With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided b...With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.展开更多
Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to ...Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to improve sleep quality and resilience in this population.This study aimed to investigate the effect of virtual reality(VR)combined with forest therapy interventions on psychological resilience and sleep quality among submarine personnel with insomnia symptoms.Methods:Using convenience sampling,92 submarine personnel with insomnia symptoms undergoing recuperation at a PLA sanatorium between July 2023 and May 2025 were randomly allocated to experimental and control groups(n=46 each).The control group received forest therapy intervention,while the intervention group received combined VR and forest therapy interventions.Pre-and post-intervention assessments were conducted using the Pittsburgh Sleep Quality Index(PSQI)and Connor-Davidson Resilience Scale(CD-RISC).Results:There is no significant differences between two groups before the intervention on sleep or psychological resilience.Both groups showed significant pre-to post-intervention improvements in sleep and resilience;however,mixed-ANOVA results showed that the intervention(VR+forest therapy)group achieved significantly better outcomes than the control group at post-intervention after Bonferroni correction,including lower PSQI total and key component scores(subjective sleep quality,sleep efficiency,daytime dysfunction)and higher CD-RISC resilience scores.Conclusions:The integration of virtual reality and forest therapy effectively improved sleep quality and psychological resilience among submarine personnel with insomnia symptoms.This combined intervention shows promise as a non-pharmacological approach in military healthcare settings;however,further studies are needed to validate and generalize these findings.展开更多
With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effect...Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.展开更多
Objectives This scoping review aimed to identify and summarize the current research on virtual reality(VR)technologies used for health education in cancer patients,as well as to identify key areas of application.Metho...Objectives This scoping review aimed to identify and summarize the current research on virtual reality(VR)technologies used for health education in cancer patients,as well as to identify key areas of application.Methods In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines,a comprehensive literature search was performed across 11 electronic databases and gray literature sources from inception to 12 September 2025.Studies employing immersive VR tools to improve health education outcomes in cancer patients were included.Data extraction and thematic synthesis were conducted to map evidence regarding VR modalities,educational applications,and outcome measures.Results Twenty-eight studies met the inclusion criteria.VR was applied across four primary educational scenarios,including radiotherapy,chemotherapy,surgery,and healthy behavior(including rehabilitation,smoking cessation,and self-management).Eight distinct VR modalities were identified,namely VR videos,virtual environments,virtual environment for radiotherapy training(VERT),VR interactions,3D models,VR games,VR non-player characters(VR NPCs),and virtual libraries.Among these,VR videos(50.0%),virtual environments(46.4%),and VR interactions(28.6%)were the most frequently employed.The interventions led to significant improvements in patient knowledge,skills,attitudes,health behaviors,and psychological well-being.A clear evolution in VR educational approaches has been observed,shifting from static environmental familiarization toward interactive,gamified,and intelligence-driven experiences.Nevertheless,notable gaps remain regarding safety protocols and data privacy protections,with only a minority of studies addressing these issues.Conclusions VR technologies demonstrate considerable promise as an innovative educational tool in oncology care,enhancing patient understanding,psychological preparedness,and engagement throughout the cancer journey.Future implementation must address infrastructural,ethical,and user-centered design barriers to facilitate the scalable and sustainable integration of this approach into clinical practice.展开更多
In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,d...In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,due to their voltage source behavior and emulated swing dynamics,GFM converters may encounter low-frequency oscillations(LFOs)when connected to strong grids,which belongs to the self-stability problem of GFM converters.Moreover,GFM converters will also interact with grid-following(GFL)converters and thus impact the mid-frequency oscillations(MFOs)induced by phase-locked loops(PLLs).It has been preliminarily shown in the literature that GFM converters can help stabilize the PLL-induced MFOs,but currently,there is a lack of systematic design methods to coordinate the self-stability and stabilizing ability of GFM converters.This paper addresses this gap by revisiting the impedance model of a typical GFM converter and briefly analyze the oscillations caused by converters.Based on our analysis,we propose a frequency-partitioned synthesis design framework to enable dynamic virtual impedance(DVI)in GFM converters,aiming to enhance their self-stability and stabilizing ability simultaneously.Particularly,a self-stabilizing module is designed to ensure robust device-level damping,with control parameters auto-tuned using H∞methods.In parallel,a stabilizing module is introduced to stabilize GFL converters and enhance the system-level stability,which utilizes a perceive-and-optimize tuning strategy.Simulation results validate the effectiveness of the proposed synthesis DVI framework.展开更多
