Conversion-type electrode materials hold significant promise for potassium-ion batteries(PIBs)due to their high theoretical capacities,yet their practical deployment is hindered by sluggish kinetics and irreversible s...Conversion-type electrode materials hold significant promise for potassium-ion batteries(PIBs)due to their high theoretical capacities,yet their practical deployment is hindered by sluggish kinetics and irreversible structural degradation.To overcome these limitations,we propose a rationally engineered nanoreactor architecture that stabilizes defect-rich MoS_(2)via interlayer incorporation of a carbon monolayer,followed by encapsulation within a nitrogen-doped carbon shell,forming a MoSSe@NC heterostructure.This tailored structure synergistically accelerates both K^(+)diffusion kinetics and electron transfer,enabling unprecedented rate performance(107 mAh g^(-1)at 10 Ag^(-1))and ultralong cyclability(86.5%capacity retention after 1200 cycles at 3 A g^(-1)).Mechanistic insights reveal a distinctive“adsorption-conversion”pathway,where sulfur vacancies on exposed S-Mo-S basal planes act as preferential K^(+)adsorption sites,effectively suppressing parasitic phase transitions during intercalation.In situ X-ray diffraction and transmission electron microscopy corroborate the structural reversibility of the conversion reaction,with the carbon matrix dynamically accommodating strain while preserving electrode integrity.This work not only advances the understanding of defect-driven interfacial chemistry in conversion-type materials but also provides a versatile strategy for designing high-performance anodes in next-generation PIBs through heterostructure engineering.展开更多
The classical EPQ model has been used for a long ti me and is widely accepted and implemented. Nevertheless, the analysis for finding an economic lot size has based on a number of unrealistic assumptions. A common unr...The classical EPQ model has been used for a long ti me and is widely accepted and implemented. Nevertheless, the analysis for finding an economic lot size has based on a number of unrealistic assumptions. A common unrealistic assumption in using EPQ is that all units produced are of good quali ty. The classical EPQ model shows that the optimal lot size will generate minimum ma nufacturing cost, thus producing minimum setup cost and inventory cost. However, this is only true if all products manufactured in the process are assumed to be of good quality (i.e. all products are within the specification limits). In rea lity this is not the case, therefore, it is necessary to consider the cost of im perfect quality items, because this cost can influence the economic lot size. Ma ny studies and recent papers have indicated that there is a significant relation ship between economic production lot size and process/product quality. However, their models included either the imperfect quality items (not necessarily de fective) which are to be sold at a discounted price or defective items which can be reworked or rejected. The aim of this paper is to provide a framework to integrate three different sit uations (discounted pricing/rework/reject) into a single model. 100% inspection is performed in order to distinguish the amount of good quality items, imper fect quality items and defective items in each lot. In this paper, a mathematica l model is developed, and a numerical example is presented to illustrate the sol ution procedures. It is found that the economic production lot size tends to inc rease as the average percentage of imperfect quality items and defectives (rejec ted items) increases.展开更多
The rational configuration of built-in electric field(IEF)in heterogeneous materials can significantly optimize the band structure to accelerate the separation of photogenerated charge carriers.However,the strength mo...The rational configuration of built-in electric field(IEF)in heterogeneous materials can significantly optimize the band structure to accelerate the separation of photogenerated charge carriers.However,the strength modulation of IEF formed by various materials has an uncertain enhancing effect on the separation of photogenerated carriers.Herein,a mesoporous MIL-125(Ti)@BiOCl S-scheme heterojunction with controllable IEF is prepared by green photoreduction reaction to investigate the relationship between IEF,microstructure,and photocatalytic activity.Moreover,the corresponding results demonstrate the MIL-125(Ti)@BiOCl effectively regulates the IEF strength through controlling the concentration of ligand defects,thereby optimizing the band structure and improving the efficiency of photogenerated charge separation.The optimized IEF significantly enhances the photocatalytic degradation performance of mesoporous MIL-125(Ti)-3@BiOCl towards tetracycline,with a k value of 0.07 min^(–1),which are approximately 5.5 and 4.7 times greater than that of BiOCl(0.0127 min^(–1))and MIL-125(Ti)-3(0.015 min^(–1)).These findings provide a new pathway for regulating IEF within MOF-based heterojunctions,and offer new insights into the intrinsic correlations between defect structure,IEF,and photocatalytic activity.展开更多
