To address efficient operation scheduling of shipboard helicopter groups under multi-mission demands and limited deck space,a novel Flexible Operation Mode(FOM)was proposed.Mission grouping,deck operation processes,an...To address efficient operation scheduling of shipboard helicopter groups under multi-mission demands and limited deck space,a novel Flexible Operation Mode(FOM)was proposed.Mission grouping,deck operation processes,and mission time were flexibilized to construct a mission planning method.From the perspective of the deck operation lifecycle,the scheduling problem was modeled as a six-stage mixed-integer program.A bi-level optimization framework was introduced,prioritizing maximization of mission time window satisfaction and secondarily minimizing mean deck operation time.Spatial evolution during the transportation phase was managed via an offline trajectory library that converted high-dimensional constraints into low-dimensional parameter mappings,significantly reducing real-time solution complexity.A Leader-Follower Particle Swarm Optimization(LFPSO)algorithm was developed,featuring a three-stage stochastic priority encoding and a mission-chain-driven launch-re-covery decoupling strategy to reduce decision coupling.A hierarchical population structure enhanced co-evolution of global search and local refinement.The case simulation results show that the proposed model and algorithm can effectively solve the deck operation scheduling problem in complex mission scenarios,and are significantly superior to the Continuous Operation Mode(COM)and the Fixed-process FOM(FFOM)in key performance indicators such as mission time window satisfaction,average deck operation time,and average mission flight time.Its effectiveness in enhancing system scheduling capability and performance stability has been verified.This research provides systematic support for the flexible construction and intelligent decision-making of ship aviation operation systems.展开更多
In China,gas storage in deep salt caverns faces challenges due to high in situ stresses,elevated geothermal temperatures,and the presence of interbedded salt-mudstone formations.These factors lead to heterogeneous def...In China,gas storage in deep salt caverns faces challenges due to high in situ stresses,elevated geothermal temperatures,and the presence of interbedded salt-mudstone formations.These factors lead to heterogeneous deformation and stress concentration,which adversely affect the stability and sealing capacity of salt caverns.To address these issues,this study systematically investigates the differences in the mechanical responses of a dual-cavern system located in a representative deep salt district under synchronous and asynchronous injection-production processes.The impacts of key operating parameters on the long-term deformation evolution of salt caverns under thermo-mechanical coupling are examined,and the effectiveness of the asynchronous operation strategy in optimizing the cavern stability is quantitatively evaluated.The results demonstrate that asynchronous operation significantly enhances the stability of the inter-cavern pillar.Specifically,this strategy disrupts the connection between zones with high stress-to-strength ratios,thereby reducing the risk of coupled failure between the two salt caverns.Furthermore,this strategy improves the distribution of the dilatancy safety factor of the surrounding rocks.Asynchronous operation also performs well in mitigating long-term deformation of the salt caverns,resulting in a lower risk of unilateral pillar instability,reduced cavern roof subsidence,and diminished volume shrinkage.Notably,asynchronous operation can effectively suppress cavern deformation under high-frequency injection-production cycles.Increasing the operating rate and decreasing the minimum pressure result in decelerating and accelerating deformation trends,respectively.Sensitivity analysis identifies the minimum pressure as the primary factor directly controlling cavern deformation,while operating frequency benefits most from the adoption of an asynchronous operation strategy.Overall,the findings of this study are expected to advance the construction and operational optimization of deep salt caverns for gas storage in China.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
In the domain of quantum error correction,a critical task involves identifying logical operations on logical qubits for various quantum codes.However,owing to the inherent complexity of many quantum codes,devising an ...In the domain of quantum error correction,a critical task involves identifying logical operations on logical qubits for various quantum codes.However,owing to the inherent complexity of many quantum codes,devising an efficient method to implement the desired logical operations utilizing the structure of these codes presents a significant challenge.In previous studies,several methods were used to realize specific logical operations for certain quantum codes;however,they usually do not work for other quantum codes.展开更多
Accurate calibration of the beam phase(i.e.,the phase of the beam arrival relative to the cavity accelerating field)is essential for maintaining the stability and efficiency of linear accelerators.Conventional offline...Accurate calibration of the beam phase(i.e.,the phase of the beam arrival relative to the cavity accelerating field)is essential for maintaining the stability and efficiency of linear accelerators.Conventional offline phase-scan methods,such as theΔT phase scan and phase-scan signature matching,are typically performed during commissioning or maintenance,requiring the accelerator to be taken out of normal operation.Moreover,these methods cannot effectively track the gradual drifts caused by ambient conditions.An online beam phase calibration technique using beam-induced radio-frequency(RF)transients was initially developed at DESY for superconducting cavities operating under open-loop conditions.Extending the DESY method to normal-conducting cavities at the European Spallation Source(ESS)introduces challenges.When the beam pulse length approaches the cavity time constantτ=1∕ω0.5,whereω0.5is