A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary ...A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.展开更多
This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in ...This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.展开更多
Lexical analysis is a fundamental task in natural language processing,which involves several subtasks,such as word segmentation(WS),part-of-speech(POS)tagging,and named entity recognition(NER).Recent works have shown ...Lexical analysis is a fundamental task in natural language processing,which involves several subtasks,such as word segmentation(WS),part-of-speech(POS)tagging,and named entity recognition(NER).Recent works have shown that taking advantage of relatedness between these subtasks can be beneficial.This paper proposes a unified neural framework to address these subtasks simultaneously.Apart from the sequence tagging paradigm,the proposed method tackles the multitask lexical analysis via two-stage sequence span classification.Firstly,the model detects the word and named entity boundaries by multilabel classification over character spans in a sentence.Then,the authors assign POS labels and entity labels for words and named entities by multi-class classification,respectively.Furthermore,a Gated Task Transformation(GTT)is proposed to encourage the model to share valuable features between tasks.The performance of the proposed model was evaluated on Chinese and Thai public datasets,demonstrating state-of-the-art results.展开更多
Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mec...Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mechanism of arsenopyrite by evaluating the effects of physical and chemical changes of arsenopyrite in BOS chemical oxidation stage on mineral dissolution kinetics,as well as microbial growth activity and community structure composition in bio-oxidation stage.The results showed that the chemical oxidation contributed to destroying the physical and chemical structure of arsenopyrite surface and reducing the particle size,and led to the formation of nitrogenous substances on mineral surface.These chemical oxidation behaviors effectively promoted Fe^(3+)cycling in the bio-oxidation system and weakened the inhibitory effect of the sulfur film on ionic diffusion,thereby enhancing the dissolution kinetics of the arsenopyrite.Therefore,the bio-oxidation efficiency of arsenopyrite was significantly increased in the two-stage oxidation process.After 18 d,the two-stage oxidation process achieved total extraction rates of(88.8±2.0)%,(86.7±1.3)%,and(74.7±3.0)%for As,Fe,and S elements,respectively.These values represented a significant increase of(50.8±3.4)%,(47.1±2.7)%,and(46.0±0.7)%,respectively,compared to the one-stage bio-oxidation process.展开更多
Exploring the factors driving the decoupling of China’s sulfur dioxide(SO_(2))emissions from economic growth(DEI)is crucial for achieving sustainable development.By analyzing the decoupling indicators and driving fac...Exploring the factors driving the decoupling of China’s sulfur dioxide(SO_(2))emissions from economic growth(DEI)is crucial for achieving sustainable development.By analyzing the decoupling indicators and driving factors at both the generation and treatment stages of SO_(2),more effective targeted mitigation strategies can be developed.We employ the Tapio decoupling model and propose a two-stage method to examine the decoupling issues related to SO_(2).Our findings indicate that:①DEI shows a steady and significant improvement,with SO_(2)emission intensity identified as the primary driver.②for the decoupling of economic growth and SO_(2)generation,energy scale serves as the largest stimulator,while the effect of energy intensity changes from negative to positive,and pollution intensity is first positive and then negative.③For the decoupling of SO_(2)generation and SO_(2)removal,treatment efficiency leads as the largest promoter,followed by treatment intensity.Based on these results,this study recommends that China focuses more on enhancing clean energy utilization and the effectiveness of treatment processes.展开更多
BACKGROUND Two-stage revision is the most common treatment for chronic periprosthetic joint infection of the hip,involving a resection arthroplasty with or without placement of an antibiotic-loaded spacer,followed by ...BACKGROUND Two-stage revision is the most common treatment for chronic periprosthetic joint infection of the hip,involving a resection arthroplasty with or without placement of an antibiotic-loaded spacer,followed by antibiotic therapy before reimplantation.AIM To compare the outcomes and complications of two consecutive treatment protocols for two-stage revision arthroplasty of the infected hip:One using Girdlestone with an antibiotic holiday,the other using custom-made articulating spacers(CUMARS)without an antibiotic holiday.METHODS In this retrospective study,two consecutive cohorts were compared.Group A(2017-2020)underwent two-stage revision with a Girdlestone and an antibiotic holiday before reimplantation,while Group B(2020-2023)received CUMARS whenever possible,and no antibiotic holiday,or a Girdlestone if indicated.The primary outcome was successful infection eradication after one year.Secondary outcomes included surgical duration,length of hospital stay,weight-bearing allowance,discharge destination,and complications.RESULTS A total of 98 patients were included:39 patients in Group A and 59 patients in Group B.Successful infection eradication after one year was achieved in 69%of Group A and 83%of Group B(P=0.164).Patients in Group B were more frequently allowed to bear weight(64%vs 18%,P<0.001),had a shorter in-hospital stay(9 vs 16 days,P<0.001),and were more often discharged home after the first surgery(48%vs 24%,P=0.048).No significant differences were found in(mechanical)complications.CONCLUSION A protocol including CUMARS is a safe and effective treatment,offering faster recovery,shorter length of hospital stay,and enabling more patients to return home during the interval.This reduces strain on patients and the healthcare system,potentially saving costs,without compromising infection control or increasing(mechanical)complications.展开更多
Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growin...Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.展开更多
The development of efficient and clean heating technologies is crucial for reducing carbon emissions in regions with severe cold regions.This research designs a novel two-stage phase change heat storage coupled solar-...The development of efficient and clean heating technologies is crucial for reducing carbon emissions in regions with severe cold regions.This research designs a novel two-stage phase change heat storage coupled solar-air source heat pump heating system structure that is specifically designed for such regions.The two-stage heat storage device in this heating system expands the storage temperature range of solar heat.The utilization of the two-stage heat storage device not onlymakes up for the instability of the solar heating system,but can also directlymeet the building heating temperature,and can reduce the influence of low-temperature outdoor environments in severe cold regions on the heating performance of the air source heat pump by using solar energy.Therefore,the two-stage phase change heat storage coupled to the solar energy-air source heat pump heating system effectively improves the utilization rate of solar energy.A numerical model of the system components and their integration was developed using TRNSYS software in this study,and various performance aspects of the system were simulated and analyzed.The simulation results demonstrated that the two-stage heat storage device can effectively store solar energy,enabling its hierarchical utilization.The low-temperature solar energy stored by the two-stage phase change heat storage device enhances the coefficient of performance of the air source heat pump by 11.1%in severe cold conditions.Using the Hooke-Jeeves optimization method,the annual cost and carbon emissions are taken as optimization objectives,with the optimized solar heat supply accounting for 52.5%.This study offers valuable insights into operational strategies and site selection for engineering applications,providing a solid theoretical foundation for the widespread implementation of this system in severe cold regions.展开更多
Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing r...Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing renewable-energy consumption and supporting sustainable-energy systems.User participation is central to demand response;however,many users are not inclined to engage actively;therefore,the full potential of demand response remains unrealized.User satisfaction must be prioritized in demand-response assessments.This study proposed a two-stage,capacity-optimization configuration method for user-level energy systems con-sidering thermal inertia and user satisfaction.This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual,total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction.Indoor heating is adjusted,for optimizing device output and load profiles,with a focus on typical,daily,economic,and environmental objectives.The studyfindings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction.This optimization mitigates environmental concerns and enhances clean-energy integration.展开更多
As future ship system,hybrid energy ship system has a wide range of application prospects for solving the serious energy crisis.However,current optimization scheduling works lack the consideration of sea conditions an...As future ship system,hybrid energy ship system has a wide range of application prospects for solving the serious energy crisis.However,current optimization scheduling works lack the consideration of sea conditions and navigational circumstances.There-fore,this paper aims at establishing a two-stage optimization framework for hybrid energy ship power system.The proposed framework considers multiple optimizations of route,speed planning,and energy management under the constraints of sea conditions during navigation.First,a complex hybrid ship power model consisting of diesel generation system,propulsion system,energy storage system,photovoltaic power generation system,and electric boiler system is established,where sea state information and ship resistance model are considered.With objective optimization functions of cost and greenhouse gas(GHG)emissions,a two-stage optimization framework consisting of route planning,speed scheduling,and energy management is constructed.Wherein the improved A-star algorithm and grey wolf optimization algorithm are introduced to obtain the optimal solutions for route,speed,and energy optimization scheduling.Finally,simulation cases are employed to verify that the proposed two-stage optimization scheduling model can reduce load energy consumption,operating costs,and carbon emissions by 17.8%,17.39%,and 13.04%,respectively,compared with the non-optimal control group.展开更多
