English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims...English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims to explore the relationship between ESAP,the output of academic paper abstracts,and international communication effectiveness,so as to provide new ideas for enhancing international communication effectiveness.Through a questionnaire survey and combined with the structural equation model analysis method,the results show that the improvement of ESAP has a positive effect on the output of academic paper abstracts and international communication effectiveness;the output of academic paper abstracts can also positively enhance international communication effectiveness;meanwhile,the output of academic paper abstracts has a significant mediating effect.展开更多
Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to ...Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to the unique functional attributes and interaction patterns inherent to different layers.This paper addresses the critical question of whether structural information from a known layer can be used to reconstruct the unknown intralayer structure of a target layer within general weighted output-coupling multilayer networks.Building upon the generalized synchronization principle,we propose an innovative reconstruction method that incorporates two essential components in the design of structure observers,the cross-layer coupling modulator and the structural divergence term.A key advantage of the proposed reconstruction method lies in its flexibility to freely designate both the unknown target layer and the known reference layer from the general weighted output-coupling multilayer network.The reduced dependency on full-state observability enables more deployment in engineering applications with partial measurements.Numerical simulations are conducted to validate the effectiveness of the proposed structure reconstruction method.展开更多
This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loo...This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.展开更多
To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this pape...To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this paper proposes a prediction method that integrates spatial downscaling meteorological data with a convolutional neural network(CNN)-iTransformer-long short-term memory(LSTM)model.First,the rime-optimized random forest regression algorithm(RIME-RF)is employed to perform spatial downscaling on numerical weather prediction(NWP)data,thereby improving its local applicability.Second,a CNN-iTransformer-LSTM hybrid prediction model is constructed.This model utilizes a CNN as a spatial feature extractor to capture local patterns in meteorological data,employs an iTransformer to model the global dependencies among multiple variables,and leverages an LSTM to enhance the learning of short-term temporal dynamic features,thereby achieving efficient collaborative mining of multi-scale features.Finally,experiments are conducted using actual data from a photovoltaic power station in Hebei,China,during various seasons and weather conditions.The results show that the proposed model outperforms the comparison models in terms of the root mean square error(RMSE),mean absolute error(MAE),and R2,maintaining high prediction accuracy and stability even under complex weather conditions such as overcast and rainy days.The downscaling process further enhances the prediction performance,verifying the effectiveness and practicality of this method.展开更多
Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—esp...Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.展开更多
Background:While the treatment of metastatic renal cell carcinoma(mRCC)is evolving due to immune checkpoint inhibitors(ICIs),optimal strategies for later lines of therapy have yet to be defined.The combination of lenv...Background:While the treatment of metastatic renal cell carcinoma(mRCC)is evolving due to immune checkpoint inhibitors(ICIs),optimal strategies for later lines of therapy have yet to be defined.The combination of lenvatinib and everolimus represents a viable option,and the present review aimed to summarize its activity,effectiveness,and safety.Methods:A systematic review of the literature was conducted using PubMed,targeting studies published between 2018 and 2025.Eligible studies included English-language prospective and retrospective trials reporting survival outcomes in mRCC patients treated with lenvatinib and everolimus after at least one ICI-containing regimen.Results:Nine studies met the inclusion criteria,encompassing a total of 441 patients.The lenvatinib and everolimus combination was primarily used in the third and subsequent lines of therapy.Median overall survival ranged from 7.5 to 24.5 months,while median progression-free survival was more consistent,between 6.1 and 6.7 months,except for one study reporting 12.9 months.Objective response rates varied widely(14.0%–55.7%).Adverse events of grade≥3 did not exceed the expected rate,with diarrhoea and proteinuria as the most reported events.Dose reductions and treatment discontinuations due to toxicity occurred but were generally lower than in prior pivotal trials.Conclusions:Real-world evidence suggests that lenvatinib and everolimus represent an effective and safe option after ICI failure in mRCC patients.Nevertheless,the lack of randomized phase III trials and the heterogeneity of existing studies highlight the need for more robust prospective research to guide post-ICI therapeutic strategies.