the cavity half bandwidth,the detuning effects distort the trajectory of the beam-induced RF transient and degrade the beam phase measurement accuracy.Furthermore,open-loop operation is generally not advisable for high-current proton linacs because of stability and safety concerns associated with the operation.To address these issues,we revisited the cavity differential equations and proposed a detuning compensation method that corrects the distorted trajectory in the in-phase/quadrature plane of the laser beam.In addition,by analyzing the initial 1.4μs transient response before low-level RF(LLRF)feedback becomes active,beam phase calibration can be achieved under closed-loop operation.The experimental results indicate that the proposed method agrees well with beam position monitor(BPM)-based measurements.This approach enables real-time beam phase monitoring without interrupting the closed-loop operation and can be adapted to similar accelerator systems.展开更多
Human-machine collaboration is a key feature of Single Pilot Operations(SPO).With only a single pilot in the cockpit,workload monitoring and adjustment become even more critical compared to Dual-Pilot Operations(DPO)....Human-machine collaboration is a key feature of Single Pilot Operations(SPO).With only a single pilot in the cockpit,workload monitoring and adjustment become even more critical compared to Dual-Pilot Operations(DPO).Hence,a dynamic function allocation mechanism must be established—increasing the Level of Automation(LOA)under high workload conditions and reducing it under low workload conditions to maintain situational awareness.To address the challenges of excessive subjectivity and limited knowledge transfer in the existing dynamic function allocation methods,this paper proposes a dynamic function allocation method based on Bayesianenhanced Q-Learning(BQL).First,a Bayesian Network(BN)is constructed to predict HumanMachine System(HMS)performance,determining when reallocation should be triggered.Compared to the existing trigger mechanisms,this approach enables earlier activation while maintaining non-intrusive.Then,the BN-predicted HMS performance is integrated into the reward feedback for the reinforcement learning algorithm,allowing the system to continuously refine its strategy through interaction with the environment.Finally,flight experiments conducted in a low-fidelity SPO simulator,incorporating both objective physiological monitoring and subjective assessments,validate the effectiveness of the proposed method.展开更多
Over the past decades,rapid diagnostic tests(RDTs)have become the most widely deployed diagnostic tool,enabling timely treatment in resource-limited and remote settings[1].Their reliability,however,depends on rigorous...Over the past decades,rapid diagnostic tests(RDTs)have become the most widely deployed diagnostic tool,enabling timely treatment in resource-limited and remote settings[1].Their reliability,however,depends on rigorous quality assurance frameworks,with the World Health Organization(WHO)-endorsed quality control panels serving as the cornerstone for monitoring RDT performance and ensuring diagnostic fidelity across diverse epidemiological landscapes[2].Quality control panels are standardized,parasite-based reference materials used to evaluate antigen detection by RDTs under controlled conditions.They play an essential role in detecting lot-to-lot variations,guiding procurement decisions,and safeguarding programmatic confidence in RDTs[3].Despite this centrality,the practical and operational realities of quality control panel preparation in malaria-endemic regions remain underexplored.展开更多
Integrating renewable energy sources presents technical challenges due to their variable nature,particularly in predicting and managing microgrid operational modes.Accurate identification of grid statesinterconnected ...Integrating renewable energy sources presents technical challenges due to their variable nature,particularly in predicting and managing microgrid operational modes.Accurate identification of grid statesinterconnected or islanded—is essential for maintaining stability and optimizing performance under fluctuating environmental conditions to meet energy demand.This work proposes a bio-inspired,optimized binary classification model based on Multi-Layer Perceptron Artificial Neural Networks(MLP-ANN),with the architecture and hyperparameters tuned using the novel Mosquito Mating Swarm Optimization(MMSO)algorithm,inspired by mosquito mating behavior and swarm dynamics.The model employs an MLP-ANN with a variable number of hidden layers and neurons per layer,configured to maximize classification accuracy by dynamically adjusting parameters,including the learning rate and regularization coefficients.Training utilizes k-fold cross-validation on experimental microgrid data.The MMSO approach is benchmarked against Particle Swarm Optimization(PSO),Genetic Algorithm(GA),and Grey Wolf Optimizer(GWO)to validate its effectiveness.Results show that the MMSO-optimized MLP-ANN achieved an 86.34%recall,98.96%precision,and 92.29%accuracy,while minimizing the Mean Squared Error to 0.0206.The MMSO-optimized MLP-ANN model achieved competitive classification performance compared to the other algorithms evaluated;although no statistically significant differences in recall were observed among the optimizers(p=0.22),the MMSO achieved the lowest MSE(0.0206).The MMSO was the only algorithm capable of discovering a four-layer architecture hidden within the same search space,evidencing superior exploration of deeper architectural regions of the solution space.These findings demonstrate the model's capacity to predict microgrid operational modes under variable conditions,highlighting the potential of integrating bio-inspired algorithms with neural networks for energy management systems.This approach could enhance the efficiency and reliability of integrating renewable energy sources into dynamic energy systems.展开更多
This one-hour webinar is a presentation of the new CEN Technical Specification for the exchange format of operational raw data in support of the“observed data”category of the MMTIS EU delegated regulation.
