Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a fr...Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.展开更多
Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making sys...Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions.By considering the village spatial layout and terrain factors,a decision tree model of residential density and terrain type was constructed with accuracies of 76.47%and 96.00%,respectively.Combined with binary classification probability unit regression,an appropriate sewage treatment mode for the village was determined with 87.00%accuracy.The Analytic Hierarchy Process(AHP),combined with the Technique for Order Preference(TOPSIS)by Similarity to an Ideal Solution model,formed the basis for optimal treatment process selection under different emission standards.Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region,focusing on the standard effluent effect(0.3773),low investment cost(0.3196),and high standard effluent effect(0.5115)to determine the best treatment process for the same emission standard under different needs.The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated.This model matches village density,geographic feature,and social development level,and provides scientific support and a theoretical basis for rural sewage treatment decision-making.展开更多
In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD...In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.展开更多
With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medici...With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.展开更多
Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effect...Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.展开更多
The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor depositio...The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.展开更多
This paper presents new estimations for all parameters(amplitude,frequency,quality factor,and initial phase)of the_(0)S_(0)Earth fundamental mode,which was triggered by the 2004 Sumatra-Andaman earthquake with a magni...This paper presents new estimations for all parameters(amplitude,frequency,quality factor,and initial phase)of the_(0)S_(0)Earth fundamental mode,which was triggered by the 2004 Sumatra-Andaman earthquake with a magnitude of Mw9.1.Sixteen records from the IGETS superconducting gravimeters have been analyzed.Using the maximum likelihood method algorithm,frequency,initial phase,and amplitude estimates have been acquired with remarkable accuracy.The values of frequency(814.6568±0.0002μHz)and quality factor(5455±17)obtained in this study differ slightly from those of the PREM model,and the amplitude variations qualitatively correspond to those of the SKS12WM13model.The estimated time delay between the onset of the earthquake and the excitation of the mode(290 s)is consistent with the moment tensor analysis from the USGS National Earthquake Information Center.展开更多
Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordina...Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.展开更多
A high-speed single-mode vertical-cavity surface-emitting laser(VCSEL)is one of the most important light sources for optical interconnects in data centers.Single-mode VCSEL can improve the transmission distance.In thi...A high-speed single-mode vertical-cavity surface-emitting laser(VCSEL)is one of the most important light sources for optical interconnects in data centers.Single-mode VCSEL can improve the transmission distance.In this letter,we demonstrate a single-mode 850 nm VCSEL with a bit rate of 60 Gb/s under NRZ modulation and 104 Gb/s under PAM4 modulation across a 100 m length of OM5 fiber,without the need for equalization or a filter.In addition,by using optical injection locking,the 3 dB bandwidth is enhanced to 68.5 GHz.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the...Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.展开更多
Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factor...Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.展开更多
This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic hea...The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic heat.However,its longterm changes in subduction rate and volume in response to shifting climate conditions are unclear.In this study,we investigated the long-term trend of the subduction rate and volume of the South Pacific–SAMW(SPSAMW)using Simple Ocean Data Assimilation outputs during 1980–2017.The results show the overall increasing trend of the subduction rate of the SPSAMW.The increased subduction of the SPSAMW directly contributes to the volume variation in the SPSAMW.The increased subduction in the South Pacific reached(0.28±0.16)Sv-1 per year,which explains nearly 68%of the volume increase in the SPSAMW.This variability in the SPSAMW reflects alterations in the overlying atmosphere.The positive to negative phase change of the Interdecadal Pacific Oscillation(IPO)in 1980–2017 deepened the Amundsen Sea Low(ASL)via atmospheric teleconnections over the South Pacific.Further analysis reveals that the increased westerly winds during the deepening of ASL resulted in more cold water transport from the south,which deepened the winter mixed layer and thus increased subduction and volume within the SPSAMW subduction region.This finding suggests the association of the long-term trends of SPSAMW subduction and volume with the phase change of the IPO.展开更多
Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combin...Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.展开更多
In this paper,a unified terminal sliding mode(UTSM)control method is proposed for second-order nonlinear systems with uncertainties and disturbances.It is seen that the newly defined terminal sliding surface is integr...In this paper,a unified terminal sliding mode(UTSM)control method is proposed for second-order nonlinear systems with uncertainties and disturbances.It is seen that the newly defined terminal sliding surface is integrated with both conventional and fast terminal sliding mode and exhibits design advantages such as a variable exponent,adjustable sliding mode parameters,and chattering-alleviation effect.The inherent dynamic properties of the closed-loop systems with the UTSM control are discussed in detail via the phase plane and Lyapunov stability theory.Both numerical simulations and experimental results show the flexible sliding manifold design,strong robustness against uncertain dynamics,and effective attenuation of chattering phenomenon.展开更多
It is a strategic measure to implement the fundamental task of cultivating morality and nurturing people by comprehensively promoting the construction of ideological and political education in curriculum.In this paper...It is a strategic measure to implement the fundamental task of cultivating morality and nurturing people by comprehensively promoting the construction of ideological and political education in curriculum.In this paper,the Finance course at Yangtze University is taken as the research object.Addressing the current problem of the"two skins"between professional courses and ideological and political education,it systematically elaborates on the constructed"value guidance-knowledge transmission-ability cultivation"trinity integrated model of ideological and political education in curriculum,which provides a valuable reference for the ideological and political construction in similar courses through the paradigm of"localized cases+collaborative practice+systematic education".展开更多
For the ultra HVDC(UHVDC)with the hierarchical connection mode at the inverter side,considering the change of the Thevenin equivalent parameters(TEP)of post-fault AC grid,a coordinated control strategy to the subseque...For the ultra HVDC(UHVDC)with the hierarchical connection mode at the inverter side,considering the change of the Thevenin equivalent parameters(TEP)of post-fault AC grid,a coordinated control strategy to the subsequent commutation failure(SCF)at both layers is newly proposed.The originality of this work is manifested in three aspects.1)The mechanism of the SCF at the fault layer is newly found by deriving the analytical expression of the extinction angle with the TEP,and that at the non-fault layer is newly found by the voltage-time area theory with the DC current coupling.2)An estimation model for the TEPs of two AC grids at the inverter side is proposed with the post-fault quantities.To address the random noise and inaccurate measurement data,an adaptive robust least squares method based on the median principle is proposed to solve the TEP model.3)A coordinated control strategy with the estimated TEP is proposed to compensate for the extinction angle at the fault layer and limit the DC current at the non-fault layer,thus suppressing the SCF.The simulation results verify the suppression effect of the proposed control on the SCF under different fault conditions.展开更多
文摘Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.
基金supported by the Central Government Guiding Local Science and Technology Development Fund Project(No.2024SZY0343)the Joint Research Program for Ecological Conservation and High Quality Development of the Yellow River Basin(No.2022-YRUC-01-050205)+2 种基金the Higher Education Scientific Research Project of Inner Mongolia Autonomous Region(No.NJZZ23078)the project of Inner Mongolia"Prairie Talents"Engineering Innovation Entrepreneurship Talent Team,the Major Projects of Erdos Science and Technology(No.2022EEDSKJZDZX015)the Innovation Team of the Inner Mongolia Academy of Science and Technology(No.CXTD2023-01-016).
文摘Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions.By considering the village spatial layout and terrain factors,a decision tree model of residential density and terrain type was constructed with accuracies of 76.47%and 96.00%,respectively.Combined with binary classification probability unit regression,an appropriate sewage treatment mode for the village was determined with 87.00%accuracy.The Analytic Hierarchy Process(AHP),combined with the Technique for Order Preference(TOPSIS)by Similarity to an Ideal Solution model,formed the basis for optimal treatment process selection under different emission standards.Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region,focusing on the standard effluent effect(0.3773),low investment cost(0.3196),and high standard effluent effect(0.5115)to determine the best treatment process for the same emission standard under different needs.The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated.This model matches village density,geographic feature,and social development level,and provides scientific support and a theoretical basis for rural sewage treatment decision-making.
