The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ...The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.展开更多
This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state obs...This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.展开更多
Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Couple...Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.展开更多
Chassis-by-wire technology has gained significant attention,with the scope of chassis domain control expanding from traditional two-dimensional plane motion control to encompass three-dimensional space motion control....Chassis-by-wire technology has gained significant attention,with the scope of chassis domain control expanding from traditional two-dimensional plane motion control to encompass three-dimensional space motion control.Modern chassis-by-wire systems manage an increasing number of heterogeneous chassis execution systems,including distributed drive,all-wheel drive(AWD),brake-by-wire(BBW),steer-by-wire(SBW),rear-wheel steering(RWS),active stabilizer bar(ASB)and active suspension system(ASS),greatly enhancing the controllable degrees of freedom compared to conventional chassis configurations.To advance research in chassis domain control,it is essential to understand how these heterogeneous execution systems influence vehicle dynamics.This paper focuses on the modeling and analysis of the lateral,longitudinal,and vertical chassis control and execution systems,-as well as their impact on vehicle lateral motion.Using a vehicle simulation platform,both the vehicle dynamics model and the individual dynamics models of each execution system were developed to analyze the influence of these systems on lateral dynamics.Additionally,a hierarchical control architecture was designed to control the vehicle’s lateral stability.The effectiveness of the proposed control scheme was demonstrated and validated through hardware-in-the-loop(HIL)tests and real-world vehicle testing.展开更多
Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal ene...Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.展开更多
With the advancement of more electric aircraft(MEA)technology,the application of electro-hydrostatic actuators(EHAs)in aircraft actuation systems has become increasingly prevalent.This paper focuses on the modeling an...With the advancement of more electric aircraft(MEA)technology,the application of electro-hydrostatic actuators(EHAs)in aircraft actuation systems has become increasingly prevalent.This paper focuses on the modeling and mode switching analysis of EHA used in the primary flight control actuation systems of large aircraft,addressing the challenges associated with mode switching.First,we analyze the functional architecture and operational characteristics of multi-mode EHA,and sumarize the operating modes and implementation methods.Based on the EHA system architecture,we then develop a theoretical mathematical model and a simulation model.Using the simulation model,we analyze the performance of the EHA during normal operation.Finally,the performance of the EHA during mode switching under various functional switching scenarios is investigated.The results indicate that the EHA meets the performance requirements in terms of accuracy,bandwidth,and load capacity.Additionally,the hydraulic cylinder operates smoothly during the EHA mode switching,and the response time for switching between different modes is less than the specified threshold.These findings validate the system performance of multi-mode EHA,which helps to improve the reliability of EHA and the safety of aircraft flight control systems.展开更多
This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the elec...This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the electro-hydraulic power-shift system is developed,incorporating pipeline characteristics through impedance analysis and examining coupling effects between the pilot solenoid valve,main valve,and pipeline.Then,the model’s accuracy is validated through experimental testing,demonstrating high precision and minimal model errors.A comparative analysis between simulation data(both with and without pipeline characteristics)and experimental results reveals that the model considering pipeline parameters aligns more closely with experimental data,highlighting its superior accuracy.The research further explores the influence of key factors on system stability,including damping coefficient,feedback cavity orifice diameter,spring stiffness,pipeline length,and pipeline diameter.Significant findings include the critical impact of damping coefficient,orifice diameter,and pipeline length on stability,while spring stiffness has a minimal effect.These findings provide valuable insights for optimizing electro-hydraulic control modules in intelligent chassis systems,with practical implications for automotive and construction machinery applications.展开更多
