Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is stil...Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.展开更多
BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown...BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.展开更多
Background:Atrial septal defect(ASD)is a common form of adult congenital heart disease that can lead to long-term adverse outcomes if left untreated.Early closure of ASD has been associated with excellent outcomes and...Background:Atrial septal defect(ASD)is a common form of adult congenital heart disease that can lead to long-term adverse outcomes if left untreated.Early closure of ASD has been associated with excellent outcomes and lower complication rates.However,there is limited evidence regarding the prognosis of ASD closure in older adults.This study aims to evaluate the mortality rates in older ASD patients with and without closure.Methods:A retrospective cohort study was conducted on patients aged 40 years or older with ASD between 2001 and 2017.Patients were followed up to assess all-cause mortality.Univariable and multivariable analyses were performed to identify the predictors of mortality.A p-value of<0.05 was considered statistically significant.Results:The cohort consisted of 450 patients(mean age 56.6±10.4 years,77.3%female),with 66%aged between 40 and 60 years,and 34%over 60 years.Within the cohort,299 underwent ASD closure(201 with transcatheter and 98 with surgical closure).During the median follow-up duration of 7.9 years,51 patients died.The unadjusted cumulative 10-year rate of mortality was 3%in patients with ASD closure,and 28%in patients without ASD closure(log-rank p<0.001).Multivariable analysis revealed that age(hazard ratio[HR]1.04,95%confidence interval[CI]1.006–1.06,p=0.01),NYHA class(HR 2.75,95%CI 1.63–4.62,p<0.001),blood urea nitrogen(BUN)(HR 1.07,95%CI 1.03–1.12,p<0.001),right ventricular systolic pressure(RVSP)(HR 1.07,95%CI 1.003–1.04,p=0.01),and lack of ASD closure(HR 15.12,95%CI 5.63–40.59,p<0.001)were independently associated with mortality.Conclusion:ASD closure demonstrated favorable outcomes in older patients.Age,NYHA class,BUN,RVSP,and lack of ASD closure were identified as independent factors linked to mortality in this population.展开更多
Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,t...Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,the three primary micro-defect types at potential stress concentrations in sintered AgNPs are identified,categorized,and quantified.Molecular dynamics(MD)simulations are employed to observe the failure evolution of different microscopic defects.The dominant mechanisms responsible for this evolution are dislocation nucleation and dislocation motion.At the same time,this paper clarifies the quantitative relationship between the tensile strain amount and the failure mechanism transitions of the three defect types by defining key strain points.The impact of defect types on the failure process is also discussed.Furthermore,traction-separation curves extracted from microscopic defect evolutions serve as a bridge to connect the macro-scale model.The validity of the crack propagation model is confirmed through tensile tests.Finally,we thoroughly analyze how micro-defect types influence macro-crack propagation and attempt to find supporting evidence from the MD model.Our findings provide a multi-perspective reference for the reliability analysis of sintered AgNPs.展开更多
The rapid advancement of halide-based hybrid perovskite materials has garnered significant research attention,particularly in the domain of photovoltaic technology.Owing to their exceptional optoelec-tronic properties...The rapid advancement of halide-based hybrid perovskite materials has garnered significant research attention,particularly in the domain of photovoltaic technology.Owing to their exceptional optoelec-tronic properties,they demonstrated power conversion efficiency(PcE)of over 25%in single junction solar cells.Despite the notable progress in PCE over the past decade,the inherent high defect density pre-senting in perovskite materials gives rise to several loss mechanisms and associated ion migration in per-ovskite solar cells(PsCs)during operational conditions.These factors collectively contribute to a significant stability challenge in PsCs,placing their longevity far behind for commercialization.While numerous reports have explored defects,ion migration,and their impacts on device performance,a com-prehensive correlation between the types of defects and the degradation kinetics of perovskite materials and PsCs has been lacking.In this context,this review aims to provide a comprehensive overview of the origins of defects and ion migration,emphasizing their correlation with the degradation kinetics of per-ovskite materials and PsCs,leveraging reliable characterization techniques.Furthermore,these charac-terization techniques are intended to comprehend loss mechanisms by different passivation approaches to enhance the durability and PCE of PSCs.展开更多
