At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, i...At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, incomplete last-kilometer implementation for translating skills into practice, and inadequate incentive mechanisms. As a novel educational form deeply integrating digital information technology with teaching and learning, distance open education provides multi-directional empowerment for enhancing village cadres digital literacy. This is achieved through open learning methods, the application of modern digital technologies, tailored learning programs, and the establishment of "overpass bridges" for translating learning outcomes into practice. Based on this, it is essential to further streamline the pathways for educating and cultivating village cadres, vigorously promote the digitalization of teaching, practice, and support services, develop systematic and localized digital education resources, and actively explore and establish a complementary credit bank system for their digital literacy cultivation.展开更多
Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric ana...Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.展开更多
With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systemat...Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systematic literature review examines the status, enabling technologies, case studies, and frameworks for DT applications in railway systems with 91 selected papers from Scopus, Web of Science, IEEE, and the Snowballing Technique. The review focuses on four primary subsystems: tracks, civil structures, vehicles, and overhead contact line structures. Key findings reveal that DT has successfully optimized maintenance strategies, improved operational efficiency, and enhanced system safety. Internet of Things (IoT) devices, Artificial Intelligence (AI), machine learning, and cloud computing are critical in implementing DT models. However, challenges like data integration, high implementation costs, and cybersecurity risks remain, necessitating the discussed implications. Future research should focus on improving data interoperability, reducing costs through scalable cloud-based solutions, and addressing cybersecurity vulnerabilities. DT technology has the potential to revolutionize railway infrastructure management, ensuring greater efficiency, safety, and sustainability.展开更多
Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and...Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and diversity of auscultation,along with variations in devices,analytical methods,and applications,bring challenges to its standardization and deeper application.This review presents the advancements in auscultation equipment and systems,auscultation characteristic parameters,and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years,while also exploring the progress and challenges of current digital research of auscultation.This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data,the incorporation of advanced artificial intelligence(AI)auscultation analysis methods,and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes,so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes.展开更多
This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as ru...This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.展开更多
In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This s...In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This system restores the essential characteristics of currency while providing auxiliary services related to the formation,circulation,storage,application,and promotion of digital currency.Compared to traditional currency management technologies,big data analysis technology,which is primarily embedded in digital currency systems,enables the rapid acquisition of information.This facilitates the identification of standard associations within currency data and provides technical support for the operational framework of digital currency.展开更多
To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase n...To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synth...[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synthesized based on the conserved sequence of the heat-resistant nuclease gene nuc of S.aureus.cdPCR was employed to detect S.aureus,and the sensitivity of this technique was systematically assessed in samples exhibiting low levels of contamination.[Results]cdPCR demonstrated precise quantification when the initial concentration of the sample enrichment solution was equal to or greater than 50 CFU/mL.The detection dynamic range extended across at least five orders of magnitude,with a minimum DNA detection limit of 0.2304 pg/μL.In artificially contaminated cheese samples,the method s lower limit of quantification for detecting S.aureus was 8×10^(2) CFU/g.Regression analysis demonstrated that the gene copy number concentration measured by cdPCR exhibited a strong linear correlation with bacterial contamination concentration across a broad range.[Conclusions]The cdPCR method developed in this study demonstrates high sensitivity and robust quantitative capabilities,offering a reliable technical approach for the precise detection of low-level S.aureus contamination in dairy products.展开更多