Objective:Nurse-led virtual outpatient clinics are now a familiar component of healthcare delivery across many disciplines,including cancer care,or thopedics,rheumatology,and gastroenterology.However,establishing a nu...Objective:Nurse-led virtual outpatient clinics are now a familiar component of healthcare delivery across many disciplines,including cancer care,or thopedics,rheumatology,and gastroenterology.However,establishing a nurse-led vir tual clinic is challenging for nursing management,par ticularly regarding resources.We aimed to investigate nursing practices and processes and patient experiences in relation to vir tual outpatient clinics.Methods:This was a cross-sectional,descriptive study using mixed data collection methods.Patients(n=324)from 4 specialist clinics completed the Virtual Clinics Patient Satisfaction Questionnaire(VCSQ)survey.Five Nurse Specialists participated in a focus group interview.Results:Most participants(86.3%)reported being satisfied/very satisfied with the virtual clinics,particularly those that were nurse-led.Nurse specialists identified electronic health records(EHRs)and additional IT and administrative support as important for efficiency and effectiveness of the clinics.Conclusions:Nurse-led virtual clinics can be an effective and efficient way to provide care to patients.Nurse managers need to ensure supportive structures are in place,for example,dedicated administrators,IT support and infrastructure,education/training,and relevant policies/procedures.The success of nurse-led virtual services requires key infrastructure to support nursing staff and sustain this service.展开更多
During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm ...During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm regions in the generated image when these regions of the person occlude the garment;blurring and deformation in the generated image when the person performs large pose movements and the target garment is complex with detailed patterns.To solve these two problems,an improved virtual try-on network model,denoted as IPF-Flow-Style-VTON,is proposed.Firstly,a target warped garment mask refinement module(M-RM)is introduced to refine the warped garment mask and remove erroneous information in the arm and palm regions,thereby improving the quality of subsequent image generation.Secondly,an improved global attention module(GAM)is integrated into the original image generation network,enhancing the ResUNet’s understanding of global context and optimizing the fusion of local features and global information,thereby further improving image generation quality.Finally,the UniPose model is used to provide the pose keypoint information of the target person image,guiding the task execution during the image generation phase.Experiments conducted on the VITON dataset show that the proposed method outperforms the original method,Flow-Style-VTON,by 5.4%,0.3%,6.7%,and 2.2%in Frchet inception distance(FID),structural similarity index measure(SSIM),learned perceptual image patch similarity(LPIPS),and peak signal-to-noise ratio(PSNR),respectively.Overall,the proposed method effectively improves upon the shortcomings of the original network and achieves better visual results.展开更多
To address the challenge of low survival rates and limited data collection efficiency in current virtual probe deployments,which results from anomaly detection mechanisms in location-based service(LBS)applications,thi...To address the challenge of low survival rates and limited data collection efficiency in current virtual probe deployments,which results from anomaly detection mechanisms in location-based service(LBS)applications,this paper proposes a novel virtual probe deployment method based on user behavioral feature analysis.The core idea is to circumvent LBS anomaly detection by mimicking real-user behavior patterns.First,we design an automated data extraction algorithm that recognizes graphical user interface(GUI)elements to collect spatio-temporal behavior data.Then,by analyzing the automatically collected user data,we identify normal users’spatio-temporal patterns and extract their features such as high-activity time windows and spatial clustering characteristics.Subsequently,an antidetection scheduling strategy is developed,integrating spatial clustering optimization,load-balanced allocation,and time window control to generate probe scheduling schemes.Additionally,a self-correction mechanism based on an exponential backoff strategy is implemented to rectify anomalous behaviors andmaintain system stability.Experiments in real-world environments demonstrate that the proposed method significantly outperforms baseline methods in terms of both probe ban rate and task completion rate,while maintaining high time efficiency.This study provides a more reliable and clandestine solution for geosocial data collection and lays the foundation for building more robust virtual probe systems.展开更多
Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic effici...Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.展开更多
Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid adv...Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid advancement of computer technology has enabled the integration of virtual reality(VR)into medical training,thereby revolutionizing ophthalmic surgical education through VRbased educational methods.VR technology offers a safe,risk-free environment for trainees to practice repeatedly,enhancing surgical skills and accelerating the learning curve without compromising patient safety.This research outlines the application of VR technology in ophthalmic surgical skills training,particularly in cataract and vitreoretinal surgery.Including assessing the effectiveness of intraocular surgery training systems,evaluating skills transfer to the operating room,comparing it with wet lab cataract surgery training,and enhancing non-dominant hand training for cataract surgery,among other aspects.Additionally,this paper will identify the limitations of VR technology in ocular surgical skills training,offer improvement strategies,and detail the advantages and prospects,with the objective of guiding subsequent researchers.展开更多
Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, w...Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.展开更多
Objective:To analyze the effectiveness of an integrated teaching platform combining virtual reality(VR)technology and high-end simulators in practical obstetrics and gynecology teaching.Methods:A total of 39 interns w...Objective:To analyze the effectiveness of an integrated teaching platform combining virtual reality(VR)technology and high-end simulators in practical obstetrics and gynecology teaching.Methods:A total of 39 interns who underwent obstetrics and gynecology internships from March 2023 to March 2024 were included in the reference group and received conventional practical teaching methods.Another 39 interns who underwent internships from April 2024 to April 2025 were included in the observation group and received the integrated teaching platform combining VR and high-end simulators.The teaching effects of the two groups were compared.Results:The observation group achieved higher assessment scores than the reference group,with higher scores in self-directed learning ability and clinical thinking ability after teaching,as well as higher teaching satisfaction(p<0.05).Conclusion:The integrated teaching platform combining VR and high-end simulators can improve the assessment scores of obstetrics and gynecology interns,cultivate their self-directed learning ability and clinical thinking ability,and achieve high teaching satisfaction.展开更多
Unequal virtual water transfer may aggravate local water scarcity risk.However,the quantitative confirmation of a clear geographic convergence between virtual water transfer and water scarcity risk remains undetermine...Unequal virtual water transfer may aggravate local water scarcity risk.However,the quantitative confirmation of a clear geographic convergence between virtual water transfer and water scarcity risk remains undetermined.We present an analytical framework that reveals the spatial matching between global water scarcity risk and virtual water trade inequality.This framework integrates a three-dimensional water scarcity risk assessment,hybrid input-output analysis,pollution trade term construction,and geographic convergence identification.The framework is applied to 123 countries for long-term validation from 1991 to 2021.We show that despite global improvements in water efficiency and security,countries exceeding the maximum water vulnerability threshold have increased by 50%.South Asia is the largest net exporter of virtual water.Central Asia exhibits the most pronounced virtual water trade inequality.To achieve the same economic growth,Central Asia needs to pay several times the local water consumption costs of developed regions(15.9−83.6 times,2021).In the past 30 years,the average geographic convergence index exceeded 0.8.Countries facing severe water scarcity also exhibit pronounced inequalities in virtual water trade,indicating that a significant geographic convergence relationship exists.Effectively responding to this unsustainable relationship necessitates balancing both domestic resource risk management and global virtual water trade regulation.展开更多
This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint...This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint programming approach is adopted to address uncertainties stemming from renewable generation and load demand within individual VPPs,while robust optimization techniques manage electricity and thermal price volatilities.Building upon this foundation,a hierarchical Nash-Stackelberg game model is established across multiple VPPs.Within each VPP,a Stackelberg game resolves the strategic interaction between the operator and photovoltaic prosumers(PVP).Among VPPs,a cooperative Nash bargaining model coordinates alliance formation.The problem is decomposed into two subproblems:maximizing coalitional benefits,and allocating cooperative surpluses via payment bargaining,solved distributively using the alternating direction method of multipliers(ADMM).Case studies demonstrate that the proposed strategy significantly enhances the economic efficiency and uncertainty resilience of multi-VPP alliances.展开更多
Pricing competition between virtual power plants(VPPs)for distributed energy resources(DERs)is considered in this paper.Due to limited amount of DERs in one distributed area,VPPs have to compete for the rights to work...Pricing competition between virtual power plants(VPPs)for distributed energy resources(DERs)is considered in this paper.Due to limited amount of DERs in one distributed area,VPPs have to compete for the rights to work with DERs and then sell electricity from internal DERs in the wholesale market.To address this pricing problem,a Markov decision process(MDP)with continuous state and action spaces is formulated for the VPP to consider future rewards brought by contract statuses of DERs.Deep deterministic policy gradient(DDPG)algorithm is applied to solve the pricing problem in MDP form.To deal with the non-stationary environment in the training process brought by competing VPP,a fictitious adversary method is put forward in this paper to combine with DDPG algorithm for the first time.The proposed fictitious adversary method can help the VPP in finding competitive and robust pricing strategies under competition.Numerical results demonstrate effectiveness of the proposed methodology in finding satisfying pricing strategies that consider competitor behavior and long-term values of DERs.展开更多
In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to...In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.展开更多
基金financially supported by the Talent Initiation Fund of Wuxi University(550220008).