In order to address the synergistic optimization of energy efficiency improvement in the waste incineration power plant(WIPP)and renewable energy accommodation,an electricity-hydrogen-waste multi-energy system integra...In order to address the synergistic optimization of energy efficiency improvement in the waste incineration power plant(WIPP)and renewable energy accommodation,an electricity-hydrogen-waste multi-energy system integrated with phase change material(PCM)thermal storage is proposed.First,a thermal energy management framework is constructed,combining PCM thermal storage with the alkaline electrolyzer(AE)waste heat recovery and the heat pump(HP),while establishing a PCM-driven waste drying system to enhance the efficiency of waste incineration power generation.Next,a flue gas treatment method based on purification-separation-storage coordination is adopted,achieving spatiotemporal decoupling between waste incineration and flue gas treatment.Subsequently,a two-stage optimal dispatching strategy for the multi-energy system is developed:the first stage establishes a dayahead economic dispatch model with the objective of minimizing net system costs,while the second stage introduces model predictive control(MPC)to realize intraday rolling optimization.Finally,The optimal dispatching strategies under different scenarios are obtained using the Gurobi solver,followed by a comparative analysis of the optimized operational outcomes.Simulation results demonstrate that the proposed system optimizes the output and operational states of each unit,simultaneously reducing carbon trading costs while increasing electricity sales revenue.The proposed scheduling strategy demonstrates effective grid peak-shaving functionality,thereby simultaneously improving the system’s economic performance and operational flexibility while providing an innovative technical pathway for municipal solid waste(MSW)resource utilization and low-carbon transformation of energy systems.展开更多
The emission regulations for heavy-duty diesel engines regarding nitrogen oxide(NO_(x))are becoming increasingly stringent,particularly in relation to cold start cycles.While the twostage selective catalytic reduction...The emission regulations for heavy-duty diesel engines regarding nitrogen oxide(NO_(x))are becoming increasingly stringent,particularly in relation to cold start cycles.While the twostage selective catalytic reduction(SCR)has the potential to achieve ultra-low NO_(x) emissions,several challenges remain,including the accurate prediction of ammonia(NH_(3))storage mass and the co-control of the two-stage SCR.The first step in this study involved the establishment of a rapid control prototype platform to facilitate the development and validation of a two-stage SCR control strategy.Secondly,an initial method for predicting the NH_(3) storage based on the mass conservation law was proposed,which was subsequently improved by filling and emptying experiments.The third step involved the development of a two-stage SCR co-control strategy,including obtaining the steady-state NH_(3) storage target value,dynamic correction for NH_(3) storage target value,regulation of NH_(3) storage,and control of the close-coupled SCR urea injector state.Finally,the two-stage SCR urea injection control strategy was certified under the world harmonized transient cycle(WHTC).The results demonstrate that the composite value of engine outlet NO_(x) emissions under cold and hot start WHTC cycles is 13 g/(kW·h).Meanwhile,the composite value of tailpipe NO_(x) emissions under cold and hot start WHTC cycles is 0.065 g/(kW·h),representing only 14%of the EU VI limit value of 0.46 g/(kW·h).Thus,the findings demonstrate that integrating an accurate NH_(3) storage prediction method with the two-stage SCR co-control function is crucial for heavy-duty diesel engines to achieve ultra-low NO_(x) emissions.展开更多
Early exiting has shown significant potential in accelerating the inference of pre-trained language models(PLMs)by allowing easy samples to exit from shallow layers.However,existing early exiting methods primarily rel...Early exiting has shown significant potential in accelerating the inference of pre-trained language models(PLMs)by allowing easy samples to exit from shallow layers.However,existing early exiting methods primarily rely on local information from individual samples to estimate prediction uncertainty for making exiting decisions,overlooking the global information provided by the sample population.This impacts the estimation of prediction uncertainty,compromising the reliability of exiting de-cisions.To remedy this,inspired by principal component analysis(PCA),the authors define a residual score to capture the deviation of features from the principal space of the sample population,providing a global perspective for estimating prediction uncertainty.Building on this,a two-stage exiting strategy is proposed that integrates global information from residual scores with local information from energy scores at both the decision and feature levels.This strategy incorporates three-way decisions to enable more reliable exiting decisions for boundary region samples by delaying judgement.Extensive experiments on the GLUE benchmark validate that the method achieves an average speed-up ratio of 2.17×across all tasks with minimal per-formance degradation.Additionally,it surpasses the state-of-the-art E-LANG by 11%in model acceleration,along with a performance improvement of 0.6 points,demonstrating a better performance-efficiency trade-off.展开更多
To address the problem that a general augmented state Kalman filter or a two-stage Kalman filter cannot achieve satisfactory positioning performance when facing uncertain noise of the micro-electro-mechanical system（...To address the problem that a general augmented state Kalman filter or a two-stage Kalman filter cannot achieve satisfactory positioning performance when facing uncertain noise of the micro-electro-mechanical system（MEMS） inertial sensors, a novel interacting multiple model-based two-stage Kalman filter（IMM-TSKF） is proposed to adapt to the uncertain inertial sensor noise. Three bias filters are developed based on different noise characteristics to cover a wide range of noise levels. Then, an accurate estimation of biases is calculated by the interacting multiple model algorithm to correct the bias-free filter. Thus, the vehicle positioning system can achieve good performance when suffering from uncertain inertial sensor noise. The experimental results indicate that the average position error of the proposed IMMTSKF is 25% lower than that of the general TSKF.展开更多
