This study examines the reliability and validity of AI-generated scoring for continuation writing tasks.By comparing GPT-4 with eight experienced human raters across 21 student responses,it evaluates AI’s consistency...This study examines the reliability and validity of AI-generated scoring for continuation writing tasks.By comparing GPT-4 with eight experienced human raters across 21 student responses,it evaluates AI’s consistency,severity,and alignment with human scoring criteria.Results show that AI exhibits high self-consistency and adapts effectively to different scoring roles(e.g.,teacher vs.highstakes rater).However,AI scores were more lenient than human raters and demonstrated divergent evaluation focuses—prioritizing narrative coherence and emotional depth,while teachers emphasized linguistic accuracy and richness of detail.The findings suggest AI’s potential as a supplementary assessment tool,offering rapid,holistic feedback,but highlight the need for further calibration to align with educational standards.Implications include exploring hybrid evaluation models that leverage the strengths of both AI and human raters to achieve more equitable,efficient,and pedagogically meaningful writing assessments.展开更多
The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous ...The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous pattern changes in order to operate profitably–meaning they require machines that offer maximum flexibility,reliability and cost efficiency.KARL MAYER understands the challenges of the market and is launching its new RE 6 EL.The Raschel machine offers the core strengths of the classic RSE 6 EL and essentially the same performance parameters,but has been further cost-optimised largely due to local production advantages.This makes the newcomer an efficiency champion in production,especially when it comes to frequent pattern changes.展开更多
Background:The World Health Organization Disability Assessment Schedule 2.0(WHODAS 2.0)is a popular tool for eval-uating functioning and disability in a range of population demographics and medical situations.However,...Background:The World Health Organization Disability Assessment Schedule 2.0(WHODAS 2.0)is a popular tool for eval-uating functioning and disability in a range of population demographics and medical situations.However,very little is known about the WHODAS 2.0's validity and reliability,particularly when dealing with potentially life-threatening maternal condi-tions(PLTCs).The aim of this study was to evaluate the validity of the WHODAS 2.0 Tigrigna version.Methods:This cross-sectional study was conducted in Tigray,northern Ethiopia,from December 15 to 20,2023.Following translation and back translation,women who had experienced PLTCs during a recent pregnancy,childbirth,or postpartum period were administered the 36-item WHODAS 2.0 in Tigrigna version 6 months after the childbirth.In total,121 women with a history of PLTCs participated.Cronbach′sαwas used to evaluate internal consistency in all six WHODAS 2.0 domains,while Spearman′s correlation coefficient was used to evaluate convergent validity.With confirmatory factor analysis,construct validity was also examined.Results:All domain scores of the Tigrigna version of the WHODAS 2.0 indicated excellent internal consistency(α=0.917-0.978 for 36 items andα=0.874-0.940 for 12 items),while the Cronbach′sαcoefficients for the summary score were 0.981 and 0.952 for 36 and 12 items,respectively.The convergent validity between the 36-item and 12-item WHODAS 2.0 showed a strong correlation between similar constructs(r=0.909-0.981).Conclusion:Despite the small sample limitation,the WHODAS 2.0 tool adapted to the Tigrigna version indicated an acceptable reliability and validity and therefore could be applied to women with a history of PLTCs at 6 months postpartum.展开更多
Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the ten...Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the tensile stress in the area has exceeded the tensile strength of the soil,leading to local instability.To explore the impact of tensile failure behavior on the stability and failure modes of reservoir landslides,the Huangtupo Riverside Slump#1 is taken as a case study.By considering local tensile failure,potential tensile cracks are incorporated into the analysis via the limit equilibrium method and reliability theory.The reliability of landslides under different tensile failure scenarios is quantified.Strain-softening characteristics of the soil are combined to further analyze the failure transmission path of the landslide.Finally,these potential failure modes were validated through physical model tests.The results show that cracks developing at rear positions reduce the stability of the slope and increase the probability of instability.During the destruction process,retrogressive failures with multiple sliding surfaces are likely to occur.However,tensile failure at the forefront reduces the likelihood of an individual slide mass descending.Progressive failure results in both regular and skip transmission patterns.Additionally,cracks and water level changes can also lead to shifts in the positions of the most dangerous blocks.Therefore,in practical landslide analysis and prevention,it is necessary to consider local tensile damage and identify potential tensile crack locations in advance to optimize prevention measures and accurately evaluate landslide risk.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