Gas-fired power plants in Jiangsu Province are characterized by large installed capacity,concentrated geographic distribution,and prominent peak-shaving functions,making them a critical source of flexible support for ...Gas-fired power plants in Jiangsu Province are characterized by large installed capacity,concentrated geographic distribution,and prominent peak-shaving functions,making them a critical source of flexible support for the regional power system.Currently,these plants face significant operational pressure due to a combination of factors,including high volatility in power generation output,elevated gas prices and operating costs,inadequate price transmission between gas and electricity markets,and an underdeveloped electricity pricing mechanism.This paper analyzes the operational characteristics and practical challenges of gas-fired power plants in Jiangsu Province,and proposes countermeasures in terms of policy optimization,mechanism innovation,and upstream-downstream coordination,with a view to supporting power security and advancing the low-carbon energy transition.展开更多
On December 18,2025, Hainan Free Trade Port (Hainan FTP) officially began islandwide special customs operations.Although only two months have passed since this landmark step, the shift is already visible everywhere—f...On December 18,2025, Hainan Free Trade Port (Hainan FTP) officially began islandwide special customs operations.Although only two months have passed since this landmark step, the shift is already visible everywhere—from the bustling flow of international passengers at Haikou Meilan International Airport to the steady stream of cargo vessels calling at Yangpu Port, and even in the sustained attention investors are paying to “Hainan-related” stocks.Together, these signals point to one clear conclusion:China’s largest special economic zone has entered a new phase of development.展开更多
Objective:Taking the reform of the Diagnosis-Related Groups(DRG)payment system for medical insurance as an opportunity,we aim to construct a closed-loop management system for lean hospital operations under the trustee...Objective:Taking the reform of the Diagnosis-Related Groups(DRG)payment system for medical insurance as an opportunity,we aim to construct a closed-loop management system for lean hospital operations under the trusteeship of urban medical groups,thereby promoting high-quality hospital development.Methods:Led by the Medical Insurance DRG Management Committee,we established a closed-loop MDT-DRG management system,data analysis system,pharmaceutical and consumable management system,discipline construction management system,and standardized medical record front page filling management system.These measures enabled refined operational management,fostering high-quality hospital development.Results:After the trusteeship of Qingdao Municipal Hospital from 2024 to 2025,leveraging the reform of the medical insurance DRG payment system,combined with the integration of medical disciplines and improved performance management,lean operational management effectively achieved six improvements(15.25%year-on-year increase in outpatient and emergency visits,7.62%increase in discharges,50.08%increase in surgeries,71.89%increase in Level IV surgeries,10.76%increase in Case Mix Index,and 45.99%increase in cases with weights>2),two reductions(41.18%decrease in average inpatient drug costs and 28.69%decrease in average outpatient drug costs),and one innovation(78.92%year-on-year increase in Level IV surgeries for national examinations).Conclusion:This effectively promoted the overall operational efficiency and competitiveness of the hospital,laying a solid foundation for the establishment of a tertiary hospital and achieving the goal of satisfaction for the government,hospital,medical insurance,and patients.展开更多
Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operato...Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.展开更多
With over 1.3 billion people worldwide facing irregular water access,efficient water management is a global priority.This study presented a comprehensive approach for optimizing the operation of intermittent water dis...With over 1.3 billion people worldwide facing irregular water access,efficient water management is a global priority.This study presented a comprehensive approach for optimizing the operation of intermittent water distribution networks through the creation of district metered areas(DMAs).It advanced traditional DMA design by integrating network partitioning with optimized operational schedules,offering a practical framework for managing intermittent water supply systems.The proposed methodology aims to reduce water losses while improving service equity and quality.First,the network is partitioned using the fast-greedy community detection algorithm based on modularity from graph theory,enabling DMAs to operate independently at different times of a day.Flow control valves are installed at DMA entry points,while isolation valves isolate remaining boundary pipes,enhancing operational flexibility.Second,the particle swarm optimization algorithm optimizes the operational schedule of each DMA and determines the optimal start time and water supply duration for each DMA.This step minimizes total daily distributed volume while ensuring adequate service.This approach reduced the daily distributed volume of the Modena network by approximately 720.0 m3 and significantly decreased the leakage rate from 30.5% to 18.7%,demonstrating its effectiveness.展开更多
Space manipulators are crucial for conducting various space missions.To accurately simulate these operations on Earth,this paper presents a full-physical simulation system and corresponding method based on disturbance...Space manipulators are crucial for conducting various space missions.To accurately simulate these operations on Earth,this paper presents a full-physical simulation system and corresponding method based on disturbance moment identification,addressing the issue of incomplete gravity unloading in space dexterous operations.Full-physical simulation is the comprehensive modeling of real-world physical interactions such as motion,forces,and collisions in a virtual environment with high fidelity and accuracy.The system’s hardware configuration is introduced first.Then an innovative full-physical method is proposed mainly consisting of the modeling and optimization of disturbance moment(force).The disturbance moment(force)model is optimized to enhance full-physical simulation accuracy.The control framework gives the system framework and signal flows.Numerical simulations are done to verify the optimization process.Interior point method is utilized to decrease the disturbance moment enormously and to reduce the largest joint moment significantly.Multi-objective particle swarm optimization is then implemented to achieve optimal unloading forces.Finally,experiments confirm the effectiveness of the proposed fullphysical methodology from two aspects:the verification of the identification method and that of optimization method.展开更多
