,improves communication efficiency between the involved parties,and mitigates the costs and time inefficiencies associated with design modifications.By drawing on the successful experiences of other industries and integrating them with the unique characteristics of landscape engineering,BIM visualization technology is poised to assume a more significant role within this field.This integration is expected to advance the entire industry towards greater intelligence and informatization,while simultaneously enhancing the efficiency and quality of design,construction,and maintenance processes.
文摘The advent of the big data era has made data visualization a crucial tool for enhancing the efficiency and insights of data analysis. This theoretical research delves into the current applications and potential future trends of data visualization in big data analysis. The article first systematically reviews the theoretical foundations and technological evolution of data visualization, and thoroughly analyzes the challenges faced by visualization in the big data environment, such as massive data processing, real-time visualization requirements, and multi-dimensional data display. Through extensive literature research, it explores innovative application cases and theoretical models of data visualization in multiple fields including business intelligence, scientific research, and public decision-making. The study reveals that interactive visualization, real-time visualization, and immersive visualization technologies may become the main directions for future development and analyzes the potential of these technologies in enhancing user experience and data comprehension. The paper also delves into the theoretical potential of artificial intelligence technology in enhancing data visualization capabilities, such as automated chart generation, intelligent recommendation of visualization schemes, and adaptive visualization interfaces. The research also focuses on the role of data visualization in promoting interdisciplinary collaboration and data democratization. Finally, the paper proposes theoretical suggestions for promoting data visualization technology innovation and application popularization, including strengthening visualization literacy education, developing standardized visualization frameworks, and promoting open-source sharing of visualization tools. This study provides a comprehensive theoretical perspective for understanding the importance of data visualization in the big data era and its future development directions.
基金Supported by The Key Medical Specialty Nurturing Program of Foshan During The 14th Five-Year Plan Period,No.FSPY145205The Medical Research Project of Foshan Health Bureau,No.20230814A010024+1 种基金The Guangzhou Science and Technology Plan Project,No.202102010251the Guangdong Science and Technology Program,No.2017ZC0222.
文摘BACKGROUND Biliary stone disease is a highly prevalent condition and a leading cause of hospitalization worldwide.Hepatolithiasis with associated strictures has high residual and recurrence rates after traditional multisession percutaneous transhepatic cholangioscopic lithotripsy(PTCSL).AIM To study one-step PTCSL using the percutaneous transhepatic one-step biliary fistulation(PTOBF)technique guided by three-dimensional(3D)visualization.METHODS This was a retrospective,single-center study analyzing,140 patients who,between October 2016 and October 2023,underwent one-step PTCSL for hepatolithiasis.The patients were divided into two groups:The 3D-PTOBF group and the PTOBF group.Stone clearance on choledochoscopy,complications,and long-term clearance and recurrence rates were assessed.RESULTS Age,total bilirubin,direct bilirubin,Child-Pugh class,and stone location were similar between the 2 groups,but there was a significant difference in bile duct strictures,with biliary strictures more common in the 3D-PTOBF group(P=0.001).The median follow-up time was 55.0(55.0,512.0)days.The immediate stone clearance ratio(88.6%vs 27.1%,P=0.000)and stricture resolution ratio(97.1%vs 78.6%,P=0.001)in the 3D-PTOBF group were significantly greater than those in the PTOBF group.Postoperative complication(8.6%vs 41.4%,P=0.000)and stone recurrence rates(7.1%vs 38.6%,P=0.000)were significantly lower in the 3D-PTOBF group.CONCLUSION Three-dimensional visualization helps make one-step PTCSL a safe,effective,and promising treatment for patients with complicated primary hepatolithiasis.The perioperative and long-term outcomes are satisfactory for patients with complicated primary hepatolithiasis.This minimally invasive method has the potential to be used as a substitute for hepatobiliary surgery.
基金supported by the National Key Research and Development Project of China(Nos.2022YFB3708200 and 2021YFB3703500)the National Natural Science Foundation of China(Nos.52271089 and 52001023).
文摘High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.