文摘In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.
基金supported by the National Natural Science Foundation of China(Grant 62293545)Shenzhen Science and Technology Program(Grant ZDSYS20220323112000001).
文摘With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.Ashit Kumar Dutta would like to thank AlMaarefa University for supporting this research under project number MHIRSP2025017.
文摘Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3608602)the National Natural Science Foundation of China(Grant Nos.62404215 and 62574199)Instrument and Equipment Development Project of CAS(Grant No.PTYQ2024TD0003)。
文摘The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
基金conducted under the state assignment of Lomonosov Moscow State University。
文摘This paper presents new estimations for all parameters(amplitude,frequency,quality factor,and initial phase)of the_(0)S_(0)Earth fundamental mode,which was triggered by the 2004 Sumatra-Andaman earthquake with a magnitude of Mw9.1.Sixteen records from the IGETS superconducting gravimeters have been analyzed.Using the maximum likelihood method algorithm,frequency,initial phase,and amplitude estimates have been acquired with remarkable accuracy.The values of frequency(814.6568±0.0002μHz)and quality factor(5455±17)obtained in this study differ slightly from those of the PREM model,and the amplitude variations qualitatively correspond to those of the SKS12WM13model.The estimated time delay between the onset of the earthquake and the excitation of the mode(290 s)is consistent with the moment tensor analysis from the USGS National Earthquake Information Center.
基金supported by the National Natural Science Foundation of China(Grants 42374215,42230209,42374199,42304183,42422406,42174185,72061147004 and 72342001)the Science and Technology Development Fund,Macao SAR(File no.0042/2024/RIA1 and 0008/2024/AKP)+1 种基金the Natural Science Foundation of Hunan Province(Grant 2023JJ20038)the Research Project of Science and Technology of Hunan Province(2025JJ10009,2022RC4025,2025QK1004,2023JJ50312,2023JJ50010 and 2024RC9012).
文摘Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.
基金supported by the National Key R&D Program of China(2021YFB2801000).
文摘A high-speed single-mode vertical-cavity surface-emitting laser(VCSEL)is one of the most important light sources for optical interconnects in data centers.Single-mode VCSEL can improve the transmission distance.In this letter,we demonstrate a single-mode 850 nm VCSEL with a bit rate of 60 Gb/s under NRZ modulation and 104 Gb/s under PAM4 modulation across a 100 m length of OM5 fiber,without the need for equalization or a filter.In addition,by using optical injection locking,the 3 dB bandwidth is enhanced to 68.5 GHz.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number-ber 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Admin-istration Climate Change Special Program[grant number QBZ202303]。
文摘Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.
基金the funding provided by the China Scholarship Council(Grant No.201804910634)the Ecology Fund of the Royal Netherlands Academy of Arts and Sciences(KNAWWF/807/19039)to Deyi Wang.
文摘Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金supported by the National Natural Science Foundation of China(Nos.42406256,42376034,and 42430402)the Qingdao Postdoctoral Application Research Project(No.QDBSH20220202152)+1 种基金the National Key R&D Program of China(No.2018YFA0605701)the Chinese Arctic and Antarctic Administration(No.IRASCC2020-2022-02-01-03)。
文摘The subantarctic mode water(SAMW)represents a large water mass in the Southern Ocean.This body of water forms through deep convection(subduction)in winter and contributes to the uptake and storage of anthropogenic heat.However,its longterm changes in subduction rate and volume in response to shifting climate conditions are unclear.In this study,we investigated the long-term trend of the subduction rate and volume of the South Pacific–SAMW(SPSAMW)using Simple Ocean Data Assimilation outputs during 1980–2017.The results show the overall increasing trend of the subduction rate of the SPSAMW.The increased subduction of the SPSAMW directly contributes to the volume variation in the SPSAMW.The increased subduction in the South Pacific reached(0.28±0.16)Sv-1 per year,which explains nearly 68%of the volume increase in the SPSAMW.This variability in the SPSAMW reflects alterations in the overlying atmosphere.The positive to negative phase change of the Interdecadal Pacific Oscillation(IPO)in 1980–2017 deepened the Amundsen Sea Low(ASL)via atmospheric teleconnections over the South Pacific.Further analysis reveals that the increased westerly winds during the deepening of ASL resulted in more cold water transport from the south,which deepened the winter mixed layer and thus increased subduction and volume within the SPSAMW subduction region.This finding suggests the association of the long-term trends of SPSAMW subduction and volume with the phase change of the IPO.