Digital twin technology,that creates virtual replicas of physical entities using real-time data and simulation models,has emerged as a transformative innovation across multiple healthcare domains.Its application in ph...Digital twin technology,that creates virtual replicas of physical entities using real-time data and simulation models,has emerged as a transformative innovation across multiple healthcare domains.Its application in physiotherapy and rehabilitation represents a paradigm shift from traditional therapeutic approaches to personalized data-driven interventions that optimize patient outcomes.This narrative review examines the current applications,benefits,challenges,and future prospects of digital twin technology in physiotherapy and rehabilitation,providing a comprehensive analysis of the manner in which this technology is reshaping clinical practice and patient care.A narrative review approach was employed,systematically searching PubMed,IEEE Xplore,Scopus,and Web of Science databases.Studies describing digital twin applications,development methodologies,clinical implementations,and theoretical frameworks in physiotherapy and rehabilitation contexts were included.Digital twin technology demonstrates significant potential in personalizing rehabilitation programs,enabling real-time monitoring of patient progress,predicting treatment outcomes,and facilitating remote therapeutic interventions.Current applications span musculoskeletal rehabilitation,neurological recovery,post surgical care,and sports injury management.Key benefits include enhanced treatment precision,improved patient engagement,reduced healthcare costs,and accelerated recovery times.However,implementation faces challenges including technological complexity,data privacy concerns,interoperability issues,and the need for substantial infrastructure investment.Digital twin technology represents a promising frontier in physiotherapy and rehabilitation,offering unprecedented opportunities for personalized,efficient,and effective patient care.Successful integration requires addressing the current limitations while fostering interdisciplinary collaboration between clinicians,engineers,and data scientists.展开更多
In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial...In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.展开更多
Objective:To systematically sort out the application forms and effects of digital health intervention technologies in oral health management,and provide references for the digital development of stomatology.Methods:By...Objective:To systematically sort out the application forms and effects of digital health intervention technologies in oral health management,and provide references for the digital development of stomatology.Methods:By reviewing relevant domestic and foreign studies and clinical practices,this paper summarizes and analyzes the main application forms of digital health interventions,including digital health education,intelligent detection equipment,telemedicine platforms,oral health big data platforms,and school-hospital collaborative screening robots.Results:Studies have shown that digital health interventions can effectively improve the public’s oral health knowledge level,optimize personal health behaviors,enhance clinical diagnosis efficiency,reduce overall medical costs,and promote the innovation and upgrading of oral health management models.Conclusion:Digital health intervention represents an inevitable trend in the future development of stomatology.In the future,it is still necessary to improve data security and privacy protection,technology adaptability and popularity,as well as relevant policies and norms,to give full play to its potential value.展开更多
This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural...This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”展开更多
Background:Intrinsic capacity reflects the overall health status of older adults and decline in intrinsic abilities can lead to adverse health outcomes.However,empirical studies examining the association between digit...Background:Intrinsic capacity reflects the overall health status of older adults and decline in intrinsic abilities can lead to adverse health outcomes.However,empirical studies examining the association between digital health literacy,health-promoting lifestyles and intrinsic capacity are scarce.Methods:A cross-sectional study was conducted.Using convenience sampling method,371 older adults were recruited from communities.Multidimensional intrinsic capacity,digital health literacy,health promoting lifestyle and sociodemographic information were measured.Results:The intrinsic capacity of older adults scored 3.75±1.10.The prevalences of declined cognitive capacity,psychological capacity,sensory capacity,vitality,and locomotor capacity were 13.7%,24.3%,19.1%,14.8%,53.1%,respectively.The multiple regression analysis revealed that age(β=−0.253),only living with children and/or grandchildren(β=0.249),current working status(β=−0.132),number of chronic diseases(β=−0.149),frequency of Internet usage(β=0.193),the domain of ability to acquire and evaluate digital health information(β=0.197)in digital health literacy,and the domain of nutrition(β=0.171)in health-promoting lifestyle were the significant factors influencing intrinsic capacity,explaining 27.1%of the variance.Conclusion:Digital health literacy and health-promoting lifestyle have a significant impact on intrinsic capacity.Enhancing digital health literacy and advocating a health-promoting lifestyle are critical to promoting intrinsic capacity for community-dwelling older adults.展开更多
Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that...Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that reflect systemic health(e.g.,glucose,cortisol,and inflammatory markers)[1],offers the advantage of non-invasive sampling.Its superior environmental stability and strong connection to key physiological processes make it an ideal candidate in the field of digital medicine,serving as a natural gateway to personalized health monitoring.Therefore,the oral cavity represents not only a convenient sampling site but also a strategic interface for realizing the vision of continuous,personalized digital health monitoring.展开更多