A high-activity and stable bifunctional oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)electrocatalyst is critical for seawater-based Zn-air batteries(ZABs).Herein,we report a wood-derived chainmail e...A high-activity and stable bifunctional oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)electrocatalyst is critical for seawater-based Zn-air batteries(ZABs).Herein,we report a wood-derived chainmail electrocatalyst containing defective nitrogen-doped carbon nanotubes encapsulating cobalt nanoparticles(Co@D-NCNT/CW)to enhance the ORR/OER activity and stability in seawater medium.During the preparation process,the introduction and removal of Zn increased the defect sites and pyridine N content in the carbon material,modulating charge distribution and influencing the adsorption and activation processes.The highly ordered open channels in Co@D-NCNT/CW promoted mass transfer of reactants and accelerated gas diffusion.The resultant chainmail electrocatalyst exhibited impressive bifunctional ORR and OER activities with an ultra-low gap of 0.67 V in sea water-based alkaline electrolyte.The Co@D-NCNT/CW-assembled seawater-based rechargeable liquid ZABs demonstrated a maximum power density of 245.3 mW cm^(-2)and a long-term cycling performance over 500 h.The seawater-based all-solid-state ZABs achieved the maximum power density of 48.2 mW cm^(-2)and stabilized over 30 h.Density functional theory revealed that the presence of defects and pyridine nitrogen in Co@D-NCNT/CW modulated the electronic structure of Co,optimizing the binding affinity of the Co sites with intermediates and weakening Cl^(-)adsorption.This work provides a new approach to preparing high-activity and stable ORR/OER electrocatalyst utilizing wood nanostructures,boosting the development of seawater-based ZABs.展开更多
We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic o...We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic order can be extended,and modulation near the cutoff order becomes smaller for the second plateau by increasing the time delay.These effects are due to an increase of the electron population in higher energy bands,where the larger band gap allows electrons to release more energy,and the long electronic paths are suppressed.Additionally,we also investigate the HHG of defective solids by Bohmian trajectories(BT).It is found that the harmonic intensity of the second plateau can be further enhanced.Simultaneously,cutoff order is also extended due to Bohmian particles moving farther away from the defective zone.展开更多
The photocatalytic oxidation of methane to methanol using molecule oxygen directly is an attractive catalytic reaction,but designing catalysts to avoid over-oxidation remains a significant challenge.Herein,Cu single-a...The photocatalytic oxidation of methane to methanol using molecule oxygen directly is an attractive catalytic reaction,but designing catalysts to avoid over-oxidation remains a significant challenge.Herein,Cu single-atom anchored on the defective carbon nitride structure(Cu SA/Def-CN)is designed for selective photocatalytic oxidation of methane into methanol using O_(2) under mild conditions.The Cu SA/Def-CN catalyst exhibits a high methanol selectivity of 92.8%under optimized conditions.Mechanistic studies reveal a synergistic effect between Def-CN and Cu SA,where Def-CN is responsible for the in-situ generation of hydrogen peroxide,which is subsequently decomposed by the Cu SA sites to produce·OH radicals that play a key role in the rate-determining step of methane activation to form methanol.Additionally,the presence of Cu SA not only enhances the electron-hole separation efficiency and improves the transfer of the photo-generated charges,but also increases the number of active sites for methane adsorption and activation.These insights provide valuable guidance for designing efficient catalysts for the highly selective photocatalytic oxidation of methane to methanol.展开更多
Defective phononic crystals(PnCs)have enabled spatial localization and quantitative amplification of elastic wave energy.Most previous research has focused on applications such as narrow-bandpass filters,ultrasonic se...Defective phononic crystals(PnCs)have enabled spatial localization and quantitative amplification of elastic wave energy.Most previous research has focused on applications such as narrow-bandpass filters,ultrasonic sensors,and piezoelectric energy harvesters,typically operating under the assumption of an external elastic wave incidence.Recently,a novel approach that uses defective PnCs as ultrasonic actuators to generate amplified waves has emerged.However,the existing studies are limited to the generation of either longitudinal or bending waves,with no research addressing the concurrent generation of both.Hence,this paper proposes a straightforward methodology for the concurrent generation and amplification of both wave types utilizing defect modes at independent defect-band frequencies.Bimorph piezoelectric elements are attached to the defect,with each element connected to independent external voltage sources.By precisely adjusting the magnitude and temporal phase differences between the voltage sources,concurrently amplified wave generation is achieved.The paper highlights the advantages of the proposed analytical model.This model is both computationally time-efficient and accurate,in comparison with the COMSOL simulation results.For instance,in case studies,the analytical model reduces the computational time from one hour to mere seconds,while maintaining acceptable error rates of 1%in peak frequencies.This concurrent wave-generation methodology opens new avenues for applications in rotating machinery fault diagnosis,structural health monitoring,and medical imaging.展开更多