Based on heterogeneity extraction,this paper analyzes four potential characteristics of the supervisory board,they are Individual Heterogeneity of the Supervisory Member(Internal Heterogeneity),Organization Size of th...Based on heterogeneity extraction,this paper analyzes four potential characteristics of the supervisory board,they are Individual Heterogeneity of the Supervisory Member(Internal Heterogeneity),Organization Size of the Supervisory Board(Organization Size),Structural Characteristics of the Supervisory Board(Structural Characteristics)and Identity Background of the Supervisory Board(Identity Background);and verifies the impact and action path of the potential characteristics on irregularities.Then,systematically evaluates the micro enterprise organization construction and corporate governance behavior by using the methods of factor analysis and Heckman two-stage model.Empirical research shows that the scale of corporate assets does have an important impact on corporate irregularities and the governance of the board of supervisors.Under the regulation of the company scale,the three potential characteristics:Organization Size,Identity Background and Structural Characteristics have played a significant inhibitory role on irregularities,and the Internal Heterogeneity has no significant effect.When using violation behavior as an alternative variable of supervision performance,the sample selection deviation will be caused by the lack of information disclosure.This paper suggests that we should pay attention to the team of the board of supervisors scientifically and reasonably,weaken the appropriate personalized differences within the board of supervisors,and comprehensively consider the interaction between the company scale,asset quality and the performance of the board of supervisors when formulating the corporate internal management system.展开更多
The biotransformation of food waste(FW)to bioenergy has attracted considerable research attention as a means to address the energy crisis and waste disposal problems.To this end,a promising technique is two-stage anae...The biotransformation of food waste(FW)to bioenergy has attracted considerable research attention as a means to address the energy crisis and waste disposal problems.To this end,a promising technique is two-stage anaerobic digestion(TSAD),in which the FW is transformed to biohythane,a gaseous mixture of biomethane and biohydrogen.This review summarises the main characteristics of FW and describes the basic principle of TSAD.Moreover,the factors influencing the TSAD performance are identified,and an overview of the research status;economic aspects;and strategies such as pre-treatment,co-digestion,and regulation of microbial consortia to increase the biohythane yield from TSAD is provided.Additionally,the challenges and future considerations associated with the treatment of FW by TSAD are highlighted.This paper can provide valuable reference for the improvement and widespread implementation of TSAD-based FW treatment.展开更多
Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the ...Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.展开更多
This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a dis...This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.展开更多
基金supported by the National Key R&D Program of China(No.2021YFB3400900)the National Natural Science Foundation of China(Nos.52175373,52205435)+1 种基金Natural Science Foundation of Hunan Province,China(No.2022JJ40621)the Innovation Fund of National Commercial Aircraft Manufacturing Engineering Technology Center,China(No.COMACSFGS-2022-1875)。
文摘A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘This study proposes a novel visual maintenance method for photovoltaic(PV)modules based on a two-stage Wiener degradation model,addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance.The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules.This enables accurate determination of the optimal timing for postfailure corrective maintenance.To optimize the maintenance strategy,the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate.The model considers multiple cost factors,including inspection costs,preventive maintenance costs,restorative maintenance costs,and penalty costs associated with delayed fault detection.Through this optimization framework,the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions.Comparative analysis demonstrates that the twostage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models.When evaluated against traditional maintenance approaches,including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies,the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components.The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization,leading to enhanced power generation performance.These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.
基金supported by National Natural Science Foundation of China(Grant No.62266028,62266027,U21B2027,and U24A20334)Major Science and Technology Programs in Yunnan Province(Grant No.202302AD080003,202402AG050007,and 202303AP140008)+1 种基金Yunnan Province Basic Research Program(Grant No.202301AS070047,202301AT070471,and 202401BC070021)Kunming University of Science and Technology's"Double First-rate"construction joint project(Grant No.202201BE070001-021).
