The problem of stabilizing a class of large-scale non-linear multiple delay systems is considered.The complicated system is decomposed into several subsystems; each function of them is expressed by a set of components...The problem of stabilizing a class of large-scale non-linear multiple delay systems is considered.The complicated system is decomposed into several subsystems; each function of them is expressed by a set of components of the overall state vector,with interconnections between them, and the subsystems are coupled by the delayed state. In this paper, a method is devised to be a suitable choice of state feedback controls of every subsystems, moreover, it is proved that the large-scale system is exponential stable.展开更多
To detect the bias fault in stochastic non-linear dynamic systems, a new Unscented Kalman Filtering（UKF） based real-time recursion detection method is brought forward with the consideration of the flaws of tradition...To detect the bias fault in stochastic non-linear dynamic systems, a new Unscented Kalman Filtering（UKF） based real-time recursion detection method is brought forward with the consideration of the flaws of traditional Extended Kalman Filtering（ EKF）. It uses the UKF as the residual generation method and the Weighted-Sum Squared Residual （WSSR） as the fault detection strategy. The simulation results are provided which demonstrate better effectiveness and a higher detection ratio of the developed methods.展开更多
This paper deals with the problem of delay size stability analysis of single input-delayed linear and nonlinear systems. Conventional reduction, reduction linked by sliding mode, and linear memoryless control approach...This paper deals with the problem of delay size stability analysis of single input-delayed linear and nonlinear systems. Conventional reduction, reduction linked by sliding mode, and linear memoryless control approaches are used for simple input-delayed systems to obtain the stability conditions. Several first order examples are investigated systematically to demonstrate the capabilities and limitations of the advanced stability analysis techniques including Lyapunov-Krasovskii functionals, Newton-Leibniz formula, and a newly addressed Lagrange mean value theorem. Numerical comparative results show the usefulness and effectiveness of the advanced delay size analysis techniques proposed in this paper.展开更多
This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to es...This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contempo...Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.展开更多
This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced...This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced distributionally robust optimization approach,this study integrates deep learning models,especially generative adversarial networks,to adeptly handle the inherent variability and uncertainties of renewable energy and fluctuating consumer demands.The effectiveness of this framework is rigorously tested through detailed simulations mirroring real-world urban energy consumption,renewable energy production,and market price fluctuations over an annual period.The results reveal substantial improvements in the resilience and efficiency of the grid,achieving a reduction in power distribution losses by 15%and enhancing voltage stability by 20%,markedly outperforming conventional systems.Additionally,the framework facilitates up to 25%in cost reductions during peak demand periods,significantly lowering operational costs.The adoption of stochastic gradients further refines the framework’s ability to continually adjust to real-time changes in environmental and market conditions,ensuring stable grid operations and fostering active consumer engagement in demand-side management.This strategy not only aligns with contem-porary sustainable energy practices but also provides scalable and robust solutions to pressing challenges in modern power network management.展开更多
Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the ...Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the emerging artificial intelligence and machine learning,traditional modeling techniques in these energy systems have met challenges in still leveraging physics model and first principle-based approaches.Moreover,with the rapid development of hardware and computing techniques,new modeling approaches for energy systems have become more and more important for system design,integration,analysis,control,and management.展开更多
The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review exa...The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.展开更多
The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,infl...The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,influence microbial composition and function through variations in diet,genetic selection,environmental exposure,and antibiotic use.Conventional systems typically rely on formulated diets and controlled housing conditions,often with routine antimicrobial use.In contrast,organic systems emphasize natural feed ingredients,including roughage,outdoor access,and strict limitations on the use of antibiotics.These divergent practices shape the gut microbiota differently,with organic systems generally associated with greater exposure to environmental microbes and,consequently,greater microbial diversity.However,the implications of this increased diversity for poultry health and performance are complex,as organic systems may also carry a higher risk of pathogen exposure.This review summarizes current findings on the chicken gut microbiome across conventional and alternative production systems(antibiotic-free,freerange,and organic),focusing on microbial diversity,functional potential,and disease resilience.The need for standardized methodologies and consistent nomenclature in microbiome research is also discussed to improve comparability across studies.Understanding how production systems influence the gut microbiota is essential for improving poultry health and productivity while addressing challenges related to antimicrobial resistance and sustainable farming practices.展开更多
