Prisoner’s Dilemma is a master trope for relaying the permanent impasse or dilemma of cooperation versus defection.In Prisoner’s Dilemma Richard Powers narrates a multiform of dilemma mainly narrating Eddie Hobson’...Prisoner’s Dilemma is a master trope for relaying the permanent impasse or dilemma of cooperation versus defection.In Prisoner’s Dilemma Richard Powers narrates a multiform of dilemma mainly narrating Eddie Hobson’s traumatic history,along with Eddie’s attempt to carry out a strategy—Eddie’s ideal Hobstown which is supposed to cope with the confused dilemma.Pow⁃ers’strategic moral insights are revealed by assuming that each player feels sympathy for the other and a moral cooperative instead of antagonistic solution to the Prisoner’s Dilemma will be found.展开更多
Without cooperative behaviors, our society or organization falls into social dilemma situations where every member selects uncooperative （defective） behaviors, and the situation gets worse and worse. Such a situatio...Without cooperative behaviors, our society or organization falls into social dilemma situations where every member selects uncooperative （defective） behaviors, and the situation gets worse and worse. Such a situation in a society or an organization leads to violation of social or organizational rules, and at the worst case it suffers from serious accidents or scandals. Therefore, it is important for us to make efforts and take measures to elicit cooperative behaviors. It was demonstrated theoretically that altruism strategy and adaptive prediction and ascertainment strategy are in some cases better than rational strategy under the situation of social dilemma. We built up a mathematical model in order to examine how the probability of correctly predicting and ascertaining the behavior （cooperation or defection） of opponents and the mixture of （a） altruism （all cooperation） strategy, （b） individualism （all defection） strategy, and （c） adaptive prediction and ascertainment strategy affected the expected profit. Simulation results showed that the tit-for-tat strategy was better than the rational （individualism） strategy when the probability of correctly predicting and ascertaining defection of the opponent was considerably higher. As an application of the basic study above, it was explored, using a simulation method, how such a system as opening reputation or peer review in public could work satisfactorily to prevent defective behaviors in auction dealing. The result showed that the information on the handle name and the reputation effectively worked to prevent defective behaviors.展开更多
In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framewo...In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framework,the sliding multi-time slicing(SMTS)method.We apply this method to data from the largest marketplace in Greece,namely,Skroutz,considering the standard features that account for the important characteristics of customer activity and custom performance metrics aimed at capturing business-related goals established by the company.The dataset comprises customers over a relatively short period,since April 2018,the number of which has also exhibited a significant increase in recent months.Despite these difficulties and the inherent seasonality of customer defection,our results demonstrate that,with SMTS,developing models that outperform previous approaches and optimize decision-making is possible.We validate the approach to a benchmark dataset from the commerce sector and discuss the practical considerations and requirements of the proposed method.展开更多
In our society, it is a major issue to enhance cooperative behaviors. Without this, our society fall into social dilemma situations, and gets worse and worse. Such a situation in an organization leads to violation of ...In our society, it is a major issue to enhance cooperative behaviors. Without this, our society fall into social dilemma situations, and gets worse and worse. Such a situation in an organization leads to violation of social or organizational rules, and at the worst case it suffers from serious accidents or scandals. Therefore, it is important for organizational managers to make efforts and take measures to enhance cooperative behaviors. Although there seem to be many ways to constantly elicit cooperative behaviors, the punishment is one of the most effective measures for enhancing cooperation. This study focused on the effects of penalty and probability of the revelation of defection on the cooperation, and getting insight into how punishment strategy should be used to get rid of social dilemmas and enhance cooperation. This study conducted a simulation experiment to find the proper penal regulations condition that can suppress violations （defective behavior） in a 2-person prisoner＇s dilemma situation. The effects of probability of the revelation of defection and penalty to revelation on the cooperative behavior were identified with the interactive effect of both experimental factors. The defection （uncooperative behavior） decreased when the penalty to the defection was heavy and the probability of the revelation of defection was low than that when the penalty to the defection was light and the probability of the revelation of the defection was high.展开更多
T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection met...T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.展开更多
Biomass-derived carbon materials are favored for their abundance and sustainability,and ease of preparation and modification.By surface activation and modification they can have a good electrical conductivity,excellen...Biomass-derived carbon materials are favored for their abundance and sustainability,and ease of preparation and modification.By surface activation and modification they can have a good electrical conductivity,excellent catalytic activity,a remarkable adsorption capacity,and different interfacial physicochemical functionalities.Surface-modified biochars have found wide applications in energy storage,environmental remediation,and catalysis.However,achieving precise and controllable modification of their active sites remains a challenge.Recent advances and future prospects for controlling their surface morphology,defect engineering,and surface coating strategies,with particular attention to their means of fabrication,are reviewed.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