Niobium pentoxide(Nb_(2)O_(5))is deemed one of the promising anode materials for lithium-ion batteries(LIBs)for its outstanding intrinsic fast Li-(de)intercalation kinetics.The specific capacity,however,is still limit...Niobium pentoxide(Nb_(2)O_(5))is deemed one of the promising anode materials for lithium-ion batteries(LIBs)for its outstanding intrinsic fast Li-(de)intercalation kinetics.The specific capacity,however,is still limited,because the(de)intercalation of excessive Li-ions brings the undesired stress to damage Nb_(2)O_(5) crystals.To increase the capacity of Nb_(2)O_(5) and alleviate the lattice distortion caused by stress,numerous homogeneous H-and M-phases junction interfaces were proposed to produce coercive stress within theNb_(2)O_(5)crystals.Such interfaces bring about rich oxygen vacancies with structural shrinkage tendency,which pre-generate coercive stress to resist the expansion stress caused by excessive Li-ions intercalation.Therefore,the synthesized Nb_(2)O_(5) achieves the highest lithium storage capacity of 315 mA h g−1 to date,and exhibits high-rate performance(118 mA h g^(-1) at 20 C)as well as excellent cycling stability(138 mA h g^(-1) at 10 C after 600 cycles).展开更多
Introduction: Ventricular septal defect (VSD) is the most common congenital heart disease of all congenital heart defects. The aim of this study was to investigate the echographic, therapeutic and evolutionary aspects...Introduction: Ventricular septal defect (VSD) is the most common congenital heart disease of all congenital heart defects. The aim of this study was to investigate the echographic, therapeutic and evolutionary aspects of ventricular septal defects (VSD) in the general cardiology department of the Hôpital National Ignace Deen. Methods: A retrospective data collection was carried out from January 2018 to December 2023 including 85 cases of isolated IVC was performed. The variables studied were epidemiological, clinical, paraclinical, therapeutic and evolutionary. Results: Of the 320 patients seen during the study period for congenital heart disease, 85 (26.556%) were isolated IVCs. Age at diagnosis ranged from 3 months to 16 years, with an average age of 3.59 years. The most represented ethnic group was the Fulani (50.58%). The 8.24% came from consanguineous marriage versus 22.35%. 91.76% of children had a history of bronchitis. The most common clinical signs found were systolic murmur (90.58%), growth retardation (51.76%). Only 4 cases (4.70%) had a malformation associated with IVC represented by DiGeorges disease (2.35%) and trisomy 21 (2.35%). Nearly half the patients had type IIb VIC (44.71%). The other half were represented by type 1 (18.82%), type IIa (20%), type III (10.59%) and type IV (5.88%). According to site more than two-thirds of VICs (71.64%) were perimembranous in location, followed by infundibular (16.47%) and muscular (11.76%) VICs. In our study 55.29% presented an indication for both surgical intervention and medical treatment, while 16.47% required only medical treatment. In contrast, 28.23% were placed under exclusive surveillance. Of the 47 patients for whom surgery was indicated, 29 (61.17%) underwent surgical repair, while 18 (38.83%) were awaiting confirmation for surgery. Conclusion: VIC is the most common congenital heart disease. An early detection strategy and the establishment of specialized centers could improve the outcome of these children.展开更多
In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2) and FeS_(2),first-principles calculation method was used to investigate the alloys.The calculat...In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2) and FeS_(2),first-principles calculation method was used to investigate the alloys.The calculated results of materials without vacancy are consistent with those reported in the literatures,while the results of materials with vacancy defect were different from those of literatures due to the difference vacancy concentration.The Co vacancy defect hardly changes the half-metallic characteristic of CoS_(2).The Fe vacancy defect changes FeS_(2) from semiconductor to half-metal,and the bottom of the spin-down conduction band changes from the p orbital state of S to the d(t_(2g))orbital state of Fe,while the top of the valence band remains the d orbital d(eg)state of Fe.The half-metallic Co vacancy defects of CoS_(2) and Fe vacancy defects of FeS_(2) are expected to be used in spintronic devices.S vacancy defects make both CoS_(2) and FeS_(2) metallic.Both the Co and S vacancy defects lead to the decrease of the magnetic moment of CoS_(2),while both the Fe and S vacancy defects lead to the obvious magnetic property of FeS_(2).Vacancy defects enhance the absorption coefficient of infrared band and long band of visible light obviously,and produce obvious red shift phenomenon,which is expected to be used in photoelectric devices.展开更多