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Fueled by the increasing imperative for sustainable energy solutions and the burgeoning emphasis on health awareness,self-powered techniques have undergone notable strides in advancement.Triboelectric nanogenerators(T...Fueled by the increasing imperative for sustainable energy solutions and the burgeoning emphasis on health awareness,self-powered techniques have undergone notable strides in advancement.Triboelectric nanogenerators(TENGs)stand out as a prominent device capitalizing on the principles of triboelectrification and electrostatic induction to generate electricity or electrical signals.In efforts to augment the electrical output performance of TENGs and broaden their range of applications,researchers have endeavored to refine materials,surface morphology,and structural design.Among them,physical morphological modifications play a pivotal role in enhancing the electrical properties of TENGs by increasing the contact surface area,which can be achieved by building micro-/nano-structures on the surface or inside the friction material.In this review,we summarize the common morphologies of TENGs,categorize the morphologies into surface and internal structures,and elucidate their roles in enhancing the electric output performance of devices.Moreover,we systematically classify the methodologies employed for morphological preparation into physical and chemical approaches,thereby furnishing a comprehensive survey of the diverse techniques.Subsequently,typical applications of TENGs with special morphology divided by energy harvesting and self-powered sensors are presented.Finally,an overview of the challenges and future trajectories pertinent to TENGs is conducted.Through this endeavor,the aim of this article is to catalyze the evolution of further strategies for enhancing performance of TENGs.展开更多
The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical ...The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical output still remains a significant challenge.Here,a strategy of inducing constrained phase separation on single nanofibers via shear force was proposed.Employing electrospinning technology,a polyacrylonitrile/polyvinylidene difluoride(PAN/PVDF)nanofibrous membrane was fabricated in one step,which enabled simultaneous piezoelectric and triboelectric conversion within a single-layer membrane.Each nanofiber contained independent components of PAN and PVDF and exhibited a rough surface.The abundant frictional contact points formed between these heterogeneous components contributed to an enhanced endogenous triboelectric output,showcasing an excellent synergistic effect of piezoelectric and triboelectric response in the nanofibrous membrane.Additionally,the component mass ratio influenced the microstructure,piezoelectric conformation and piezoelectric performance of the PAN/PVDF nanofibrous membranes.Through comprehensive performance comparison,the optimal mass ratio of PAN to PVDF was determined to be 9∶1.The piezoelectric devices made of the optimal PAN/PVDF nanofibrous membranes with rough nanofiber surfaces generated an output voltage of 20 V,which was about 1.8 times that of the smooth one at the same component mass ratio.The strategy of constrained phase separation on the surface of individual nanofibers provides a new approach to enhance the output performance of single-layer piezoelectric nanofibrous materials.展开更多
As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of ai...As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of aircraft structures. The assessment of electromagnetic SE for Slotted Composite Structures(SCSs) is particularly challenging due to their complex geometries and there remains a lack of suitable models for accurately predicting the SE performance of these intricate configurations. To address this issue, this paper introduces SCS-Net, a Deep Neural Network (DNN) method designed to accurately predict the SE of SCS. This method considers the impacts of various structural parameters, material properties and incident wave parameters on the SE of SCSs. In order to better model the SCS, an improved Nicolson-Ross-Weir (NRW) method is introduced in this paper to provide an equivalent flat structure for the SCS and to calculate the electromagnetic parameters of the equivalent structure. Additionally, the prediction of SE via DNNs is limited by insufficient test data, which hinders support for large-sample training. To address the issue of limited measured data, this paper develops a Measurement-Computation Fusion (MCF) dataset construction method. The predictions based on the simulation results show that the proposed method maintains an error of less than 0.07 dB within the 8–10 GHz frequency range. Furthermore, a new loss function based on the weighted L1-norm is established to improve the prediction accuracy for these parameters. Compared with traditional loss functions, the new loss function reduces the maximum prediction error for equivalent electromagnetic parameters by 47%. This method significantly improves the prediction accuracy of SCS-Net for measured data, with a maximum improvement of 23.88%. These findings demonstrate that the proposed method enables precise SE prediction and design for composite structures while reducing the number of test samples needed.展开更多
Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback com...Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback combination of the agent's own state and neighbors' output,which can achieve exponential output consensus through intermittent communication. The controller is obtained by solving two linear matrix equations, and Zeno behavior is excluded.展开更多
In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law t...In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.展开更多
In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that globa...In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.展开更多
This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state d...This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.展开更多
Owing to their high practicability,solar PV/T(photovoltaic/thermal)collectors have attracted considerable attention from researchers in both photovoltaic and solar-thermal fields worldwide.In this study,we designed an...Owing to their high practicability,solar PV/T(photovoltaic/thermal)collectors have attracted considerable attention from researchers in both photovoltaic and solar-thermal fields worldwide.In this study,we designed and constructed a novel solar-cooled PV/T system.Through experimental methods,we conducted an in-depth investigation of its thermal and electrical output characteristics and developed mathematical models for both thermal performance and electrical performance.Finally,we validated the experimental data against simulations.The results demonstrate that the designed solar-cooled PV/T system exhibits excellent thermal and electrical output performance.The utilization rate of waste heat from the PV module’s back plate reached 18.59%,and the system’s electrical efficiency improved by 1.92%compared to a conventional PV/T system.This work provides theoretical and experimental guidance for the further optimization and improvement of the solar-cooled PV/T system.展开更多
The energy release of energetic composites is severely limited by the inert alumina(Al_(2)O_(3))layer on the surface of aluminum(Al).Polytetrafluoroethylene(PTFE)could eliminate Al_(2)O_(3)layer due to its highly elec...The energy release of energetic composites is severely limited by the inert alumina(Al_(2)O_(3))layer on the surface of aluminum(Al).Polytetrafluoroethylene(PTFE)could eliminate Al_(2)O_(3)layer due to its highly electronegativity and oxidability of fluorine.However,adding PTFE particles would weaken interfacial interactions resulted in poor mechanical properties and interfacial exothermic reaction.Herein,a bridging Al-PTFE as fuel and interfacial reinforcing agent was added and used to prepare LLM-105/AlPTFE microspheres,achieving both high energy output and excellent mechanical properties.The energy release and combustion reaction performance of LLM-105/Al-PTFE microspheres are significantly improved due to high reaction heat and increased interfacial reaction area of Al-PTFE.The maximum pressure and pressurization rate of LLM-105/Al-PTFE microspheres are 164.06 kPa and 29.88 kPa/s,respectively,which are 40.11%and 16.67%higher than those of physical mixed samples.Furthermore,the tensile strength and compressive strength of LLM-105/Al-PTFE microspheres are 100.40%and 26.47%higher than those of LLM-105/Al.This work provides a new approach to improve the energy release and mechanical properties for energetic composites.展开更多
Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the s...Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.展开更多
Hydrogen peroxide(H_(2)O_(2))production via electrochemical two-electron oxygen reduction reaction(ORR)holds a great promise for sustainable energy storage.However,the issues such as high energy consumption and diffic...Hydrogen peroxide(H_(2)O_(2))production via electrochemical two-electron oxygen reduction reaction(ORR)holds a great promise for sustainable energy storage.However,the issues such as high energy consumption and difficult extraction of thermodynamically unstable H_(2)O_(2) still need to be resolved.Herein,we reported a unified system for energy-out production and downstream conversion of H_(2)O_(2).By replacing the sluggish oxygen evolution reaction with a hydrazine oxidation reaction(HzOR),the cell of twoelectron ORR coupled with HzOR achieves the co-generation of electricity energy and valuable H_(2)O_(2).By employing Ru single atoms anchored on cobalt hydroxide(for HzOR)and NiSe_(2)(for ORR)as electrocatalysts,both exhibiting onset potentials near the theoretical values for their respective reactions,the ORR‖HzOR cell exhibits an energy output of 3.58 mW cm^(-2) and generates 0.66 kWh of electricity per kg of H_(2)O_(2).with a production rate of 583 mmol h^(-1) H_(2)O_(2).The produced H_(2)O_(2) was subsequently in-situ upgraded via three downstream conversion pathways to yield value-added products of sodium percarbonate,sodium peroxyborate,and ethylene glycol.A techno-economic analysis confirmed the economic viability of this ORR‖HzOR coupled with downstream conversion system.展开更多