The Internet of Things(IoT)and cloud computing have significantly contributed to the development of smart cities,enabling real-time monitoring,intelligent decision-making,and efficient resource management.These system...The Internet of Things(IoT)and cloud computing have significantly contributed to the development of smart cities,enabling real-time monitoring,intelligent decision-making,and efficient resource management.These systems,particularly in IoT networks,rely on numerous interconnected devices that handle time-sensitive data for critical applications.In related approaches,trusted communication and reliable device interaction have been overlooked,thereby lowering security when sharing sensitive IoT data.Moreover,it incurs additional energy consumption and overhead while addressing potential threats in the dynamic environment.In this research,an Artificial Intelligence(AI)recommended fault-tolerant framework is proposed that leverages blockchain technology,aiming to enhance device trustworthiness and ensure data privacy.In addition,the intelligence of the proposed framework enables more authentic and authorized device involvement in data routing,thereby enabling seamless transmission in smart cities integrated with lightweight computing.To evaluate dynamic network conditions,the proposed framework offers a timely decision-making system to ensure robust delivery of IoT-assisted services.Using simulations,the efficacy of the proposed framework is validated by comparing it with existing approaches across various network metrics,demonstrating remarkable performance while achieving energy efficiency and optimizing network resources.展开更多
Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities ofte...Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.展开更多
Dear Editor,With the growing food demands and the rapid development of intensive vegetable cultivation,the vegetable yield and planting area have increased to 230 million tons and 2.13 million hectares,respectively,in...Dear Editor,With the growing food demands and the rapid development of intensive vegetable cultivation,the vegetable yield and planting area have increased to 230 million tons and 2.13 million hectares,respectively,in China in 2021(MARAPRC,2023).展开更多
Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for...Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.展开更多
This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consen...This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.展开更多
The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention a...The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention and treatment methods.Animal models serve as essential tools for investigating disease mechanisms and assessing novel therapeutic strategies,and the scientific rigor of their construction and validation significantly impacts the reliability of research findings.This paper systematically reviews the research progress and evaluation systems of BAS animal models over the past decade,aiming to provide a robust foundation for the optimized construction of BAS models,intervention studies,and clinical translation.This effort is intended to facilitate the innovation and advancement in BAS prevention and treatment strategies.展开更多
In this paper,we investigate the convex roof measures of quantum coherence,with a focus on their superadditive properties.We propose sufficient conditions and establish a framework for coherence superadditivity in tri...In this paper,we investigate the convex roof measures of quantum coherence,with a focus on their superadditive properties.We propose sufficient conditions and establish a framework for coherence superadditivity in tripartite and multipartite systems.Through theoretical derivation,the relevant theorems are given.These results not only expand our understanding of the superadditivity of pure and mixed states but also characterize the conditions under which the superadditivity relations reach equality.Finally,the proposed methods and conclusions are verified through representative examples,providing new theoretical insights into the distribution of quantum coherence in multipartite systems.展开更多
Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transporta...Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transportation systems(ITS).This paper presents a systematic review of ILC's developmental progress,current methodologies,and practical implementations across these two critical domains.The review first analyzes the key technical challenges encountered when integrating ILC into precision manufacturing workflows.Through case studies,it evaluates demonstrated improvements in positioning accuracy,surface finish quality,and production throughput.Furthermore,the study examines ILC’s applications in ITS,with particular focus on vehicular motion control applications including autonomous vehicle trajectory tracking,platoon coordination,and traffic signal timing optimization,where its data-driven characteristics enhance adaptability to dynamic environments.Finally,the paper proposes targeted future research directions that are essential for fully realizing ILC’s potential in advancing these interconnected yet distinct fields.展开更多
In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence ...In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence of pipeline hydraulic residence time(HRT)on disinfection efficiency,by-product formation,microbial activity,and biofilm growth were considered.The results show that both microbial activities and metabolite secretion were stimulated by increasing HRT,aggravating the potential risk of microbial pollution in DWDS.The enhanced microbial metabolism could further weaken disinfection efficiency by consuming extra residual Chlorine,after which the formation of disinfection by-products was facilitated.Residual Chlorine was found negatively correlated with HRT.With prolonging HRT from 5 to 40 h,the concentration of disinfection by-products(Chlorate,Chlorite,and Trichloromethane)was on a continuously increasing trend by 37%,140%,and 75%,respectively.But the water kept in pipeline still reliably satisfied the Standards for drinking water quality in China(GB5749–2022).Besides,more biofilm with denser morphologies developed on rubber pipeline gaskets rather than the iron/plastic ones.Rubber material was inappropriate for DWDS due to its potential risk of secondary biological pollution.Prolonging HRT also enhanced the accumulation of dominant bacteria(e.g.Bradyrhizobium and Obscuribacter)and decreased microbial diversity.展开更多
文摘The problem of stabilizing a class of large-scale non-linear multiple delay systems is considered.The complicated system is decomposed into several subsystems; each function of them is expressed by a set of components of the overall state vector,with interconnections between them, and the subsystems are coupled by the delayed state. In this paper, a method is devised to be a suitable choice of state feedback controls of every subsystems, moreover, it is proved that the large-scale system is exponential stable.