文摘With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.
文摘Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to improve sleep quality and resilience in this population.This study aimed to investigate the effect of virtual reality(VR)combined with forest therapy interventions on psychological resilience and sleep quality among submarine personnel with insomnia symptoms.Methods:Using convenience sampling,92 submarine personnel with insomnia symptoms undergoing recuperation at a PLA sanatorium between July 2023 and May 2025 were randomly allocated to experimental and control groups(n=46 each).The control group received forest therapy intervention,while the intervention group received combined VR and forest therapy interventions.Pre-and post-intervention assessments were conducted using the Pittsburgh Sleep Quality Index(PSQI)and Connor-Davidson Resilience Scale(CD-RISC).Results:There is no significant differences between two groups before the intervention on sleep or psychological resilience.Both groups showed significant pre-to post-intervention improvements in sleep and resilience;however,mixed-ANOVA results showed that the intervention(VR+forest therapy)group achieved significantly better outcomes than the control group at post-intervention after Bonferroni correction,including lower PSQI total and key component scores(subjective sleep quality,sleep efficiency,daytime dysfunction)and higher CD-RISC resilience scores.Conclusions:The integration of virtual reality and forest therapy effectively improved sleep quality and psychological resilience among submarine personnel with insomnia symptoms.This combined intervention shows promise as a non-pharmacological approach in military healthcare settings;however,further studies are needed to validate and generalize these findings.
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
基金supported by the National Natural Science Foundation of China(Nos.12175321,W2443004,11975021,11675275,U1932101)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)+2 种基金National Key Research and Development Program of China(Nos.2023YFA1606000 and 2020YFA0406400)National College Students Science and Technology Innovation ProjectUndergraduate Base Scientific Research Project of Sun Yat-sen University。
文摘Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.
基金supported by a project supported by Scientific Research Fund of Zhejiang Provincial Education Department(Grant number Y202457058).
文摘Objectives This scoping review aimed to identify and summarize the current research on virtual reality(VR)technologies used for health education in cancer patients,as well as to identify key areas of application.Methods In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines,a comprehensive literature search was performed across 11 electronic databases and gray literature sources from inception to 12 September 2025.Studies employing immersive VR tools to improve health education outcomes in cancer patients were included.Data extraction and thematic synthesis were conducted to map evidence regarding VR modalities,educational applications,and outcome measures.Results Twenty-eight studies met the inclusion criteria.VR was applied across four primary educational scenarios,including radiotherapy,chemotherapy,surgery,and healthy behavior(including rehabilitation,smoking cessation,and self-management).Eight distinct VR modalities were identified,namely VR videos,virtual environments,virtual environment for radiotherapy training(VERT),VR interactions,3D models,VR games,VR non-player characters(VR NPCs),and virtual libraries.Among these,VR videos(50.0%),virtual environments(46.4%),and VR interactions(28.6%)were the most frequently employed.The interventions led to significant improvements in patient knowledge,skills,attitudes,health behaviors,and psychological well-being.A clear evolution in VR educational approaches has been observed,shifting from static environmental familiarization toward interactive,gamified,and intelligence-driven experiences.Nevertheless,notable gaps remain regarding safety protocols and data privacy protections,with only a minority of studies addressing these issues.Conclusions VR technologies demonstrate considerable promise as an innovative educational tool in oncology care,enhancing patient understanding,psychological preparedness,and engagement throughout the cancer journey.Future implementation must address infrastructural,ethical,and user-centered design barriers to facilitate the scalable and sustainable integration of this approach into clinical practice.