Objective:To explore the application effect of digital intraoral scanning impression technique in oral implant restoration for periodontitis patients and analyze its impact on patients’Visual Analogue Scale(VAS)score...Objective:To explore the application effect of digital intraoral scanning impression technique in oral implant restoration for periodontitis patients and analyze its impact on patients’Visual Analogue Scale(VAS)scores.Methods:A total of 80 periodontitis patients who received implant restoration in our hospital from May 2023 to May 2025 were selected as research subjects.They were randomly divided into an observation group and a control group using a random number table method,with 40 cases in each group.The observation group used the digital intraoral scanning impression technique to obtain impressions,while the control group used the traditional silicone rubber impression technique.The impression-taking time,the number of prostheses try-ins,implant survival rate,periodontal health indicators(probing depth,gingival index,bleeding index),and VAS scores(pain during treatment and comfort after restoration)were compared between the two groups.Results:The observation group was superior to the control group in terms of impression-taking time,the number of prostheses try-ins,and implant survival rate(p<0.05).Six months after restoration,the improvement in periodontal health indicators in the observation group was significantly better than that in the control group(p<0.05).In addition,the pain VAS score of the observation group during treatment was lower than that of the control group,and the comfort VAS score after restoration was higher than that of the control group(p<0.05).Conclusion:Digital intraoral scanning impression technology can effectively enhance the efficiency and success rate of implant restoration in periodontitis patients,improve periodontal health,alleviate patients’discomfort during treatment,and increase post-restoration comfort,demonstrating high clinical application value.展开更多
The integration of digital twin(DT)technology with microseismic(MS)monitoring for evaluating the dynamic response of high-arch dams remains under-explored.This paper investigates the application of MS monitoring on th...The integration of digital twin(DT)technology with microseismic(MS)monitoring for evaluating the dynamic response of high-arch dams remains under-explored.This paper investigates the application of MS monitoring on the Dagangshan high-arch dam during its normal water storage operating period to assess potential damage.The study analyzes the MS characteristics of the dam during the Luding earthquake(Ms=6.8).A framework for constructing a damage driven DT model of a high-arch dam is proposed.The DT model is capable of self-updating its mechanical parameters based on MS data.Seismic response calculations are conducted utilizing cloud computing,allowing for the direct presentation of results within the DT model.The results indicate a high-risk area of the Dagangshan arch dam,characterized by significantMS deformation,primarily centered on the arch crown beam.This zone encompasses dam sections Nos.5-6,10-11,13-16,and 19-20,all located above 1030 m elevation.Under seismic loading,the arch dam exhibits a back-and-forth movement along the river,ultimately reaching a stable state.Following the earthquake,the stress state of the dam does not experience substantial changes.The average relative error between numerical results and measured peak ground acceleration values is 17%when considering the cumulative effect of damage,compared to 36%when neglecting this effect.This study presents a more reliable approach for assessing the state of dams.展开更多
The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,...The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.展开更多
When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical ...When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical degradation of low-dimensional chaotic maps. This paper presents a novel method to construct high-dimensional digital chaotic systems in the domain of finite computing precision. The model is proposed by coupling a high-dimensional digital system with a continuous chaotic system. A rigorous proof is given that the controlled digital system is chaotic in the sense of Devaney's definition of chaos. Numerical experimental results for different high-dimensional digital systems indicate that the proposed method can overcome the degradation problem and construct high-dimensional digital chaos with complicated dynamical properties. Based on the construction method, a kind of pseudorandom number generator (PRNG) is also proposed as an application.展开更多
基金Supported by Science Research Fund Project of Yunnan Provincial Department of Education-Research on the Pathways for Distance Open Education to Empower the Enhancement of Digital Literacy and Skills of Rural"Leading Geese"in Ethnic Areas(2023J0792)The Ideological and Political Education Reform Project of Yunnan Province in 2022-Exploration and Practice of Integrating Ideological and Political Education into the Training Mode of"Leading Goose"Talents for Rural Revitalization in the Course of Agricultural and Forestry Economics and Management in Open Education.