As computer technology continues to advance,factories have increasingly higher demands for detecting defects.However,detecting defects in a plant environment remains a challenging task due to the presence of complex b...As computer technology continues to advance,factories have increasingly higher demands for detecting defects.However,detecting defects in a plant environment remains a challenging task due to the presence of complex backgrounds and defects of varying shapes and sizes.To address this issue,this paper proposes YOLO-DD,a defect detectionmodel based on YOLOv5 that is effective and robust.To improve the feature extraction process and better capture global information,the vanilla YOLOv5 is augmented with a new module called Relative-Distance-Aware Transformer(RDAT).Additionally,an Information Gap Filling Strategy(IGFS)is proposed to improve the fusion of features at different scales.The classic lightweight attention mechanism Squeeze-and-Excitation(SE)module is also incorporated into the neck section to enhance feature expression and improve the model’s performance.Experimental results on the NEU-DET dataset demonstrate that YOLO-DDachieves competitive results compared to state-of-the-art methods,with a 2.0% increase in accuracy compared to the original YOLOv5,achieving 82.41% accuracy and38.25FPS(framesper second).Themodel is also testedon a self-constructed fabric defect dataset,and the results show that YOLO-DD is more stable and has higher accuracy than the original YOLOv5,demonstrating its stability and generalization ability.The high efficiency of YOLO-DD enables it to meet the requirements of industrial high accuracy and real-time detection.展开更多
Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an i...Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.展开更多
Segment Anything Model(SAM)is a cutting-edge model that has shown impressive performance in general object segmentation.The birth of the segment anything is a groundbreaking step towards creating a universal intellige...Segment Anything Model(SAM)is a cutting-edge model that has shown impressive performance in general object segmentation.The birth of the segment anything is a groundbreaking step towards creating a universal intelligent model.Due to its superior performance in general object segmentation,it quickly gained attention and interest.This makes SAM particularly attractive in industrial surface defect segmentation,especially for complex industrial scenes with limited training data.However,its segmentation ability for specific industrial scenes remains unknown.Therefore,in this work,we select three representative and complex industrial surface defect detection scenarios,namely strip steel surface defects,tile surface defects,and rail surface defects,to evaluate the segmentation performance of SAM.Our results show that although SAM has great potential in general object segmentation,it cannot achieve satisfactory performance in complex industrial scenes.Our test results are available at:https://github.com/VDT-2048/SAM-IS.展开更多
With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivo...With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.展开更多
Electrocatalytic water splitting seems to be an efficient strategy to deal with increasingly serious environmental problems and energy crises but still suffers from the lack of stable and efficient electrocatalysts.De...Electrocatalytic water splitting seems to be an efficient strategy to deal with increasingly serious environmental problems and energy crises but still suffers from the lack of stable and efficient electrocatalysts.Designing practical electrocatalysts by introducing defect engineering,such as hybrid structure,surface vacancies,functional modification,and structural distortions,is proven to be a dependable solution for fabricating electrocatalysts with high catalytic activities,robust stability,and good practicability.This review is an overview of some relevant reports about the effects of defect engineering on the electrocatalytic water splitting performance of electrocatalysts.In detail,the types of defects,the preparation and characterization methods,and catalytic performances of electrocatalysts are presented,emphasizing the effects of the introduced defects on the electronic structures of electrocatalysts and the optimization of the intermediates'adsorption energy throughout the review.Finally,the existing challenges and personal perspectives of possible strategies for enhancing the catalytic performances of electrocatalysts are proposed.An in-depth understanding of the effects of defect engineering on the catalytic performance of electrocatalysts will light the way to design high-efficiency electrocatalysts for water splitting and other possible applications.展开更多