文摘To detect the bias fault in stochastic non-linear dynamic systems, a new Unscented Kalman Filtering（UKF） based real-time recursion detection method is brought forward with the consideration of the flaws of traditional Extended Kalman Filtering（ EKF）. It uses the UKF as the residual generation method and the Weighted-Sum Squared Residual （WSSR） as the fault detection strategy. The simulation results are provided which demonstrate better effectiveness and a higher detection ratio of the developed methods.
文摘This paper deals with the problem of delay size stability analysis of single input-delayed linear and nonlinear systems. Conventional reduction, reduction linked by sliding mode, and linear memoryless control approaches are used for simple input-delayed systems to obtain the stability conditions. Several first order examples are investigated systematically to demonstrate the capabilities and limitations of the advanced stability analysis techniques including Lyapunov-Krasovskii functionals, Newton-Leibniz formula, and a newly addressed Lagrange mean value theorem. Numerical comparative results show the usefulness and effectiveness of the advanced delay size analysis techniques proposed in this paper.
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
文摘This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
文摘Modern business information systems face significant challenges in managing heterogeneous data sources,integrating disparate systems,and providing real-time decision support in complex enterprise environments.Contemporary enterprises typically operate 200+interconnected systems,with research indicating that 52% of organizations manage three or more enterprise content management systems,creating information silos that reduce operational efficiency by up to 35%.While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision,their systematic application to business information systems remains largely unexplored.This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System(HABIS)framework that applies multi-level attention mechanisms to enterprise environments.We provide a comprehensive mathematical formulation of the framework,analyze its computational complexity,and present a proof-of-concept implementation with simulation-based validation that demonstrates a 42% reduction in crosssystem query latency compared to legacy ERP modules and 70% improvement in prediction accuracy over baseline methods.The theoretical framework introduces four hierarchical attention levels:system-level attention for dynamic weighting of business systems,process-level attention for business process prioritization,data-level attention for critical information selection,and temporal attention for time-sensitive pattern recognition.Our complexity analysis demonstrates that the framework achieves O(n log n)computational complexity for attention computation,making it scalable to large enterprise environments including retail supply chains with 200+system-scale deployments.The proof-of-concept implementation validates the theoretical framework’s feasibility withMSE loss of 0.439 and response times of 0.000120 s per query,demonstrating its potential for addressing key challenges in business information systems.This work establishes a foundation for future empirical research and practical implementation of attention-driven enterprise systems.
基金supported by the National Key R&D Program of China(No.2021ZD0112700).
文摘This paper develops an advanced framework for the operational optimization of integrated multi-energy systems that encompass electricity,gas,and heating networks.Introducing a cutting-edge stochastic gradient-enhanced distributionally robust optimization approach,this study integrates deep learning models,especially generative adversarial networks,to adeptly handle the inherent variability and uncertainties of renewable energy and fluctuating consumer demands.The effectiveness of this framework is rigorously tested through detailed simulations mirroring real-world urban energy consumption,renewable energy production,and market price fluctuations over an annual period.The results reveal substantial improvements in the resilience and efficiency of the grid,achieving a reduction in power distribution losses by 15%and enhancing voltage stability by 20%,markedly outperforming conventional systems.Additionally,the framework facilitates up to 25%in cost reductions during peak demand periods,significantly lowering operational costs.The adoption of stochastic gradients further refines the framework’s ability to continually adjust to real-time changes in environmental and market conditions,ensuring stable grid operations and fostering active consumer engagement in demand-side management.This strategy not only aligns with contem-porary sustainable energy practices but also provides scalable and robust solutions to pressing challenges in modern power network management.
基金supported by the Ministry of Industry and Information Technology,China,the Science Foundation of the Ministry of Education of China(No.21YJC630072)the Key Talent Project of the Yan Zhao Golden Platform for Talent Attraction in Hebei Province,China(No.HJYB202528).
文摘Diverse energy and power systems have been playing a significantly critical role in the revolution of sustainable energy supply for the future,which have a great impact on energy resources and efficiencies.Due to the emerging artificial intelligence and machine learning,traditional modeling techniques in these energy systems have met challenges in still leveraging physics model and first principle-based approaches.Moreover,with the rapid development of hardware and computing techniques,new modeling approaches for energy systems have become more and more important for system design,integration,analysis,control,and management.