The linker defect engineering for MOFs is a viable strategy that usually can effectively augment conductivity to further promote charge carrier separation,which is the most excellent conductivity of preserved metal cl...The linker defect engineering for MOFs is a viable strategy that usually can effectively augment conductivity to further promote charge carrier separation,which is the most excellent conductivity of preserved metal clusters.However,the partially missing photosensitive linker often leads to the diminished light utilization efficiency.As we know,in the linker defect engineering,addressing the lack of photosensitivity while maintaining outstanding conductivity is still in its infancy.In this essay,the linkerdefective NH_(2)-MIL-125 was obtained by adding the glacial acetic acid regulator,subsequently,the excellent light-responsive Pt/CQDs with up-conversion effect was in-situ encapsulated into the enlarged pore space of linker-defective NH_(2)-MIL-125.It is excited that the fabricated dual-functional composite ideally integrates photosensitivity and conductivity for photocatalytic hydrogen evolution and NO elimination.The optimal Pt/CQDs@NM-125-4 exhibited very superior photocatalytic hydrogen evolution(28.75mmol/g),it was 11.63 times as that of the initial NH_(2)-MIL-125(2.47 mmol/g)and 1.4 times as that of the defective NM-125-4(20.46 mmol/g).In addition,the excellent photocatalytic NO removal efficiency was 52.12%for Pt/CQDs@NM-125-4,whereas the original NH_(2)-MIL-125 only reached 30%and the defective NM-125-4 achieved 44.96%.The corresponding optical and electrical characterization based on UV-vis,up-conversion photoluminescence(UCPL),and electrochemical impedance spectroscopy(EIS)etc.demonstrated the defect engineering accelerates the charge carriers transfer via enhancing conductivity,and the in-situ confined up-conversion Pt/CQDs promote the visible light response.Our work presents a feasible avenue to integrate photosensitivity and conductivity via in-situ fabricating excellent lightresponsive Pt/CQDs within linker-defective NH_(2)-MIL-125 for further significantly boosting photocatalytic performance.展开更多
Lithium-sulfur(Li-S)batteries are regarded as the most formidable competitor to lithium-ion batteries due to their superior theoretical capacity.However,the negative impact of soluble lithium polysulfide(LiPSs)and slo...Lithium-sulfur(Li-S)batteries are regarded as the most formidable competitor to lithium-ion batteries due to their superior theoretical capacity.However,the negative impact of soluble lithium polysulfide(LiPSs)and slow redox reaction kinetics seriously hamper the commercialization of Li-S batteries.In this study,a defect-rich single-atom catalyst with an oversaturated asymmetric Fe-N_(5)coordination structure anchored in defective g-C_(3)N_(4)(C_(3)N_(4)-Fe@rGO)is designed via an absorption-pyrolysis strategy.The two-dimensional(2D)conducting C_(3)N_(4)@graphene structure with abundant defect sites accelerates the trans-fer and transportation of lithium ions and electrons.The oversaturated asymmetric Fe-N_(5)coordination structure effectively improves the adsorbility of LiPSs and accelerates the redox kinetics of sulfur species.Hence,the Li-S cell with a C_(3)N_(4)-Fe@rGO modified separator reveals a high initial capacity(1197.1 mAh g^(-1) at 0.2 C)and a low capacity decay rate(0.037%per cycle after 900 cycles at 1 C).Even at high sulfur loading and extreme temperatures of 0℃,it also shows good cycling performance.This work creates ideas for synthesizing oversaturated single-atom coordination environments and an efficient route to the practical realization of the Li-S batteries.展开更多
Defect engineering improves the catalytic performance of metal-organic frameworks(MOFs)loaded metal nanoparticles(MNPs@MOFs),but there is still a challenge in defining the structure-activity relationships.Herein,the c...Defect engineering improves the catalytic performance of metal-organic frameworks(MOFs)loaded metal nanoparticles(MNPs@MOFs),but there is still a challenge in defining the structure-activity relationships.Herein,the content of linker-missing defects in UiO-66(Ce)was systematically regulated via formic acid as the modulators,and defective UiO-66(Ce)loaded Ni nanoparticles(NPs)were constructed for dicyclopentadiene(DCPD)hydrogenation.The fine regulation of defect engineering and reduction conditions affected the structure properties of UiO-66(Ce)and the electronic metal-support interaction between MOFs and Ni NPs,thereby optimizing the microenvironment and electronic state of Ni NPs.The optimized U(Ce)-40eq with suitable defects,small size and structure stability effectively promoted the production of highly dispersed abundant electron-deficient Ni^(0) active sites,enhancing the adsorption and activation of H_(2) and C=C bonds,especially accelerating the rate-determining step.Therefore,U(Ce)-40eq loaded 5 wt%Ni NPs achieved DCPD saturated hydrogenation to tetrahydrodicyclopentadiene(70℃,2 MPa,90 min),superior to most high-loading Ni-based catalysts.This work reveals the synergistic mechanism of MOFs defect engineering and electronic structure of Ni NPs,providing effective guidance for the precise preparation of highly efficient and stable MNPs@MOFs heterogeneous catalysts.展开更多
Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult t...Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.展开更多
Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propo...Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.展开更多