A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimens...A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at https://github.com/yuanyeswu/PINLF/blob/mainIPINLF-code.zip.展开更多
With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier un...With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.展开更多
In this work,a computational modelling and analysis framework is developed to investigate the thermal buckling behavior of doubly-curved composite shells reinforced with graphene-origami(G-Ori)auxetic metamaterials.A ...In this work,a computational modelling and analysis framework is developed to investigate the thermal buckling behavior of doubly-curved composite shells reinforced with graphene-origami(G-Ori)auxetic metamaterials.A semi-analytical formulation based on the First-Order Shear Deformation Theory(FSDT)and the principle of virtual displacements is established,and closed-form solutions are derived via Navier’s method for simply supported boundary conditions.The G-Ori metamaterial reinforcements are treated as programmable constructs whose effective thermo-mechanical properties are obtained via micromechanical homogenization and incorporated into the shell model.A comprehensive parametric study examines the influence of folding geometry,dispersion arrangement,reinforcement weight fraction,curvature parameters,and elastic foundation support on the critical buckling temperature(CBT).The results reveal that,under optimal folding geometry and reinforcement alignment with principal stress trajectories,the CBT can increase by more than 150%.Furthermore,the combined effect of G-Ori reinforcement and elastic foundation substantially enhances thermal buckling resistance.These findings establish design guidelines for architected composite shells in applications such as aerospace thermal skins,morphing structures,and thermally-responsive systems,and illustrate the potential of auxetic graphene metamaterials for multifunctional,lightweight,and thermally robust structural components.展开更多
Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategie...Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.展开更多
Objective:To observe the clinical efficacy of sitting-position knee adjustment Tuina(Chinese therapeutic massage)and therapeutic ultrasound in treating knee osteoarthritis(KOA)and the impact on gait analysis parameter...Objective:To observe the clinical efficacy of sitting-position knee adjustment Tuina(Chinese therapeutic massage)and therapeutic ultrasound in treating knee osteoarthritis(KOA)and the impact on gait analysis parameters.Methods:In a randomized controlled design,80 KOA patients were randomly allocated to a manipulation group and an ultrasound group,each with 40 cases.Patients in the manipulation group received the sitting-position knee adjustment Tuina treatment;patients in the ultrasound group received low-frequency ultrasounds for treatment.The intervention was conducted twice weekly,and therapeutic efficacy was evaluated after 4 weeks of treatment.Before treatment,immediately after treatment,and after 2-week and 4-week treatment,the visual analog scale(VAS)and the Western Ontario and McMaster Universities osteoarthritis index(WOMAC)scores were observed;the gait analysis outcomes were compared before treatment and after 4-week treatment,including cadence,speed,step length,stride length,single stance phase,double stance phase,and the maximal flexion angle of the knee joint.Results:Intra-group comparisons revealed that both groups showed decreased VAS scores and increased WOMAC scores immediately after treatment and after 2-week and 4-week treatment,with statistical significance(P<0.05).Immediately after treatment,the VAS score was lower in the manipulation group than in the ultrasound group(P<0.05),and the WOMAC pain score was higher in the manipulation group(P<0.05),while the ultrasound group had a higher WOMAC stiffness score than the manipulation group(P<0.05).After 2 weeks of treatment,there were no significant differences in VAS and WOMAC scores between the two groups(P>0.05).After 4-week treatment,the ultrasound group had a higher WOMAC pain score than the manipulation group(P<0.05),and the manipulation group had higher WOMAC stiffness and function scores than the ultrasound group(P<0.05).The between-group difference in the WOMAC total score remained statistically insignificant throughout the treatment(P>0.05).Regarding the gait parameters,both groups showed improvements in the cadence,speed,step length,stride length,single stance phase,double stance phase,swing phase,and maximal knee flexion angle immediately after treatment and after 2 and 4 weeks of treatment;the intra-group differences were all statistically significant(P<0.05).After 4-week treatment,the manipulation group surpassed the ultrasound group in improvements in stride length,step length,swing phase,single stance phase,and maximal knee flexion angle(P<0.05).Conclusion:Both the sitting-position knee adjustment Tuina and low-frequency ultrasound therapies are effective in treating KOA and can improve the patient’s walking ability;the sitting-position knee adjustment manipulation demonstrates superior immediate pain relief and long-term improvement of stiffness,joint function,and walking ability compared to the low-frequency ultrasound.展开更多