文摘The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.
基金supported by funds of the Federal Ministry of Agriculture,Food and Regional Identity(BMLEH)based on a decision of the parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food(BLE)under the Federal Programme for Ecological Farming and Other Forms of Sustainable Agriculture(FKZ 2821OE034)。
文摘The poultry gut microbiome plays a key role in nutrient digestion,immune function,and overall health.Differences among various farming systems,including conventional,antibiotic-free,free-range,and organic systems,influence microbial composition and function through variations in diet,genetic selection,environmental exposure,and antibiotic use.Conventional systems typically rely on formulated diets and controlled housing conditions,often with routine antimicrobial use.In contrast,organic systems emphasize natural feed ingredients,including roughage,outdoor access,and strict limitations on the use of antibiotics.These divergent practices shape the gut microbiota differently,with organic systems generally associated with greater exposure to environmental microbes and,consequently,greater microbial diversity.However,the implications of this increased diversity for poultry health and performance are complex,as organic systems may also carry a higher risk of pathogen exposure.This review summarizes current findings on the chicken gut microbiome across conventional and alternative production systems(antibiotic-free,freerange,and organic),focusing on microbial diversity,functional potential,and disease resilience.The need for standardized methodologies and consistent nomenclature in microbiome research is also discussed to improve comparability across studies.Understanding how production systems influence the gut microbiota is essential for improving poultry health and productivity while addressing challenges related to antimicrobial resistance and sustainable farming practices.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-02152).
文摘The Internet of Things(IoT)and cloud computing have significantly contributed to the development of smart cities,enabling real-time monitoring,intelligent decision-making,and efficient resource management.These systems,particularly in IoT networks,rely on numerous interconnected devices that handle time-sensitive data for critical applications.In related approaches,trusted communication and reliable device interaction have been overlooked,thereby lowering security when sharing sensitive IoT data.Moreover,it incurs additional energy consumption and overhead while addressing potential threats in the dynamic environment.In this research,an Artificial Intelligence(AI)recommended fault-tolerant framework is proposed that leverages blockchain technology,aiming to enhance device trustworthiness and ensure data privacy.In addition,the intelligence of the proposed framework enables more authentic and authorized device involvement in data routing,thereby enabling seamless transmission in smart cities integrated with lightweight computing.To evaluate dynamic network conditions,the proposed framework offers a timely decision-making system to ensure robust delivery of IoT-assisted services.Using simulations,the efficacy of the proposed framework is validated by comparing it with existing approaches across various network metrics,demonstrating remarkable performance while achieving energy efficiency and optimizing network resources.
文摘Large-scale complex systems are integral to the functioning of various organizations within the national economy.Despite their significance,the lengthy construction cycles and the involvement of multiple entities often result in the deprioritization of standardized management practices,as they do not yield immediate benefits.The implementation of such systems typically encompasses the integrated phases of "development,construction,utiliz ation,and operation and maintenance".To enhance the overall delivery quality of these systems,it is imperative to dismantle the management barriers among these phases and adopt a holistic approach to standardized management.This paper takes a specific system project as a research object to identify common challenges,and proposes improvement strategies in the implementation of standar dized management.Empirical results indicate a substantial reduction in the system s full-lifecycle costs.
基金supported by the Science and Technology Planning Social Development Project of Zhenjiang City,China(No.SH2017045)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(No.SJCX23_2065)。
文摘Dear Editor,With the growing food demands and the rapid development of intensive vegetable cultivation,the vegetable yield and planting area have increased to 230 million tons and 2.13 million hectares,respectively,in China in 2021(MARAPRC,2023).
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane”,CityU ref.:9231419“Research and application of antibacterial and healing-promoting smart nanofiber dressing for children’s burn wounds”,CityU ref:PJ9240111)+1 种基金the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers”,Grant No.51673162)Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare”,Grant No.9380116).
文摘Radiative cooling systems(RCSs)possess the distinctive capability to dissipate heat energy via solar and thermal radiation,making them suitable for thermal regulation and energy conservation applications,essential for mitigating the energy crisis.A comprehensive review connecting the advancements in engineered radiative cooling systems(ERCSs),encompassing material and structural design as well as thermal and energy-related applications,is currently absent.Herein,this review begins with a concise summary of the essential concepts of ERCSs,followed by an introduction to engineered materials and structures,containing nature-inspired designs,chromatic materials,meta-structural configurations,and multilayered constructions.It subsequently encapsulates the primary applications,including thermal-regulating textiles and energy-saving devices.Next,it highlights the challenges of ERCSs,including maximized thermoregulatory effects,environmental adaptability,scalability and sustainability,and interdisciplinary integration.It seeks to offer direction for forthcoming fundamental research and industrial advancement of radiative cooling systems in real-world applications.
