Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through...Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.展开更多
Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natur...Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natural gas system(NGS)when a disturbance happens in one system,a series of complicated sequences of dependent events may follow in another system.Therefore,an integrated planning model jointing security-constrained considering cascading effects is proposed in this paper.Meanwhile,natural gas and electricity transmission systems considering stochastic failures and various operating characteristics of components can be viewed as a multistate systems.Moreover,power-to-gas(P2G),as a promising technology proposed to store surplus renewable energy,is considered in the integrated planning.First,multi-state models for different components are developed to describe realistic operating conditions in natural gas and electricity transmission systems.Furthermore,a mixed-integer linear programming(MILP)approach considers N-1 contingency and cascading effects between natural gas and the electrical power systems.Therefore,a security-constrained integrated planning model of natural gas and electricity transmission systems is represented.The proposed methods are validated using an integrated gas and power test system.展开更多
[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical sim...[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.展开更多
In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy sys...In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.展开更多
The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language proc...The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.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
For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one d...For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one disease endangering human health in the world today.The risk indicators of CHD are complicated,so selecting effective methods to screen the risk characteristics can make the risk predictionmore efficient.In this paper,we present a comprehensive analysis ofCHDrisk indicators fromboth data and algorithmic levels,propose a method for CHDrisk indicator identification based on multi-angle integrated measurements and Sequential Backward Selection(SBS),and then build a risk prediction model.In the multi-angle integrated measurements stage,mRMR(Maximum Relevance Minimum Redundancy)is selected from the angle of feature correlation and redundancy of the dataset itself,SHAPRF(SHapley Additive exPlanations-Random Forest)is selected from the angle of interpretation of each feature to the results,and ARFS-RF(Algorithmic Randomness Feature Selection Random Forest)is selected from the angle of statistical interpretation of classification algorithm to measure the degree of feature importance.In the SBS stage,the features with low scores are deleted successively,and the accuracy of LightGBM(Light Gradient Boosting Machine)model is used as the evaluation index to select the final feature subset.This new risk assessment method is used to identify important factors affecting CHD,and the CHD dataset from the Kaggle website is used as the study subject.Finally,11 features are retained to construct a risk assessment indicator system for CHD.Using the LightGBM classifier as the core evaluationmetric,ourmethod achieved an accuracy of 0.8656 on the Kaggle CHD dataset(4238 samples,16 initial features),outperforming individual feature selection methods(mRMR,SHAP-RF,ARFS-RF)in both accuracy and feature reduction.This demonstrates the novelty and effectiveness of our multi-angle integrated measurement approach combined with SBS in building a concise yet highly predictive CHD risk model.展开更多
In order to promote the utilization level of new energy resources for local and efficient consumption,this paper introduces the biogas(BG)fermentation technology into the integrated energy system(IES).This initiative ...In order to promote the utilization level of new energy resources for local and efficient consumption,this paper introduces the biogas(BG)fermentation technology into the integrated energy system(IES).This initiative is to study the collaborative and optimal scheduling of IES with wind power(WP),photovoltaic(PV),and BG,while integrating carbon capture system(CCS)and power-to-gas(P2G)system.Firstly,the framework of collaborative operation of IES for BG-CCS-P2G is constructed.Secondly,the flexible scheduling resources of the source and load sides are fully exploited,and the collaborative operation mode of CCS-P2G is proposed to establish a model of IES with WP,PV,and BG multi-energy flow coupling.Then,with the objective of minimizing the intra-day operating cost and the constraints of system energy balance and equipment operating limits,the IES withWP,PV,and BG collaborative optimal scheduling model is established.Finally,taking into account the uncertainty of the output of WP and PV generation,the proposed optimal scheduling model is solved by CPLEX,and its validity is verified by setting several scenarios.The results show that the proposed collaborative operation mode and optimal scheduling model can realize the efficient,low-carbon,and economic operation of the IES with WP,PV,and BG and significantly enhance the utilization of new energy for local consumption.展开更多
Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investig...Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.展开更多