The original online version of this article was revised:The layout update for Article 758 has impacted the page range in the published issue,but did not affect the scholarly content.To ensure consistency with the orig...The original online version of this article was revised:The layout update for Article 758 has impacted the page range in the published issue,but did not affect the scholarly content.To ensure consistency with the originally assigned pages(2595-2614),we will need to publish an erratum to correct the article and restore the original page range.The original article has been corrected.展开更多
Osteogenesis imperfecta(OI)is a group of diseases caused by defects in type I collagen processing which result in skeletal fragility.While these disorders have been regarded as defects in osteoblast function,the role ...Osteogenesis imperfecta(OI)is a group of diseases caused by defects in type I collagen processing which result in skeletal fragility.While these disorders have been regarded as defects in osteoblast function,the role of matrix-embedded osteocytes in OI pathogenesis remains largely unknown.Homozygous human SP7(c.946 C>T,R316C)mutation results in a recessive form of OI characterized by fragility fractures,low bone mineral density and osteocyte dendrite defects.To better understand how the OI-causing R316C mutation affects the function of SP7,we generated Sp7^(R342C)knock-in mice.Consistent with patient phenotypes,Sp7^(R342C/R342C)mice demonstrate increased cortical porosity and reduced cortical bone mineral density.Sp7^(R342C/R342C)mice show osteocyte dendrite defects,increased osteocyte apoptosis,and intracortical bone remodeling with ectopic intracortical osteoclasts and elevated osteocyte Tnfsf11 expression.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermo...The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.展开更多
In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalm...In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.展开更多
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.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
To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects,similar defects and background features,and similarities between differ...To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects,similar defects and background features,and similarities between different defects,this paper proposes a lightweight detection model named multiscale edge and squeeze-and-excitation attention detection network(MSESE),which is built upon the You Only Look Once version 11 nano(YOLOv11n).To address the difficulty of locating defect edges,we first propose an edge enhancement module(EEM),apply it to the process of multiscale feature extraction,and then propose a multiscale edge enhancement module(MSEEM).By obtaining defect features from different scales and enhancing their edge contours,the module uses the dual-domain selection mechanism to effectively focus on the important areas in the image to ensure that the feature images have richer information and clearer contour features.By fusing the squeeze-and-excitation attention mechanism with the EEM,we obtain a lighter module that can enhance the representation of edge features,which is named the edge enhancement module with squeeze-and-excitation attention(EEMSE).This module was subsequently integrated into the detection head.The enhanced detection head achieves improved edge feature enhancement with reduced computational overhead,while effectively adjusting channel-wise importance and further refining feature representation.Experiments on the NEU-DET dataset show that,compared with the original YOLOv11n,the improved model achieves improvements of 4.1%and 2.2%in terms of mAP@0.5 and mAP@0.5:0.95,respectively,and the GFLOPs value decreases from the original value of 6.4 to 6.2.Furthermore,when compared to current mainstream models,Mamba-YOLOT and RTDETR-R34,our method achieves superior performance with 6.5%and 8.9%higher mAP@0.5,respectively,while maintaining a more compact parameter footprint.These results collectively validate the effectiveness and efficiency of our proposed approach.展开更多
基金financially supported by the supported by Shandong Provincial Natural Science Foundation(ZR2024MB108)Taishan Young Scholar Program(tsqn202312312)Excellent Young Scholars of the Shandong Provincial Natural Science Foundation(Overseas)(2023HWYQ-112)。
文摘Conversion-type electrode materials hold significant promise for potassium-ion batteries(PIBs)due to their high theoretical capacities,yet their practical deployment is hindered by sluggish kinetics and irreversible structural degradation.To overcome these limitations,we propose a rationally engineered nanoreactor architecture that stabilizes defect-rich MoS_(2)via interlayer incorporation of a carbon monolayer,followed by encapsulation within a nitrogen-doped carbon shell,forming a MoSSe@NC heterostructure.This tailored structure synergistically accelerates both K^(+)diffusion kinetics and electron transfer,enabling unprecedented rate performance(107 mAh g^(-1)at 10 Ag^(-1))and ultralong cyclability(86.5%capacity retention after 1200 cycles at 3 A g^(-1)).Mechanistic insights reveal a distinctive“adsorption-conversion”pathway,where sulfur vacancies on exposed S-Mo-S basal planes act as preferential K^(+)adsorption sites,effectively suppressing parasitic phase transitions during intercalation.In situ X-ray diffraction and transmission electron microscopy corroborate the structural reversibility of the conversion reaction,with the carbon matrix dynamically accommodating strain while preserving electrode integrity.This work not only advances the understanding of defect-driven interfacial chemistry in conversion-type materials but also provides a versatile strategy for designing high-performance anodes in next-generation PIBs through heterostructure engineering.