基金supported by the National Natural Science Foundation of China(62463007,62463005)the Natural Science Foundation of Hainan Province(625RC710,625MS047)+1 种基金the System Control and Information Processing Education Ministry Key Laboratory Open Funding,China(Scip20240119)the Science Research Funding of Hainan University,China(KYQD(ZR)22180,KYQD(ZR)23180).
文摘This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.
基金National Natural Science Foundation of China,Grant/Award Number:82000102 and 82270112。
文摘The incidence of benign airway stenosis(BAS)is on the rise,and current treatment options are associated with a significant risk of restenosis.Therefore,there is an urgent need to explore new and effective prevention and treatment methods.Animal models serve as essential tools for investigating disease mechanisms and assessing novel therapeutic strategies,and the scientific rigor of their construction and validation significantly impacts the reliability of research findings.This paper systematically reviews the research progress and evaluation systems of BAS animal models over the past decade,aiming to provide a robust foundation for the optimized construction of BAS models,intervention studies,and clinical translation.This effort is intended to facilitate the innovation and advancement in BAS prevention and treatment strategies.
基金supported by the NNSF of China(Grant No.12471427)the Fundamental Research Funds for the Central Universities(Grant No.4303088)。
文摘In this paper,we investigate the convex roof measures of quantum coherence,with a focus on their superadditive properties.We propose sufficient conditions and establish a framework for coherence superadditivity in tripartite and multipartite systems.Through theoretical derivation,the relevant theorems are given.These results not only expand our understanding of the superadditivity of pure and mixed states but also characterize the conditions under which the superadditivity relations reach equality.Finally,the proposed methods and conclusions are verified through representative examples,providing new theoretical insights into the distribution of quantum coherence in multipartite systems.
基金funded by the Wuxi Young Scientific and Technological Talent Support Initiative,project number:TJXD-2024-203the Natural Science Foundation of the Jiangsu Higher Education Institutions of China,grant number:24KJB470027.
文摘Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transportation systems(ITS).This paper presents a systematic review of ILC's developmental progress,current methodologies,and practical implementations across these two critical domains.The review first analyzes the key technical challenges encountered when integrating ILC into precision manufacturing workflows.Through case studies,it evaluates demonstrated improvements in positioning accuracy,surface finish quality,and production throughput.Furthermore,the study examines ILC’s applications in ITS,with particular focus on vehicular motion control applications including autonomous vehicle trajectory tracking,platoon coordination,and traffic signal timing optimization,where its data-driven characteristics enhance adaptability to dynamic environments.Finally,the paper proposes targeted future research directions that are essential for fully realizing ILC’s potential in advancing these interconnected yet distinct fields.
基金supported by the National Natural Science Foundation of China(Nos.52170070,52400022,and 52200088)the Youth S&T Talent Support Programme of Guangdong Provincial Association for Science and Technology(GDSTA)(No.SKXRC202406)+1 种基金the“One hundred Youth”Science and Technology Plan,Guangdong University of Technology,China(No.263113906)China Postdoctoral Science Foundation(No.2023M740754).
文摘In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence of pipeline hydraulic residence time(HRT)on disinfection efficiency,by-product formation,microbial activity,and biofilm growth were considered.The results show that both microbial activities and metabolite secretion were stimulated by increasing HRT,aggravating the potential risk of microbial pollution in DWDS.The enhanced microbial metabolism could further weaken disinfection efficiency by consuming extra residual Chlorine,after which the formation of disinfection by-products was facilitated.Residual Chlorine was found negatively correlated with HRT.With prolonging HRT from 5 to 40 h,the concentration of disinfection by-products(Chlorate,Chlorite,and Trichloromethane)was on a continuously increasing trend by 37%,140%,and 75%,respectively.But the water kept in pipeline still reliably satisfied the Standards for drinking water quality in China(GB5749–2022).Besides,more biofilm with denser morphologies developed on rubber pipeline gaskets rather than the iron/plastic ones.Rubber material was inappropriate for DWDS due to its potential risk of secondary biological pollution.Prolonging HRT also enhanced the accumulation of dominant bacteria(e.g.Bradyrhizobium and Obscuribacter)and decreased microbial diversity.