文摘Lexical analysis is a fundamental task in natural language processing,which involves several subtasks,such as word segmentation(WS),part-of-speech(POS)tagging,and named entity recognition(NER).Recent works have shown that taking advantage of relatedness between these subtasks can be beneficial.This paper proposes a unified neural framework to address these subtasks simultaneously.Apart from the sequence tagging paradigm,the proposed method tackles the multitask lexical analysis via two-stage sequence span classification.Firstly,the model detects the word and named entity boundaries by multilabel classification over character spans in a sentence.Then,the authors assign POS labels and entity labels for words and named entities by multi-class classification,respectively.Furthermore,a Gated Task Transformation(GTT)is proposed to encourage the model to share valuable features between tasks.The performance of the proposed model was evaluated on Chinese and Thai public datasets,demonstrating state-of-the-art results.
基金Project(52274348)supported by the National Natural Science Foundation of ChinaProject(2022JH1/10400024)supported by the Major Projects for the“Revealed Top”Science and Technology of Liaoning Province,China。
文摘Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mechanism of arsenopyrite by evaluating the effects of physical and chemical changes of arsenopyrite in BOS chemical oxidation stage on mineral dissolution kinetics,as well as microbial growth activity and community structure composition in bio-oxidation stage.The results showed that the chemical oxidation contributed to destroying the physical and chemical structure of arsenopyrite surface and reducing the particle size,and led to the formation of nitrogenous substances on mineral surface.These chemical oxidation behaviors effectively promoted Fe^(3+)cycling in the bio-oxidation system and weakened the inhibitory effect of the sulfur film on ionic diffusion,thereby enhancing the dissolution kinetics of the arsenopyrite.Therefore,the bio-oxidation efficiency of arsenopyrite was significantly increased in the two-stage oxidation process.After 18 d,the two-stage oxidation process achieved total extraction rates of(88.8±2.0)%,(86.7±1.3)%,and(74.7±3.0)%for As,Fe,and S elements,respectively.These values represented a significant increase of(50.8±3.4)%,(47.1±2.7)%,and(46.0±0.7)%,respectively,compared to the one-stage bio-oxidation process.
基金the National Natural Science Foundation of China[Grant No.52270183].
文摘Exploring the factors driving the decoupling of China’s sulfur dioxide(SO_(2))emissions from economic growth(DEI)is crucial for achieving sustainable development.By analyzing the decoupling indicators and driving factors at both the generation and treatment stages of SO_(2),more effective targeted mitigation strategies can be developed.We employ the Tapio decoupling model and propose a two-stage method to examine the decoupling issues related to SO_(2).Our findings indicate that:①DEI shows a steady and significant improvement,with SO_(2)emission intensity identified as the primary driver.②for the decoupling of economic growth and SO_(2)generation,energy scale serves as the largest stimulator,while the effect of energy intensity changes from negative to positive,and pollution intensity is first positive and then negative.③For the decoupling of SO_(2)generation and SO_(2)removal,treatment efficiency leads as the largest promoter,followed by treatment intensity.Based on these results,this study recommends that China focuses more on enhancing clean energy utilization and the effectiveness of treatment processes.
文摘BACKGROUND Two-stage revision is the most common treatment for chronic periprosthetic joint infection of the hip,involving a resection arthroplasty with or without placement of an antibiotic-loaded spacer,followed by antibiotic therapy before reimplantation.AIM To compare the outcomes and complications of two consecutive treatment protocols for two-stage revision arthroplasty of the infected hip:One using Girdlestone with an antibiotic holiday,the other using custom-made articulating spacers(CUMARS)without an antibiotic holiday.METHODS In this retrospective study,two consecutive cohorts were compared.Group A(2017-2020)underwent two-stage revision with a Girdlestone and an antibiotic holiday before reimplantation,while Group B(2020-2023)received CUMARS whenever possible,and no antibiotic holiday,or a Girdlestone if indicated.The primary outcome was successful infection eradication after one year.Secondary outcomes included surgical duration,length of hospital stay,weight-bearing allowance,discharge destination,and complications.RESULTS A total of 98 patients were included:39 patients in Group A and 59 patients in Group B.Successful infection eradication after one year was achieved in 69%of Group A and 83%of Group B(P=0.164).Patients in Group B were more frequently allowed to bear weight(64%vs 18%,P<0.001),had a shorter in-hospital stay(9 vs 16 days,P<0.001),and were more often discharged home after the first surgery(48%vs 24%,P=0.048).No significant differences were found in(mechanical)complications.CONCLUSION A protocol including CUMARS is a safe and effective treatment,offering faster recovery,shorter length of hospital stay,and enabling more patients to return home during the interval.This reduces strain on patients and the healthcare system,potentially saving costs,without compromising infection control or increasing(mechanical)complications.