文摘At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, incomplete last-kilometer implementation for translating skills into practice, and inadequate incentive mechanisms. As a novel educational form deeply integrating digital information technology with teaching and learning, distance open education provides multi-directional empowerment for enhancing village cadres digital literacy. This is achieved through open learning methods, the application of modern digital technologies, tailored learning programs, and the establishment of "overpass bridges" for translating learning outcomes into practice. Based on this, it is essential to further streamline the pathways for educating and cultivating village cadres, vigorously promote the digitalization of teaching, practice, and support services, develop systematic and localized digital education resources, and actively explore and establish a complementary credit bank system for their digital literacy cultivation.
基金supported by grants for development of new faculty staff,Ratchadaphiseksomphot Fund,Chulalongkorn University,Thailand.
文摘Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
文摘Digital Twin (DT) technology is revolutionizing the railway sector by providing a virtual replica of physical systems, enabling real-time monitoring, predictive maintenance, and enhanced decision-making. This systematic literature review examines the status, enabling technologies, case studies, and frameworks for DT applications in railway systems with 91 selected papers from Scopus, Web of Science, IEEE, and the Snowballing Technique. The review focuses on four primary subsystems: tracks, civil structures, vehicles, and overhead contact line structures. Key findings reveal that DT has successfully optimized maintenance strategies, improved operational efficiency, and enhanced system safety. Internet of Things (IoT) devices, Artificial Intelligence (AI), machine learning, and cloud computing are critical in implementing DT models. However, challenges like data integration, high implementation costs, and cybersecurity risks remain, necessitating the discussed implications. Future research should focus on improving data interoperability, reducing costs through scalable cloud-based solutions, and addressing cybersecurity vulnerabilities. DT technology has the potential to revolutionize railway infrastructure management, ensuring greater efficiency, safety, and sustainability.
基金National Natural Science Foundation of China(82104738)National Administration of Traditional Chinese Medicine(TCM)High-level Key Discipline Construction Project:TCM Diagnostics(ZYYZDXK-2023069).
文摘Traditional Chinese medicine(TCM)auscultation has a long history,and with advancements in equipment and analytical methods,the quantitative analysis of auscultation parameters has determined.However,the complexity and diversity of auscultation,along with variations in devices,analytical methods,and applications,bring challenges to its standardization and deeper application.This review presents the advancements in auscultation equipment and systems,auscultation characteristic parameters,and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years,while also exploring the progress and challenges of current digital research of auscultation.This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data,the incorporation of advanced artificial intelligence(AI)auscultation analysis methods,and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes,so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes.
文摘This research aims to address the challenges of fault detection and isolation(FDI)in digital grids,focusing on improving the reliability and stability of power systems.Traditional fault detection techniques,such as rule-based fuzzy systems and conventional FDI methods,often struggle with the dynamic nature of modern grids,resulting in delays and inaccuracies in fault classification.To overcome these limitations,this study introduces a Hybrid NeuroFuzzy Fault Detection Model that combines the adaptive learning capabilities of neural networks with the reasoning strength of fuzzy logic.The model’s performance was evaluated through extensive simulations on the IEEE 33-bus test system,considering various fault scenarios,including line-to-ground faults(LGF),three-phase short circuits(3PSC),and harmonic distortions(HD).The quantitative results show that the model achieves 97.2%accuracy,a false negative rate(FNR)of 1.9%,and a false positive rate(FPR)of 2.3%,demonstrating its high precision in fault diagnosis.The qualitative analysis further highlights the model’s adaptability and its potential for seamless integration into smart grids,micro grids,and renewable energy systems.By dynamically refining fuzzy inference rules,the model enhances fault detection efficiency without compromising computational feasibility.These findings contribute to the development of more resilient and adaptive fault management systems,paving the way for advanced smart grid technologies.
