A new type of localized oscillatory pattern is presented in a two-layer coupled reaction-diffusion system under conditions in which no Hopf instability can be discerned in either layer.The transitions from stationary ...A new type of localized oscillatory pattern is presented in a two-layer coupled reaction-diffusion system under conditions in which no Hopf instability can be discerned in either layer.The transitions from stationary patterns to asynchronous and synchronous oscillatory patterns are obtained.A novel method based on decomposing coupled systems into two associated subsystems has been proposed to elucidate the mechanism of formation of oscillating patterns.Linear stability analysis of the associated subsystems reveals that the Turing pattern in one layer induces the other layer locally,undergoes a supercritical Hopf bifurcation and gives rise to localized oscillations.It is found that the sizes and positions of oscillations are determined by the spatial distribution of the Turing patterns.When the size is large,localized traveling waves such as spirals and targets emerge.These results may be useful for deeper understanding of pattern formation in complex systems,particularly multilayered systems.展开更多
In this paper, the problem of initial boundary value for nonlinear coupled reaction-diffusion systems arising in biochemistry, engineering and combustion_theory is considered.
Using the sign-invariant theory, we study the nonlinear reaction-diffusion systems. We also obtain some new explicit solutions to the nonlinear resulting systems.
Boundary control for a class of partial integro-differential systems with space and time dependent coefficients is consid- ered. A control law is derived via the partial differential equation （PDE） backstepping. The...Boundary control for a class of partial integro-differential systems with space and time dependent coefficients is consid- ered. A control law is derived via the partial differential equation （PDE） backstepping. The existence of kernel equations is proved. Exponential stability of the closed-loop system is achieved. Simulation results are presented through figures.展开更多
Differential method and homotopy analysis method are used for solving the two-dimensional reaction-diffusion model. And the structure of the solutions is analyzed. Finally, the homotopy series solutions are simulated ...Differential method and homotopy analysis method are used for solving the two-dimensional reaction-diffusion model. And the structure of the solutions is analyzed. Finally, the homotopy series solutions are simulated with the mathematical software Matlab, so the Turing patterns will be produced. Overall analysis and experimental simulation of the model show that the different parameters lead to different Turing pattern structures. As time goes on, the structure of Turing patterns changes, and the final solutions tend to stationary state.展开更多
This paper deals with an initial boundary value problem for the strongly coupledreaction-diffusion systems with a full matrix of diffusion coefficients. The global existence ofsolutions is proved by using the techniqu...This paper deals with an initial boundary value problem for the strongly coupledreaction-diffusion systems with a full matrix of diffusion coefficients. The global existence ofsolutions is proved by using the techniques based on invariant regions, Lyapunov functionalmethods, and local Lp prior estimates independent of time.展开更多
The asymptotic behaviour of solutions for general partly dissipative reaction-diffusion systems in Rn is studied. The asymptotic compactness of the solutions and then the existence of the global attractor are proved i...The asymptotic behaviour of solutions for general partly dissipative reaction-diffusion systems in Rn is studied. The asymptotic compactness of the solutions and then the existence of the global attractor are proved in L2(Rn )× L2(Rn ) .展开更多
In this paper we discuss the following nonlinear degenerate parabolic systems u_i=△a_i(u_i)+b_i(x,t,u_i)Du_i+f_i(x,t,u)for i = 1,2, …, m and u = (u_1,…, u_m) is a vector function, with Dirichlet boundary condition....In this paper we discuss the following nonlinear degenerate parabolic systems u_i=△a_i(u_i)+b_i(x,t,u_i)Du_i+f_i(x,t,u)for i = 1,2, …, m and u = (u_1,…, u_m) is a vector function, with Dirichlet boundary condition. Under some structure conditions on a_i,b_i and f_i and initial data u_i^o∈Li(Ω) for some pi>p_i^o = 1,2,…,m, the result on existence and uniquence of global solution is established.展开更多
In the one-dimensional space, traveling wave solutions of parabolic differential equations have been widely studied and well characterized. Recently, the mathematical study on higher-dimensional traveling fronts has a...In the one-dimensional space, traveling wave solutions of parabolic differential equations have been widely studied and well characterized. Recently, the mathematical study on higher-dimensional traveling fronts has attracted a lot of attention and many new types of nonplanar traveling waves have been observed for scalar reaction-diffusion equations with various nonlinearities. In this paper, by using the comparison argument and constructing appropriate super- and subsolutions, we study the existence, uniqueness and stability of three- dimensional traveling fronts of pyramidal shape for monotone bistable systems of reaction-diffusion equations in R3. The pyramidal traveling fronts are characterized as either a combination of planar traveling fronts on the lateral surfaces or a combination of two-dimensional V-form waves on the edges of the pyramid. In particular, our results are applicable to some important models in biology, such as Lotk,u-Volterra competition-diffusion systems with or without spatio-temporal delays, and reaction-diffusion systems of multiple obligate mutualists.展开更多