文摘The classical EPQ model has been used for a long ti me and is widely accepted and implemented. Nevertheless, the analysis for finding an economic lot size has based on a number of unrealistic assumptions. A common unrealistic assumption in using EPQ is that all units produced are of good quali ty. The classical EPQ model shows that the optimal lot size will generate minimum ma nufacturing cost, thus producing minimum setup cost and inventory cost. However, this is only true if all products manufactured in the process are assumed to be of good quality (i.e. all products are within the specification limits). In rea lity this is not the case, therefore, it is necessary to consider the cost of im perfect quality items, because this cost can influence the economic lot size. Ma ny studies and recent papers have indicated that there is a significant relation ship between economic production lot size and process/product quality. However, their models included either the imperfect quality items (not necessarily de fective) which are to be sold at a discounted price or defective items which can be reworked or rejected. The aim of this paper is to provide a framework to integrate three different sit uations (discounted pricing/rework/reject) into a single model. 100% inspection is performed in order to distinguish the amount of good quality items, imper fect quality items and defective items in each lot. In this paper, a mathematica l model is developed, and a numerical example is presented to illustrate the sol ution procedures. It is found that the economic production lot size tends to inc rease as the average percentage of imperfect quality items and defectives (rejec ted items) increases.
文摘The rational configuration of built-in electric field(IEF)in heterogeneous materials can significantly optimize the band structure to accelerate the separation of photogenerated charge carriers.However,the strength modulation of IEF formed by various materials has an uncertain enhancing effect on the separation of photogenerated carriers.Herein,a mesoporous MIL-125(Ti)@BiOCl S-scheme heterojunction with controllable IEF is prepared by green photoreduction reaction to investigate the relationship between IEF,microstructure,and photocatalytic activity.Moreover,the corresponding results demonstrate the MIL-125(Ti)@BiOCl effectively regulates the IEF strength through controlling the concentration of ligand defects,thereby optimizing the band structure and improving the efficiency of photogenerated charge separation.The optimized IEF significantly enhances the photocatalytic degradation performance of mesoporous MIL-125(Ti)-3@BiOCl towards tetracycline,with a k value of 0.07 min^(–1),which are approximately 5.5 and 4.7 times greater than that of BiOCl(0.0127 min^(–1))and MIL-125(Ti)-3(0.015 min^(–1)).These findings provide a new pathway for regulating IEF within MOF-based heterojunctions,and offer new insights into the intrinsic correlations between defect structure,IEF,and photocatalytic activity.
基金financial support by the Excellent Youth Foundation of Shandong Province(No.ZR2022YQ22)National Natural Science Foundation of China(No.32101451)Youth Innovation Team Project of Shandong Province(No.2022KJ303)。
文摘A high-activity and stable bifunctional oxygen reduction reaction(ORR)and oxygen evolution reaction(OER)electrocatalyst is critical for seawater-based Zn-air batteries(ZABs).Herein,we report a wood-derived chainmail electrocatalyst containing defective nitrogen-doped carbon nanotubes encapsulating cobalt nanoparticles(Co@D-NCNT/CW)to enhance the ORR/OER activity and stability in seawater medium.During the preparation process,the introduction and removal of Zn increased the defect sites and pyridine N content in the carbon material,modulating charge distribution and influencing the adsorption and activation processes.The highly ordered open channels in Co@D-NCNT/CW promoted mass transfer of reactants and accelerated gas diffusion.The resultant chainmail electrocatalyst exhibited impressive bifunctional ORR and OER activities with an ultra-low gap of 0.67 V in sea water-based alkaline electrolyte.The Co@D-NCNT/CW-assembled seawater-based rechargeable liquid ZABs demonstrated a maximum power density of 245.3 mW cm^(-2)and a long-term cycling performance over 500 h.The seawater-based all-solid-state ZABs achieved the maximum power density of 48.2 mW cm^(-2)and stabilized over 30 h.Density functional theory revealed that the presence of defects and pyridine nitrogen in Co@D-NCNT/CW modulated the electronic structure of Co,optimizing the binding affinity of the Co sites with intermediates and weakening Cl^(-)adsorption.This work provides a new approach to preparing high-activity and stable ORR/OER electrocatalyst utilizing wood nanostructures,boosting the development of seawater-based ZABs.