基金supported by the National Natural Science Foundation of China(No.62101587)the National Funded Postdoctoral Researcher Program of China(No.GZC20233578)。
文摘Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.
基金This work was supported by the project of the Research on Energy Consumption of Office Space in Colleges and Universities under the“Dual Carbon Target”(No.CJ202301006).
文摘The development of efficient and clean heating technologies is crucial for reducing carbon emissions in regions with severe cold regions.This research designs a novel two-stage phase change heat storage coupled solar-air source heat pump heating system structure that is specifically designed for such regions.The two-stage heat storage device in this heating system expands the storage temperature range of solar heat.The utilization of the two-stage heat storage device not onlymakes up for the instability of the solar heating system,but can also directlymeet the building heating temperature,and can reduce the influence of low-temperature outdoor environments in severe cold regions on the heating performance of the air source heat pump by using solar energy.Therefore,the two-stage phase change heat storage coupled to the solar energy-air source heat pump heating system effectively improves the utilization rate of solar energy.A numerical model of the system components and their integration was developed using TRNSYS software in this study,and various performance aspects of the system were simulated and analyzed.The simulation results demonstrated that the two-stage heat storage device can effectively store solar energy,enabling its hierarchical utilization.The low-temperature solar energy stored by the two-stage phase change heat storage device enhances the coefficient of performance of the air source heat pump by 11.1%in severe cold conditions.Using the Hooke-Jeeves optimization method,the annual cost and carbon emissions are taken as optimization objectives,with the optimized solar heat supply accounting for 52.5%.This study offers valuable insights into operational strategies and site selection for engineering applications,providing a solid theoretical foundation for the widespread implementation of this system in severe cold regions.
基金supported by the science and technology foundation of Guizhou province[2022]general 013the science and technology foundation of Guizhou province[2022]general 014+1 种基金the science and technology foundation of Guizhou province GCC[2022]016-1the educational technology foundation of Guizhou province[2022]043.
文摘Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing renewable-energy consumption and supporting sustainable-energy systems.User participation is central to demand response;however,many users are not inclined to engage actively;therefore,the full potential of demand response remains unrealized.User satisfaction must be prioritized in demand-response assessments.This study proposed a two-stage,capacity-optimization configuration method for user-level energy systems con-sidering thermal inertia and user satisfaction.This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual,total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction.Indoor heating is adjusted,for optimizing device output and load profiles,with a focus on typical,daily,economic,and environmental objectives.The studyfindings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction.This optimization mitigates environmental concerns and enhances clean-energy integration.
基金supported by the National Natural Science Foundation of China under Grant 62473328by the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing Institute of Technology under No.XTCX202203.
文摘As future ship system,hybrid energy ship system has a wide range of application prospects for solving the serious energy crisis.However,current optimization scheduling works lack the consideration of sea conditions and navigational circumstances.There-fore,this paper aims at establishing a two-stage optimization framework for hybrid energy ship power system.The proposed framework considers multiple optimizations of route,speed planning,and energy management under the constraints of sea conditions during navigation.First,a complex hybrid ship power model consisting of diesel generation system,propulsion system,energy storage system,photovoltaic power generation system,and electric boiler system is established,where sea state information and ship resistance model are considered.With objective optimization functions of cost and greenhouse gas(GHG)emissions,a two-stage optimization framework consisting of route planning,speed scheduling,and energy management is constructed.Wherein the improved A-star algorithm and grey wolf optimization algorithm are introduced to obtain the optimal solutions for route,speed,and energy optimization scheduling.Finally,simulation cases are employed to verify that the proposed two-stage optimization scheduling model can reduce load energy consumption,operating costs,and carbon emissions by 17.8%,17.39%,and 13.04%,respectively,compared with the non-optimal control group.
文摘In order to address the synergistic optimization of energy efficiency improvement in the waste incineration power plant(WIPP)and renewable energy accommodation,an electricity-hydrogen-waste multi-energy system integrated with phase change material(PCM)thermal storage is proposed.First,a thermal energy management framework is constructed,combining PCM thermal storage with the alkaline electrolyzer(AE)waste heat recovery and the heat pump(HP),while establishing a PCM-driven waste drying system to enhance the efficiency of waste incineration power generation.Next,a flue gas treatment method based on purification-separation-storage coordination is adopted,achieving spatiotemporal decoupling between waste incineration and flue gas treatment.Subsequently,a two-stage optimal dispatching strategy for the multi-energy system is developed:the first stage establishes a dayahead economic dispatch model with the objective of minimizing net system costs,while the second stage introduces model predictive control(MPC)to realize intraday rolling optimization.Finally,The optimal dispatching strategies under different scenarios are obtained using the Gurobi solver,followed by a comparative analysis of the optimized operational outcomes.Simulation results demonstrate that the proposed system optimizes the output and operational states of each unit,simultaneously reducing carbon trading costs while increasing electricity sales revenue.The proposed scheduling strategy demonstrates effective grid peak-shaving functionality,thereby simultaneously improving the system’s economic performance and operational flexibility while providing an innovative technical pathway for municipal solid waste(MSW)resource utilization and low-carbon transformation of energy systems.