文摘In the contemporary era,characterized by the Internet and digitalization as fundamental features,the operation and application of digital currency have gradually developed into a comprehensive structural system.This system restores the essential characteristics of currency while providing auxiliary services related to the formation,circulation,storage,application,and promotion of digital currency.Compared to traditional currency management technologies,big data analysis technology,which is primarily embedded in digital currency systems,enables the rapid acquisition of information.This facilitates the identification of standard associations within currency data and provides technical support for the operational framework of digital currency.
基金supported in part by National Natural Science Foundation of China(No.62271080)in part by Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2022ZT06)in part by BUPT Excellent Ph.D Students Foundation(No.CX2022102).
文摘To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金Supported by Science and Technology Program of Inner Mongolia Autonomous Region"Research and Demonstration of Novel Molecular Biological Identification Technology for Multiple Source Components in Milk and Dairy Products"(2025YFSH0029).
文摘[Objectives]This study aimed to evaluate the detection sensitivity of Staphylococcus aureus in dairy products utilizing the chip digital PCR(cdPCR)technique.[Methods]Specific primers and probes were designed and synthesized based on the conserved sequence of the heat-resistant nuclease gene nuc of S.aureus.cdPCR was employed to detect S.aureus,and the sensitivity of this technique was systematically assessed in samples exhibiting low levels of contamination.[Results]cdPCR demonstrated precise quantification when the initial concentration of the sample enrichment solution was equal to or greater than 50 CFU/mL.The detection dynamic range extended across at least five orders of magnitude,with a minimum DNA detection limit of 0.2304 pg/μL.In artificially contaminated cheese samples,the method s lower limit of quantification for detecting S.aureus was 8×10^(2) CFU/g.Regression analysis demonstrated that the gene copy number concentration measured by cdPCR exhibited a strong linear correlation with bacterial contamination concentration across a broad range.[Conclusions]The cdPCR method developed in this study demonstrates high sensitivity and robust quantitative capabilities,offering a reliable technical approach for the precise detection of low-level S.aureus contamination in dairy products.
文摘Digital twin technology,that creates virtual replicas of physical entities using real-time data and simulation models,has emerged as a transformative innovation across multiple healthcare domains.Its application in physiotherapy and rehabilitation represents a paradigm shift from traditional therapeutic approaches to personalized data-driven interventions that optimize patient outcomes.This narrative review examines the current applications,benefits,challenges,and future prospects of digital twin technology in physiotherapy and rehabilitation,providing a comprehensive analysis of the manner in which this technology is reshaping clinical practice and patient care.A narrative review approach was employed,systematically searching PubMed,IEEE Xplore,Scopus,and Web of Science databases.Studies describing digital twin applications,development methodologies,clinical implementations,and theoretical frameworks in physiotherapy and rehabilitation contexts were included.Digital twin technology demonstrates significant potential in personalizing rehabilitation programs,enabling real-time monitoring of patient progress,predicting treatment outcomes,and facilitating remote therapeutic interventions.Current applications span musculoskeletal rehabilitation,neurological recovery,post surgical care,and sports injury management.Key benefits include enhanced treatment precision,improved patient engagement,reduced healthcare costs,and accelerated recovery times.However,implementation faces challenges including technological complexity,data privacy concerns,interoperability issues,and the need for substantial infrastructure investment.Digital twin technology represents a promising frontier in physiotherapy and rehabilitation,offering unprecedented opportunities for personalized,efficient,and effective patient care.Successful integration requires addressing the current limitations while fostering interdisciplinary collaboration between clinicians,engineers,and data scientists.