Novel thin films consisting of optical materials such as lithium niobate and barium titanate enable various high-performance integrated photonic devices.However,the nanofabrication of these devices requires high-quali...Novel thin films consisting of optical materials such as lithium niobate and barium titanate enable various high-performance integrated photonic devices.However,the nanofabrication of these devices requires high-quality etching of these thin films,necessitating the long-term development of the fabrication recipe and specialized equipment.Here we present a strong-confinement low-index-rib-loaded waveguide structure as the building block of various passive and active integrated photonic devices based on novel thin films.By optimizing this low-index-rib-loaded waveguide structure without etching the novel thin film,we can simultaneously realize strong optical power confinement in the thin film,low optical propagation loss,and strong electro-optic coupling for the fundamental transverse electric mode.Based on our low-index-rib-loaded waveguide structure,we designed and fabricated a thin film lithium niobate(TFLN)modulator,featuring a 3-dB modulation bandwidth over 110 GHz and a voltage-length product as low as 2.26 V·cm,which is comparable to those of the state-of-the-art etched TFLN modulators.By alleviating the etching of novel thin films,the proposed structure opens up new ways of fast proof-of-concept demonstration and even mass production of high-performance integrated electro-optic and nonlinear devices based on novel thin films.展开更多
Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sen...Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.展开更多
Under the“dual carbon”goals,this paper constructs an optimization model of the comprehensive energy system in the park.A stepwise carbon excess rate mechanism and an electric vehicle coupling strategy are proposed:A...Under the“dual carbon”goals,this paper constructs an optimization model of the comprehensive energy system in the park.A stepwise carbon excess rate mechanism and an electric vehicle coupling strategy are proposed:A carbon quota trading system is established based on the baseline method,and the stepwise function is adopted to quantify the cost of excess carbon emissions;Introduce the price demand response and the two-way interaction mechanism of electric Vehicle vehicle-to-grid(V2G)to enhance the flexible regulation ability.Aiming at the uncertainty of wind and solar output,a typical scene set is generated by combining Latin hypercube sampling with the scene reduction method.The goal is to minimize the operating cost and maximize the consumption of renewable energy,and it is solved through the CPLEX solver in the MATLAB platform.Through simulation verification of the proposed models and methods in various scenarios,the simulation results show that under the coupling of the carbon excess rate trading mechanism,the demand response mechanism,and the vehicle-to-grid interaction of electric vehicles,the total daily operating cost of the system decreases by 25.3%,reduce the dual pressure of energy consumption costs and the economic environment,and achieve the coordinated optimization of economic and ecological benefits.展开更多
Optical polarizers,which allow the transmission of specific polarization states,are essential components in modern optical systems.Here,we experimentally demonstrate integrated photonic polarizers incorporating reduce...Optical polarizers,which allow the transmission of specific polarization states,are essential components in modern optical systems.Here,we experimentally demonstrate integrated photonic polarizers incorporating reduced graphene oxide(rGO)films.2D graphene oxide(GO)films are integrated onto silicon waveguides and microring resonators(MRRs)with precise control over their thicknesses and sizes,followed by GO reduction via two different methods including uniform thermal reduction and localized photothermal reduction.We measure devices with various lengths,thicknesses,and reduction degrees of GO films.The results show that the devices with rGO exhibit better performance than those with GO,achieving a polarization-dependent loss of~47 dB and a polarization extinction ratio of~16 dB for the hybrid waveguides and MRRs with rGO,respectively.By fitting the experimental results with theory,it is found that rGO exhibits more significant anisotropy in loss,with an anisotropy ratio over 4 times that of GO.In addition,rGO shows higher thermal stability and greater robustness to photothermal reduction than GO.These results highlight the strong potential of rGO films for implementing high-performance polarization selective devices in integrated photonic platforms.展开更多