Background:The optimal surgical timing and clinical outcomes of ventricular septal defect(VSD)closure in neo-nates remain unclear.We aimed to evaluate the clinical outcomes of VSD closure in neonates(age≤30 days).Met...Background:The optimal surgical timing and clinical outcomes of ventricular septal defect(VSD)closure in neo-nates remain unclear.We aimed to evaluate the clinical outcomes of VSD closure in neonates(age≤30 days).Methods:We retrospectively reviewed 50 consecutive neonates who underwent VSD closure for isolated VSDs between August 2003 and June 2021.Indications for the procedure included congestive heart failure/failure to thrive and pulmonary hypertension.Major adverse events(MAEs)were defined as the composite of all-cause mortality,reoperation,persistent atrioventricular block,and significant(≥grade 2)valvular dysfunction.Results:The median age and body weight at operation were 26.0 days(interquartile range[IQR],18.8–28.3)and 3.7 kg(IQR,3.3–4.2),respectively.The median follow-up duration was 110.4 months(IQR,56.8–165.0).Seven patients required preoperative respiratory support,andfive had significant(≥grade 2)preoperative valvular dysfunction.One early mortality occurred due to irreversible cardiogenic shock;no late mortality was observed.One reopera-tion was due to hemodynamically significant residual VSD at 103.8 months postoperatively.The overall survival,freedom from reoperation,and freedom from MAE at 15-years were 98.0%,96.3%,and 94.4%,respectively.Pre-operative mechanical ventilation was associated with a longer duration of postoperative mechanical ventilation(p<0.001)and a longer length of intensive care unit stay(p<0.001).Conclusions:VSD closure with favorable outcomes without morbidities is feasible even in neonates.However,neonates requiring preoperative respiratory support may require careful postoperative management considering the long-term postoperative risks.Overall,surgical VSD closure might be indicated earlier in neonates with respiratory compromise.展开更多
Background and Objective:The most feared complication of uncorrected secundum Atrial Septal Defect(ASD)is pulmonary arterial hypertension(PAH).Pulmonary vascular resistance(PVR)is crucial in detecting precapil-lary pu...Background and Objective:The most feared complication of uncorrected secundum Atrial Septal Defect(ASD)is pulmonary arterial hypertension(PAH).Pulmonary vascular resistance(PVR)is crucial in detecting precapil-lary pulmonary hypertension(PH)to guide the need for PAH-specific therapy.There is a change in the cut-off value of PVR according to the recently updated PH guideline.How echocardiographic PVR(PVRecho)correlates to PVR by right heart catheterization(RHC)(PVRcath)according to the new guidelines has not been known.The aim of this study is to determine the reliability of PVRecho in detecting PAH in Uncorrected Ostium Secundum ASD based on the current updated guideline and to help screen the high PVR group.Methods:429 ostium secun-dum ASD in the COngenital HeARt Disease in Adult and Pulmonary Hypertension(COHARD-PH)registry was divided into three groups according to the PVR.PVRecho was calculated using Abbas’Formula and compared the its gold standard,the PVRcath.The correlation between the two methods was analyzed.The Bland-Altman plot was used to analyze the agreement between the two methods.Receiver operating characteristics(ROC)analysis was used to determine the PVRecho cut-off value for high PVR.Results:The majority of the population(63.5%)had high PVR.Female gender dominated the study population(84%).PVR_(echo) was significantly correlated with PVRcath(r=0.6225,p<0.0001).Bland-Altman plot among all groups and in subgroups analysis showed a wide range of agreement.PVRecho underestimated PVRcath 5.124 WU.In subgroup analysis,PVRecho overestimated PVRcath 0.35 WU in those with PVR<2 WU.In the second and third groups,PVR_(echo) underestimated PVRcath 0.52 and 10.77 WU,respectively.Conclusion:PVRecho is reliable in predicting high PVR in uncorrected secun-dum ASD.However,there is a wide range of agreement.PVR_(echo) cut-off value of>1.62 WU showed good dis-criminatory power in determining high PVR.展开更多