BACKGROUND:Pulse indicated continuous cardiac output(PiCCO)has largely replaced Swan-Ganz catheterization in shock patients.However,whether PiCCO monitoring can improve outcomes of shock patients,such as mortality,len...BACKGROUND:Pulse indicated continuous cardiac output(PiCCO)has largely replaced Swan-Ganz catheterization in shock patients.However,whether PiCCO monitoring can improve outcomes of shock patients,such as mortality,length of hospital stay,duration of mechanical ventilation,or laboratory parameters,remains unknown.METHODS:This retrospective cohort study included patients with shock in the intensive care unit(ICU)from January 2013 to January 2020.Patients were divided into PiCCO group and non-PiCCO group based on treatment with PiCCO monitoring or not.Demographic characteristics,Acute Physiology and Chronic Health Evaluation(APACHE)II scores,quick Sequential Organ Failure Assessment(qSOFA)scores,14-day mortality,and N-terminal pro-B-type natriuretic peptide(NT-proBNP)levels at 0,1,3 and 7 days after onset of shock,duration of mechanical ventilation,length of hospital stay and hospitalization costs were compiled and analyzed using propensity score matching(PSM).RESULTS:Real-world analysis of 1,583 ICU patients suff ering shock after propensity score matching revealed that 14-day mortality did not differ between PiCCO and non-PiCCO groups(36.2%vs.32.6%,P=0.343).Duration of mechanical ventilation,hospital stay,and hospitalization costs were also similar between the two groups(P>0.05).No diff erences in changes of NT-proBNP levels on days 0,1,3,and 7 as compared to baseline were noted between the two groups(P>0.05).CONCLUSIONS:The results of our real-world indicate that PiCCO monitoring may not shorten the duration of mechanical ventilation,length of hospital stay,or reduce hospitalization costs,nor will it bring survival benefi ts to ICU patients suff ering shock.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
基金This paper is part of the research results of the National Social Science Fund Project(Project No.:21XYY015)Hainan Provincial Education Reform Project(Project No.:Hnjg2023-136)。
文摘English for Specific Academic Purposes(ESAP)focuses on English language skills in specific disciplines or research fields,and has played an important role in international communication in recent years.This paper aims to explore the relationship between ESAP,the output of academic paper abstracts,and international communication effectiveness,so as to provide new ideas for enhancing international communication effectiveness.Through a questionnaire survey and combined with the structural equation model analysis method,the results show that the improvement of ESAP has a positive effect on the output of academic paper abstracts and international communication effectiveness;the output of academic paper abstracts can also positively enhance international communication effectiveness;meanwhile,the output of academic paper abstracts has a significant mediating effect.
基金Project supported by the National Natural Science Foun-dation of China(Grant No.62373197)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province,China(Grant No.23KJB120010)+1 种基金the Industry-University-Research Cooperation Project of Jiangsu Province,China(Grant No.BY20251038)the Cultivation and In-cubation Project of the College of Automation,Nanjing Uni-versity of Posts and Telecommunications.
文摘Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to the unique functional attributes and interaction patterns inherent to different layers.This paper addresses the critical question of whether structural information from a known layer can be used to reconstruct the unknown intralayer structure of a target layer within general weighted output-coupling multilayer networks.Building upon the generalized synchronization principle,we propose an innovative reconstruction method that incorporates two essential components in the design of structure observers,the cross-layer coupling modulator and the structural divergence term.A key advantage of the proposed reconstruction method lies in its flexibility to freely designate both the unknown target layer and the known reference layer from the general weighted output-coupling multilayer network.The reduced dependency on full-state observability enables more deployment in engineering applications with partial measurements.Numerical simulations are conducted to validate the effectiveness of the proposed structure reconstruction method.
文摘This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.
文摘To enhance the accuracy of short-term photovoltaic power output prediction and address issues such as insufficient spatial resolution of meteorological forecast data and weak generalization ability of models,this paper proposes a prediction method that integrates spatial downscaling meteorological data with a convolutional neural network(CNN)-iTransformer-long short-term memory(LSTM)model.First,the rime-optimized random forest regression algorithm(RIME-RF)is employed to perform spatial downscaling on numerical weather prediction(NWP)data,thereby improving its local applicability.Second,a CNN-iTransformer-LSTM hybrid prediction model is constructed.This model utilizes a CNN as a spatial feature extractor to capture local patterns in meteorological data,employs an iTransformer to model the global dependencies among multiple variables,and leverages an LSTM to enhance the learning of short-term temporal dynamic features,thereby achieving efficient collaborative mining of multi-scale features.Finally,experiments are conducted using actual data from a photovoltaic power station in Hebei,China,during various seasons and weather conditions.The results show that the proposed model outperforms the comparison models in terms of the root mean square error(RMSE),mean absolute error(MAE),and R2,maintaining high prediction accuracy and stability even under complex weather conditions such as overcast and rainy days.The downscaling process further enhances the prediction performance,verifying the effectiveness and practicality of this method.