Against the backdrop of China’s“dual-carbon”target,clean energy generation currently accounts for about 3.8 trillion kilowatt-hours,or 39.7 percent of total power generation,establishing a reasonable market trading...Against the backdrop of China’s“dual-carbon”target,clean energy generation currently accounts for about 3.8 trillion kilowatt-hours,or 39.7 percent of total power generation,establishing a reasonable market trading mechanism while enhancing the low-carbon economic benefits of the integrated energy system(IES)and optimizing the interests of various entities within the distribution system has become a significant challenge.Consequently,this paper proposes an optimization strategy for a low-carbon economy within a multi-agent IES that considers carbon capture systems(CCS)and power-to-gas(P2G).In this framework,the integrated energy system operator(IESO)acts as the primary leader,while energy suppliers(ES),energy storage operators(ESO),and load aggregators(LA)follow.At the level of low-carbon technology,a coupling model of P2G and CCS is developed,leading to the establishment of an IES that incorporates energy conversion and storage equipment.Economically,effective control of system carbon emissions in market trading is progressively established.Lastly,the trading decision model of the system is integrated within a master-slave game framework,utilizing an improved differential evolution algorithm in conjunction with the distributed equilibrium method of quadratic programming for solution.The calculation example demonstrates that the strategy safeguards the benefits for both parties in the game and achieves energy savings and carbon reduction for the system.展开更多
This empirical study examines the integration of medical and elderly care services in Guangyuan City through stratified random sampling,targeting 283 eligible residents aged 60+from three representative integrated ins...This empirical study examines the integration of medical and elderly care services in Guangyuan City through stratified random sampling,targeting 283 eligible residents aged 60+from three representative integrated institutions.The research employed a self-designed questionnaire titled“Humanistic Care Experience and Demand Influencing Factors”to collect subjective perceptions regarding basic care,psychological support,health education,and social interaction using a Likert five-point scale.Descriptive statistics,one-way ANOVA,and multiple regression modeling were conducted with SPSS 25.0 software.Results indicated that overall humanistic care experience scores were moderately high,with the“caregiving”dimension scoring highest and“psychological/social support”the lowest.Analysis revealed significant correlations between educational attainment,income,self-reported health status,and family support frequency(P<0.001),particularly among seniors with higher education,better health,and stronger family support.While integrated care facilities provide relatively comprehensive basic care,they should focus on addressing gaps in humanistic services,especially providing targeted support for groups with“low education,low income,poor health,and lack of family support.”展开更多
A regional electricity-heating integrated energy system(REH-IES)can make extensive use of renewable energy sources,realize complementary and coordinated operation of multiple energy sources,reduce carbon emissions and...A regional electricity-heating integrated energy system(REH-IES)can make extensive use of renewable energy sources,realize complementary and coordinated operation of multiple energy sources,reduce carbon emissions and promote the development of zero/low carbon systems.This paper proposes a risk-averse stochastic optimal scheduling model for REHIES.An energy flow framework for the REH-IES is proposed considering energy interaction between the electric-heating microgrids(EHMs)and electricity distribution network and the heating network.Then,considering the uncertainties of power output of renewable energy sources,dynamic characteristics of pipelines in the heating network,and thermal inertia of smart buildings,a stochastic optimal scheduling model for the REH-IES is established.Uncertainties of renewable energy sources bring financial risks to optimal scheduling of the REH-IES.Therefore,conditional value-at-risk(CVaR)theory is adopted to measure the risk and to limit the risk within an acceptable range,to achieve minimum expected scheduling cost of the REH-IES.The stochastic programming-based problem is transformed into a second-order cone programming(SOCP)model through secondorder cone relaxation method.Case studies verify the stochastic optimal scheduling model can reduce expected scheduling cost of the REH-IES,promote consumption of renewable energy sources and reduce carbon emissions.展开更多
To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a ...To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.展开更多
The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due t...The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due to fluctuations in renewable energy generation.Leveraging building flexibility to address these power fluctuations within IES is a promising strategy,which requires coordinated control between air-conditioning systems and other IES components.This study proposes a cross-time-scale control framework that contains optimal scheduling and on-the-fly flexible control to reduce the cost impacts of a residential IES system equipped with photovoltaic(PV)panels,batteries,a heat pump,and a domestic hot water tank.The method involves three key steps:solar irradiance prediction,day-ahead optimal scheduling of energy storage,and intra-day flexible control of the heat pump.The method is validated through a high-fidelity residential building model with actual weather and energy usage data in Frankfurt,Germany.Results reveal that the proposed method limits the cost increase to just 2.67% compared to the day-ahead schedule,whereas the cost could increase by 7.39% without the flexible control.Additionally,computational efficiency is enhanced by transforming the mixed-integer programming(MIP)into nonlinear programming(NLP)problem via introducing action-exclusive constraints.This approach offers valuable support for residential IES operations.展开更多