基金National Social Science Fund of China(18KXS009)the Sichuan Provincial Soft Science Program(22JDR0261)the Sichuan University“From 0 to 1”Innovation Research Program(2021CXC10)。
文摘In the context of the revolution in new technologies,a key question is whether the rapid growth of the digital economy,driven by digital technologies,has improved regional innovation performance.Using inter-provincial panel data from China(2012–2022)and adopting a business environment perspective,this study applies a Panel Extended Regression Model(PERM),a Panel Simultaneous Equation Model(PSEM),and a Tobit-IV model to analyze how the development of the digital economy influences regional innovation.The results reveal a pronounced U-shaped relationship between the digital economy and the regional innovation performance at the provincial level in China,with the business environment serving as a significant mediator in this relationship.Moreover,regional innovation performance in China exhibits a“ratchet effect,”with the impact of the digital economy varying markedly across regions.While the eastern and western regions have entered an upward phase,whereby the digital economy boosts innovation,the central region displays a weaker effect.Further analysis indicates that the synergy between the business environment and the digital economy in driving innovation remains suboptimal.These findings were supported by robust checks.This study offers theoretical insights and empirical evidence that support the coordinated development of digital government and the digital factor market,as well as business environment reforms that are in alignment with the innovation demands of the digital era.
文摘Objective:To systematically sort out the application forms and effects of digital health intervention technologies in oral health management,and provide references for the digital development of stomatology.Methods:By reviewing relevant domestic and foreign studies and clinical practices,this paper summarizes and analyzes the main application forms of digital health interventions,including digital health education,intelligent detection equipment,telemedicine platforms,oral health big data platforms,and school-hospital collaborative screening robots.Results:Studies have shown that digital health interventions can effectively improve the public’s oral health knowledge level,optimize personal health behaviors,enhance clinical diagnosis efficiency,reduce overall medical costs,and promote the innovation and upgrading of oral health management models.Conclusion:Digital health intervention represents an inevitable trend in the future development of stomatology.In the future,it is still necessary to improve data security and privacy protection,technology adaptability and popularity,as well as relevant policies and norms,to give full play to its potential value.
基金Youth project under the National Social Science Foundation of China(15CJY054)key project in Philosophy and Social Sciences funded by the Chongqing Municipal Education Commission(22SKGH091)。
文摘This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”
基金funded by the College Students’Innovation and Entrepreneurship Program(X2024110650385).
文摘Background:Intrinsic capacity reflects the overall health status of older adults and decline in intrinsic abilities can lead to adverse health outcomes.However,empirical studies examining the association between digital health literacy,health-promoting lifestyles and intrinsic capacity are scarce.Methods:A cross-sectional study was conducted.Using convenience sampling method,371 older adults were recruited from communities.Multidimensional intrinsic capacity,digital health literacy,health promoting lifestyle and sociodemographic information were measured.Results:The intrinsic capacity of older adults scored 3.75±1.10.The prevalences of declined cognitive capacity,psychological capacity,sensory capacity,vitality,and locomotor capacity were 13.7%,24.3%,19.1%,14.8%,53.1%,respectively.The multiple regression analysis revealed that age(β=−0.253),only living with children and/or grandchildren(β=0.249),current working status(β=−0.132),number of chronic diseases(β=−0.149),frequency of Internet usage(β=0.193),the domain of ability to acquire and evaluate digital health information(β=0.197)in digital health literacy,and the domain of nutrition(β=0.171)in health-promoting lifestyle were the significant factors influencing intrinsic capacity,explaining 27.1%of the variance.Conclusion:Digital health literacy and health-promoting lifestyle have a significant impact on intrinsic capacity.Enhancing digital health literacy and advocating a health-promoting lifestyle are critical to promoting intrinsic capacity for community-dwelling older adults.
基金support from the Guangdong Basic and Applied Basic Research Foundation(Nos.2021A1515110388,2024A1515011707)Science and Technology Projects in Guangzhou(No.2024A04J5195)Shenzhen Natural Science Foundation(Nos.JCYJ20230807111120043).
文摘Wearable sensors have revolutionized health monitoring by transitioning from clinical diagnostics to continuous,real-time applications in daily life.The oral cavity,rich in saliva containing over 1,000 biomarkers that reflect systemic health(e.g.,glucose,cortisol,and inflammatory markers)[1],offers the advantage of non-invasive sampling.Its superior environmental stability and strong connection to key physiological processes make it an ideal candidate in the field of digital medicine,serving as a natural gateway to personalized health monitoring.Therefore,the oral cavity represents not only a convenient sampling site but also a strategic interface for realizing the vision of continuous,personalized digital health monitoring.