A stochastic predator-prey system with Markov switching is explored.We have developed a new chasing technique to efficiently solve the Fokker-Planck-Kolmogorov and backward Kolmogorov equations.Dynamic balance and rel...A stochastic predator-prey system with Markov switching is explored.We have developed a new chasing technique to efficiently solve the Fokker-Planck-Kolmogorov and backward Kolmogorov equations.Dynamic balance and reliability of the switching system are evaluated via stationary probability density function and first-passage failure theory,taking into account factors such as switching frequencies,noise intensities,and initial conditions.Results reveal that Markov switching leads to stochastic P-bifurcation,enhancing dynamic balance and reducing white-noise-induced oscillations.But frequent switching can heighten initial value dependence,harming reliability.Further,the influence of the subsystem on the switching system is not proportional to its action probabilities.Monte Carlo simulations validate the findings,offering an in-depth exploration of these dynamics.展开更多
The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the e...The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the end effector of the automatic loading system,and its motion state significantly impacts the accuracy of projectiles.Therefore,it is of immense importance to precisely and effectively evaluate the reliability of the motion accuracy of the ammunition conveyor.This paper aims to propose a practical and efficient analysis method for evaluating the reliability of the motion accuracy of the ammunition conveyor.The proposed approach involves the use of a deep learning network to approximate the physical model and the extremum method to obtain a single cycle sequence decoupling strategy for solving the time-varying reliability issue of complex systems.Employing this strategy,the time-varying reliability of the ammunition conveyor is transformed into a static reliability problem.The proposed method includes the use of a deep feedforward neural network,second-order saddle point ap-proximation(SPA)method,extremum method,and efficient global optimization(EGO)technology.The results reveal that the reliability of the motion accuracy of the ammunition conveyor is 93.42%,with the maximum failure probability occurring at 0.21 s.These results serve as an important reference for the structural optimi-zation design of the ammunition conveyor based on reliability and the maintenance of the operational process.展开更多
There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology conti...There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology continues to scale down,the bit-flip errors in the memory of edge devices become more frequent,thereby leading to substantial DNN inference accuracy loss.Though several techniques have been proposed to alleviate the accuracy loss in edge environments,they require complex computations and additional parity bits for error correction,thus resulting in significant performance and storage overheads.In this paper,we propose FeatherGuard,a data-driven lightweight error protection scheme for DNN inference on edge devices.FeatherGuard selectively protects critical bit positions(that have a significant impact on DNN inference accuracy)against bit-flip errors,by considering various DNN characteristics(e.g.,data format,layer-wise weight distribution,actually stored logical values).Thus,it achieves high error tolerability during DNN inference.Since FeatherGuard reduces the bit-flip errors based on only a few simple arithmetic operations(e.g.,NOT operations)without parity bits,it causes negligible performance overhead and no storage overhead.Our experimental results show that FeatherGuard improves the error tolerability by up to 6667×and 4000×,compared to the conventional systems and the state-of-the-art error protection technique for edge environments,respectively.展开更多
In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5...In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5,6 nm)exhibit excellent electrical performance and superior uniformity.The reliability properties of ITO TFTs were evaluated in detail under positive bias stress(PBS)conditions before and after passivation.Compared to the devices without passivation,the passivated devices have only 50%threshold voltage degradation(ΔV_(th))and 50%newly generated traps due to excellent isolation of the ambient atmosphere.The negligible performance degradation of ITO TFTs with passivation during negative bias stress(NBS)and negative bias temperature stress(NBTS)verifies the outstanding immunity to the water vapor of the SiO_(2)passivation layer.Overall,the ITO TFT with the t_(ch)of 6 nm and with SiO_(2)passivation exhibits the best performance in terms of electrical properties,uniformity,and reliability,which is promising in large-area production.展开更多
As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.Ho...As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.展开更多