The air conditioning manufacturing industry is characterized by discrete manufacturing features including multiple processes,a wide variety of products,small batch sizes and rapid production cycles.Traditional product...The air conditioning manufacturing industry is characterized by discrete manufacturing features including multiple processes,a wide variety of products,small batch sizes and rapid production cycles.Traditional production lines have been rendered insufficient to meet the rapidly evolving market demands concerning flexibility,efficiency,quality and resource management.To address this challenge,an intelligent production line and operational model has been proposed and validated for air conditioning manufacturing,based on the concept of data-driven,system-integrated,and intelligently-scheduled operations.First,three core hypotheses were formulated based on theoretical considerations.An integrated technical framework was subsequently established,incorporating a cyber-physical system architecture,core assembly processes,four sub-production line systems and an intelligent maintenance platform.Key innovations were implemented in technologies including radio frequency identification traceability,artificial intelligence visual inspection,automated equipment integration,Internet of Things sensing networks,as well as an integrated air-ground coordinated transportation system.Through comparative studies with traditional air conditioner production lines,the intelligent production line was shown to significantly outperform traditional systems in production capacity:daily output increased by 57.6%,cycle time was reduced by 57.6%,workforce requirements decreased by 57.4%and unit per person per hour improved to 3.8 times the original level.Additionally,lighting energy consumption was reduced by an average of 60%and the system achieved substantial improvements in efficiency across six dimensions.The established intelligent air conditioner production line model not only effectively validated the research hypotheses and addressed critical limitations of traditional production lines but also provided theoretical support and technical pathways for the intelligent transformation of the discrete manufacturing industry,demonstrating considerable engineering application value and promotion potential.展开更多
In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm ...In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.展开更多
Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardwar...Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardware implementations face two main problems,including wasted area resources and excessive critical path delay.These issues limit the energy efficiency and integration level of stream cipher chips.To address these problems,this paper proposes an energy-efficient design method for a 64-bit Boolean function reconfigurable operation unit(BFROU),aiming to improve the computational efficiency of Boolean functions in stream ciphers.To optimize the design of BFROU,this paper takes the NPN equivalence theory as a guide.First,customized designs at the transistor level were performed for both 2-and 3-variable RM logic units(denoted as TRM).On this basis,this paper uses the port sharing strategy to further optimize the design of 4-to-6-variable TRM logic units and construct a multi-variable TRM process library.Then,by combining multi-variable TRM logic units with the mathematical definition of Boolean functions,this paper proposes a theoretical model of BFROU.Based on this model and combined with the statistical analysis results of Boolean functions,the optimal TRM unit configuration is determined,and the overall optimization of the 64-bit BFROU is finally completed.Experimental results show that when TRM-3 and TRM-4 units are mixed as the first-level operation module of BFROU,its area-delay product(ADP)reaches the minimum.The 64-bit BFROU unit implemented according to this scheme has an actual measured area of 137.28μm2 and a critical path delay of 0.278 ns under the SMIC 40 nm typical process corner.This unit supports Boolean function operations with up to 64 variables,and 94.4%of the functions can complete mapping within 2 iterations.Compared with existing schemes such as look-up table(LUT)architecture and And-Inverter Cone(AIC)array,the BFROU proposed in this paper has obvious advantages in area,delay,ADP and number of iterations,providing effective hardware support for the design of high-energy-efficiency stream cipher chips.展开更多
The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling tec...The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling technologies into TPUs has the potential to improve their operational flexibility and regulation capability.However,existing research seldom investigates the combined effects of MSTS retrofitting and thermal-electric output coupling on short-term dispatchability,especially under rapid load variation conditions.This study proposes a comprehensive modeling and multi-timescale optimization framework for MSTS-retrofitted TPUs with rapid load variation capability,enabling coordinated thermal and electrical dispatch in both day-ahead and real-time stages.The TPU model incorporates steam heating,electric heating,MSTS charge and discharge characteristics,and ladder typer ramping constraints,enabling detailed representation of thermal-electric coupling interactions.The proposed scheduling framework consists of a day-ahead economic dispatch model and a minute-level intraday rolling optimization.In the day-ahead stage,the model maximizes operational revenue while considering flexibility reserve requirements,multi-period peak shaving,reserve allocation,and thermal-electric coupling strategies that coordinate steam and electric heating with MSTS charging and discharging.In the intraday rolling stage,real-time RES fluctuations and load variations are incorporated to update dispatch decisions,ensuring continuous power–heat balance and efficient use of stored thermal energy.Simulation results verify that thermal-electric coupling enhances the system’s capability to maintain real-time power balance,while MSTS operation effectively mitigates output fluctuations and supports stable,economical operation for addressing RES variation.展开更多
The non-selective oxidation of NH3at CO oxidation sites is a major limitation for bifunctional catalysts used in NH3-selective catalytic reduction and CO oxidation.This issue restricts these catalysts from achie...The non-selective oxidation of NH3at CO oxidation sites is a major limitation for bifunctional catalysts used in NH3-selective catalytic reduction and CO oxidation.This issue restricts these catalysts from achieving a wide operational temperature window,where both NOxand CO conversions exceed 90%,thus hindering their industrial application.Herein,we propose a novel strategy to expand the temperature window of bifunctional catalysts.By exploiting the synergistic effects of interfacial electron regulation and spatial decoupling of acid sites,we demonstrate that the CuO/Cu-SSZ-13 catalyst achieves an unprecedented operational window(200–425℃),surpassing previously reported results.Our investigation reveals a new mechanism of bifunctional synergy,driven by Cu–O bond reconstruction at the interface and the preferential anchoring of Brönsted acid sites on NH3.This mechanism mitigates the non-selective oxidation of NH3,thereby extending the catalyst’s temperature window.This work provides a new design paradigm for bifunctional catalysts,facilitating broader operational temperature windows and advancing the field.展开更多
基金supported in part by the National Natural Sci-ence Foundation of China(No.62403486)in part by the Young Elite Scientists Sponsorship Program by CAST.