For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model f...For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.展开更多
With deregulation of the energy market,the pricing strategy of energy sellers in a regional integrated energy system(RIES)can affect the interests of all participants in the market and the operation of the system.This...With deregulation of the energy market,the pricing strategy of energy sellers in a regional integrated energy system(RIES)can affect the interests of all participants in the market and the operation of the system.This paper proposes a pricing strategy for integrated energy service providers in RIES based on a deep reinforcement learning(DRL)algorithm considering privacy protection.The transaction process between the integrated energy service provider(IESP)and user aggregators(UAs)in RIES is modeled as a Stackelberg game.IESP serves as the leader in making retail prices,and different UAs serve as followers in optimizing their energy consumption strategies.Considering UAs’strategies are temporally coupled,a Markov decision process(MDP)is designed differently from existing studies.Case studies demonstrate that the proposed method is accurate and stable when solving a Stackelberg equilibrium without privacy leakage.The obtained pricing strategy avoids unreasonable pricing and guarantees the revenue of IESP and the energy demand of UAs.展开更多
基金supported by grants from the Fundamental Research Funds for the Central Universities(No.2025ZFJH03)the Central Guidance Fund for Local Science and Technology Development(No.2024ZY01054)the CAMS Innovation Fund for Medical Sciences(No.2019-I2M-5-045).
文摘Background:Giant cell arteritis(GCA),the most common systemic vasculitis affecting elderly individuals,currently lacks specific therapies.This study aimed to systematically identify therapeutic targets for GCA through integration of large-scale multi-omics datasets.Methods:We constructed a multi-stage analytical framework encompassing 32 proteomic datasets(covering 2914 unique plasma proteins)and 6 transcriptomic datasets.Multi-omics integration strategies,including two-sample Mendelian randomization,colocalization analysis,and functional enrichment analysis,were employed to identify and validate causal relationships between candidate targets and GCA risk across 4 independent European-ancestry GCA cohorts.Single-cell RNA sequencing analysis of peripheral blood mononuclear cells from untreated GCA patients was performed to characterize hub gene-immune cell relationships.Results:We identified 43 plasma proteins causally associated with GCA[false discovery rate(FDR)<0.05],with 17 representing novel therapeutic targets.Through dual validation using proteome-wide association studies and transcriptome-wide association studies,we identified 13 high-confidence candidate targets with distinct tissue-specific expression patterns.Unc-51 like kinase 3(ULK3)emerged as the strongest protective factor(odds ratio=0.47,95%confidence interval:0.37–0.71)through autophagy regulation,while SLAMF7 represents an immediate drug repositioning opportunity as the target of food and drug administration-approved elotuzumab.Five targets have existing approved drugs(SLAMF7,ICAM1,IL18,IL6ST,CTSS).Single-cell analysis revealed profound disruption of hub gene-immune cell relationships in untreated GCA patients,with cell-type-specific alterations in inflammatory gene expression,and TYMP as the most critical hub gene.Conclusions:This study provides a clinically-actionable atlas of 43 potential therapeutic targets in GCA,identifying novel mechanisms including autophagy modulation and metabolic reprogramming,with immediate drug repositioning opportunities and precision medicine strategies based on tissue-specific and cell-type-specific expression patterns.These findings require experimental validation before clinical translation.
基金supported in part by the Key Projects of National Natural Science Foundation of China under Grant 51936003.
文摘Integration of natural gas and electricity transmission systems has strengthened interdependence between the two systems.Due to the close interconnection through coupling elements between the power system(PS)and natural gas system(NGS)when a disturbance happens in one system,a series of complicated sequences of dependent events may follow in another system.Therefore,an integrated planning model jointing security-constrained considering cascading effects is proposed in this paper.Meanwhile,natural gas and electricity transmission systems considering stochastic failures and various operating characteristics of components can be viewed as a multistate systems.Moreover,power-to-gas(P2G),as a promising technology proposed to store surplus renewable energy,is considered in the integrated planning.First,multi-state models for different components are developed to describe realistic operating conditions in natural gas and electricity transmission systems.Furthermore,a mixed-integer linear programming(MILP)approach considers N-1 contingency and cascading effects between natural gas and the electrical power systems.Therefore,a security-constrained integrated planning model of natural gas and electricity transmission systems is represented.The proposed methods are validated using an integrated gas and power test system.