基金supported by the Zhenjiang Key R&D Plan(GY2021009)Lianyungang City Major Technology Breakthrough(CGJBGS2104)+2 种基金National Natural Science Foundation of China under Grant(12302456)National Key Laboratory Foundation of Science and Technology on Materials under Shock and Impact under Grant(6142902241601)China Postdoctoral Science Foundation under Grants(2025M774217)。
文摘Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.
基金supported by the National Natural Science Foundation of China(62473337,62003305)the Key Research and Development Program of Zhejiang Province(2024C03040,2022C03029)the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang Province(2023R01006)。
文摘In this paper,a unified terminal sliding mode(UTSM)control method is proposed for second-order nonlinear systems with uncertainties and disturbances.It is seen that the newly defined terminal sliding surface is integrated with both conventional and fast terminal sliding mode and exhibits design advantages such as a variable exponent,adjustable sliding mode parameters,and chattering-alleviation effect.The inherent dynamic properties of the closed-loop systems with the UTSM control are discussed in detail via the phase plane and Lyapunov stability theory.Both numerical simulations and experimental results show the flexible sliding manifold design,strong robustness against uncertain dynamics,and effective attenuation of chattering phenomenon.
基金Supported by the General Project of Hubei Provincial Education Science Planning in 2025(2025GB482)the First Batch of Collaborative Education Projects between Industry and University at Yangtze University in 2025(Reform and Practice of Collaborative Intelligent Teaching between Industry and University in Finance under the Background of Digital Transformation)the Teaching Reform Research Project of Yangtze University in 2024(JY2024059).
文摘It is a strategic measure to implement the fundamental task of cultivating morality and nurturing people by comprehensively promoting the construction of ideological and political education in curriculum.In this paper,the Finance course at Yangtze University is taken as the research object.Addressing the current problem of the"two skins"between professional courses and ideological and political education,it systematically elaborates on the constructed"value guidance-knowledge transmission-ability cultivation"trinity integrated model of ideological and political education in curriculum,which provides a valuable reference for the ideological and political construction in similar courses through the paradigm of"localized cases+collaborative practice+systematic education".
基金supported in part by the National Natural Science Foundation of China under Grant 51877061.
文摘For the ultra HVDC(UHVDC)with the hierarchical connection mode at the inverter side,considering the change of the Thevenin equivalent parameters(TEP)of post-fault AC grid,a coordinated control strategy to the subsequent commutation failure(SCF)at both layers is newly proposed.The originality of this work is manifested in three aspects.1)The mechanism of the SCF at the fault layer is newly found by deriving the analytical expression of the extinction angle with the TEP,and that at the non-fault layer is newly found by the voltage-time area theory with the DC current coupling.2)An estimation model for the TEPs of two AC grids at the inverter side is proposed with the post-fault quantities.To address the random noise and inaccurate measurement data,an adaptive robust least squares method based on the median principle is proposed to solve the TEP model.3)A coordinated control strategy with the estimated TEP is proposed to compensate for the extinction angle at the fault layer and limit the DC current at the non-fault layer,thus suppressing the SCF.The simulation results verify the suppression effect of the proposed control on the SCF under different fault conditions.