基金supported by the Natural Science Foundation of Jilin Province of China(Grant No.20230101014JC)the Fundamental Research Funds for the Central Universities(Grant No.2572021BC05)the National Natural Science Foundation of China(Grant No.12374265)。
文摘We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic order can be extended,and modulation near the cutoff order becomes smaller for the second plateau by increasing the time delay.These effects are due to an increase of the electron population in higher energy bands,where the larger band gap allows electrons to release more energy,and the long electronic paths are suppressed.Additionally,we also investigate the HHG of defective solids by Bohmian trajectories(BT).It is found that the harmonic intensity of the second plateau can be further enhanced.Simultaneously,cutoff order is also extended due to Bohmian particles moving farther away from the defective zone.
文摘The photocatalytic oxidation of methane to methanol using molecule oxygen directly is an attractive catalytic reaction,but designing catalysts to avoid over-oxidation remains a significant challenge.Herein,Cu single-atom anchored on the defective carbon nitride structure(Cu SA/Def-CN)is designed for selective photocatalytic oxidation of methane into methanol using O_(2) under mild conditions.The Cu SA/Def-CN catalyst exhibits a high methanol selectivity of 92.8%under optimized conditions.Mechanistic studies reveal a synergistic effect between Def-CN and Cu SA,where Def-CN is responsible for the in-situ generation of hydrogen peroxide,which is subsequently decomposed by the Cu SA sites to produce·OH radicals that play a key role in the rate-determining step of methane activation to form methanol.Additionally,the presence of Cu SA not only enhances the electron-hole separation efficiency and improves the transfer of the photo-generated charges,but also increases the number of active sites for methane adsorption and activation.These insights provide valuable guidance for designing efficient catalysts for the highly selective photocatalytic oxidation of methane to methanol.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea,funded by the Ministry of Education(No.2022R1I1A1A01056406)。
文摘Defective phononic crystals(PnCs)have enabled spatial localization and quantitative amplification of elastic wave energy.Most previous research has focused on applications such as narrow-bandpass filters,ultrasonic sensors,and piezoelectric energy harvesters,typically operating under the assumption of an external elastic wave incidence.Recently,a novel approach that uses defective PnCs as ultrasonic actuators to generate amplified waves has emerged.However,the existing studies are limited to the generation of either longitudinal or bending waves,with no research addressing the concurrent generation of both.Hence,this paper proposes a straightforward methodology for the concurrent generation and amplification of both wave types utilizing defect modes at independent defect-band frequencies.Bimorph piezoelectric elements are attached to the defect,with each element connected to independent external voltage sources.By precisely adjusting the magnitude and temporal phase differences between the voltage sources,concurrently amplified wave generation is achieved.The paper highlights the advantages of the proposed analytical model.This model is both computationally time-efficient and accurate,in comparison with the COMSOL simulation results.For instance,in case studies,the analytical model reduces the computational time from one hour to mere seconds,while maintaining acceptable error rates of 1%in peak frequencies.This concurrent wave-generation methodology opens new avenues for applications in rotating machinery fault diagnosis,structural health monitoring,and medical imaging.