文摘[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.
基金supported by the Central Government Guides Local Science and Technology Development Fund Project(2023ZY0020)Key R&D and Achievement Transformation Project in InnerMongolia Autonomous Region(2022YFHH0019)+3 种基金the Fundamental Research Funds for Inner Mongolia University of Science&Technology(2022053)Natural Science Foundation of Inner Mongolia(2022LHQN05002)National Natural Science Foundation of China(52067018)Metallurgical Engineering First-Class Discipline Construction Project in Inner Mongolia University of Science and Technology,Control Science and Engineering Quality Improvement and Cultivation Discipline Project in Inner Mongolia University of Science and Technology。
文摘In this paper,a bilevel optimization model of an integrated energy operator(IEO)–load aggregator(LA)is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system(IIES).The upper level represents the integrated energy operator,and the lower level is the electricity-heatgas load aggregator.Owing to the benefit conflict between the upper and lower levels of the IIES,a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed,combined with factors such as the carbon emissions of the IIES,as well as the lower load interruption power.The price of selling energy can be dynamically adjusted to the lower LA in the mechanism,according to the information on carbon emissions and load interruption power.Mutual benefits and win-win situations are achieved between the upper and lower multistakeholders.Finally,CPLEX is used to iteratively solve the bilevel optimization model.The optimal solution is selected according to the joint optimal discrimination mechanism.Thesimulation results indicate that the sourceload coordinate operation can reduce the upper and lower operation costs.Using the proposed pricingmechanism,the carbon emissions and load interruption power of IEO-LA are reduced by 9.78%and 70.19%,respectively,and the capture power of the carbon capture equipment is improved by 36.24%.The validity of the proposed model and method is verified.
基金the National Research Foundation(NRF)Singapore mid-sized center grant(NRF-MSG-2023-0002)FrontierCRP grant(NRF-F-CRP-2024-0006)+2 种基金A*STAR Singapore MTC RIE2025 project(M24W1NS005)IAF-PP project(M23M5a0069)Ministry of Education(MOE)Singapore Tier 2 project(MOE-T2EP50220-0014).
文摘The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.
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(No.72071150)the Fujian Provincial Natural Science Foundation of China(Nos.2024J01903,2025J01393).
文摘For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one disease endangering human health in the world today.The risk indicators of CHD are complicated,so selecting effective methods to screen the risk characteristics can make the risk predictionmore efficient.In this paper,we present a comprehensive analysis ofCHDrisk indicators fromboth data and algorithmic levels,propose a method for CHDrisk indicator identification based on multi-angle integrated measurements and Sequential Backward Selection(SBS),and then build a risk prediction model.In the multi-angle integrated measurements stage,mRMR(Maximum Relevance Minimum Redundancy)is selected from the angle of feature correlation and redundancy of the dataset itself,SHAPRF(SHapley Additive exPlanations-Random Forest)is selected from the angle of interpretation of each feature to the results,and ARFS-RF(Algorithmic Randomness Feature Selection Random Forest)is selected from the angle of statistical interpretation of classification algorithm to measure the degree of feature importance.In the SBS stage,the features with low scores are deleted successively,and the accuracy of LightGBM(Light Gradient Boosting Machine)model is used as the evaluation index to select the final feature subset.This new risk assessment method is used to identify important factors affecting CHD,and the CHD dataset from the Kaggle website is used as the study subject.Finally,11 features are retained to construct a risk assessment indicator system for CHD.Using the LightGBM classifier as the core evaluationmetric,ourmethod achieved an accuracy of 0.8656 on the Kaggle CHD dataset(4238 samples,16 initial features),outperforming individual feature selection methods(mRMR,SHAP-RF,ARFS-RF)in both accuracy and feature reduction.This demonstrates the novelty and effectiveness of our multi-angle integrated measurement approach combined with SBS in building a concise yet highly predictive CHD risk model.