This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advance...Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the...Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation anal...In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation analysis on two typical co-pollution events in Beijing,occurring from July 22 to July 28,2019,and from April 25 to May 2,2020.These events were categorized into pre-trough southerly airflow type(Type 1)and post-trough northwest flow type(Type 2).Subsequently,sensitivity analyses using the GRAPES-CUACE adjoint model were performed to quantify the contributions of precursor emissions from Beijing and surrounding areas to PM_(2.5)and O_(3) concentrations in Beijing for two types of co-pollution.The results indicated that the spatiotemporal distribution of sensitive source region varied among different circulation types.Primary PM_(2.5)(PPM_(2.5))emissions from Hebei contributed the most to the 24-hour average PM_(2.5)(24-h PM_(2.5))peak concentration(41.6%-45.4%),followed by Beijing emissions(31%-35.7%).The maximum daily 8-hour average ozone peak concentration was primarily influenced by the emissions from Hebei and Beijing,with contribution ratios respectively of 32.8%-44.8% and 29%-42.1%.Additionally,NO_(x)emissions were the main contributors in Type 1,while both NO_(x)and VOCs emissions contributed similarly in Type 2.The iterative emission reduction experiments for two types of co-pollution indicated that Type 1 required emission reductions in NO_(x)(52.4%-71.8%)and VOCs(14.1%-33.8%)only.In contrast,Type 2 required combined emission reductions in NO_(x)(37.0%-65.1%),VOCs(30.7%-56.2%),and PPM_(2.5)(31%-46.9%).This study provided a reference for controlling co-pollution events and improving air quality in Beijing.展开更多
Purpose:This study provides a comprehensive bibliometric analysis of the environmental management control tools literature.It seeks to summarize this body of literature’s growth and identify the most influential auth...Purpose:This study provides a comprehensive bibliometric analysis of the environmental management control tools literature.It seeks to summarize this body of literature’s growth and identify the most influential authors,journals,and articles in this field.The main objective of this article is to determine which tools are most prominent in the literature.Methodology/approach:The study examined 541 articles published in 126 academically indexed journals in the Scopus database.The analyzed timeframe covers the period from 2011 to 2023.We used VOSviewer software for statistical calculations to map the collaborations among authors and journals and to develop a conceptual and intellectual map of the field.Results:Our findings show that the literature on environmental management control tools is flourishing.The authors who dominated this period are mainly Schaltegger,Sala,and Ulgiati.The Journal of Cleaner Production is the primary source of publications,with an astounding 241 documents.The United States attained the leading position in terms of publication with 86 documents,which explains its willingness to collaborate with other countries,followed by China and Australia with 70 and 66 papers,respectively.Finally,bibliometric analysis shows that“life cycle assessment”,“cost-benefit analysis”,and“sustainability reporting”are the most prominent tools in research on this topic.Originality/value:This article provides several starting points for researchers and practitioners investigating environmental management control tools.It contributes to broadening the field’s vision and then offers recommendations for future studies.展开更多
基金Project(U2034211)supported by the National Natural Science Foundation of ChinaProject(20232ACE01013)supported by the Major Scientific and Technological Research and Development Special Project of Jiangxi Province,China。
文摘The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473344,92471204)the Natural Science Basic Research Program of Shaanxi(Grant No.2025JC-YBQN035)Ministry of Education's Industry School Cooperation Collaborative Education Project(Grant No.240704701190619)。
文摘This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272411 and 42007259).
文摘Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.
基金Supported by National Nature Science Foundation of China(Grant Nos.52325212,52372394)National Key Research and Development Program of China(Grant Nos.2022YFE0117100,2021YFB2501201)+1 种基金Industry-University-Research Innovation Fund for Chinese Universities(Grand No.2024HT010)Fundamental Research Funds for the Central Universities.