基金supported by the National Natural Science Foundation of China(Nos.22001026,22171233,22201193)Sichuan Science and Technology Program(No.2023NSFSC0109)+1 种基金the Fundamental Research Funds for the Central Universitiesthe Hundred Talent Program of Sichuan University(No.YJ2021158)。
文摘The linker defect engineering for MOFs is a viable strategy that usually can effectively augment conductivity to further promote charge carrier separation,which is the most excellent conductivity of preserved metal clusters.However,the partially missing photosensitive linker often leads to the diminished light utilization efficiency.As we know,in the linker defect engineering,addressing the lack of photosensitivity while maintaining outstanding conductivity is still in its infancy.In this essay,the linkerdefective NH_(2)-MIL-125 was obtained by adding the glacial acetic acid regulator,subsequently,the excellent light-responsive Pt/CQDs with up-conversion effect was in-situ encapsulated into the enlarged pore space of linker-defective NH_(2)-MIL-125.It is excited that the fabricated dual-functional composite ideally integrates photosensitivity and conductivity for photocatalytic hydrogen evolution and NO elimination.The optimal Pt/CQDs@NM-125-4 exhibited very superior photocatalytic hydrogen evolution(28.75mmol/g),it was 11.63 times as that of the initial NH_(2)-MIL-125(2.47 mmol/g)and 1.4 times as that of the defective NM-125-4(20.46 mmol/g).In addition,the excellent photocatalytic NO removal efficiency was 52.12%for Pt/CQDs@NM-125-4,whereas the original NH_(2)-MIL-125 only reached 30%and the defective NM-125-4 achieved 44.96%.The corresponding optical and electrical characterization based on UV-vis,up-conversion photoluminescence(UCPL),and electrochemical impedance spectroscopy(EIS)etc.demonstrated the defect engineering accelerates the charge carriers transfer via enhancing conductivity,and the in-situ confined up-conversion Pt/CQDs promote the visible light response.Our work presents a feasible avenue to integrate photosensitivity and conductivity via in-situ fabricating excellent lightresponsive Pt/CQDs within linker-defective NH_(2)-MIL-125 for further significantly boosting photocatalytic performance.
基金supported by the National Natural Science Foundation of China(Nos.U21A2060 and 22178116)the Natural Science Foundation of Shanghai(No.22ZR1417400)the Fundamental Research Funds for the Central Universities(Nos.222201817001,50321041918013,JKA01221601,JKD01241701).
文摘Lithium-sulfur(Li-S)batteries are regarded as the most formidable competitor to lithium-ion batteries due to their superior theoretical capacity.However,the negative impact of soluble lithium polysulfide(LiPSs)and slow redox reaction kinetics seriously hamper the commercialization of Li-S batteries.In this study,a defect-rich single-atom catalyst with an oversaturated asymmetric Fe-N_(5)coordination structure anchored in defective g-C_(3)N_(4)(C_(3)N_(4)-Fe@rGO)is designed via an absorption-pyrolysis strategy.The two-dimensional(2D)conducting C_(3)N_(4)@graphene structure with abundant defect sites accelerates the trans-fer and transportation of lithium ions and electrons.The oversaturated asymmetric Fe-N_(5)coordination structure effectively improves the adsorbility of LiPSs and accelerates the redox kinetics of sulfur species.Hence,the Li-S cell with a C_(3)N_(4)-Fe@rGO modified separator reveals a high initial capacity(1197.1 mAh g^(-1) at 0.2 C)and a low capacity decay rate(0.037%per cycle after 900 cycles at 1 C).Even at high sulfur loading and extreme temperatures of 0℃,it also shows good cycling performance.This work creates ideas for synthesizing oversaturated single-atom coordination environments and an efficient route to the practical realization of the Li-S batteries.
文摘Defect engineering improves the catalytic performance of metal-organic frameworks(MOFs)loaded metal nanoparticles(MNPs@MOFs),but there is still a challenge in defining the structure-activity relationships.Herein,the content of linker-missing defects in UiO-66(Ce)was systematically regulated via formic acid as the modulators,and defective UiO-66(Ce)loaded Ni nanoparticles(NPs)were constructed for dicyclopentadiene(DCPD)hydrogenation.The fine regulation of defect engineering and reduction conditions affected the structure properties of UiO-66(Ce)and the electronic metal-support interaction between MOFs and Ni NPs,thereby optimizing the microenvironment and electronic state of Ni NPs.The optimized U(Ce)-40eq with suitable defects,small size and structure stability effectively promoted the production of highly dispersed abundant electron-deficient Ni^(0) active sites,enhancing the adsorption and activation of H_(2) and C=C bonds,especially accelerating the rate-determining step.Therefore,U(Ce)-40eq loaded 5 wt%Ni NPs achieved DCPD saturated hydrogenation to tetrahydrodicyclopentadiene(70℃,2 MPa,90 min),superior to most high-loading Ni-based catalysts.This work reveals the synergistic mechanism of MOFs defect engineering and electronic structure of Ni NPs,providing effective guidance for the precise preparation of highly efficient and stable MNPs@MOFs heterogeneous catalysts.