基金supported by the National Natural Science Foundation of China(No.51921004).
文摘The emission regulations for heavy-duty diesel engines regarding nitrogen oxide(NO_(x))are becoming increasingly stringent,particularly in relation to cold start cycles.While the twostage selective catalytic reduction(SCR)has the potential to achieve ultra-low NO_(x) emissions,several challenges remain,including the accurate prediction of ammonia(NH_(3))storage mass and the co-control of the two-stage SCR.The first step in this study involved the establishment of a rapid control prototype platform to facilitate the development and validation of a two-stage SCR control strategy.Secondly,an initial method for predicting the NH_(3) storage based on the mass conservation law was proposed,which was subsequently improved by filling and emptying experiments.The third step involved the development of a two-stage SCR co-control strategy,including obtaining the steady-state NH_(3) storage target value,dynamic correction for NH_(3) storage target value,regulation of NH_(3) storage,and control of the close-coupled SCR urea injector state.Finally,the two-stage SCR urea injection control strategy was certified under the world harmonized transient cycle(WHTC).The results demonstrate that the composite value of engine outlet NO_(x) emissions under cold and hot start WHTC cycles is 13 g/(kW·h).Meanwhile,the composite value of tailpipe NO_(x) emissions under cold and hot start WHTC cycles is 0.065 g/(kW·h),representing only 14%of the EU VI limit value of 0.46 g/(kW·h).Thus,the findings demonstrate that integrating an accurate NH_(3) storage prediction method with the two-stage SCR co-control function is crucial for heavy-duty diesel engines to achieve ultra-low NO_(x) emissions.
基金supported by the National Natural Science Foundation of China(No.62376198)the National Key Research and Development Program of China(No.2022YFB3104700)the Shanghai Baiyulan Pujiang Project(No.08002360429).
文摘Early exiting has shown significant potential in accelerating the inference of pre-trained language models(PLMs)by allowing easy samples to exit from shallow layers.However,existing early exiting methods primarily rely on local information from individual samples to estimate prediction uncertainty for making exiting decisions,overlooking the global information provided by the sample population.This impacts the estimation of prediction uncertainty,compromising the reliability of exiting de-cisions.To remedy this,inspired by principal component analysis(PCA),the authors define a residual score to capture the deviation of features from the principal space of the sample population,providing a global perspective for estimating prediction uncertainty.Building on this,a two-stage exiting strategy is proposed that integrates global information from residual scores with local information from energy scores at both the decision and feature levels.This strategy incorporates three-way decisions to enable more reliable exiting decisions for boundary region samples by delaying judgement.Extensive experiments on the GLUE benchmark validate that the method achieves an average speed-up ratio of 2.17×across all tasks with minimal per-formance degradation.Additionally,it surpasses the state-of-the-art E-LANG by 11%in model acceleration,along with a performance improvement of 0.6 points,demonstrating a better performance-efficiency trade-off.
基金The National Natural Science Foundation of China(No.61273236)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1637),China Scholarship Council
文摘To address the problem that a general augmented state Kalman filter or a two-stage Kalman filter cannot achieve satisfactory positioning performance when facing uncertain noise of the micro-electro-mechanical system（MEMS） inertial sensors, a novel interacting multiple model-based two-stage Kalman filter（IMM-TSKF） is proposed to adapt to the uncertain inertial sensor noise. Three bias filters are developed based on different noise characteristics to cover a wide range of noise levels. Then, an accurate estimation of biases is calculated by the interacting multiple model algorithm to correct the bias-free filter. Thus, the vehicle positioning system can achieve good performance when suffering from uncertain inertial sensor noise. The experimental results indicate that the average position error of the proposed IMMTSKF is 25% lower than that of the general TSKF.