文摘In order to promote the utilization level of new energy resources for local and efficient consumption,this paper introduces the biogas(BG)fermentation technology into the integrated energy system(IES).This initiative is to study the collaborative and optimal scheduling of IES with wind power(WP),photovoltaic(PV),and BG,while integrating carbon capture system(CCS)and power-to-gas(P2G)system.Firstly,the framework of collaborative operation of IES for BG-CCS-P2G is constructed.Secondly,the flexible scheduling resources of the source and load sides are fully exploited,and the collaborative operation mode of CCS-P2G is proposed to establish a model of IES with WP,PV,and BG multi-energy flow coupling.Then,with the objective of minimizing the intra-day operating cost and the constraints of system energy balance and equipment operating limits,the IES withWP,PV,and BG collaborative optimal scheduling model is established.Finally,taking into account the uncertainty of the output of WP and PV generation,the proposed optimal scheduling model is solved by CPLEX,and its validity is verified by setting several scenarios.The results show that the proposed collaborative operation mode and optimal scheduling model can realize the efficient,low-carbon,and economic operation of the IES with WP,PV,and BG and significantly enhance the utilization of new energy for local consumption.
文摘Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.
基金financial supports from National Key Research and Development Program of China (2021YFA1401000)National Natural Science Foundation of China (62435009)+2 种基金Beijing Municipal Natural Science Foundation (Z220008)Zhuhai Industry University Research Collaboration Project (ZH-2201700121010)supported by the Center of High Performance Computing,Tsinghua University
文摘Novel thin films consisting of optical materials such as lithium niobate and barium titanate enable various high-performance integrated photonic devices.However,the nanofabrication of these devices requires high-quality etching of these thin films,necessitating the long-term development of the fabrication recipe and specialized equipment.Here we present a strong-confinement low-index-rib-loaded waveguide structure as the building block of various passive and active integrated photonic devices based on novel thin films.By optimizing this low-index-rib-loaded waveguide structure without etching the novel thin film,we can simultaneously realize strong optical power confinement in the thin film,low optical propagation loss,and strong electro-optic coupling for the fundamental transverse electric mode.Based on our low-index-rib-loaded waveguide structure,we designed and fabricated a thin film lithium niobate(TFLN)modulator,featuring a 3-dB modulation bandwidth over 110 GHz and a voltage-length product as low as 2.26 V·cm,which is comparable to those of the state-of-the-art etched TFLN modulators.By alleviating the etching of novel thin films,the proposed structure opens up new ways of fast proof-of-concept demonstration and even mass production of high-performance integrated electro-optic and nonlinear devices based on novel thin films.
基金supported by the National Natural Science Foundation of China(52272177,12204010)the Foundation for the Introduction of High-Level Talents of Anhui University(S020118002/097)+1 种基金the University Synergy Innovation Program of Anhui Province(GXXT-2023-066)the Scientific Research Project of Anhui Provincial Higher Education Institution(2023AH040008)。
文摘Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.
基金sponsored by National Natural Science Foundation of China(52077137).
文摘Under the“dual carbon”goals,this paper constructs an optimization model of the comprehensive energy system in the park.A stepwise carbon excess rate mechanism and an electric vehicle coupling strategy are proposed:A carbon quota trading system is established based on the baseline method,and the stepwise function is adopted to quantify the cost of excess carbon emissions;Introduce the price demand response and the two-way interaction mechanism of electric Vehicle vehicle-to-grid(V2G)to enhance the flexible regulation ability.Aiming at the uncertainty of wind and solar output,a typical scene set is generated by combining Latin hypercube sampling with the scene reduction method.The goal is to minimize the operating cost and maximize the consumption of renewable energy,and it is solved through the CPLEX solver in the MATLAB platform.Through simulation verification of the proposed models and methods in various scenarios,the simulation results show that under the coupling of the carbon excess rate trading mechanism,the demand response mechanism,and the vehicle-to-grid interaction of electric vehicles,the total daily operating cost of the system decreases by 25.3%,reduce the dual pressure of energy consumption costs and the economic environment,and achieve the coordinated optimization of economic and ecological benefits.