文摘Chassis-by-wire technology has gained significant attention,with the scope of chassis domain control expanding from traditional two-dimensional plane motion control to encompass three-dimensional space motion control.Modern chassis-by-wire systems manage an increasing number of heterogeneous chassis execution systems,including distributed drive,all-wheel drive(AWD),brake-by-wire(BBW),steer-by-wire(SBW),rear-wheel steering(RWS),active stabilizer bar(ASB)and active suspension system(ASS),greatly enhancing the controllable degrees of freedom compared to conventional chassis configurations.To advance research in chassis domain control,it is essential to understand how these heterogeneous execution systems influence vehicle dynamics.This paper focuses on the modeling and analysis of the lateral,longitudinal,and vertical chassis control and execution systems,-as well as their impact on vehicle lateral motion.Using a vehicle simulation platform,both the vehicle dynamics model and the individual dynamics models of each execution system were developed to analyze the influence of these systems on lateral dynamics.Additionally,a hierarchical control architecture was designed to control the vehicle’s lateral stability.The effectiveness of the proposed control scheme was demonstrated and validated through hardware-in-the-loop(HIL)tests and real-world vehicle testing.
基金supported by the National Natural Science Foundation of China(12305185)Natural Science Foundation of Hunan Province,China(No.2023JJ50122)+1 种基金International Cooperative Research Project of the Ministry of Education,China(No.HZKY20220355)Scientific Research Foundation of the Education Department of Hunan Province,China(No.22A0307).
文摘Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.
基金supported by the Chinese Civil Aircraft Project(No.MJ-2017-S49).
文摘With the advancement of more electric aircraft(MEA)technology,the application of electro-hydrostatic actuators(EHAs)in aircraft actuation systems has become increasingly prevalent.This paper focuses on the modeling and mode switching analysis of EHA used in the primary flight control actuation systems of large aircraft,addressing the challenges associated with mode switching.First,we analyze the functional architecture and operational characteristics of multi-mode EHA,and sumarize the operating modes and implementation methods.Based on the EHA system architecture,we then develop a theoretical mathematical model and a simulation model.Using the simulation model,we analyze the performance of the EHA during normal operation.Finally,the performance of the EHA during mode switching under various functional switching scenarios is investigated.The results indicate that the EHA meets the performance requirements in terms of accuracy,bandwidth,and load capacity.Additionally,the hydraulic cylinder operates smoothly during the EHA mode switching,and the response time for switching between different modes is less than the specified threshold.These findings validate the system performance of multi-mode EHA,which helps to improve the reliability of EHA and the safety of aircraft flight control systems.
基金Supported by the Basic Product Innovation Plan for Vehicle Power Scientific Research Project(Grant No.JCCPCX201704).
文摘This research presents an advanced study on the modeling and stability analysis of electro-hydraulic control modules used in intelligent chassis systems.Firstly,a comprehensive nonlinear mathematical model of the electro-hydraulic power-shift system is developed,incorporating pipeline characteristics through impedance analysis and examining coupling effects between the pilot solenoid valve,main valve,and pipeline.Then,the model’s accuracy is validated through experimental testing,demonstrating high precision and minimal model errors.A comparative analysis between simulation data(both with and without pipeline characteristics)and experimental results reveals that the model considering pipeline parameters aligns more closely with experimental data,highlighting its superior accuracy.The research further explores the influence of key factors on system stability,including damping coefficient,feedback cavity orifice diameter,spring stiffness,pipeline length,and pipeline diameter.Significant findings include the critical impact of damping coefficient,orifice diameter,and pipeline length on stability,while spring stiffness has a minimal effect.These findings provide valuable insights for optimizing electro-hydraulic control modules in intelligent chassis systems,with practical implications for automotive and construction machinery applications.
基金supported in part by the National Natural Science Foundation of China(62372385,62272078)the Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069).
文摘A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at https://github.com/yuanyeswu/PINLF/blob/mainIPINLF-code.zip.
基金funded by the Science and Technology Projects of State Grid Zhejiang Electric Power Co.,Ltd.(5211DS24000G).
文摘With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.