Intrinsic topological defect engineering has been proven as a promising strategy to elevate the electrocatalytic activity of carbon materials.However,the controllable construction of high-density and specific topologi...Intrinsic topological defect engineering has been proven as a promising strategy to elevate the electrocatalytic activity of carbon materials.However,the controllable construction of high-density and specific topological defects in carbon frameworks to reveal the relationship between reactivity and defect structure remains a challenging task.Herein,the intrinsic pentagon carbon sites that can favor electron overflow and enhance their binding affinity towards the intermediates of catalytic reaction are firstly presented by the work function and the p-band center calculations.To experimentally verify this,the cage-opening reaction of fullerene is proposed and utilized for synthesizing carbon quantum dots with specific pentagon configuration(CQDs-P),subsequently utilizing CQDs-P to modulate the micro-scale defect density of three-dimensional reduced graphene oxide(rGO)viaπ-πinteractions.The multiple spatial-scale rGO-conjugated CQDs-P structure simultaneously possesses abundant pentagon and edge defects as catalytic active sites and long-range-orderedπelectron delocalization system as conductive network.The defects-rich CQDs-P/rGO-4 all-carbon-based catalyst exhibits superb catalytic activity for triiodide reduction reaction with a high photoelectric conversion efficiency of 8.40%,superior to the Pt reference(7.97%).Theoretical calculations suggest that pentagon defects in the carbon frameworks can promote charge transfer and modulate the adsorption/dissociation behavior of the reaction intermediates,thus enhancing the electrocatalytic activity of the catalyst.This work confirms the role of intrinsic pentagon defects in catalytic reactions and provides a new insight into the synthesis of defects-rich carbon catalysts.展开更多
Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after packaging.Image-processing-based methods do not provide a detailed evaluation of the three-dim...Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after packaging.Image-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding wire.Therefore,a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision,which can achieve non-destructive detection of bonding wire defects is proposed.The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires.Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface,a point cloud segmentation method based on spatial surface feature detection(SFD)was proposed.SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process.Furthermore,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires.The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires.The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires,and the average accuracy of defect recognition is 96.47%,which meets the production requirements of bonding wire defect detection.展开更多
Good crystallinity can reduce the charge recombination centers caused by defects,whilst structures with strong polycondensation have high charge mobility,leading to more charge transfer to the material surface for rea...Good crystallinity can reduce the charge recombination centers caused by defects,whilst structures with strong polycondensation have high charge mobility,leading to more charge transfer to the material surface for reaction.Much effort has been put into the preparation of a highly efficient g-C_(3)N_(4) with defects to improve its application potential under the premise in high crystallinity.Hence,this review paper emphasizes the importance to balance the defect and crystallinity of g-C_(3)N_(4).In addition,detailed discussion on the relationship between defects and activity of g-C_(3)N_(4) was carried out based on its applications in environmental purification(e.g.,VOCs oxidation,NO_(x) oxidation,H_(2)O_(2) evolution,sterilization,pesticide oxidation)and energy conversion(H_(2) evolution,N_(2) fixation and CO_(2) reduction).Lastly,the challenge in developing more efficient defective g-C_(3)N_(4) photocatalytic materials is summarized.展开更多
Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the pres...Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the presence of defects within these perovskites has a substantial influence on the emission efficiency and durability of the devices.In this study,we revealed a synergistic passivation mechanism on perovskite films by using a dual-functional compound of potassium bromide.The dual functional potassium bromide on the one hand can passivate the defects of halide vacancies with bromine anions and,on the other hand,can screen the charged defects at the grain boundaries with potassium cations.This approach effectively reduces the probability of carriers quenching resulting from charged defects capture and consequently enhances the radiative recombination efficiency of perovskite thin films,leading to a significant enhancement of photoluminescence quantum yield to near-unity values(95%).Meanwhile,the potassium bromide treatment promoted the growth of homogeneous and smooth film,facilitating the charge carrier injection in the devices.Consequently,the perovskite light-emitting diodes based on this strategy achieve a maximum external quantum efficiency of~21%and maximum luminance of~60,000 cd m^(-2).This work provides a deeper insight into the passivation mechanism of ionic compound additives in perovskite with the solution method.展开更多
Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal depende...Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal dependence,and noise.Therefore,methodologies for data augmentation and conversion of time series data into images for analysis have been studied.This paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to noise.The method of data augmentation is set as the addition of noise.It involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the model.In addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into images.It enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the data.For anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat maps.It allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies occur.The performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to images.Additionally,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training time.The proposed method can provide an important springboard for research in the field of anomaly detection using time series data.Besides,it helps solve problems such as analyzing complex patterns in data lightweight.展开更多
基金the support of the Australia Research Council (ARC) through the Discovery Project (DP230101040)the Natural Science Foundation of Shandong Province (ZR2022QB139, No. ZR2020KF025)+3 种基金the Starting Research Fund (Grant No. 20210122) from the Ludong Universitythe Natural Science Foundation of China (12274190) from the Ludong Universitythe support of the Shandong Youth Innovation Team Introduction and Education Programthe Special Fund for Taishan Scholars Project (No. tsqn202211186) in Shandong Province。
文摘Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.
基金National Natural Science Foundation of China,No.U20A20403This study was conducted in accordance with the Animal Ethics Committee of the Institute of Antler Science and Product Technology,Changchun Sci-Tech University(AEC No:CKARI202309).
文摘BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.
基金This study was approved by the Siriraj Institutional Review Board(SIRB),Faculty of Medicine Siriraj Hospital,Mahidol University(COA no.Si 760/2021).The need for consent was waived by the board due to its retrospective nature and as all personal identifying information was obliterated.The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.
文摘Background:Atrial septal defect(ASD)is a common form of adult congenital heart disease that can lead to long-term adverse outcomes if left untreated.Early closure of ASD has been associated with excellent outcomes and lower complication rates.However,there is limited evidence regarding the prognosis of ASD closure in older adults.This study aims to evaluate the mortality rates in older ASD patients with and without closure.Methods:A retrospective cohort study was conducted on patients aged 40 years or older with ASD between 2001 and 2017.Patients were followed up to assess all-cause mortality.Univariable and multivariable analyses were performed to identify the predictors of mortality.A p-value of<0.05 was considered statistically significant.Results:The cohort consisted of 450 patients(mean age 56.6±10.4 years,77.3%female),with 66%aged between 40 and 60 years,and 34%over 60 years.Within the cohort,299 underwent ASD closure(201 with transcatheter and 98 with surgical closure).During the median follow-up duration of 7.9 years,51 patients died.The unadjusted cumulative 10-year rate of mortality was 3%in patients with ASD closure,and 28%in patients without ASD closure(log-rank p<0.001).Multivariable analysis revealed that age(hazard ratio[HR]1.04,95%confidence interval[CI]1.006–1.06,p=0.01),NYHA class(HR 2.75,95%CI 1.63–4.62,p<0.001),blood urea nitrogen(BUN)(HR 1.07,95%CI 1.03–1.12,p<0.001),right ventricular systolic pressure(RVSP)(HR 1.07,95%CI 1.003–1.04,p=0.01),and lack of ASD closure(HR 15.12,95%CI 5.63–40.59,p<0.001)were independently associated with mortality.Conclusion:ASD closure demonstrated favorable outcomes in older patients.Age,NYHA class,BUN,RVSP,and lack of ASD closure were identified as independent factors linked to mortality in this population.
