The presented study analyses the impact of hysteresis on the response of mechanical systems.The main objective is to determine how the hysteretic models influence the system behaviour and if they can be utilised to de...The presented study analyses the impact of hysteresis on the response of mechanical systems.The main objective is to determine how the hysteretic models influence the system behaviour and if they can be utilised to describe a damaged or a faulty system.The hysteretic models are able to describe various types of nonlinear behaviour that can reflect the wear or damage of the system components.The data obtained from these models can possibly serve as a basis for the advanced approaches,such as digital twin modelling and predictive maintenance.All the results presented in this study were obtained in the MATLAB environment.The first part of the study provides a concise review of hysteretic models and compares them under the condition of equal energy dissipation per loading cycle.The models considered include the linear,bilinear,Bouc-Wen,Wang-Wen,and generalised Bouc-Wen models.The second part focuses on the development of a mechanical model and the implementation of the mentioned hysteretic models.The stochastic modelling of the driving forces is carried out using the Kanai-Tajimi differential model.The results show that the hysteretic models noticeably influence the treated model.This is also reflected in the frequency domain.The behaviour of hysteretic systems suggests increased energy dissipation combined with the changes in stiffness of the suspension components.Among the presented models,the asymmetric models can be considered as the most suitable for further modelling of damaged systems.展开更多
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
We present a compact self-interference incoherent digital holography(SIDH)system that incorporates a quarter-waveplate(QWP)-based geometric phase(GP)lens to achieve high-fidelity,full-color holographic imaging under b...We present a compact self-interference incoherent digital holography(SIDH)system that incorporates a quarter-waveplate(QWP)-based geometric phase(GP)lens to achieve high-fidelity,full-color holographic imaging under broadband incoherent illumination.Traditional SIDH systems that utilize half-waveplate(HWP)-based GP lenses are hindered by unavoidable triple-wavefront polarization interference,stemming from chromatic dispersion in phase retardation.This interference introduces color-dependent artifacts in the reconstructed images.In contrast,our QWP-based design inherently suppresses such interference by using the non-diffracted beam as the reference,enabling stable dual-wavefront modulation.This approach produces phase-encoded polarization interference patterns that remain spectrally consistent across the red,green,and blue(RGB)channels.Experimental results demonstrate substantial noise suppression and significantly improved full-color image fidelity,supported by channelspecific noise analysis and structural similarity metrics.The system also preserves a simplified optical configuration without active polarization control,allowing for compact integration and cost-effective fabrication.These advantages position the proposed QWP-GP SIDH architecture as a promising solution for portable,real-time digital holographic 3D imaging,with scalable potential in applications such as augmented reality,optical diagnostics,and spectral holography.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
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
This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeologi...This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeological site of Memphis in Egypt,Chinese-developed digital technology is now creating“annual rings”of memory for a civilisation dating back to the pharaohs.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
Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and ...Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.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
Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,...Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,picture and video information as carriers to encrypt and decrypt the watermark information is realized by integrating and stacking the watermark detection functions on the processor platform of the switching nodes in the off-chain communication network within blockchain systems,using the sliding window mechanism of Loongson 2K to control the smoothness of the digital information,and by multi-thread mechanism of the processor to control the real-time performance of the digital signal transmission.The performance of the least significant bit(LSB)algorithm,discrete cosine transform(DCT)algorithm,and DWT algorithm is analyzed.The performance comparison of LSB algorithm,DCT algorithm,and DWT algorithm under filtering attack,scaling attack,noise attack,cropping attack,and spin attack is simulated respectively.The experimental results show that,filtered attack normalized correlation(NC)coefficient for DWT is 0.95786,for scaled attack is 0.98962,for noise attack is 0.93842,spin attack NC is 0.86823,and clipped attack NC is 0.878814.The DWT algorithm has the small image distortion rate,is more robust to audio and video watermarking against attack effects,and the experimental data are superior to the LSB and DCT algorithms.Using Loongson 2K multi-threading mode to control the real-time data transmission,greatly improves the practicability of DWT algorithm on embedded devices,which can be effectively applied to authenticity verification when media data such as images and audio are uploaded to the blockchain.展开更多
Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively i...Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.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
On October 28,2025,in the bustling diplomatic hub of Kuala Lumpur,a defining moment in Asian economic history quietly and solemnly unfolded when leaders from China and ASEAN member states witnessed the official signin...On October 28,2025,in the bustling diplomatic hub of Kuala Lumpur,a defining moment in Asian economic history quietly and solemnly unfolded when leaders from China and ASEAN member states witnessed the official signing of the protocol to upgrade the China-ASEAN Free Trade Area(CAFTA)to Version 3.0.The ceremony marked the culmination of nearly three years of intense negotiations.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
基金supported by projects KEGA,Nos.002ŽU-4/2023,and 005ŽU-4/2024,and by the project VEGA,No.1/0423/23.
文摘The presented study analyses the impact of hysteresis on the response of mechanical systems.The main objective is to determine how the hysteretic models influence the system behaviour and if they can be utilised to describe a damaged or a faulty system.The hysteretic models are able to describe various types of nonlinear behaviour that can reflect the wear or damage of the system components.The data obtained from these models can possibly serve as a basis for the advanced approaches,such as digital twin modelling and predictive maintenance.All the results presented in this study were obtained in the MATLAB environment.The first part of the study provides a concise review of hysteretic models and compares them under the condition of equal energy dissipation per loading cycle.The models considered include the linear,bilinear,Bouc-Wen,Wang-Wen,and generalised Bouc-Wen models.The second part focuses on the development of a mechanical model and the implementation of the mentioned hysteretic models.The stochastic modelling of the driving forces is carried out using the Kanai-Tajimi differential model.The results show that the hysteretic models noticeably influence the treated model.This is also reflected in the frequency domain.The behaviour of hysteretic systems suggests increased energy dissipation combined with the changes in stiffness of the suspension components.Among the presented models,the asymmetric models can be considered as the most suitable for further modelling of damaged systems.