基金supported by National Natural Science Foundation of China(U24B6008,U22B6008)State Grid Zhejiang Electric Power Co.,Ltd.Science,and Technology Project(B311DS240015).
文摘In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,due to their voltage source behavior and emulated swing dynamics,GFM converters may encounter low-frequency oscillations(LFOs)when connected to strong grids,which belongs to the self-stability problem of GFM converters.Moreover,GFM converters will also interact with grid-following(GFL)converters and thus impact the mid-frequency oscillations(MFOs)induced by phase-locked loops(PLLs).It has been preliminarily shown in the literature that GFM converters can help stabilize the PLL-induced MFOs,but currently,there is a lack of systematic design methods to coordinate the self-stability and stabilizing ability of GFM converters.This paper addresses this gap by revisiting the impedance model of a typical GFM converter and briefly analyze the oscillations caused by converters.Based on our analysis,we propose a frequency-partitioned synthesis design framework to enable dynamic virtual impedance(DVI)in GFM converters,aiming to enhance their self-stability and stabilizing ability simultaneously.Particularly,a self-stabilizing module is designed to ensure robust device-level damping,with control parameters auto-tuned using H∞methods.In parallel,a stabilizing module is introduced to stabilize GFL converters and enhance the system-level stability,which utilizes a perceive-and-optimize tuning strategy.Simulation results validate the effectiveness of the proposed synthesis DVI framework.
基金supported by Nursing and Midwifery Practice Development Unit(NMPDU),Dublin South,Kildare,and Wicklow,Nurses preparedness for end of life conversations(No.P210537)。
文摘Objective:Nurse-led virtual outpatient clinics are now a familiar component of healthcare delivery across many disciplines,including cancer care,or thopedics,rheumatology,and gastroenterology.However,establishing a nurse-led vir tual clinic is challenging for nursing management,par ticularly regarding resources.We aimed to investigate nursing practices and processes and patient experiences in relation to vir tual outpatient clinics.Methods:This was a cross-sectional,descriptive study using mixed data collection methods.Patients(n=324)from 4 specialist clinics completed the Virtual Clinics Patient Satisfaction Questionnaire(VCSQ)survey.Five Nurse Specialists participated in a focus group interview.Results:Most participants(86.3%)reported being satisfied/very satisfied with the virtual clinics,particularly those that were nurse-led.Nurse specialists identified electronic health records(EHRs)and additional IT and administrative support as important for efficiency and effectiveness of the clinics.Conclusions:Nurse-led virtual clinics can be an effective and efficient way to provide care to patients.Nurse managers need to ensure supportive structures are in place,for example,dedicated administrators,IT support and infrastructure,education/training,and relevant policies/procedures.The success of nurse-led virtual services requires key infrastructure to support nursing staff and sustain this service.
基金National Key R&D Program of China(No.2019YFC1521300)。
文摘During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm regions in the generated image when these regions of the person occlude the garment;blurring and deformation in the generated image when the person performs large pose movements and the target garment is complex with detailed patterns.To solve these two problems,an improved virtual try-on network model,denoted as IPF-Flow-Style-VTON,is proposed.Firstly,a target warped garment mask refinement module(M-RM)is introduced to refine the warped garment mask and remove erroneous information in the arm and palm regions,thereby improving the quality of subsequent image generation.Secondly,an improved global attention module(GAM)is integrated into the original image generation network,enhancing the ResUNet’s understanding of global context and optimizing the fusion of local features and global information,thereby further improving image generation quality.Finally,the UniPose model is used to provide the pose keypoint information of the target person image,guiding the task execution during the image generation phase.Experiments conducted on the VITON dataset show that the proposed method outperforms the original method,Flow-Style-VTON,by 5.4%,0.3%,6.7%,and 2.2%in Frchet inception distance(FID),structural similarity index measure(SSIM),learned perceptual image patch similarity(LPIPS),and peak signal-to-noise ratio(PSNR),respectively.Overall,the proposed method effectively improves upon the shortcomings of the original network and achieves better visual results.