This paper is devoted to the investigation of stability for a class of coupled impulsive Markovian jump reaction-diffusion systems on networks(CIMJRDSNs). By using graph theory, a systematic method is provided to cons...This paper is devoted to the investigation of stability for a class of coupled impulsive Markovian jump reaction-diffusion systems on networks(CIMJRDSNs). By using graph theory, a systematic method is provided to construct global Lyapunov functions for the CIMJRDSNs. Based on Lyapunov functions and stochastic analysis method, some novel stability principles associated with the topology property of the networks are established.展开更多
This paper is concerned with the existence of entire solutions of some reaction-diffusion systems. We first consider Belousov-Zhabotinskii reaction model. Then we study a general model. Using the comparing argument an...This paper is concerned with the existence of entire solutions of some reaction-diffusion systems. We first consider Belousov-Zhabotinskii reaction model. Then we study a general model. Using the comparing argument and sub-super-solutions method, we obtain the existence of entire solutions which behave as two wavefronts coming from the both sides of x-axis, where an entire solution is meant by a classical solution defined for all space and time variables. At last, we give some examples to explain our results for the general models.展开更多
This work is concerned with the numerical simulations for two reactiondiffusion systems,i.e.,the Brusselator model and the Gray-Scott model.The numerical algorithm is based upon a moving finite element method which he...This work is concerned with the numerical simulations for two reactiondiffusion systems,i.e.,the Brusselator model and the Gray-Scott model.The numerical algorithm is based upon a moving finite element method which helps to resolve large solution gradients.High quality meshes are obtained for both the spot replication and the moving wave along boundaries by using proper monitor functions.Unlike[33],this work finds out the importance of the boundary grid redistribution which is particularly important for a class of problems for the Brusselator model.Several ways for verifying the quality of the numerical solutions are also proposed,which may be of important use for comparisons.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
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275065,12275064,12475203)the Natural Science Foundation of Hebei Province(Grant Nos.A2021201010 and A2024201020)+3 种基金Interdisciplinary Research Program of Natural Science of Hebei University(Grant No.DXK202108)Hebei Provincial Central Government Guiding Local Science and Technology Development Funds(Grant No.236Z1501G)Scientific Research and Innovation Team Foundation of Hebei University(Grant No.IT2023B03)the Excellent Youth Research Innovation Team of Hebei University(Grant No.QNTD202402)。
文摘A new type of localized oscillatory pattern is presented in a two-layer coupled reaction-diffusion system under conditions in which no Hopf instability can be discerned in either layer.The transitions from stationary patterns to asynchronous and synchronous oscillatory patterns are obtained.A novel method based on decomposing coupled systems into two associated subsystems has been proposed to elucidate the mechanism of formation of oscillating patterns.Linear stability analysis of the associated subsystems reveals that the Turing pattern in one layer induces the other layer locally,undergoes a supercritical Hopf bifurcation and gives rise to localized oscillations.It is found that the sizes and positions of oscillations are determined by the spatial distribution of the Turing patterns.When the size is large,localized traveling waves such as spirals and targets emerge.These results may be useful for deeper understanding of pattern formation in complex systems,particularly multilayered systems.
文摘In this paper, the problem of initial boundary value for nonlinear coupled reaction-diffusion systems arising in biochemistry, engineering and combustion_theory is considered.
基金National Natural Science Foundation of China under Grant Nos.10447007 and 10671156the Natural Science Foundation of Shaanxi Province of China under Grant No.2005A13
文摘Using the sign-invariant theory, we study the nonlinear reaction-diffusion systems. We also obtain some new explicit solutions to the nonlinear resulting systems.
文摘Boundary control for a class of partial integro-differential systems with space and time dependent coefficients is consid- ered. A control law is derived via the partial differential equation （PDE） backstepping. The existence of kernel equations is proved. Exponential stability of the closed-loop system is achieved. Simulation results are presented through figures.