基金supported by the China Scholarship Council (CSC) (No.202206020149)the Academic Excellence Foundation of BUAA for PhD Students,the Funding Project of Science and Technology on Reliability and Environmental Engineering Laboratory (No.6142004210106).
文摘Sintered silver nanoparticles(AgNPs)arewidely used in high-power electronics due to their exceptional properties.However,the material reliability is significantly affected by various microscopic defects.In this work,the three primary micro-defect types at potential stress concentrations in sintered AgNPs are identified,categorized,and quantified.Molecular dynamics(MD)simulations are employed to observe the failure evolution of different microscopic defects.The dominant mechanisms responsible for this evolution are dislocation nucleation and dislocation motion.At the same time,this paper clarifies the quantitative relationship between the tensile strain amount and the failure mechanism transitions of the three defect types by defining key strain points.The impact of defect types on the failure process is also discussed.Furthermore,traction-separation curves extracted from microscopic defect evolutions serve as a bridge to connect the macro-scale model.The validity of the crack propagation model is confirmed through tensile tests.Finally,we thoroughly analyze how micro-defect types influence macro-crack propagation and attempt to find supporting evidence from the MD model.Our findings provide a multi-perspective reference for the reliability analysis of sintered AgNPs.
基金financial grants from DST,India,through the projects DST/TSG/PT/2009/23,DST/TMD/ICMAP/2K20/03,and DST/CRG/2019/002164,Deity,India,no.5(9)/2012-NANO(Vol.II)the Max-Planck-Gesellschaft IGSTC/MPG/PG(PKI)/2011A/48 and MHRD,India,through the SPARC project SPARC/2018-2019/P1097/SLPMRF(Prime Minister's Research Fellowship),Ministry of Education,Government of India for providing funds to carry out this research.
文摘The rapid advancement of halide-based hybrid perovskite materials has garnered significant research attention,particularly in the domain of photovoltaic technology.Owing to their exceptional optoelec-tronic properties,they demonstrated power conversion efficiency(PcE)of over 25%in single junction solar cells.Despite the notable progress in PCE over the past decade,the inherent high defect density pre-senting in perovskite materials gives rise to several loss mechanisms and associated ion migration in per-ovskite solar cells(PsCs)during operational conditions.These factors collectively contribute to a significant stability challenge in PsCs,placing their longevity far behind for commercialization.While numerous reports have explored defects,ion migration,and their impacts on device performance,a com-prehensive correlation between the types of defects and the degradation kinetics of perovskite materials and PsCs has been lacking.In this context,this review aims to provide a comprehensive overview of the origins of defects and ion migration,emphasizing their correlation with the degradation kinetics of per-ovskite materials and PsCs,leveraging reliable characterization techniques.Furthermore,these charac-terization techniques are intended to comprehend loss mechanisms by different passivation approaches to enhance the durability and PCE of PSCs.
基金supported by the National Natural Science Foundation of China(Nos.51673199,51972301,51677176)the Youth Innovation Promotion Association of CAS(2015148,Y201940)+2 种基金the Youth Innovation Foundation of DICP(ZZBS201615,ZZBS201708)the Dalian Outstanding Young Scientific Talent(2018RJ03)the National Key Research and Development Project(2019YFA0705600)。
文摘Niobium pentoxide(Nb_(2)O_(5))is deemed one of the promising anode materials for lithium-ion batteries(LIBs)for its outstanding intrinsic fast Li-(de)intercalation kinetics.The specific capacity,however,is still limited,because the(de)intercalation of excessive Li-ions brings the undesired stress to damage Nb_(2)O_(5) crystals.To increase the capacity of Nb_(2)O_(5) and alleviate the lattice distortion caused by stress,numerous homogeneous H-and M-phases junction interfaces were proposed to produce coercive stress within theNb_(2)O_(5)crystals.Such interfaces bring about rich oxygen vacancies with structural shrinkage tendency,which pre-generate coercive stress to resist the expansion stress caused by excessive Li-ions intercalation.Therefore,the synthesized Nb_(2)O_(5) achieves the highest lithium storage capacity of 315 mA h g−1 to date,and exhibits high-rate performance(118 mA h g^(-1) at 20 C)as well as excellent cycling stability(138 mA h g^(-1) at 10 C after 600 cycles).