基金National Key Research and Development Program of China,Grant/Award Number:2023YFC2410403。
文摘Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.
基金funded by Multimedia University,Cyberjaya,Selangor,Malaysia(Grant Number:PostDoc(MMUI/240029)).
文摘Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.
文摘The original online version of this article was revised:The layout update for Article 758 has impacted the page range in the published issue,but did not affect the scholarly content.To ensure consistency with the originally assigned pages(2595-2614),we will need to publish an erratum to correct the article and restore the original page range.The original article has been corrected.
基金support from the National Institute of Health(K99AR081897,R00AR081897)M.N.W.acknowledges funding support from the National Institute of Health(P01DK011794,R01DK116716)+1 种基金the Smith Family Foundation Odyssey Award,and the Chen Institute Massachusetts General Hospital Research Scholar(2024-2029)awardμCT and bone histomorphometry were performed by the Center for Skeletal Research at Massachusetts General Hospital,a NIH-funded program(P30AR066261 and AR075042)led by Mary Bouxsein and Marie Demay.
文摘Osteogenesis imperfecta(OI)is a group of diseases caused by defects in type I collagen processing which result in skeletal fragility.While these disorders have been regarded as defects in osteoblast function,the role of matrix-embedded osteocytes in OI pathogenesis remains largely unknown.Homozygous human SP7(c.946 C>T,R316C)mutation results in a recessive form of OI characterized by fragility fractures,low bone mineral density and osteocyte dendrite defects.To better understand how the OI-causing R316C mutation affects the function of SP7,we generated Sp7^(R342C)knock-in mice.Consistent with patient phenotypes,Sp7^(R342C/R342C)mice demonstrate increased cortical porosity and reduced cortical bone mineral density.Sp7^(R342C/R342C)mice show osteocyte dendrite defects,increased osteocyte apoptosis,and intracortical bone remodeling with ectopic intracortical osteoclasts and elevated osteocyte Tnfsf11 expression.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
基金supported by the State Grid Southwest Branch Project“Research on Defect Diagnosis and Early Warning Technology of Relay Protection and Safety Automation Devices Based on Multi-Source Heterogeneous Defect Data”.
文摘The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.
基金supported in part by the National Natural Science Foundation of China(Grant No.62071123)in part by the Natural Science Foundation of Fujian Province(Grant Nos.2024J01971,2022J05202)in part by the Young and Middle-Aged Teacher Education Research Project of Fujian Province(Grant No.JAT210370).
文摘In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
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.
基金funded by Ministry of Education Humanities and Social Science Research Project,grant number 23YJAZH034The Postgraduate Research and Practice Innovation Program of Jiangsu Province,grant number SJCX25_17National Computer Basic Education Research Project in Higher Education Institutions,grant number 2024-AFCEC-056,2024-AFCEC-057.
文摘To solve the false detection and missed detection problems caused by various types and sizes of defects in the detection of steel surface defects,similar defects and background features,and similarities between different defects,this paper proposes a lightweight detection model named multiscale edge and squeeze-and-excitation attention detection network(MSESE),which is built upon the You Only Look Once version 11 nano(YOLOv11n).To address the difficulty of locating defect edges,we first propose an edge enhancement module(EEM),apply it to the process of multiscale feature extraction,and then propose a multiscale edge enhancement module(MSEEM).By obtaining defect features from different scales and enhancing their edge contours,the module uses the dual-domain selection mechanism to effectively focus on the important areas in the image to ensure that the feature images have richer information and clearer contour features.By fusing the squeeze-and-excitation attention mechanism with the EEM,we obtain a lighter module that can enhance the representation of edge features,which is named the edge enhancement module with squeeze-and-excitation attention(EEMSE).This module was subsequently integrated into the detection head.The enhanced detection head achieves improved edge feature enhancement with reduced computational overhead,while effectively adjusting channel-wise importance and further refining feature representation.Experiments on the NEU-DET dataset show that,compared with the original YOLOv11n,the improved model achieves improvements of 4.1%and 2.2%in terms of mAP@0.5 and mAP@0.5:0.95,respectively,and the GFLOPs value decreases from the original value of 6.4 to 6.2.Furthermore,when compared to current mainstream models,Mamba-YOLOT and RTDETR-R34,our method achieves superior performance with 6.5%and 8.9%higher mAP@0.5,respectively,while maintaining a more compact parameter footprint.These results collectively validate the effectiveness and efficiency of our proposed approach.