文摘In this work,a computational modelling and analysis framework is developed to investigate the thermal buckling behavior of doubly-curved composite shells reinforced with graphene-origami(G-Ori)auxetic metamaterials.A semi-analytical formulation based on the First-Order Shear Deformation Theory(FSDT)and the principle of virtual displacements is established,and closed-form solutions are derived via Navier’s method for simply supported boundary conditions.The G-Ori metamaterial reinforcements are treated as programmable constructs whose effective thermo-mechanical properties are obtained via micromechanical homogenization and incorporated into the shell model.A comprehensive parametric study examines the influence of folding geometry,dispersion arrangement,reinforcement weight fraction,curvature parameters,and elastic foundation support on the critical buckling temperature(CBT).The results reveal that,under optimal folding geometry and reinforcement alignment with principal stress trajectories,the CBT can increase by more than 150%.Furthermore,the combined effect of G-Ori reinforcement and elastic foundation substantially enhances thermal buckling resistance.These findings establish design guidelines for architected composite shells in applications such as aerospace thermal skins,morphing structures,and thermally-responsive systems,and illustrate the potential of auxetic graphene metamaterials for multifunctional,lightweight,and thermally robust structural components.
基金funding from the China National Key Research and Development Program(No.2023YFC3603104)the National Natural Science Foundation of China(Nos.82472243 and 82272180)+6 种基金the Fundamental Research Funds for the Central Universities(No.226-2025-00024)the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(No.LHDMD24H150001)the Key Research&Development Project of Zhejiang Province(No.2024C03240)a collaborative scientific project co-established by the Science and Technology Department of the National Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine(No.GZY-ZJ-KJ-24082)he General Health Science and Technology Program of Zhejiang Province(No.2024KY1099)the Project of Zhejiang University Longquan Innovation Center(No.ZJDXLQCXZCJBGS2024016)Wu Jieping Medical Foundation Special Research Grant(No.320.6750.2024-23-07).
文摘Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.
基金supported by Shanghai Key Clinical Specialty Project(上海市临床重点专科项目,No.shslczdzk04001)High-level Key Discipline of National Administration of Traditional Chinese Medicine-Tuina Science(国家中医药管理局高水平重点学科-推拿学,No.zyyzdxk-2023061)The 10th Batch of Talent Cultivation Project Under the“Young Talents Program”of Yueyang Hospital(岳阳医院第十批青苗计划人才培养项目,No.RY411.07.02.23).
文摘Objective:To observe the clinical efficacy of sitting-position knee adjustment Tuina(Chinese therapeutic massage)and therapeutic ultrasound in treating knee osteoarthritis(KOA)and the impact on gait analysis parameters.Methods:In a randomized controlled design,80 KOA patients were randomly allocated to a manipulation group and an ultrasound group,each with 40 cases.Patients in the manipulation group received the sitting-position knee adjustment Tuina treatment;patients in the ultrasound group received low-frequency ultrasounds for treatment.The intervention was conducted twice weekly,and therapeutic efficacy was evaluated after 4 weeks of treatment.Before treatment,immediately after treatment,and after 2-week and 4-week treatment,the visual analog scale(VAS)and the Western Ontario and McMaster Universities osteoarthritis index(WOMAC)scores were observed;the gait analysis outcomes were compared before treatment and after 4-week treatment,including cadence,speed,step length,stride length,single stance phase,double stance phase,and the maximal flexion angle of the knee joint.Results:Intra-group comparisons revealed that both groups showed decreased VAS scores and increased WOMAC scores immediately after treatment and after 2-week and 4-week treatment,with statistical significance(P<0.05).Immediately after treatment,the VAS score was lower in the manipulation group than in the ultrasound group(P<0.05),and the WOMAC pain score was higher in the manipulation group(P<0.05),while the ultrasound group had a higher WOMAC stiffness score than the manipulation group(P<0.05).After 2 weeks of treatment,there were no significant differences in VAS and WOMAC scores between the two groups(P>0.05).After 4-week treatment,the ultrasound group had a higher WOMAC pain score than the manipulation group(P<0.05),and the manipulation group had higher WOMAC stiffness and function scores than the ultrasound group(P<0.05).The between-group difference in the WOMAC total score remained statistically insignificant throughout the treatment(P>0.05).Regarding the gait parameters,both groups showed improvements in the cadence,speed,step length,stride length,single stance phase,double stance phase,swing phase,and maximal knee flexion angle immediately after treatment and after 2 and 4 weeks of treatment;the intra-group differences were all statistically significant(P<0.05).After 4-week treatment,the manipulation group surpassed the ultrasound group in improvements in stride length,step length,swing phase,single stance phase,and maximal knee flexion angle(P<0.05).Conclusion:Both the sitting-position knee adjustment Tuina and low-frequency ultrasound therapies are effective in treating KOA and can improve the patient’s walking ability;the sitting-position knee adjustment manipulation demonstrates superior immediate pain relief and long-term improvement of stiffness,joint function,and walking ability compared to the low-frequency ultrasound.