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 the National Research Foundation(NRF)funded by the Korean government(MSIT)(No.RS-2024-00416272)supported by Electronics and Telecommunications Research Institute(ETRI)grant funded by ICT R&D program of MSIT/IITP[2019-0-00001,Development of Holo-TV Core Technologies for Hologram Media Services].
文摘We present a compact self-interference incoherent digital holography(SIDH)system that incorporates a quarter-waveplate(QWP)-based geometric phase(GP)lens to achieve high-fidelity,full-color holographic imaging under broadband incoherent illumination.Traditional SIDH systems that utilize half-waveplate(HWP)-based GP lenses are hindered by unavoidable triple-wavefront polarization interference,stemming from chromatic dispersion in phase retardation.This interference introduces color-dependent artifacts in the reconstructed images.In contrast,our QWP-based design inherently suppresses such interference by using the non-diffracted beam as the reference,enabling stable dual-wavefront modulation.This approach produces phase-encoded polarization interference patterns that remain spectrally consistent across the red,green,and blue(RGB)channels.Experimental results demonstrate substantial noise suppression and significantly improved full-color image fidelity,supported by channelspecific noise analysis and structural similarity metrics.The system also preserves a simplified optical configuration without active polarization control,allowing for compact integration and cost-effective fabrication.These advantages position the proposed QWP-GP SIDH architecture as a promising solution for portable,real-time digital holographic 3D imaging,with scalable potential in applications such as augmented reality,optical diagnostics,and spectral holography.
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.
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This year marks the third anniversary of China’s Global Civilisation Initiative.Over the past three years,cultural exchange and mutual learning have flourished across continents,from Asia to Africa.At the archaeological site of Memphis in Egypt,Chinese-developed digital technology is now creating“annual rings”of memory for a civilisation dating back to the pharaohs.
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.
文摘Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.
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National Key Research and Development Program of China(2022YFB2702800)National Natural Science Foundation of China(72334003)+1 种基金Shandong Key Research and Development Program(2020ZLYS09)Jinan Program(2021GXRC084-2)。
文摘Discrete wavelet transform(DWT)algorithm is an encryption algorithm based on wavelet transform for frequency decomposition of signals or images on multiple scales.Based on the Loongson 2K processor platform,the audio,picture and video information as carriers to encrypt and decrypt the watermark information is realized by integrating and stacking the watermark detection functions on the processor platform of the switching nodes in the off-chain communication network within blockchain systems,using the sliding window mechanism of Loongson 2K to control the smoothness of the digital information,and by multi-thread mechanism of the processor to control the real-time performance of the digital signal transmission.The performance of the least significant bit(LSB)algorithm,discrete cosine transform(DCT)algorithm,and DWT algorithm is analyzed.The performance comparison of LSB algorithm,DCT algorithm,and DWT algorithm under filtering attack,scaling attack,noise attack,cropping attack,and spin attack is simulated respectively.The experimental results show that,filtered attack normalized correlation(NC)coefficient for DWT is 0.95786,for scaled attack is 0.98962,for noise attack is 0.93842,spin attack NC is 0.86823,and clipped attack NC is 0.878814.The DWT algorithm has the small image distortion rate,is more robust to audio and video watermarking against attack effects,and the experimental data are superior to the LSB and DCT algorithms.Using Loongson 2K multi-threading mode to control the real-time data transmission,greatly improves the practicability of DWT algorithm on embedded devices,which can be effectively applied to authenticity verification when media data such as images and audio are uploaded to the blockchain.
文摘Under the strategic framework of rural revitalization and agricultural modernization, Xinjiashan Specialty Coffee Base, located in Zaotang Village, Lujiang Town, Longyang District, Baoshan City, has been proactively investigating innovative models for agricultural development. Through extensive communication and collaboration, this base has established close partnerships with research institutions including Kunming University of Science and Technology, Baoshan University, and Yunnan Academy of Agricultural Sciences, with a commitment to thoroughly exploring the potential for resource recycling and ecological complementarity. An innovative four-in-one three-dimensional integrated planting system incorporating "coffee, bananas, green manure, and bees" has been implemented. Concurrently, technological and digital management strategies have been comprehensively integrated to improve planting efficiency. Under this model, the proportion of specialty coffee attains 71%, and the per-unit yield is 17% greater than that of the conventional planting model. This approach not only substantially enhances economic returns but also promotes the integrated development of ecological and social benefits, offering a valuable practical example and experiential reference for the specialty and sustainable advancement of the coffee industry in comparable regions.
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On October 28,2025,in the bustling diplomatic hub of Kuala Lumpur,a defining moment in Asian economic history quietly and solemnly unfolded when leaders from China and ASEAN member states witnessed the official signing of the protocol to upgrade the China-ASEAN Free Trade Area(CAFTA)to Version 3.0.The ceremony marked the culmination of nearly three years of intense negotiations.
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.