基金supported by theNationalNatural Science Foundation of China(No.U23A20305)National Key Research and Development Program of China(No.2022YFB3102900)+1 种基金Innovation Scientists and Technicians Troop Construction Projects of Henan Province,China(No.254000510007)Key Research and Development Project of Henan Province(No.221111321200).
文摘To address the challenge of low survival rates and limited data collection efficiency in current virtual probe deployments,which results from anomaly detection mechanisms in location-based service(LBS)applications,this paper proposes a novel virtual probe deployment method based on user behavioral feature analysis.The core idea is to circumvent LBS anomaly detection by mimicking real-user behavior patterns.First,we design an automated data extraction algorithm that recognizes graphical user interface(GUI)elements to collect spatio-temporal behavior data.Then,by analyzing the automatically collected user data,we identify normal users’spatio-temporal patterns and extract their features such as high-activity time windows and spatial clustering characteristics.Subsequently,an antidetection scheduling strategy is developed,integrating spatial clustering optimization,load-balanced allocation,and time window control to generate probe scheduling schemes.Additionally,a self-correction mechanism based on an exponential backoff strategy is implemented to rectify anomalous behaviors andmaintain system stability.Experiments in real-world environments demonstrate that the proposed method significantly outperforms baseline methods in terms of both probe ban rate and task completion rate,while maintaining high time efficiency.This study provides a more reliable and clandestine solution for geosocial data collection and lays the foundation for building more robust virtual probe systems.
基金funded by the Department of Education of Liaoning Province and was supported by the Basic Scientific Research Project of the Department of Education of Liaoning Province(Grant No.LJ222411632051)and(Grant No.LJKQZ2021085)Natural Science Foundation Project of Liaoning Province(Grant No.2022-BS-222).
文摘Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.
基金Supported by the Key Special Project of“Cutting-Edge Biotechnology”in the National Key Research and Development Program of China(No.2024YFC3406200)Sanming Project of Medicine in Shenzhen(No.SZSM202411007)Shenzhen Science and Technology Program(No.JCYJ20240813152704006).
文摘Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid advancement of computer technology has enabled the integration of virtual reality(VR)into medical training,thereby revolutionizing ophthalmic surgical education through VRbased educational methods.VR technology offers a safe,risk-free environment for trainees to practice repeatedly,enhancing surgical skills and accelerating the learning curve without compromising patient safety.This research outlines the application of VR technology in ophthalmic surgical skills training,particularly in cataract and vitreoretinal surgery.Including assessing the effectiveness of intraocular surgery training systems,evaluating skills transfer to the operating room,comparing it with wet lab cataract surgery training,and enhancing non-dominant hand training for cataract surgery,among other aspects.Additionally,this paper will identify the limitations of VR technology in ocular surgical skills training,offer improvement strategies,and detail the advantages and prospects,with the objective of guiding subsequent researchers.
文摘Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.
基金2024 Undergraduate Teaching Reform Research Project,Department of Education of Shandong Province,2025 Key Project of University-Level Education and Teaching Reform and Research,Research Title:Research on Talent Demand in the Biomedical Industry Chain and Strategies for High-Quality Higher Education Talent Cultivation in Shandong Province under the Background of New Quality Productivity(Project No.:Z2024208)Shandong Second Medical University,Research Title:Construction and Application of an Integrated Teaching Platform Combining Virtual Simulation and High-Fidelity Simulators in Obstetrics and Gynecology Practice Teaching,Project No.:2025SJZX053)。
文摘Objective:To analyze the effectiveness of an integrated teaching platform combining virtual reality(VR)technology and high-end simulators in practical obstetrics and gynecology teaching.Methods:A total of 39 interns who underwent obstetrics and gynecology internships from March 2023 to March 2024 were included in the reference group and received conventional practical teaching methods.Another 39 interns who underwent internships from April 2024 to April 2025 were included in the observation group and received the integrated teaching platform combining VR and high-end simulators.The teaching effects of the two groups were compared.Results:The observation group achieved higher assessment scores than the reference group,with higher scores in self-directed learning ability and clinical thinking ability after teaching,as well as higher teaching satisfaction(p<0.05).Conclusion:The integrated teaching platform combining VR and high-end simulators can improve the assessment scores of obstetrics and gynecology interns,cultivate their self-directed learning ability and clinical thinking ability,and achieve high teaching satisfaction.