基金supported by the Australian Research Council Centre of Excellence Project in Optical Microcombs for Breakthrough Science(No.CE230100006)the Australian Research Council Discovery Projects Programs(Nos.P190103186 and FT210100806)+4 种基金Linkage Program(Nos.LP210200345 and LP210100467)the Swinburne ECR-SUPRA program,the Industrial Transformation Training Centres scheme(No.IC180100005)the National Natural Science Foundation of China(No.12404375)the Beijing Natural Science Foundation(No.Z180007)the Innovation Program for Quantum Science and Technology(No.2021ZD0300703).
文摘Optical polarizers,which allow the transmission of specific polarization states,are essential components in modern optical systems.Here,we experimentally demonstrate integrated photonic polarizers incorporating reduced graphene oxide(rGO)films.2D graphene oxide(GO)films are integrated onto silicon waveguides and microring resonators(MRRs)with precise control over their thicknesses and sizes,followed by GO reduction via two different methods including uniform thermal reduction and localized photothermal reduction.We measure devices with various lengths,thicknesses,and reduction degrees of GO films.The results show that the devices with rGO exhibit better performance than those with GO,achieving a polarization-dependent loss of~47 dB and a polarization extinction ratio of~16 dB for the hybrid waveguides and MRRs with rGO,respectively.By fitting the experimental results with theory,it is found that rGO exhibits more significant anisotropy in loss,with an anisotropy ratio over 4 times that of GO.In addition,rGO shows higher thermal stability and greater robustness to photothermal reduction than GO.These results highlight the strong potential of rGO films for implementing high-performance polarization selective devices in integrated photonic platforms.
基金supported by the National Natural Science Foundation of China(No.52077137).
文摘Against the backdrop of China’s“dual-carbon”target,clean energy generation currently accounts for about 3.8 trillion kilowatt-hours,or 39.7 percent of total power generation,establishing a reasonable market trading mechanism while enhancing the low-carbon economic benefits of the integrated energy system(IES)and optimizing the interests of various entities within the distribution system has become a significant challenge.Consequently,this paper proposes an optimization strategy for a low-carbon economy within a multi-agent IES that considers carbon capture systems(CCS)and power-to-gas(P2G).In this framework,the integrated energy system operator(IESO)acts as the primary leader,while energy suppliers(ES),energy storage operators(ESO),and load aggregators(LA)follow.At the level of low-carbon technology,a coupling model of P2G and CCS is developed,leading to the establishment of an IES that incorporates energy conversion and storage equipment.Economically,effective control of system carbon emissions in market trading is progressively established.Lastly,the trading decision model of the system is integrated within a master-slave game framework,utilizing an improved differential evolution algorithm in conjunction with the distributed equilibrium method of quadratic programming for solution.The calculation example demonstrates that the strategy safeguards the benefits for both parties in the game and achieves energy savings and carbon reduction for the system.
基金Survey and Analysis on Humanistic Care Experience and Influencing Factors of Elderly Residents in 3 Integrated Medical and Nursing Institutions in Guangyuan City(Project No.:24SCLN055)。
文摘This empirical study examines the integration of medical and elderly care services in Guangyuan City through stratified random sampling,targeting 283 eligible residents aged 60+from three representative integrated institutions.The research employed a self-designed questionnaire titled“Humanistic Care Experience and Demand Influencing Factors”to collect subjective perceptions regarding basic care,psychological support,health education,and social interaction using a Likert five-point scale.Descriptive statistics,one-way ANOVA,and multiple regression modeling were conducted with SPSS 25.0 software.Results indicated that overall humanistic care experience scores were moderately high,with the“caregiving”dimension scoring highest and“psychological/social support”the lowest.Analysis revealed significant correlations between educational attainment,income,self-reported health status,and family support frequency(P<0.001),particularly among seniors with higher education,better health,and stronger family support.While integrated care facilities provide relatively comprehensive basic care,they should focus on addressing gaps in humanistic services,especially providing targeted support for groups with“low education,low income,poor health,and lack of family support.”
基金supported by the National Natural Science Foundation of China(52377080,U24B2078)the Department of Science and Technology of Jilin Province(20230101374JC).