文摘Objective:To explore the application effect of digital intraoral scanning impression technique in oral implant restoration for periodontitis patients and analyze its impact on patients’Visual Analogue Scale(VAS)scores.Methods:A total of 80 periodontitis patients who received implant restoration in our hospital from May 2023 to May 2025 were selected as research subjects.They were randomly divided into an observation group and a control group using a random number table method,with 40 cases in each group.The observation group used the digital intraoral scanning impression technique to obtain impressions,while the control group used the traditional silicone rubber impression technique.The impression-taking time,the number of prostheses try-ins,implant survival rate,periodontal health indicators(probing depth,gingival index,bleeding index),and VAS scores(pain during treatment and comfort after restoration)were compared between the two groups.Results:The observation group was superior to the control group in terms of impression-taking time,the number of prostheses try-ins,and implant survival rate(p<0.05).Six months after restoration,the improvement in periodontal health indicators in the observation group was significantly better than that in the control group(p<0.05).In addition,the pain VAS score of the observation group during treatment was lower than that of the control group,and the comfort VAS score after restoration was higher than that of the control group(p<0.05).Conclusion:Digital intraoral scanning impression technology can effectively enhance the efficiency and success rate of implant restoration in periodontitis patients,improve periodontal health,alleviate patients’discomfort during treatment,and increase post-restoration comfort,demonstrating high clinical application value.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379098 and 42122052)the Liaoning XingLiao Talent Program(Grant No.XLYC2203008).
文摘The integration of digital twin(DT)technology with microseismic(MS)monitoring for evaluating the dynamic response of high-arch dams remains under-explored.This paper investigates the application of MS monitoring on the Dagangshan high-arch dam during its normal water storage operating period to assess potential damage.The study analyzes the MS characteristics of the dam during the Luding earthquake(Ms=6.8).A framework for constructing a damage driven DT model of a high-arch dam is proposed.The DT model is capable of self-updating its mechanical parameters based on MS data.Seismic response calculations are conducted utilizing cloud computing,allowing for the direct presentation of results within the DT model.The results indicate a high-risk area of the Dagangshan arch dam,characterized by significantMS deformation,primarily centered on the arch crown beam.This zone encompasses dam sections Nos.5-6,10-11,13-16,and 19-20,all located above 1030 m elevation.Under seismic loading,the arch dam exhibits a back-and-forth movement along the river,ultimately reaching a stable state.Following the earthquake,the stress state of the dam does not experience substantial changes.The average relative error between numerical results and measured peak ground acceleration values is 17%when considering the cumulative effect of damage,compared to 36%when neglecting this effect.This study presents a more reliable approach for assessing the state of dams.
文摘The food industry is evolving toward intelligence and digitalization,but is faced with challenges such as inconsistent standards and poor system compatibility due to lack of unified technical guidance.GB/T 46511-2025,General technical requirements for food digital factory,the first general technical national standard for food digital factory,was released recently.It bridges the gap in the industry,serving as the technical support and implementation framework for the intelligent and digital transformation of enterprises in the food industry.
基金Project supported by the National Key R&D Program of China(Grant No.2017YFB0802000)the Cryptography Theoretical Research of National Cryptography Development Fund,China(Grant No.MMJJ20170109).
文摘When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical degradation of low-dimensional chaotic maps. This paper presents a novel method to construct high-dimensional digital chaotic systems in the domain of finite computing precision. The model is proposed by coupling a high-dimensional digital system with a continuous chaotic system. A rigorous proof is given that the controlled digital system is chaotic in the sense of Devaney's definition of chaos. Numerical experimental results for different high-dimensional digital systems indicate that the proposed method can overcome the degradation problem and construct high-dimensional digital chaos with complicated dynamical properties. Based on the construction method, a kind of pseudorandom number generator (PRNG) is also proposed as an application.