Among various advanced oxidation processes(AOPs),heterogeneous catalytic ozonation has garnered extensive attention in wastewater treatment owing to its broad pH range applicability and the elimination of the need for...Among various advanced oxidation processes(AOPs),heterogeneous catalytic ozonation has garnered extensive attention in wastewater treatment owing to its broad pH range applicability and the elimination of the need for additional energy input.Enhancing catalyst activity by introducing oxygen vacancies has been used extensively in heterogeneous catalytic ozonation.This paper reviews prevalent methods for the construction and characterization of oxygen vacancies.Based on a thorough examination of existing research,the role of oxygen vacancies is categorized according to their primary mechanisms of action in heterogeneous catalytic ozonation.For example,modulation of the catalyst electronic structure to enhance electron transfer;participation in the reaction as an active site to generate radicals and non-radicals;and exposure of more metal sites to enhance the reaction.Lastly,the paper delineates the limitations and future research directions concerning the role of oxygen vacancies in catalytic ozonation.This review addresses the gap in existing literature concerning the role of oxygen vacancies in catalytic ozone systems,establishes a comprehensive theoretical framework to aid in the design of efficient ozone catalysts,and delves into the functionality of oxygen vacancies in heterogeneous catalytic ozone reactions.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
Density functional theory(DFT)calculations were employed to investigate the adsorption behavior of NH_(3),AsH_(3),PH_(3),CO_(2),and CH_(4)molecules on both pristine and mono-vacancy phosphorene sheets.The pristine pho...Density functional theory(DFT)calculations were employed to investigate the adsorption behavior of NH_(3),AsH_(3),PH_(3),CO_(2),and CH_(4)molecules on both pristine and mono-vacancy phosphorene sheets.The pristine phosphorene surface showsweak physisorption with all the gasmolecules,inducing onlyminor changes in its structural and electronic properties.However,the introduction ofmono-vacancies significantly enhances the interaction strength with NH_(3),PH_(3),CO_(2),and CH_(4).These variations are attributed to substantial charge redistribution and orbital hybridization in the presence of defects.The defective phosphorene sheet also exhibits enhanced adsorption energies,along with favorable sensitivity and recovery characteristics,highlighting its potential as a promising gas sensor for NH_(3),AsH_(3),PH_(3),CO_(2),and CH_(4)at ambient conditions.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
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
This comprehensive study investigates the formation and evolution of intermetallic compounds during the solidification process of magnesium alloys using advanced micro X-ray computed tomography.By analyzing both commo...This comprehensive study investigates the formation and evolution of intermetallic compounds during the solidification process of magnesium alloys using advanced micro X-ray computed tomography.By analyzing both common industrial Mg-Al-Zn alloys and a novel rare earth-containing Mg-Ni-Gd-Y alloy,we aim to characterize the nucleation,growth,and distribution of Al-Mn and eutectic intermetallics across various stages of solidification.The non destructive imaging technique employed in this research provides high-resolution,three-dimensional insights into the microstructural development,allowing for a detailed examination of the morphology,spatial arrangement,and interconnectivity of intermetallic phases.This approach overcomes limitations of traditional two-dimensional metallographic methods,offering a more comprehensive understanding of the complex three-dimensional structures formed during solidification.展开更多
Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remain...Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.展开更多
Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled t...Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood.In this study,transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys,suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation.To complement these observations,first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum.The stress response,total energy,density of states(DOS),and differential charge density were examined under varying compressive strain(ε=0–0.1)and temperature(0–600 K).The results indicate that face-centered vacancies tend to reduce mechanical strength and perturb electronic states near the Fermi level,whereas corner and edge vacancies appear to have weaker effects.Elevated temperatures may partially restore electronic uniformity through thermal excitation.Overall,these findings suggest that vacancy position exerts a critical but position-dependent influence on coupled structure-property relationships,offering theoretical insights and preliminary experimental support for defect-engineered aluminum alloy design.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
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
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
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
Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated...Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated safety risks,including container drops during lifting operations.Timely and accurate inspection before and after transit is therefore essential.Traditional inspection methods rely heavily on manual observation of internal and external surfaces,which are time-consuming,resource-intensive,and prone to subjective errors.Container roofs pose additional challenges due to limited visibility,while grapple slots are especially vulnerable to wear from frequent use.This study proposes a two-stage automated detection framework targeting defects in container roof grapple slots.In the first stage,YOLOv7 is employed to localize grapple slot regions with high precision.In the second stage,ResNet50 classifies the extracted slots as either intact or defective.The results from both stages are integrated into a human-machine interface for real-time visualization and user verification.Experimental evaluations demonstrate that YOLOv7 achieves a 99%detection rate at 100 frames per second(FPS),while ResNet50 attains 87%classification accuracy at 34 FPS.Compared to some state of the arts,the proposed system offers significant speed,reliability,and usability improvements,enabling efficient defect identification and visual reconfirmation via the interface.展开更多
文摘Prisoner’s Dilemma is a master trope for relaying the permanent impasse or dilemma of cooperation versus defection.In Prisoner’s Dilemma Richard Powers narrates a multiform of dilemma mainly narrating Eddie Hobson’s traumatic history,along with Eddie’s attempt to carry out a strategy—Eddie’s ideal Hobstown which is supposed to cope with the confused dilemma.Pow⁃ers’strategic moral insights are revealed by assuming that each player feels sympathy for the other and a moral cooperative instead of antagonistic solution to the Prisoner’s Dilemma will be found.