Air conditioning is a major energy-consuming component in buildings,and accurate air conditioning load forecasting is of great significance for maximizing energy utilization efficiency.However,the deep learning models...Air conditioning is a major energy-consuming component in buildings,and accurate air conditioning load forecasting is of great significance for maximizing energy utilization efficiency.However,the deep learning models currently used in the field of air conditioning load forecasting often suffer from issues such as distribution bias in load data and insufficient expression ability of nonlinear features in the model,which affect the accuracy of load forecasting.To address this,this paper proposes a novel load forecasting model.Firstly,the model employs the Dish-TS(DS)module to standardize the input window data through self-learning standardized parameters,thereby addressing the spatial intra-bias problem existing between data.Secondly,DS-Kansformer introduces Kolmogorov-Arnold Networks(KANs)to enhance the expression ability of nonlinear features.Finally,the output window is denormalized through the self-learning parameter of the DS module to restore the original distribution of the predicted data.In this paper,experiments were carried out based on the air-conditioning load dataset collected from a multi-functional comprehensive building,and the experimental results show that after adding the DS module,the Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and R-squared(R^(2))of the model are 20.46%,34.44%,and 92.61%,respectively;after introducing KAN,the MAE,RMSE,and R^(2) are 22.81%,35.72%,and 92.05%,respectively;the model also exhibits high prediction accuracy after integrating the two modules(with RMSE,MAE,and R^(2) being 19.75%,34.05%,and 92.78%,respectively),outperforming common time series prediction models,confirming the reliability and efficiency of the model,which can provide reliable support for intelligent energy management in buildings.展开更多
To study the durability of concrete in harsh environments in Northwest China,concrete was prepared with various durability-improving materials such as concrete anti-erosion inhibitor(SBT-TIA),acrylate polymer(AP),supe...To study the durability of concrete in harsh environments in Northwest China,concrete was prepared with various durability-improving materials such as concrete anti-erosion inhibitor(SBT-TIA),acrylate polymer(AP),super absorbent resin(SAP).The erosion mode and internal deterioration mechanism under salt freeze-thaw cycle and dry-wet cycle were explored.The results show that the addition of enhancing materials can effectively improve the resistance of concrete to salt freezing and sulfate erosion:the relevant indexes of concrete added with X-AP and T-AP are improved after salt freeze-thaw cycles;concrete added with SBTTIA shows optimal sulfate corrosion resistance;and concrete added with AP displays the best resistance to salt freezing.Microanalysis shows that the increase in the number of cycles decreases the generation of internal hydration products and defects in concrete mixed with enhancing materials and improves the related indexes.Based on the Wiener model analysis,the reliability of concrete with different lithologies and enhancing materials is improved,which may provide a reference for the application of manufactured sand concrete and enhancing materials in Northwest China,especially for the study of the improvement effects and mechanism of enhancing materials on the performance of concrete.展开更多
Chinese President Xi Jinping receives a steady stream of Western leaders over the past two months,demonstrating China’s role as a reliable partner on the international stage.SINCE the start of 2026,Chinese President ...Chinese President Xi Jinping receives a steady stream of Western leaders over the past two months,demonstrating China’s role as a reliable partner on the international stage.SINCE the start of 2026,Chinese President Xi Jinping has welcomed a succession of leaders from Western countries.From British Prime Minister Keir Starmer and Canadian Prime Minister Mark Carney to the leaders of Ireland and Finland.展开更多
The performance degradation of micro light-emitting diodes(micro-LEDs)is closely associated with the deterioration of sidewall passivation layers under prolonged electrical bias.We investigate reliability improvements...The performance degradation of micro light-emitting diodes(micro-LEDs)is closely associated with the deterioration of sidewall passivation layers under prolonged electrical bias.We investigate reliability improvements in 20μm×20μm InGaN/GaN blue micro-LEDs by suppressing the formation of an unstable interfacial layer during sidewall passivation.SiO_(2)is deposited on the etched mesa sidewalls using either Sputtering or plasma-enhanced chemical vapor deposition(PECVD).Comparative analysis reveals that PECVD-passivated devices experience more severe performance degradation,primarily due to the increased leakage current.After 100 h of accelerated aging,external quantum efficiency decreases by 44%in PECVD-passivated samples,whereas Sputter-passivated devices exhibit only an11%reduction.This discrepancy is attributed to the formation of a thicker and chemically unstable gallium oxynitride(Ga-O_(X)-N_(1-X))interfacial layer at the SiO_(2)∕GaN-based interface,which facilitates the generation of sidewall defects.Suppressing the formation of this interlayer enhances the crystallinity and structural stability of the passivation layer,thereby mitigating the activation of point defects.Notably,Sputter deposition is more effective in minimizing the formation of Ga-O-N interlayer.These findings emphasize the critical role of achieving low-defect-density sidewall passivation to improve the reliability of micro-LEDs for next-generation high-resolution display applications.