文摘Based on heterogeneity extraction,this paper analyzes four potential characteristics of the supervisory board,they are Individual Heterogeneity of the Supervisory Member(Internal Heterogeneity),Organization Size of the Supervisory Board(Organization Size),Structural Characteristics of the Supervisory Board(Structural Characteristics)and Identity Background of the Supervisory Board(Identity Background);and verifies the impact and action path of the potential characteristics on irregularities.Then,systematically evaluates the micro enterprise organization construction and corporate governance behavior by using the methods of factor analysis and Heckman two-stage model.Empirical research shows that the scale of corporate assets does have an important impact on corporate irregularities and the governance of the board of supervisors.Under the regulation of the company scale,the three potential characteristics:Organization Size,Identity Background and Structural Characteristics have played a significant inhibitory role on irregularities,and the Internal Heterogeneity has no significant effect.When using violation behavior as an alternative variable of supervision performance,the sample selection deviation will be caused by the lack of information disclosure.This paper suggests that we should pay attention to the team of the board of supervisors scientifically and reasonably,weaken the appropriate personalized differences within the board of supervisors,and comprehensively consider the interaction between the company scale,asset quality and the performance of the board of supervisors when formulating the corporate internal management system.
基金supported by the National Natural Science Foundation of China(Nos.51978498 and 52131002)the National Key R&D Program of China(No.2019YFC1906301)。
文摘The biotransformation of food waste(FW)to bioenergy has attracted considerable research attention as a means to address the energy crisis and waste disposal problems.To this end,a promising technique is two-stage anaerobic digestion(TSAD),in which the FW is transformed to biohythane,a gaseous mixture of biomethane and biohydrogen.This review summarises the main characteristics of FW and describes the basic principle of TSAD.Moreover,the factors influencing the TSAD performance are identified,and an overview of the research status;economic aspects;and strategies such as pre-treatment,co-digestion,and regulation of microbial consortia to increase the biohythane yield from TSAD is provided.Additionally,the challenges and future considerations associated with the treatment of FW by TSAD are highlighted.This paper can provide valuable reference for the improvement and widespread implementation of TSAD-based FW treatment.
基金supported by North China Electric Power Research Institute’s Self-Funded Science and Technology Project“Research on Distributed Energy Storage Optimal Configuration and Operation Control Technology for Photovoltaic Promotion in the Entire County”(KJZ2022049).
文摘Aiming at the consumption problems caused by the high proportion of renewable energy being connected to the distribution network,it also aims to improve the power supply reliability of the power system and reduce the operating costs of the power system.This paper proposes a two-stage planning method for distributed generation and energy storage systems that considers the hierarchical partitioning of source-storage-load.Firstly,an electrical distance structural index that comprehensively considers active power output and reactive power output is proposed to divide the distributed generation voltage regulation domain and determine the access location and number of distributed power sources.Secondly,a two-stage planning is carried out based on the zoning results.In the phase 1 distribution network-zoning optimization layer,the network loss is minimized so that the node voltage in the area does not exceed the limit,and the distributed generation configuration results are initially determined;in phase 2,the partition-node optimization layer is planned with the goal of economic optimization,and the distance-based improved ant lion algorithm is used to solve the problem to obtain the optimal distributed generation and energy storage systemconfiguration.Finally,the IEEE33 node systemwas used for simulation.The results showed that the voltage quality was significantly improved after optimization,and the overall revenue increased by about 20.6%,verifying the effectiveness of the two-stage planning.
基金supported by the National Basic Research Program of China(2010CB951002)the Dr.Western-funded Project of Chinese Academy of Science(XBBS201010 and XBBS201005)+1 种基金the National Natural Sciences Foundation of China (51190095)the Open Research Fund Program of State Key Laboratory of Hydro-science and Engineering(sklhse-2012-A03)
文摘This study presented a simulation-based two-stage interval-stochastic programming （STIP） model to support water resources management in the Kaidu-Konqi watershed in Northwest China. The modeling system coupled a distributed hydrological model with an interval two-stage stochastic programing （ITSP）. The distributed hydrological model was used for establishing a rainfall-runoff forecast system, while random parameters were pro- vided by the statistical analysis of simulation outcomes water resources management planning in Kaidu-Konqi The developed STIP model was applied to a real case of watershed, where three scenarios with different water re- sources management policies were analyzed. The results indicated that water shortage mainly occurred in agri- culture, ecology and forestry sectors. In comparison, the water demand from municipality, industry and stock- breeding sectors can be satisfied due to their lower consumptions and higher economic values. Different policies for ecological water allocation can result in varied system benefits, and can help to identify desired water allocation plans with a maximum economic benefit and a minimum risk of system disruption under uncertainty.