基金supported by National Natural Science Foundation of China(Grant No.52279027)National Key R&D Program of China(Grant No.2021YFC3200201)+1 种基金Key Research Project on Decision Consultation of the Strategic Development Department of China Association for Science and Technology(Grant No.2023070615CG111504)China Engineering Science and Technology Development Strategy Henan Research Institute Strategic Consulting Research Project(Grant No.2024HENYB01).
文摘Unequal virtual water transfer may aggravate local water scarcity risk.However,the quantitative confirmation of a clear geographic convergence between virtual water transfer and water scarcity risk remains undetermined.We present an analytical framework that reveals the spatial matching between global water scarcity risk and virtual water trade inequality.This framework integrates a three-dimensional water scarcity risk assessment,hybrid input-output analysis,pollution trade term construction,and geographic convergence identification.The framework is applied to 123 countries for long-term validation from 1991 to 2021.We show that despite global improvements in water efficiency and security,countries exceeding the maximum water vulnerability threshold have increased by 50%.South Asia is the largest net exporter of virtual water.Central Asia exhibits the most pronounced virtual water trade inequality.To achieve the same economic growth,Central Asia needs to pay several times the local water consumption costs of developed regions(15.9−83.6 times,2021).In the past 30 years,the average geographic convergence index exceeded 0.8.Countries facing severe water scarcity also exhibit pronounced inequalities in virtual water trade,indicating that a significant geographic convergence relationship exists.Effectively responding to this unsustainable relationship necessitates balancing both domestic resource risk management and global virtual water trade regulation.
基金supported by Science and Technology Project of SGCC(Research on Distributed Cooperative Control of Virtual Power Plants Based on Hybrid Game)(5700-202418337A-2-1-ZX).
文摘This paper suggests a way to improve teamwork and reduce uncertainties in operations by using a game theory approach involving multiple virtual power plants(VPP).A generalized credibility-based fuzzy chance constraint programming approach is adopted to address uncertainties stemming from renewable generation and load demand within individual VPPs,while robust optimization techniques manage electricity and thermal price volatilities.Building upon this foundation,a hierarchical Nash-Stackelberg game model is established across multiple VPPs.Within each VPP,a Stackelberg game resolves the strategic interaction between the operator and photovoltaic prosumers(PVP).Among VPPs,a cooperative Nash bargaining model coordinates alliance formation.The problem is decomposed into two subproblems:maximizing coalitional benefits,and allocating cooperative surpluses via payment bargaining,solved distributively using the alternating direction method of multipliers(ADMM).Case studies demonstrate that the proposed strategy significantly enhances the economic efficiency and uncertainty resilience of multi-VPP alliances.
基金supported by the National Key R&D Program of China(2020YFB09060002020YFB0906005).
文摘Pricing competition between virtual power plants(VPPs)for distributed energy resources(DERs)is considered in this paper.Due to limited amount of DERs in one distributed area,VPPs have to compete for the rights to work with DERs and then sell electricity from internal DERs in the wholesale market.To address this pricing problem,a Markov decision process(MDP)with continuous state and action spaces is formulated for the VPP to consider future rewards brought by contract statuses of DERs.Deep deterministic policy gradient(DDPG)algorithm is applied to solve the pricing problem in MDP form.To deal with the non-stationary environment in the training process brought by competing VPP,a fictitious adversary method is put forward in this paper to combine with DDPG algorithm for the first time.The proposed fictitious adversary method can help the VPP in finding competitive and robust pricing strategies under competition.Numerical results demonstrate effectiveness of the proposed methodology in finding satisfying pricing strategies that consider competitor behavior and long-term values of DERs.
基金supported by Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the Korean government(MSIT)(No.2019-0-01842,Artificial Intelligence Graduate School Program(GIST))supported by Korea Planning&Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)(RS-2025-25448249+1 种基金Automotive Industry Technology Development(R&D)Program)supported by the Regional Innovation System&Education(RISE)programthrough the(Gwangju RISE Center),funded by the Ministry of Education(MOE)and the Gwangju Metropolitan City,Republic of Korea(2025-RISE-05-001).
文摘In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