基金funded by the National Natural Science Foundation of China(NSFC)under Grant Number 72071209.
文摘Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.
文摘Background:While the treatment of metastatic renal cell carcinoma(mRCC)is evolving due to immune checkpoint inhibitors(ICIs),optimal strategies for later lines of therapy have yet to be defined.The combination of lenvatinib and everolimus represents a viable option,and the present review aimed to summarize its activity,effectiveness,and safety.Methods:A systematic review of the literature was conducted using PubMed,targeting studies published between 2018 and 2025.Eligible studies included English-language prospective and retrospective trials reporting survival outcomes in mRCC patients treated with lenvatinib and everolimus after at least one ICI-containing regimen.Results:Nine studies met the inclusion criteria,encompassing a total of 441 patients.The lenvatinib and everolimus combination was primarily used in the third and subsequent lines of therapy.Median overall survival ranged from 7.5 to 24.5 months,while median progression-free survival was more consistent,between 6.1 and 6.7 months,except for one study reporting 12.9 months.Objective response rates varied widely(14.0%–55.7%).Adverse events of grade≥3 did not exceed the expected rate,with diarrhoea and proteinuria as the most reported events.Dose reductions and treatment discontinuations due to toxicity occurred but were generally lower than in prior pivotal trials.Conclusions:Real-world evidence suggests that lenvatinib and everolimus represent an effective and safe option after ICI failure in mRCC patients.Nevertheless,the lack of randomized phase III trials and the heterogeneity of existing studies highlight the need for more robust prospective research to guide post-ICI therapeutic strategies.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
基金financially supported by the Natural Science Foundation of Guangdong Province(No.2024A1515010639)PolyU Postdoc Matching Fund Scheme(No.1-W327),PolyU Grant(No.1-CE0H)+3 种基金Shenzhen Science and Technology Program(No.ZDSYS20220606100406016)Shenzhen Key Laboratory of Photonics and Biophotonics(No.ZDSYS20210623092006020)National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment(Shenzhen)(No.868-000003010103)National Natural Science Foundation of China(No.52208272)。
文摘Fueled by the increasing imperative for sustainable energy solutions and the burgeoning emphasis on health awareness,self-powered techniques have undergone notable strides in advancement.Triboelectric nanogenerators(TENGs)stand out as a prominent device capitalizing on the principles of triboelectrification and electrostatic induction to generate electricity or electrical signals.In efforts to augment the electrical output performance of TENGs and broaden their range of applications,researchers have endeavored to refine materials,surface morphology,and structural design.Among them,physical morphological modifications play a pivotal role in enhancing the electrical properties of TENGs by increasing the contact surface area,which can be achieved by building micro-/nano-structures on the surface or inside the friction material.In this review,we summarize the common morphologies of TENGs,categorize the morphologies into surface and internal structures,and elucidate their roles in enhancing the electric output performance of devices.Moreover,we systematically classify the methodologies employed for morphological preparation into physical and chemical approaches,thereby furnishing a comprehensive survey of the diverse techniques.Subsequently,typical applications of TENGs with special morphology divided by energy harvesting and self-powered sensors are presented.Finally,an overview of the challenges and future trajectories pertinent to TENGs is conducted.Through this endeavor,the aim of this article is to catalyze the evolution of further strategies for enhancing performance of TENGs.
基金National Natural Science Foundation of China(No.52373281)National Energy-Saving and Low-Carbon Materials Production and Application Demonstration Platform Program,China(No.TC220H06N)。
文摘The research,fabrication and development of piezoelectric nanofibrous materials offer effective solutions to the challenges related to energy consumption and non-renewable resources.However,enhancing their electrical output still remains a significant challenge.Here,a strategy of inducing constrained phase separation on single nanofibers via shear force was proposed.Employing electrospinning technology,a polyacrylonitrile/polyvinylidene difluoride(PAN/PVDF)nanofibrous membrane was fabricated in one step,which enabled simultaneous piezoelectric and triboelectric conversion within a single-layer membrane.Each nanofiber contained independent components of PAN and PVDF and exhibited a rough surface.The abundant frictional contact points formed between these heterogeneous components contributed to an enhanced endogenous triboelectric output,showcasing an excellent synergistic effect of piezoelectric and triboelectric response in the nanofibrous membrane.Additionally,the component mass ratio influenced the microstructure,piezoelectric conformation and piezoelectric performance of the PAN/PVDF nanofibrous membranes.Through comprehensive performance comparison,the optimal mass ratio of PAN to PVDF was determined to be 9∶1.The piezoelectric devices made of the optimal PAN/PVDF nanofibrous membranes with rough nanofiber surfaces generated an output voltage of 20 V,which was about 1.8 times that of the smooth one at the same component mass ratio.The strategy of constrained phase separation on the surface of individual nanofibers provides a new approach to enhance the output performance of single-layer piezoelectric nanofibrous materials.