文摘Without cooperative behaviors, our society or organization falls into social dilemma situations where every member selects uncooperative （defective） behaviors, and the situation gets worse and worse. Such a situation in a society or an organization leads to violation of social or organizational rules, and at the worst case it suffers from serious accidents or scandals. Therefore, it is important for us to make efforts and take measures to elicit cooperative behaviors. It was demonstrated theoretically that altruism strategy and adaptive prediction and ascertainment strategy are in some cases better than rational strategy under the situation of social dilemma. We built up a mathematical model in order to examine how the probability of correctly predicting and ascertaining the behavior （cooperation or defection） of opponents and the mixture of （a） altruism （all cooperation） strategy, （b） individualism （all defection） strategy, and （c） adaptive prediction and ascertainment strategy affected the expected profit. Simulation results showed that the tit-for-tat strategy was better than the rational （individualism） strategy when the probability of correctly predicting and ascertaining defection of the opponent was considerably higher. As an application of the basic study above, it was explored, using a simulation method, how such a system as opening reputation or peer review in public could work satisfactorily to prevent defective behaviors in auction dealing. The result showed that the information on the handle name and the reputation effectively worked to prevent defective behaviors.
文摘In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framework,the sliding multi-time slicing(SMTS)method.We apply this method to data from the largest marketplace in Greece,namely,Skroutz,considering the standard features that account for the important characteristics of customer activity and custom performance metrics aimed at capturing business-related goals established by the company.The dataset comprises customers over a relatively short period,since April 2018,the number of which has also exhibited a significant increase in recent months.Despite these difficulties and the inherent seasonality of customer defection,our results demonstrate that,with SMTS,developing models that outperform previous approaches and optimize decision-making is possible.We validate the approach to a benchmark dataset from the commerce sector and discuss the practical considerations and requirements of the proposed method.
文摘In our society, it is a major issue to enhance cooperative behaviors. Without this, our society fall into social dilemma situations, and gets worse and worse. Such a situation in an organization leads to violation of social or organizational rules, and at the worst case it suffers from serious accidents or scandals. Therefore, it is important for organizational managers to make efforts and take measures to enhance cooperative behaviors. Although there seem to be many ways to constantly elicit cooperative behaviors, the punishment is one of the most effective measures for enhancing cooperation. This study focused on the effects of penalty and probability of the revelation of defection on the cooperation, and getting insight into how punishment strategy should be used to get rid of social dilemmas and enhance cooperation. This study conducted a simulation experiment to find the proper penal regulations condition that can suppress violations （defective behavior） in a 2-person prisoner＇s dilemma situation. The effects of probability of the revelation of defection and penalty to revelation on the cooperative behavior were identified with the interactive effect of both experimental factors. The defection （uncooperative behavior） decreased when the penalty to the defection was heavy and the probability of the revelation of defection was low than that when the penalty to the defection was light and the probability of the revelation of the defection was high.
文摘T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.
文摘Biomass-derived carbon materials are favored for their abundance and sustainability,and ease of preparation and modification.By surface activation and modification they can have a good electrical conductivity,excellent catalytic activity,a remarkable adsorption capacity,and different interfacial physicochemical functionalities.Surface-modified biochars have found wide applications in energy storage,environmental remediation,and catalysis.However,achieving precise and controllable modification of their active sites remains a challenge.Recent advances and future prospects for controlling their surface morphology,defect engineering,and surface coating strategies,with particular attention to their means of fabrication,are reviewed.
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support from the Key R&D Program of Zhejiang province(No.2024C03136).
文摘Among various advanced oxidation processes(AOPs),heterogeneous catalytic ozonation has garnered extensive attention in wastewater treatment owing to its broad pH range applicability and the elimination of the need for additional energy input.Enhancing catalyst activity by introducing oxygen vacancies has been used extensively in heterogeneous catalytic ozonation.This paper reviews prevalent methods for the construction and characterization of oxygen vacancies.Based on a thorough examination of existing research,the role of oxygen vacancies is categorized according to their primary mechanisms of action in heterogeneous catalytic ozonation.For example,modulation of the catalyst electronic structure to enhance electron transfer;participation in the reaction as an active site to generate radicals and non-radicals;and exposure of more metal sites to enhance the reaction.Lastly,the paper delineates the limitations and future research directions concerning the role of oxygen vacancies in catalytic ozonation.This review addresses the gap in existing literature concerning the role of oxygen vacancies in catalytic ozone systems,establishes a comprehensive theoretical framework to aid in the design of efficient ozone catalysts,and delves into the functionality of oxygen vacancies in heterogeneous catalytic ozone reactions.