文摘Differential method and homotopy analysis method are used for solving the two-dimensional reaction-diffusion model. And the structure of the solutions is analyzed. Finally, the homotopy series solutions are simulated with the mathematical software Matlab, so the Turing patterns will be produced. Overall analysis and experimental simulation of the model show that the different parameters lead to different Turing pattern structures. As time goes on, the structure of Turing patterns changes, and the final solutions tend to stationary state.
基金Supported by the Henan Innovation Project for University Prominent Research Talents (2003KJCX008)
文摘This paper deals with an initial boundary value problem for the strongly coupledreaction-diffusion systems with a full matrix of diffusion coefficients. The global existence ofsolutions is proved by using the techniques based on invariant regions, Lyapunov functionalmethods, and local Lp prior estimates independent of time.
文摘The asymptotic behaviour of solutions for general partly dissipative reaction-diffusion systems in Rn is studied. The asymptotic compactness of the solutions and then the existence of the global attractor are proved in L2(Rn )× L2(Rn ) .
基金Research supported by the Natural Science Foundation of Fujian Province Under Grant A92025.
文摘In this paper we discuss the following nonlinear degenerate parabolic systems u_i=△a_i(u_i)+b_i(x,t,u_i)Du_i+f_i(x,t,u)for i = 1,2, …, m and u = (u_1,…, u_m) is a vector function, with Dirichlet boundary condition. Under some structure conditions on a_i,b_i and f_i and initial data u_i^o∈Li(Ω) for some pi>p_i^o = 1,2,…,m, the result on existence and uniquence of global solution is established.
基金supported by National Natural Science Foundation of China (Grant Nos. 11371179 and 11271172)National Science Foundation of USA (Grant No. DMS-1412454)
文摘In the one-dimensional space, traveling wave solutions of parabolic differential equations have been widely studied and well characterized. Recently, the mathematical study on higher-dimensional traveling fronts has attracted a lot of attention and many new types of nonplanar traveling waves have been observed for scalar reaction-diffusion equations with various nonlinearities. In this paper, by using the comparison argument and constructing appropriate super- and subsolutions, we study the existence, uniqueness and stability of three- dimensional traveling fronts of pyramidal shape for monotone bistable systems of reaction-diffusion equations in R3. The pyramidal traveling fronts are characterized as either a combination of planar traveling fronts on the lateral surfaces or a combination of two-dimensional V-form waves on the edges of the pyramid. In particular, our results are applicable to some important models in biology, such as Lotk,u-Volterra competition-diffusion systems with or without spatio-temporal delays, and reaction-diffusion systems of multiple obligate mutualists.
基金supported by the National Natural Science Foundation of China under Grant Nos.61473097,11301090the State Key Program of Natural Science Foundation of China under Grant No.U1533202+2 种基金Shandong Independent Innovation and Achievements Transformation Fund under Grant No.2014CGZH1101Civil Aviation Administration of China under Grant No.MHRD20150104Guangxi Natural Science Foundation under Grant No.2016JJA110005
文摘This paper is devoted to the investigation of stability for a class of coupled impulsive Markovian jump reaction-diffusion systems on networks(CIMJRDSNs). By using graph theory, a systematic method is provided to construct global Lyapunov functions for the CIMJRDSNs. Based on Lyapunov functions and stochastic analysis method, some novel stability principles associated with the topology property of the networks are established.
文摘This paper is concerned with the existence of entire solutions of some reaction-diffusion systems. We first consider Belousov-Zhabotinskii reaction model. Then we study a general model. Using the comparing argument and sub-super-solutions method, we obtain the existence of entire solutions which behave as two wavefronts coming from the both sides of x-axis, where an entire solution is meant by a classical solution defined for all space and time variables. At last, we give some examples to explain our results for the general models.
基金The first and the third authors are partially supported by HKBU FRG grants and the Hong Kong Research Grant CouncilThe second author is partially supported by the Hong Kong RGC grant(No.201710).
文摘This work is concerned with the numerical simulations for two reactiondiffusion systems,i.e.,the Brusselator model and the Gray-Scott model.The numerical algorithm is based upon a moving finite element method which helps to resolve large solution gradients.High quality meshes are obtained for both the spot replication and the moving wave along boundaries by using proper monitor functions.Unlike[33],this work finds out the importance of the boundary grid redistribution which is particularly important for a class of problems for the Brusselator model.Several ways for verifying the quality of the numerical solutions are also proposed,which may be of important use for comparisons.
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.