基金supported by the National Natural Science Foundation of China(Nos.62101020 and 62141405)the Special Scientific Research Project of Civil Aircraft,China(No.MJZ5-2N22).
文摘As the proportion of composite materials used in aircraft continues to increase, the electromagnetic Shielding Effectiveness (SE) of these materials becomes a critical factor in the electromagnetic safety design of aircraft structures. The assessment of electromagnetic SE for Slotted Composite Structures(SCSs) is particularly challenging due to their complex geometries and there remains a lack of suitable models for accurately predicting the SE performance of these intricate configurations. To address this issue, this paper introduces SCS-Net, a Deep Neural Network (DNN) method designed to accurately predict the SE of SCS. This method considers the impacts of various structural parameters, material properties and incident wave parameters on the SE of SCSs. In order to better model the SCS, an improved Nicolson-Ross-Weir (NRW) method is introduced in this paper to provide an equivalent flat structure for the SCS and to calculate the electromagnetic parameters of the equivalent structure. Additionally, the prediction of SE via DNNs is limited by insufficient test data, which hinders support for large-sample training. To address the issue of limited measured data, this paper develops a Measurement-Computation Fusion (MCF) dataset construction method. The predictions based on the simulation results show that the proposed method maintains an error of less than 0.07 dB within the 8–10 GHz frequency range. Furthermore, a new loss function based on the weighted L1-norm is established to improve the prediction accuracy for these parameters. Compared with traditional loss functions, the new loss function reduces the maximum prediction error for equivalent electromagnetic parameters by 47%. This method significantly improves the prediction accuracy of SCS-Net for measured data, with a maximum improvement of 23.88%. These findings demonstrate that the proposed method enables precise SE prediction and design for composite structures while reducing the number of test samples needed.
基金supported by the National Science and Technology Innovation 2030-Major Program(2022ZD 0115403)the National Natural Science Foundation of China(61991414)+1 种基金Chongqing Natural Science Foundation(CSTB2023NSCQJQX0018)Beijing Natural Science Foundation(L221005)
文摘Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback combination of the agent's own state and neighbors' output,which can achieve exponential output consensus through intermittent communication. The controller is obtained by solving two linear matrix equations, and Zeno behavior is excluded.
文摘In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.
基金supported by the Zhejiang Provincial Natural Science Foundation(LY24F030011,LY23F030005)the National Natural Science Foundation of China(62373131).
文摘In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62473135 and 62173121)。
文摘This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.
文摘Owing to their high practicability,solar PV/T(photovoltaic/thermal)collectors have attracted considerable attention from researchers in both photovoltaic and solar-thermal fields worldwide.In this study,we designed and constructed a novel solar-cooled PV/T system.Through experimental methods,we conducted an in-depth investigation of its thermal and electrical output characteristics and developed mathematical models for both thermal performance and electrical performance.Finally,we validated the experimental data against simulations.The results demonstrate that the designed solar-cooled PV/T system exhibits excellent thermal and electrical output performance.The utilization rate of waste heat from the PV module’s back plate reached 18.59%,and the system’s electrical efficiency improved by 1.92%compared to a conventional PV/T system.This work provides theoretical and experimental guidance for the further optimization and improvement of the solar-cooled PV/T system.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2222027 and 12202416)。
文摘The energy release of energetic composites is severely limited by the inert alumina(Al_(2)O_(3))layer on the surface of aluminum(Al).Polytetrafluoroethylene(PTFE)could eliminate Al_(2)O_(3)layer due to its highly electronegativity and oxidability of fluorine.However,adding PTFE particles would weaken interfacial interactions resulted in poor mechanical properties and interfacial exothermic reaction.Herein,a bridging Al-PTFE as fuel and interfacial reinforcing agent was added and used to prepare LLM-105/AlPTFE microspheres,achieving both high energy output and excellent mechanical properties.The energy release and combustion reaction performance of LLM-105/Al-PTFE microspheres are significantly improved due to high reaction heat and increased interfacial reaction area of Al-PTFE.The maximum pressure and pressurization rate of LLM-105/Al-PTFE microspheres are 164.06 kPa and 29.88 kPa/s,respectively,which are 40.11%and 16.67%higher than those of physical mixed samples.Furthermore,the tensile strength and compressive strength of LLM-105/Al-PTFE microspheres are 100.40%and 26.47%higher than those of LLM-105/Al.This work provides a new approach to improve the energy release and mechanical properties for energetic composites.
