In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.展开更多
Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these netw...Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.展开更多
Wireless Power Transmission(WPT)has been widely used to replenish energy for various rechargeable devices.The ElectroMagnetic Radiation(EMR)of WPT has attracted great attention of safety concerns.It is possible for th...Wireless Power Transmission(WPT)has been widely used to replenish energy for various rechargeable devices.The ElectroMagnetic Radiation(EMR)of WPT has attracted great attention of safety concerns.It is possible for the malicious attacker to launch the EMR attack by capturing multiple wireless chargers.Little work has studied the EMR attack itself.In this paper,we propose a realistic EMR hazard model,which outputs the diminishing marginal hazard with EMR,with adjustable parameters to the target entities.We formulate three EMR attack models,termed Cumulative EMR Attack(CEA),Overall EMR Attack(OEA)and Unsafety EMR Attack(UEA),and propose the performance guaranteed algorithm of EMR attack for each model.We conduct extensive simulations and field experiments on a testbed.The results show that the proposed algorithms can output the near-optimal solution with much less running time than the optimal algorithms.The results of field experiments in a small testbed show that the utilities of CEAA and OEAA are increased by 70.5%and 12.9%than the comparison algorithms,respectively.Moreover,the number of captured chargers of UEAA is 5.9%less than the comparison algorithms.Our simulations also show the designed algorithms can perform better in a large-scale charging network.展开更多
Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be c...Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be captured back to the energy conversion of electrical energy,the whole process can be completed without physical contact energy transfer.The core mechanism is to build the energy coupling channel of the transmitter-receiver system,and realize the spatial power transmission through electromagnetic field interaction.In the electromagnetic induction coupled transmission system,the industrial frequency alternating current is converted into direct current by rectification and filtering,and then converted into high-frequency alternating current by high-frequency inverter.This current excites the primary side transmitting winding to generate a time-varying magnetic field,and through magnetic coupling in the secondary side receiving winding inductance electromotive force,and ultimately through the high-frequency rectifier and power regulation circuit to the load power supply.The essence of the process is to establish a transceiver double-ended resonant network,through the magnetic field resonance to achieve efficient energy exchange,and its transmission characteristics follow the laws of electromagnetic induction and the circuit resonance principle of double constraints.展开更多
This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity ...This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity rate of cells increased from 28.6±3.1%to 67.3±5.4%(P<0.001).In animal experiments,the terminal tumor volume in the light exposure group was 450±90 mm3,with a tumor inhibition rate of approximately 49.4%(P<0.001),and the median survival was extended to 32 days(compared to 24 days in the control group,P=0.004).Immunological tests revealed a significant increase in CD8+T cell infiltration(112±18 vs 52±10 cells/HPF,P<0.01),a 30%decrease in the proportion of Tregs(P<0.05),and an increase in the M1/M2 macrophage ratio to 1.8.The results suggest that the wireless optogenetic system can not only precisely regulate PD-L1 but also remodel the tumor immune microenvironment,providing a new approach for precise immunotherapy of GBM.展开更多
This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different...This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
文摘Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.
基金supported by National Natural Science Foundation of China(No.62372249,No.62072254)Jiangsu Graduate Scientific Research Innovation Program(No.KYCX210796).
文摘Wireless Power Transmission(WPT)has been widely used to replenish energy for various rechargeable devices.The ElectroMagnetic Radiation(EMR)of WPT has attracted great attention of safety concerns.It is possible for the malicious attacker to launch the EMR attack by capturing multiple wireless chargers.Little work has studied the EMR attack itself.In this paper,we propose a realistic EMR hazard model,which outputs the diminishing marginal hazard with EMR,with adjustable parameters to the target entities.We formulate three EMR attack models,termed Cumulative EMR Attack(CEA),Overall EMR Attack(OEA)and Unsafety EMR Attack(UEA),and propose the performance guaranteed algorithm of EMR attack for each model.We conduct extensive simulations and field experiments on a testbed.The results show that the proposed algorithms can output the near-optimal solution with much less running time than the optimal algorithms.The results of field experiments in a small testbed show that the utilities of CEAA and OEAA are increased by 70.5%and 12.9%than the comparison algorithms,respectively.Moreover,the number of captured chargers of UEAA is 5.9%less than the comparison algorithms.Our simulations also show the designed algorithms can perform better in a large-scale charging network.
文摘Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be captured back to the energy conversion of electrical energy,the whole process can be completed without physical contact energy transfer.The core mechanism is to build the energy coupling channel of the transmitter-receiver system,and realize the spatial power transmission through electromagnetic field interaction.In the electromagnetic induction coupled transmission system,the industrial frequency alternating current is converted into direct current by rectification and filtering,and then converted into high-frequency alternating current by high-frequency inverter.This current excites the primary side transmitting winding to generate a time-varying magnetic field,and through magnetic coupling in the secondary side receiving winding inductance electromotive force,and ultimately through the high-frequency rectifier and power regulation circuit to the load power supply.The essence of the process is to establish a transceiver double-ended resonant network,through the magnetic field resonance to achieve efficient energy exchange,and its transmission characteristics follow the laws of electromagnetic induction and the circuit resonance principle of double constraints.
文摘This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity rate of cells increased from 28.6±3.1%to 67.3±5.4%(P<0.001).In animal experiments,the terminal tumor volume in the light exposure group was 450±90 mm3,with a tumor inhibition rate of approximately 49.4%(P<0.001),and the median survival was extended to 32 days(compared to 24 days in the control group,P=0.004).Immunological tests revealed a significant increase in CD8+T cell infiltration(112±18 vs 52±10 cells/HPF,P<0.01),a 30%decrease in the proportion of Tregs(P<0.05),and an increase in the M1/M2 macrophage ratio to 1.8.The results suggest that the wireless optogenetic system can not only precisely regulate PD-L1 but also remodel the tumor immune microenvironment,providing a new approach for precise immunotherapy of GBM.
基金funded by Universiti Putra Malaysia under a Geran Putra Inisiatif(GPI)research grant with reference to GP-GPI/2023/9762100.
文摘This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications.