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.
基金financial support to conduct this research from the Science and Engineering Research Board(SERB)through a state university research excellence(SURE)grant(SUR/2022/004935).
文摘Density functional theory(DFT)calculations were employed to investigate the adsorption behavior of NH_(3),AsH_(3),PH_(3),CO_(2),and CH_(4)molecules on both pristine and mono-vacancy phosphorene sheets.The pristine phosphorene surface showsweak physisorption with all the gasmolecules,inducing onlyminor changes in its structural and electronic properties.However,the introduction ofmono-vacancies significantly enhances the interaction strength with NH_(3),PH_(3),CO_(2),and CH_(4).These variations are attributed to substantial charge redistribution and orbital hybridization in the presence of defects.The defective phosphorene sheet also exhibits enhanced adsorption energies,along with favorable sensitivity and recovery characteristics,highlighting its potential as a promising gas sensor for NH_(3),AsH_(3),PH_(3),CO_(2),and CH_(4)at ambient conditions.
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Project(2023YFB4606200)supported by the National Key Research and Development Program of ChinaProject(2023-SSRF-HZ-503114-2)supported by Shanghai Synchrotron Radiation Facility,Instrument BL16U2,China。
文摘This comprehensive study investigates the formation and evolution of intermetallic compounds during the solidification process of magnesium alloys using advanced micro X-ray computed tomography.By analyzing both common industrial Mg-Al-Zn alloys and a novel rare earth-containing Mg-Ni-Gd-Y alloy,we aim to characterize the nucleation,growth,and distribution of Al-Mn and eutectic intermetallics across various stages of solidification.The non destructive imaging technique employed in this research provides high-resolution,three-dimensional insights into the microstructural development,allowing for a detailed examination of the morphology,spatial arrangement,and interconnectivity of intermetallic phases.This approach overcomes limitations of traditional two-dimensional metallographic methods,offering a more comprehensive understanding of the complex three-dimensional structures formed during solidification.
基金supported by the National Natural Science Foundation of China(Grant No.62205103)the Natural Science Foundation of Hunan Province(Grant No.2023JJ40216)the Elite Youth Program by the Department of Education of Hunan Province(Grant No.24B0663)。
文摘Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.
基金supported by the Research Project on Strengthening the Construction of an Important Ecological Security Barrier in Northern China by Higher Education Institutions in the Inner Mongolia Autonomous Region(STAQZX202313)the Inner Mongolia Autonomous Region Education Science‘14th Five-Year Plan’2024 Annual Research Project(NGJGH2024635).
文摘Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood.In this study,transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys,suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation.To complement these observations,first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum.The stress response,total energy,density of states(DOS),and differential charge density were examined under varying compressive strain(ε=0–0.1)and temperature(0–600 K).The results indicate that face-centered vacancies tend to reduce mechanical strength and perturb electronic states near the Fermi level,whereas corner and edge vacancies appear to have weaker effects.Elevated temperatures may partially restore electronic uniformity through thermal excitation.Overall,these findings suggest that vacancy position exerts a critical but position-dependent influence on coupled structure-property relationships,offering theoretical insights and preliminary experimental support for defect-engineered aluminum alloy design.
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.
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(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.
文摘Container transportation is pivotal in global trade due to its efficiency,safety,and cost-effectiveness.However,structural defects—particularly in grapple slots—can result in cargo damage,financial loss,and elevated safety risks,including container drops during lifting operations.Timely and accurate inspection before and after transit is therefore essential.Traditional inspection methods rely heavily on manual observation of internal and external surfaces,which are time-consuming,resource-intensive,and prone to subjective errors.Container roofs pose additional challenges due to limited visibility,while grapple slots are especially vulnerable to wear from frequent use.This study proposes a two-stage automated detection framework targeting defects in container roof grapple slots.In the first stage,YOLOv7 is employed to localize grapple slot regions with high precision.In the second stage,ResNet50 classifies the extracted slots as either intact or defective.The results from both stages are integrated into a human-machine interface for real-time visualization and user verification.Experimental evaluations demonstrate that YOLOv7 achieves a 99%detection rate at 100 frames per second(FPS),while ResNet50 attains 87%classification accuracy at 34 FPS.Compared to some state of the arts,the proposed system offers significant speed,reliability,and usability improvements,enabling efficient defect identification and visual reconfirmation via the interface.