文摘A regional electricity-heating integrated energy system(REH-IES)can make extensive use of renewable energy sources,realize complementary and coordinated operation of multiple energy sources,reduce carbon emissions and promote the development of zero/low carbon systems.This paper proposes a risk-averse stochastic optimal scheduling model for REHIES.An energy flow framework for the REH-IES is proposed considering energy interaction between the electric-heating microgrids(EHMs)and electricity distribution network and the heating network.Then,considering the uncertainties of power output of renewable energy sources,dynamic characteristics of pipelines in the heating network,and thermal inertia of smart buildings,a stochastic optimal scheduling model for the REH-IES is established.Uncertainties of renewable energy sources bring financial risks to optimal scheduling of the REH-IES.Therefore,conditional value-at-risk(CVaR)theory is adopted to measure the risk and to limit the risk within an acceptable range,to achieve minimum expected scheduling cost of the REH-IES.The stochastic programming-based problem is transformed into a second-order cone programming(SOCP)model through secondorder cone relaxation method.Case studies verify the stochastic optimal scheduling model can reduce expected scheduling cost of the REH-IES,promote consumption of renewable energy sources and reduce carbon emissions.
基金the Foshan Science and Technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.
基金supported by the National Key Research and Development Program of China(2022YFB4200902)。
文摘The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due to fluctuations in renewable energy generation.Leveraging building flexibility to address these power fluctuations within IES is a promising strategy,which requires coordinated control between air-conditioning systems and other IES components.This study proposes a cross-time-scale control framework that contains optimal scheduling and on-the-fly flexible control to reduce the cost impacts of a residential IES system equipped with photovoltaic(PV)panels,batteries,a heat pump,and a domestic hot water tank.The method involves three key steps:solar irradiance prediction,day-ahead optimal scheduling of energy storage,and intra-day flexible control of the heat pump.The method is validated through a high-fidelity residential building model with actual weather and energy usage data in Frankfurt,Germany.Results reveal that the proposed method limits the cost increase to just 2.67% compared to the day-ahead schedule,whereas the cost could increase by 7.39% without the flexible control.Additionally,computational efficiency is enhanced by transforming the mixed-integer programming(MIP)into nonlinear programming(NLP)problem via introducing action-exclusive constraints.This approach offers valuable support for residential IES operations.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473374,62403487 and U2441243).
文摘For the longitudinal midcourse guidance problem of a cruise-glide integrated hypersonic vehicle(CGHV),an analytical method based on optimal control theory is proposed.This method constructs a guidance dynamics model for such vehicles,using aerodynamic load as the control variable,and introduces a framework for solving the guidance laws.This framework unifies the design process of guidance laws for both the glide and cruise phases.By decomposing the longitudinal guidance task into position control and velocity control,and minimizing energy consumption as the objective function,the method provides an analytical solution for velocity control load through the calculation of costate variables.This approach requires only the current state and terminal state parameters to determine the guidance law solution.Furthermore,by transforming path constraints into aerodynamic load constraints and solving backwards to obtain the angle of attack,bank angle,and throttle setting,this method ensures a smooth transition from the glide phase to the cruise phase,guaranteeing the successful completion of the guidance task.Finally,the effectiveness and practicality of the proposed method are validated through case simulations and analysis.
文摘With deregulation of the energy market,the pricing strategy of energy sellers in a regional integrated energy system(RIES)can affect the interests of all participants in the market and the operation of the system.This paper proposes a pricing strategy for integrated energy service providers in RIES based on a deep reinforcement learning(DRL)algorithm considering privacy protection.The transaction process between the integrated energy service provider(IESP)and user aggregators(UAs)in RIES is modeled as a Stackelberg game.IESP serves as the leader in making retail prices,and different UAs serve as followers in optimizing their energy consumption strategies.Considering UAs’strategies are temporally coupled,a Markov decision process(MDP)is designed differently from existing studies.Case studies demonstrate that the proposed method is accurate and stable when solving a Stackelberg equilibrium without privacy leakage.The obtained pricing strategy avoids unreasonable pricing and guarantees the revenue of IESP and the energy demand of UAs.