展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-...Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-sensor predictive accuracy,ensuring interpretability and reliable performance across varying industrial operating conditions remains a challenge[1]–[4].This is precisely what Industry 5.0,proposed by the European Commission in 2021,advocates[5],[6].It integrates various cutting-edge technologies,such as human-machine interaction,digital twins,cybersecurity and artificial intelligence,to facilitate the development of better soft sensors.展开更多
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once ag...During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.展开更多
Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that devi...Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.展开更多
文摘This study examines the reliability and validity of AI-generated scoring for continuation writing tasks.By comparing GPT-4 with eight experienced human raters across 21 student responses,it evaluates AI’s consistency,severity,and alignment with human scoring criteria.Results show that AI exhibits high self-consistency and adapts effectively to different scoring roles(e.g.,teacher vs.highstakes rater).However,AI scores were more lenient than human raters and demonstrated divergent evaluation focuses—prioritizing narrative coherence and emotional depth,while teachers emphasized linguistic accuracy and richness of detail.The findings suggest AI’s potential as a supplementary assessment tool,offering rapid,holistic feedback,but highlight the need for further calibration to align with educational standards.Implications include exploring hybrid evaluation models that leverage the strengths of both AI and human raters to achieve more equitable,efficient,and pedagogically meaningful writing assessments.
文摘The new RE 6 EL from KARL MAYER brings a breath of fresh air to raschel fabric production.Nowadays textile companies increasingly need to produce small production runs and respond to market changes with instantaneous pattern changes in order to operate profitably–meaning they require machines that offer maximum flexibility,reliability and cost efficiency.KARL MAYER understands the challenges of the market and is launching its new RE 6 EL.The Raschel machine offers the core strengths of the classic RSE 6 EL and essentially the same performance parameters,but has been further cost-optimised largely due to local production advantages.This makes the newcomer an efficiency champion in production,especially when it comes to frequent pattern changes.
文摘Background:The World Health Organization Disability Assessment Schedule 2.0(WHODAS 2.0)is a popular tool for eval-uating functioning and disability in a range of population demographics and medical situations.However,very little is known about the WHODAS 2.0's validity and reliability,particularly when dealing with potentially life-threatening maternal condi-tions(PLTCs).The aim of this study was to evaluate the validity of the WHODAS 2.0 Tigrigna version.Methods:This cross-sectional study was conducted in Tigray,northern Ethiopia,from December 15 to 20,2023.Following translation and back translation,women who had experienced PLTCs during a recent pregnancy,childbirth,or postpartum period were administered the 36-item WHODAS 2.0 in Tigrigna version 6 months after the childbirth.In total,121 women with a history of PLTCs participated.Cronbach′sαwas used to evaluate internal consistency in all six WHODAS 2.0 domains,while Spearman′s correlation coefficient was used to evaluate convergent validity.With confirmatory factor analysis,construct validity was also examined.Results:All domain scores of the Tigrigna version of the WHODAS 2.0 indicated excellent internal consistency(α=0.917-0.978 for 36 items andα=0.874-0.940 for 12 items),while the Cronbach′sαcoefficients for the summary score were 0.981 and 0.952 for 36 and 12 items,respectively.The convergent validity between the 36-item and 12-item WHODAS 2.0 showed a strong correlation between similar constructs(r=0.909-0.981).Conclusion:Despite the small sample limitation,the WHODAS 2.0 tool adapted to the Tigrigna version indicated an acceptable reliability and validity and therefore could be applied to women with a history of PLTCs at 6 months postpartum.
基金supported by the Major Program of National Natural Science Foundation of China(Grant No.42090055)the National Key ScientificInstruments and Equipment Development Projects of China(Grant No.41827808)the National Nature Science Foundation of China(Grant No.42207216).