摘要To address efficient operation scheduling of shipboard helicopter groups under multi-mission demands and limited deck space,a novel Flexible Operation Mode(FOM)was proposed.Mission grouping,deck operation processes,and mission time were flexibilized to construct a mission planning method.From the perspective of the deck operation lifecycle,the scheduling problem was modeled as a six-stage mixed-integer program.A bi-level optimization framework was introduced,prioritizing maximization of mission time window satisfaction and secondarily minimizing mean deck operation time.Spatial evolution during the transportation phase was managed via an offline trajectory library that converted high-dimensional constraints into low-dimensional parameter mappings,significantly reducing real-time solution complexity.A Leader-Follower Particle Swarm Optimization(LFPSO)algorithm was developed,featuring a three-stage stochastic priority encoding and a mission-chain-driven launch-re-covery decoupling strategy to reduce decision coupling.A hierarchical population structure enhanced co-evolution of global search and local refinement.The case simulation results show that the proposed model and algorithm can effectively solve the deck operation scheduling problem in complex mission scenarios,and are significantly superior to the Continuous Operation Mode(COM)and the Fixed-process FOM(FFOM)in key performance indicators such as mission time window satisfaction,average deck operation time,and average mission flight time.Its effectiveness in enhancing system scheduling capability and performance stability has been verified.This research provides systematic support for the flexible construction and intelligent decision-making of ship aviation operation systems.
基金supported by the National Natural Science Foundation of China(Grant No.U24B2038)Scientific and technological research projects in Sichuan province(Grant No.2025NSFTD0012,2024YFHZ0286)Hebei Natural Science Foundation(Grant No.E2024508032).
摘要In China,gas storage in deep salt caverns faces challenges due to high in situ stresses,elevated geothermal temperatures,and the presence of interbedded salt-mudstone formations.These factors lead to heterogeneous deformation and stress concentration,which adversely affect the stability and sealing capacity of salt caverns.To address these issues,this study systematically investigates the differences in the mechanical responses of a dual-cavern system located in a representative deep salt district under synchronous and asynchronous injection-production processes.The impacts of key operating parameters on the long-term deformation evolution of salt caverns under thermo-mechanical coupling are examined,and the effectiveness of the asynchronous operation strategy in optimizing the cavern stability is quantitatively evaluated.The results demonstrate that asynchronous operation significantly enhances the stability of the inter-cavern pillar.Specifically,this strategy disrupts the connection between zones with high stress-to-strength ratios,thereby reducing the risk of coupled failure between the two salt caverns.Furthermore,this strategy improves the distribution of the dilatancy safety factor of the surrounding rocks.Asynchronous operation also performs well in mitigating long-term deformation of the salt caverns,resulting in a lower risk of unilateral pillar instability,reduced cavern roof subsidence,and diminished volume shrinkage.Notably,asynchronous operation can effectively suppress cavern deformation under high-frequency injection-production cycles.Increasing the operating rate and decreasing the minimum pressure result in decelerating and accelerating deformation trends,respectively.Sensitivity analysis identifies the minimum pressure as the primary factor directly controlling cavern deformation,while operating frequency benefits most from the adoption of an asynchronous operation strategy.Overall,the findings of this study are expected to advance the construction and operational optimization of deep salt caverns for gas storage in China.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
摘要This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Natural Science Foundation of China(Grant Nos.12474486,12234002,and 92250303)the National Key Research and Development Program of China(Grant No.2024YFA1612101)。
摘要In the domain of quantum error correction,a critical task involves identifying logical operations on logical qubits for various quantum codes.However,owing to the inherent complexity of many quantum codes,devising an efficient method to implement the desired logical operations utilizing the structure of these codes presents a significant challenge.In previous studies,several methods were used to realize specific logical operations for certain quantum codes;however,they usually do not work for other quantum codes.
基金supported by the studies of intelligent LLRF control algorithms for superconducting RF cavities(No.E129851YR0)the National Natural Science Foundation of China(No.U22A20261)R&D of Intelligent Technologies for Next-Generation Industrial Linear Accelerators(HNN25XMMXWL)。
摘要Accurate calibration of the beam phase(i.e.,the phase of the beam arrival relative to the cavity accelerating field)is essential for maintaining the stability and efficiency of linear accelerators.Conventional offline phase-scan methods,such as theΔT phase scan and phase-scan signature matching,are typically performed during commissioning or maintenance,requiring the accelerator to be taken out of normal operation.Moreover,these methods cannot effectively track the gradual drifts caused by ambient conditions.An online beam phase calibration technique using beam-induced radio-frequency(RF)transients was initially developed at DESY for superconducting cavities operating under open-loop conditions.Extending the DESY method to normal-conducting cavities at the European Spallation Source(ESS)introduces challenges.When the beam pulse length approaches the cavity time constantτ=1∕ω0.5,whereω0.5is the cavity half bandwidth,the detuning effects distort the trajectory of the beam-induced RF transient and degrade the beam phase measurement accuracy.Furthermore,open-loop operation is generally not advisable for high-current proton linacs because of stability and safety concerns associated with the operation.To address these issues,we revisited the cavity differential equations and proposed a detuning compensation method that corrects the distorted trajectory in the in-phase/quadrature plane of the laser beam.In addition,by analyzing the initial 1.4μs transient response before low-level RF(LLRF)feedback becomes active,beam phase calibration can be achieved under closed-loop operation.The experimental results indicate that the proposed method agrees well with beam position monitor(BPM)-based measurements.This approach enables real-time beam phase monitoring without interrupting the closed-loop operation and can be adapted to similar accelerator systems.