基金supported by the National Natural Science Foundation of China(Nos.51775021,52302511)the Fundamental Research Funds for the Central Universities,China(Nos.YWF-23-JC-01,YWF-23-JC-04,YWF-23-JC-09)。
文摘Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.
基金the National Natural Science Foundation of China(U21A20286 to Y.H.,22206054 to Y.H.,and 22478310 to J.Z.)the Fundamental Research Funds for the Central China Normal University(CCNU)。
文摘Hydrogen peroxide(H_(2)O_(2))production via electrochemical two-electron oxygen reduction reaction(ORR)holds a great promise for sustainable energy storage.However,the issues such as high energy consumption and difficult extraction of thermodynamically unstable H_(2)O_(2) still need to be resolved.Herein,we reported a unified system for energy-out production and downstream conversion of H_(2)O_(2).By replacing the sluggish oxygen evolution reaction with a hydrazine oxidation reaction(HzOR),the cell of twoelectron ORR coupled with HzOR achieves the co-generation of electricity energy and valuable H_(2)O_(2).By employing Ru single atoms anchored on cobalt hydroxide(for HzOR)and NiSe_(2)(for ORR)as electrocatalysts,both exhibiting onset potentials near the theoretical values for their respective reactions,the ORR‖HzOR cell exhibits an energy output of 3.58 mW cm^(-2) and generates 0.66 kWh of electricity per kg of H_(2)O_(2).with a production rate of 583 mmol h^(-1) H_(2)O_(2).The produced H_(2)O_(2) was subsequently in-situ upgraded via three downstream conversion pathways to yield value-added products of sodium percarbonate,sodium peroxyborate,and ethylene glycol.A techno-economic analysis confirmed the economic viability of this ORR‖HzOR coupled with downstream conversion system.
文摘BACKGROUND:Pulse indicated continuous cardiac output(PiCCO)has largely replaced Swan-Ganz catheterization in shock patients.However,whether PiCCO monitoring can improve outcomes of shock patients,such as mortality,length of hospital stay,duration of mechanical ventilation,or laboratory parameters,remains unknown.METHODS:This retrospective cohort study included patients with shock in the intensive care unit(ICU)from January 2013 to January 2020.Patients were divided into PiCCO group and non-PiCCO group based on treatment with PiCCO monitoring or not.Demographic characteristics,Acute Physiology and Chronic Health Evaluation(APACHE)II scores,quick Sequential Organ Failure Assessment(qSOFA)scores,14-day mortality,and N-terminal pro-B-type natriuretic peptide(NT-proBNP)levels at 0,1,3 and 7 days after onset of shock,duration of mechanical ventilation,length of hospital stay and hospitalization costs were compiled and analyzed using propensity score matching(PSM).RESULTS:Real-world analysis of 1,583 ICU patients suff ering shock after propensity score matching revealed that 14-day mortality did not differ between PiCCO and non-PiCCO groups(36.2%vs.32.6%,P=0.343).Duration of mechanical ventilation,hospital stay,and hospitalization costs were also similar between the two groups(P>0.05).No diff erences in changes of NT-proBNP levels on days 0,1,3,and 7 as compared to baseline were noted between the two groups(P>0.05).CONCLUSIONS:The results of our real-world indicate that PiCCO monitoring may not shorten the duration of mechanical ventilation,length of hospital stay,or reduce hospitalization costs,nor will it bring survival benefi ts to ICU patients suff ering shock.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