文摘Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the tensile stress in the area has exceeded the tensile strength of the soil,leading to local instability.To explore the impact of tensile failure behavior on the stability and failure modes of reservoir landslides,the Huangtupo Riverside Slump#1 is taken as a case study.By considering local tensile failure,potential tensile cracks are incorporated into the analysis via the limit equilibrium method and reliability theory.The reliability of landslides under different tensile failure scenarios is quantified.Strain-softening characteristics of the soil are combined to further analyze the failure transmission path of the landslide.Finally,these potential failure modes were validated through physical model tests.The results show that cracks developing at rear positions reduce the stability of the slope and increase the probability of instability.During the destruction process,retrogressive failures with multiple sliding surfaces are likely to occur.However,tensile failure at the forefront reduces the likelihood of an individual slide mass descending.Progressive failure results in both regular and skip transmission patterns.Additionally,cracks and water level changes can also lead to shifts in the positions of the most dangerous blocks.Therefore,in practical landslide analysis and prevention,it is necessary to consider local tensile damage and identify potential tensile crack locations in advance to optimize prevention measures and accurately evaluate landslide risk.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金Project supported by the National Natural Science Foundation of China(Grant No.12472033)。
文摘A stochastic predator-prey system with Markov switching is explored.We have developed a new chasing technique to efficiently solve the Fokker-Planck-Kolmogorov and backward Kolmogorov equations.Dynamic balance and reliability of the switching system are evaluated via stationary probability density function and first-passage failure theory,taking into account factors such as switching frequencies,noise intensities,and initial conditions.Results reveal that Markov switching leads to stochastic P-bifurcation,enhancing dynamic balance and reducing white-noise-induced oscillations.But frequent switching can heighten initial value dependence,harming reliability.Further,the influence of the subsystem on the switching system is not proportional to its action probabilities.Monte Carlo simulations validate the findings,offering an in-depth exploration of these dynamics.
基金Supported by National Natural Science Foundation of China(Grant No.U2141246)Key Laboratory of Artillery Launch and Control Technology of China(Grant No.2021-001)Basic Research of State Administration of Science Technology and Industry for National Defense of China(Grant No.JXJL202208A001).
文摘The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the end effector of the automatic loading system,and its motion state significantly impacts the accuracy of projectiles.Therefore,it is of immense importance to precisely and effectively evaluate the reliability of the motion accuracy of the ammunition conveyor.This paper aims to propose a practical and efficient analysis method for evaluating the reliability of the motion accuracy of the ammunition conveyor.The proposed approach involves the use of a deep learning network to approximate the physical model and the extremum method to obtain a single cycle sequence decoupling strategy for solving the time-varying reliability issue of complex systems.Employing this strategy,the time-varying reliability of the ammunition conveyor is transformed into a static reliability problem.The proposed method includes the use of a deep feedforward neural network,second-order saddle point ap-proximation(SPA)method,extremum method,and efficient global optimization(EGO)technology.The results reveal that the reliability of the motion accuracy of the ammunition conveyor is 93.42%,with the maximum failure probability occurring at 0.21 s.These results serve as an important reference for the structural optimi-zation design of the ammunition conveyor based on reliability and the maintenance of the operational process.
基金the“Convergence and Open sharing System”Project,supported by the Ministry of Education and National Research Foundation of Korea.
文摘There has been an increasing emphasis on performing deep neural network(DNN)inference locally on edge devices due to challenges such as network congestion and security concerns.However,as DRAM process technology continues to scale down,the bit-flip errors in the memory of edge devices become more frequent,thereby leading to substantial DNN inference accuracy loss.Though several techniques have been proposed to alleviate the accuracy loss in edge environments,they require complex computations and additional parity bits for error correction,thus resulting in significant performance and storage overheads.In this paper,we propose FeatherGuard,a data-driven lightweight error protection scheme for DNN inference on edge devices.FeatherGuard selectively protects critical bit positions(that have a significant impact on DNN inference accuracy)against bit-flip errors,by considering various DNN characteristics(e.g.,data format,layer-wise weight distribution,actually stored logical values).Thus,it achieves high error tolerability during DNN inference.Since FeatherGuard reduces the bit-flip errors based on only a few simple arithmetic operations(e.g.,NOT operations)without parity bits,it causes negligible performance overhead and no storage overhead.Our experimental results show that FeatherGuard improves the error tolerability by up to 6667×and 4000×,compared to the conventional systems and the state-of-the-art error protection technique for edge environments,respectively.