摘要Human-machine collaboration is a key feature of Single Pilot Operations(SPO).With only a single pilot in the cockpit,workload monitoring and adjustment become even more critical compared to Dual-Pilot Operations(DPO).Hence,a dynamic function allocation mechanism must be established—increasing the Level of Automation(LOA)under high workload conditions and reducing it under low workload conditions to maintain situational awareness.To address the challenges of excessive subjectivity and limited knowledge transfer in the existing dynamic function allocation methods,this paper proposes a dynamic function allocation method based on Bayesianenhanced Q-Learning(BQL).First,a Bayesian Network(BN)is constructed to predict HumanMachine System(HMS)performance,determining when reallocation should be triggered.Compared to the existing trigger mechanisms,this approach enables earlier activation while maintaining non-intrusive.Then,the BN-predicted HMS performance is integrated into the reward feedback for the reinforcement learning algorithm,allowing the system to continuously refine its strategy through interaction with the environment.Finally,flight experiments conducted in a low-fidelity SPO simulator,incorporating both objective physiological monitoring and subjective assessments,validate the effectiveness of the proposed method.
摘要Over the past decades,rapid diagnostic tests(RDTs)have become the most widely deployed diagnostic tool,enabling timely treatment in resource-limited and remote settings[1].Their reliability,however,depends on rigorous quality assurance frameworks,with the World Health Organization(WHO)-endorsed quality control panels serving as the cornerstone for monitoring RDT performance and ensuring diagnostic fidelity across diverse epidemiological landscapes[2].Quality control panels are standardized,parasite-based reference materials used to evaluate antigen detection by RDTs under controlled conditions.They play an essential role in detecting lot-to-lot variations,guiding procurement decisions,and safeguarding programmatic confidence in RDTs[3].Despite this centrality,the practical and operational realities of quality control panel preparation in malaria-endemic regions remain underexplored.
基金supported by the PROSNII 2025 program granted by the University of Guadalajara to Jesus Aguila-LeonIn addition,the research was supported by the Vicerrectorado de Investigacion of the Universitat Politecnica de Valencia through the PAID-11-25 program.
摘要Integrating renewable energy sources presents technical challenges due to their variable nature,particularly in predicting and managing microgrid operational modes.Accurate identification of grid statesinterconnected or islanded—is essential for maintaining stability and optimizing performance under fluctuating environmental conditions to meet energy demand.This work proposes a bio-inspired,optimized binary classification model based on Multi-Layer Perceptron Artificial Neural Networks(MLP-ANN),with the architecture and hyperparameters tuned using the novel Mosquito Mating Swarm Optimization(MMSO)algorithm,inspired by mosquito mating behavior and swarm dynamics.The model employs an MLP-ANN with a variable number of hidden layers and neurons per layer,configured to maximize classification accuracy by dynamically adjusting parameters,including the learning rate and regularization coefficients.Training utilizes k-fold cross-validation on experimental microgrid data.The MMSO approach is benchmarked against Particle Swarm Optimization(PSO),Genetic Algorithm(GA),and Grey Wolf Optimizer(GWO)to validate its effectiveness.Results show that the MMSO-optimized MLP-ANN achieved an 86.34%recall,98.96%precision,and 92.29%accuracy,while minimizing the Mean Squared Error to 0.0206.The MMSO-optimized MLP-ANN model achieved competitive classification performance compared to the other algorithms evaluated;although no statistically significant differences in recall were observed among the optimizers(p=0.22),the MMSO achieved the lowest MSE(0.0206).The MMSO was the only algorithm capable of discovering a four-layer architecture hidden within the same search space,evidencing superior exploration of deeper architectural regions of the solution space.These findings demonstrate the model's capacity to predict microgrid operational modes under variable conditions,highlighting the potential of integrating bio-inspired algorithms with neural networks for energy management systems.This approach could enhance the efficiency and reliability of integrating renewable energy sources into dynamic energy systems.
摘要This one-hour webinar is a presentation of the new CEN Technical Specification for the exchange format of operational raw data in support of the“observed data”category of the MMTIS EU delegated regulation.
摘要Gas-fired power plants in Jiangsu Province are characterized by large installed capacity,concentrated geographic distribution,and prominent peak-shaving functions,making them a critical source of flexible support for the regional power system.Currently,these plants face significant operational pressure due to a combination of factors,including high volatility in power generation output,elevated gas prices and operating costs,inadequate price transmission between gas and electricity markets,and an underdeveloped electricity pricing mechanism.This paper analyzes the operational characteristics and practical challenges of gas-fired power plants in Jiangsu Province,and proposes countermeasures in terms of policy optimization,mechanism innovation,and upstream-downstream coordination,with a view to supporting power security and advancing the low-carbon energy transition.
摘要On December 18,2025, Hainan Free Trade Port (Hainan FTP) officially began islandwide special customs operations.Although only two months have passed since this landmark step, the shift is already visible everywhere—from the bustling flow of international passengers at Haikou Meilan International Airport to the steady stream of cargo vessels calling at Yangpu Port, and even in the sustained attention investors are paying to “Hainan-related” stocks.Together, these signals point to one clear conclusion:China’s largest special economic zone has entered a new phase of development.