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
基金Open access funding provided by The Science,Technology&Innovation Funding Authority(STDF)in cooperation with The Egyptian Knowledge Bank(EKB).
文摘Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金the financial support from the Fujian Science Foundation for Outstanding Youth(2023J06039)the National Natural Science Foundation of China(Grant No.41977259,U2005205,41972268)the Independent Research Project of Technology Innovation Center for Monitoring and Restoration Engineering of Ecological Fragile Zone in Southeast China(KY-090000-04-2022-019)。
文摘Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
基金supported by the National Key Research and Development Program of China(No.2022YFC3701205)the National Natural Science Foundation of China(No.41975173)the Science and Technology Development Fund of the Chinese Academy of Meteorological Sciences(No.2021KJ011)。
文摘In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation analysis on two typical co-pollution events in Beijing,occurring from July 22 to July 28,2019,and from April 25 to May 2,2020.These events were categorized into pre-trough southerly airflow type(Type 1)and post-trough northwest flow type(Type 2).Subsequently,sensitivity analyses using the GRAPES-CUACE adjoint model were performed to quantify the contributions of precursor emissions from Beijing and surrounding areas to PM_(2.5)and O_(3) concentrations in Beijing for two types of co-pollution.The results indicated that the spatiotemporal distribution of sensitive source region varied among different circulation types.Primary PM_(2.5)(PPM_(2.5))emissions from Hebei contributed the most to the 24-hour average PM_(2.5)(24-h PM_(2.5))peak concentration(41.6%-45.4%),followed by Beijing emissions(31%-35.7%).The maximum daily 8-hour average ozone peak concentration was primarily influenced by the emissions from Hebei and Beijing,with contribution ratios respectively of 32.8%-44.8% and 29%-42.1%.Additionally,NO_(x)emissions were the main contributors in Type 1,while both NO_(x)and VOCs emissions contributed similarly in Type 2.The iterative emission reduction experiments for two types of co-pollution indicated that Type 1 required emission reductions in NO_(x)(52.4%-71.8%)and VOCs(14.1%-33.8%)only.In contrast,Type 2 required combined emission reductions in NO_(x)(37.0%-65.1%),VOCs(30.7%-56.2%),and PPM_(2.5)(31%-46.9%).This study provided a reference for controlling co-pollution events and improving air quality in Beijing.
文摘Purpose:This study provides a comprehensive bibliometric analysis of the environmental management control tools literature.It seeks to summarize this body of literature’s growth and identify the most influential authors,journals,and articles in this field.The main objective of this article is to determine which tools are most prominent in the literature.Methodology/approach:The study examined 541 articles published in 126 academically indexed journals in the Scopus database.The analyzed timeframe covers the period from 2011 to 2023.We used VOSviewer software for statistical calculations to map the collaborations among authors and journals and to develop a conceptual and intellectual map of the field.Results:Our findings show that the literature on environmental management control tools is flourishing.The authors who dominated this period are mainly Schaltegger,Sala,and Ulgiati.The Journal of Cleaner Production is the primary source of publications,with an astounding 241 documents.The United States attained the leading position in terms of publication with 86 documents,which explains its willingness to collaborate with other countries,followed by China and Australia with 70 and 66 papers,respectively.Finally,bibliometric analysis shows that“life cycle assessment”,“cost-benefit analysis”,and“sustainability reporting”are the most prominent tools in research on this topic.Originality/value:This article provides several starting points for researchers and practitioners investigating environmental management control tools.It contributes to broadening the field’s vision and then offers recommendations for future studies.