基金supported in part by the National Natural Science Foundation of China(62404110,62274033)Natural Science Foundation of Jiangsu Province(BK20221453)+1 种基金Fundamental Research Funds for the Central UniversitiesNatural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(NY223159)。
文摘In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5,6 nm)exhibit excellent electrical performance and superior uniformity.The reliability properties of ITO TFTs were evaluated in detail under positive bias stress(PBS)conditions before and after passivation.Compared to the devices without passivation,the passivated devices have only 50%threshold voltage degradation(ΔV_(th))and 50%newly generated traps due to excellent isolation of the ambient atmosphere.The negligible performance degradation of ITO TFTs with passivation during negative bias stress(NBS)and negative bias temperature stress(NBTS)verifies the outstanding immunity to the water vapor of the SiO_(2)passivation layer.Overall,the ITO TFT with the t_(ch)of 6 nm and with SiO_(2)passivation exhibits the best performance in terms of electrical properties,uniformity,and reliability,which is promising in large-area production.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(MSIT),South Korea(RS-2024-00421181)financially supported in part by National R&D Program(2021M3H4A3A02086430)through NRF(National Research Foundation of Korea)funded by Ministry of Science and ICT+2 种基金the National Research Council of Science&Technology(NST)grant by the Korea government(MSIT)(No.GTL25021-210)The Inter-University Semiconductor Research Center,Institute of Engineering Research,and Soft Foundry Institute at Seoul National University provided research facilities for this workhe grant by the National Research Foundation of Korea(NSF)supported by the Korea government(MIST)(RS-2025-16903034)。
文摘As silicon-based transistors face fundamental scaling limits,the search for breakthrough alternatives has led to innovations in 3D architectures,heterogeneous integration,and sub-3 nm semiconductor body thicknesses.However,the true effectiveness of these advancements lies in the seamless integration of alternative semiconductors tailored for next-generation transistors.In this review,we highlight key advances that enhance both scalability and switching performance by leveraging emerging semiconductor materials.Among the most promising candidates are 2D van der Waals semiconductors,Mott insulators,and amorphous oxide semiconductors,which offer not only unique electrical properties but also low-power operation and high carrier mobility.Additionally,we explore the synergistic interactions between these novel semiconductors and advanced gate dielectrics,including high-K materials,ferroelectrics,and atomically thin hexagonal boron nitride layers.Beyond introducing these novel material configurations,we address critical challenges such as leakage current and long-term device reliability,which become increasingly crucial as transistors scale down to atomic dimensions.Through concrete examples showcasing the potential of these materials in transistors,we provide key insights into overcoming fundamental obstacles—such as device reliability,scaling down limitations,and extended applications in artificial intelligence—ultimately paving the way for the development of future transistor technologies.
基金supported by the National Natural Science Foundation with grant No.12374408。
文摘Air conditioning is a major energy-consuming component in buildings,and accurate air conditioning load forecasting is of great significance for maximizing energy utilization efficiency.However,the deep learning models currently used in the field of air conditioning load forecasting often suffer from issues such as distribution bias in load data and insufficient expression ability of nonlinear features in the model,which affect the accuracy of load forecasting.To address this,this paper proposes a novel load forecasting model.Firstly,the model employs the Dish-TS(DS)module to standardize the input window data through self-learning standardized parameters,thereby addressing the spatial intra-bias problem existing between data.Secondly,DS-Kansformer introduces Kolmogorov-Arnold Networks(KANs)to enhance the expression ability of nonlinear features.Finally,the output window is denormalized through the self-learning parameter of the DS module to restore the original distribution of the predicted data.In this paper,experiments were carried out based on the air-conditioning load dataset collected from a multi-functional comprehensive building,and the experimental results show that after adding the DS module,the Mean Absolute Error(MAE),Root Mean Square Error(RMSE),and R-squared(R^(2))of the model are 20.46%,34.44%,and 92.61%,respectively;after introducing KAN,the MAE,RMSE,and R^(2) are 22.81%,35.72%,and 92.05%,respectively;the model also exhibits high prediction accuracy after integrating the two modules(with RMSE,MAE,and R^(2) being 19.75%,34.05%,and 92.78%,respectively),outperforming common time series prediction models,confirming the reliability and efficiency of the model,which can provide reliable support for intelligent energy management in buildings.