摘要Objective:Taking the reform of the Diagnosis-Related Groups(DRG)payment system for medical insurance as an opportunity,we aim to construct a closed-loop management system for lean hospital operations under the trusteeship of urban medical groups,thereby promoting high-quality hospital development.Methods:Led by the Medical Insurance DRG Management Committee,we established a closed-loop MDT-DRG management system,data analysis system,pharmaceutical and consumable management system,discipline construction management system,and standardized medical record front page filling management system.These measures enabled refined operational management,fostering high-quality hospital development.Results:After the trusteeship of Qingdao Municipal Hospital from 2024 to 2025,leveraging the reform of the medical insurance DRG payment system,combined with the integration of medical disciplines and improved performance management,lean operational management effectively achieved six improvements(15.25%year-on-year increase in outpatient and emergency visits,7.62%increase in discharges,50.08%increase in surgeries,71.89%increase in Level IV surgeries,10.76%increase in Case Mix Index,and 45.99%increase in cases with weights>2),two reductions(41.18%decrease in average inpatient drug costs and 28.69%decrease in average outpatient drug costs),and one innovation(78.92%year-on-year increase in Level IV surgeries for national examinations).Conclusion:This effectively promoted the overall operational efficiency and competitiveness of the hospital,laying a solid foundation for the establishment of a tertiary hospital and achieving the goal of satisfaction for the government,hospital,medical insurance,and patients.
基金support of the“Pioneer”and“Leading Goose”Research&Development Program of Zhejiang(2024C01028)the State Key Laboratory of Industrial Control Technology,China(ICT2024C04)are gratefully acknowledged.
摘要Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.
基金supported by the Brazilian National Council for Scientific and Technological Development(CNPq)(Grants No.306087/2022-7 and 404605/2021-4).
摘要With over 1.3 billion people worldwide facing irregular water access,efficient water management is a global priority.This study presented a comprehensive approach for optimizing the operation of intermittent water distribution networks through the creation of district metered areas(DMAs).It advanced traditional DMA design by integrating network partitioning with optimized operational schedules,offering a practical framework for managing intermittent water supply systems.The proposed methodology aims to reduce water losses while improving service equity and quality.First,the network is partitioned using the fast-greedy community detection algorithm based on modularity from graph theory,enabling DMAs to operate independently at different times of a day.Flow control valves are installed at DMA entry points,while isolation valves isolate remaining boundary pipes,enhancing operational flexibility.Second,the particle swarm optimization algorithm optimizes the operational schedule of each DMA and determines the optimal start time and water supply duration for each DMA.This step minimizes total daily distributed volume while ensuring adequate service.This approach reduced the daily distributed volume of the Modena network by approximately 720.0 m3 and significantly decreased the leakage rate from 30.5% to 18.7%,demonstrating its effectiveness.
基金supported by the National Natural Science Foundation of China(52175022)the National Key Research and Development Program of China(2024YFB4006503).
摘要Space manipulators are crucial for conducting various space missions.To accurately simulate these operations on Earth,this paper presents a full-physical simulation system and corresponding method based on disturbance moment identification,addressing the issue of incomplete gravity unloading in space dexterous operations.Full-physical simulation is the comprehensive modeling of real-world physical interactions such as motion,forces,and collisions in a virtual environment with high fidelity and accuracy.The system’s hardware configuration is introduced first.Then an innovative full-physical method is proposed mainly consisting of the modeling and optimization of disturbance moment(force).The disturbance moment(force)model is optimized to enhance full-physical simulation accuracy.The control framework gives the system framework and signal flows.Numerical simulations are done to verify the optimization process.Interior point method is utilized to decrease the disturbance moment enormously and to reduce the largest joint moment significantly.Multi-objective particle swarm optimization is then implemented to achieve optimal unloading forces.Finally,experiments confirm the effectiveness of the proposed fullphysical methodology from two aspects:the verification of the identification method and that of optimization method.
基金supported by the National Natural Science Foundation of China(52375447 and 52305477)the Shandong Provincial Natural Science Foundation of China(ZR2023QE057,ZR2024QE100,and ZR2024ME255)+3 种基金the Shandong Provincial Science and Technology SMEs Innovation Capacity Improvement Project,China(2024TSGC0239 and 2024TSGC0237)the Special Fund of Taishan Scholars Projectthe Shandong Province Youth Science and Technology Talent Support Project,China(SDAST2024QTA043)the Open Funding of Key Laboratory of Industrial Fluid Energy Conservation and Pollution Control,Ministry of Education,China(CK-2024-0031,CK-2024-0035,and CK-2024-0036)。
摘要The air conditioning manufacturing industry is characterized by discrete manufacturing features including multiple processes,a wide variety of products,small batch sizes and rapid production cycles.Traditional production lines have been rendered insufficient to meet the rapidly evolving market demands concerning flexibility,efficiency,quality and resource management.To address this challenge,an intelligent production line and operational model has been proposed and validated for air conditioning manufacturing,based on the concept of data-driven,system-integrated,and intelligently-scheduled operations.First,three core hypotheses were formulated based on theoretical considerations.An integrated technical framework was subsequently established,incorporating a cyber-physical system architecture,core assembly processes,four sub-production line systems and an intelligent maintenance platform.Key innovations were implemented in technologies including radio frequency identification traceability,artificial intelligence visual inspection,automated equipment integration,Internet of Things sensing networks,as well as an integrated air-ground coordinated transportation system.Through comparative studies with traditional air conditioner production lines,the intelligent production line was shown to significantly outperform traditional systems in production capacity:daily output increased by 57.6%,cycle time was reduced by 57.6%,workforce requirements decreased by 57.4%and unit per person per hour improved to 3.8 times the original level.Additionally,lighting energy consumption was reduced by an average of 60%and the system achieved substantial improvements in efficiency across six dimensions.The established intelligent air conditioner production line model not only effectively validated the research hypotheses and addressed critical limitations of traditional production lines but also provided theoretical support and technical pathways for the intelligent transformation of the discrete manufacturing industry,demonstrating considerable engineering application value and promotion potential.