基金Funded by the National Natural Science Foundation of China(No.52178216)the Research on the Durability and Application of High-performance Concrete for Highway Engineering in the Cold and Arid Salt Areas of Northwest China(No.2022-24)the Construction Project of the Scientific Research Platform of Provincial Enterprises Supported by the Capital Operating Budget of Gansu Province(No.2023GZ018)。
文摘To study the durability of concrete in harsh environments in Northwest China,concrete was prepared with various durability-improving materials such as concrete anti-erosion inhibitor(SBT-TIA),acrylate polymer(AP),super absorbent resin(SAP).The erosion mode and internal deterioration mechanism under salt freeze-thaw cycle and dry-wet cycle were explored.The results show that the addition of enhancing materials can effectively improve the resistance of concrete to salt freezing and sulfate erosion:the relevant indexes of concrete added with X-AP and T-AP are improved after salt freeze-thaw cycles;concrete added with SBTTIA shows optimal sulfate corrosion resistance;and concrete added with AP displays the best resistance to salt freezing.Microanalysis shows that the increase in the number of cycles decreases the generation of internal hydration products and defects in concrete mixed with enhancing materials and improves the related indexes.Based on the Wiener model analysis,the reliability of concrete with different lithologies and enhancing materials is improved,which may provide a reference for the application of manufactured sand concrete and enhancing materials in Northwest China,especially for the study of the improvement effects and mechanism of enhancing materials on the performance of concrete.
文摘Chinese President Xi Jinping receives a steady stream of Western leaders over the past two months,demonstrating China’s role as a reliable partner on the international stage.SINCE the start of 2026,Chinese President Xi Jinping has welcomed a succession of leaders from Western countries.From British Prime Minister Keir Starmer and Canadian Prime Minister Mark Carney to the leaders of Ireland and Finland.
基金supported by the Samsung Research Funding&Incubation Center of Samsung Electronics under Project No.SRFC-MA2402-05supported by the KENTECH Center for Shared Research Facilities。
文摘The performance degradation of micro light-emitting diodes(micro-LEDs)is closely associated with the deterioration of sidewall passivation layers under prolonged electrical bias.We investigate reliability improvements in 20μm×20μm InGaN/GaN blue micro-LEDs by suppressing the formation of an unstable interfacial layer during sidewall passivation.SiO_(2)is deposited on the etched mesa sidewalls using either Sputtering or plasma-enhanced chemical vapor deposition(PECVD).Comparative analysis reveals that PECVD-passivated devices experience more severe performance degradation,primarily due to the increased leakage current.After 100 h of accelerated aging,external quantum efficiency decreases by 44%in PECVD-passivated samples,whereas Sputter-passivated devices exhibit only an11%reduction.This discrepancy is attributed to the formation of a thicker and chemically unstable gallium oxynitride(Ga-O_(X)-N_(1-X))interfacial layer at the SiO_(2)∕GaN-based interface,which facilitates the generation of sidewall defects.Suppressing the formation of this interlayer enhances the crystallinity and structural stability of the passivation layer,thereby mitigating the activation of point defects.Notably,Sputter deposition is more effective in minimizing the formation of Ga-O-N interlayer.These findings emphasize the critical role of achieving low-defect-density sidewall passivation to improve the reliability of micro-LEDs for next-generation high-resolution display applications.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
文摘Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-sensor predictive accuracy,ensuring interpretability and reliable performance across varying industrial operating conditions remains a challenge[1]–[4].This is precisely what Industry 5.0,proposed by the European Commission in 2021,advocates[5],[6].It integrates various cutting-edge technologies,such as human-machine interaction,digital twins,cybersecurity and artificial intelligence,to facilitate the development of better soft sensors.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
文摘During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.
基金supported in part by the National Natural Science Foundation of China(No.52467008)Gansu Provincial Depatment of Education Youth Doctoral Suppo Project(2024QB-051).
文摘Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.