基金Jiangsu Provincial College Student Innovation and Entrepreneurship Program(Grant No.SJCX25_2184)—“Multi-energy Complementary Optimization and Vehicle-Storage Bidirectional Interaction Technology Driven by Novel 5E Framework”(Principal Investigator:Yuan-Yuan ShiFunding Agency:Jiangsu Provincial Education Department)+3 种基金Huaian Natural Science Research Project(Grant No.HAB2024046)—“Optimal Control of Flexible Cold-Heat-Power Integrated System with Source-Grid-Load-Storage Coordination”(Principal Investigator:Jie JiFunding Agency:Huaian Science and Technology Bureau)Huaiyin Institute of TechnologyUniversity-funded Project(GrantNo.HGYK202511)—“Data-driven CooperativeOptimization Dispatch for Source-Grid-Load Systems”(Principal Investigator:Chu-Tong ZhangFunding Agency:Huaiyin Institute of Technology).
摘要In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.
基金funded by the National Natural Science Foundation of China,grant number 62302519.
摘要Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardware implementations face two main problems,including wasted area resources and excessive critical path delay.These issues limit the energy efficiency and integration level of stream cipher chips.To address these problems,this paper proposes an energy-efficient design method for a 64-bit Boolean function reconfigurable operation unit(BFROU),aiming to improve the computational efficiency of Boolean functions in stream ciphers.To optimize the design of BFROU,this paper takes the NPN equivalence theory as a guide.First,customized designs at the transistor level were performed for both 2-and 3-variable RM logic units(denoted as TRM).On this basis,this paper uses the port sharing strategy to further optimize the design of 4-to-6-variable TRM logic units and construct a multi-variable TRM process library.Then,by combining multi-variable TRM logic units with the mathematical definition of Boolean functions,this paper proposes a theoretical model of BFROU.Based on this model and combined with the statistical analysis results of Boolean functions,the optimal TRM unit configuration is determined,and the overall optimization of the 64-bit BFROU is finally completed.Experimental results show that when TRM-3 and TRM-4 units are mixed as the first-level operation module of BFROU,its area-delay product(ADP)reaches the minimum.The 64-bit BFROU unit implemented according to this scheme has an actual measured area of 137.28μm2 and a critical path delay of 0.278 ns under the SMIC 40 nm typical process corner.This unit supports Boolean function operations with up to 64 variables,and 94.4%of the functions can complete mapping within 2 iterations.Compared with existing schemes such as look-up table(LUT)architecture and And-Inverter Cone(AIC)array,the BFROU proposed in this paper has obvious advantages in area,delay,ADP and number of iterations,providing effective hardware support for the design of high-energy-efficiency stream cipher chips.
基金funded by State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project,grant number J2023118.
摘要The increasing penetration of renewable energy sources(RES)imposes stringent flexibility requirements on thermal power units(TPUs).Integrating molten salt thermal storage systems(MSTS)and thermal-electric coupling technologies into TPUs has the potential to improve their operational flexibility and regulation capability.However,existing research seldom investigates the combined effects of MSTS retrofitting and thermal-electric output coupling on short-term dispatchability,especially under rapid load variation conditions.This study proposes a comprehensive modeling and multi-timescale optimization framework for MSTS-retrofitted TPUs with rapid load variation capability,enabling coordinated thermal and electrical dispatch in both day-ahead and real-time stages.The TPU model incorporates steam heating,electric heating,MSTS charge and discharge characteristics,and ladder typer ramping constraints,enabling detailed representation of thermal-electric coupling interactions.The proposed scheduling framework consists of a day-ahead economic dispatch model and a minute-level intraday rolling optimization.In the day-ahead stage,the model maximizes operational revenue while considering flexibility reserve requirements,multi-period peak shaving,reserve allocation,and thermal-electric coupling strategies that coordinate steam and electric heating with MSTS charging and discharging.In the intraday rolling stage,real-time RES fluctuations and load variations are incorporated to update dispatch decisions,ensuring continuous power–heat balance and efficient use of stored thermal energy.Simulation results verify that thermal-electric coupling enhances the system’s capability to maintain real-time power balance,while MSTS operation effectively mitigates output fluctuations and supports stable,economical operation for addressing RES variation.
基金supported by the National Natural Science Foundation of China(22322803,22578062,U23A20113,22288101)the Postdoctoral Science Foundation of China(2025M771146)+1 种基金the Natural Science Foundation of Fujian Province(2025J011611)the Qingyuan Innovation Laboratory(00724002).
摘要The non-selective oxidation of NH3at CO oxidation sites is a major limitation for bifunctional catalysts used in NH3-selective catalytic reduction and CO oxidation.This issue restricts these catalysts from achieving a wide operational temperature window,where both NOxand CO conversions exceed 90%,thus hindering their industrial application.Herein,we propose a novel strategy to expand the temperature window of bifunctional catalysts.By exploiting the synergistic effects of interfacial electron regulation and spatial decoupling of acid sites,we demonstrate that the CuO/Cu-SSZ-13 catalyst achieves an unprecedented operational window(200–425℃),surpassing previously reported results.Our investigation reveals a new mechanism of bifunctional synergy,driven by Cu–O bond reconstruction at the interface and the preferential anchoring of Brönsted acid sites on NH3.This mechanism mitigates the non-selective oxidation of NH3,thereby extending the catalyst’s temperature window.This work provides a new design paradigm for bifunctional catalysts,facilitating broader operational temperature windows and advancing the field.