文摘Introduction: Ventricular septal defect (VSD) is the most common congenital heart disease of all congenital heart defects. The aim of this study was to investigate the echographic, therapeutic and evolutionary aspects of ventricular septal defects (VSD) in the general cardiology department of the Hôpital National Ignace Deen. Methods: A retrospective data collection was carried out from January 2018 to December 2023 including 85 cases of isolated IVC was performed. The variables studied were epidemiological, clinical, paraclinical, therapeutic and evolutionary. Results: Of the 320 patients seen during the study period for congenital heart disease, 85 (26.556%) were isolated IVCs. Age at diagnosis ranged from 3 months to 16 years, with an average age of 3.59 years. The most represented ethnic group was the Fulani (50.58%). The 8.24% came from consanguineous marriage versus 22.35%. 91.76% of children had a history of bronchitis. The most common clinical signs found were systolic murmur (90.58%), growth retardation (51.76%). Only 4 cases (4.70%) had a malformation associated with IVC represented by DiGeorges disease (2.35%) and trisomy 21 (2.35%). Nearly half the patients had type IIb VIC (44.71%). The other half were represented by type 1 (18.82%), type IIa (20%), type III (10.59%) and type IV (5.88%). According to site more than two-thirds of VICs (71.64%) were perimembranous in location, followed by infundibular (16.47%) and muscular (11.76%) VICs. In our study 55.29% presented an indication for both surgical intervention and medical treatment, while 16.47% required only medical treatment. In contrast, 28.23% were placed under exclusive surveillance. Of the 47 patients for whom surgery was indicated, 29 (61.17%) underwent surgical repair, while 18 (38.83%) were awaiting confirmation for surgery. Conclusion: VIC is the most common congenital heart disease. An early detection strategy and the establishment of specialized centers could improve the outcome of these children.
基金Funded by the Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi (No. 2020L0628)the Taiyuan Institute of Technology Scientific Research Initial Funding (No. 2022KJ072)+2 种基金the Program for the (Reserved) Discipline Leaders of Taiyuan Institute of Technologythe Fundamental Research Funds for the Central Universities (Nos. 2017TS004, 2017TS006, and GK201704005)Supported by HZWTECH for providing computational facilities
文摘In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2) and FeS_(2),first-principles calculation method was used to investigate the alloys.The calculated results of materials without vacancy are consistent with those reported in the literatures,while the results of materials with vacancy defect were different from those of literatures due to the difference vacancy concentration.The Co vacancy defect hardly changes the half-metallic characteristic of CoS_(2).The Fe vacancy defect changes FeS_(2) from semiconductor to half-metal,and the bottom of the spin-down conduction band changes from the p orbital state of S to the d(t_(2g))orbital state of Fe,while the top of the valence band remains the d orbital d(eg)state of Fe.The half-metallic Co vacancy defects of CoS_(2) and Fe vacancy defects of FeS_(2) are expected to be used in spintronic devices.S vacancy defects make both CoS_(2) and FeS_(2) metallic.Both the Co and S vacancy defects lead to the decrease of the magnetic moment of CoS_(2),while both the Fe and S vacancy defects lead to the obvious magnetic property of FeS_(2).Vacancy defects enhance the absorption coefficient of infrared band and long band of visible light obviously,and produce obvious red shift phenomenon,which is expected to be used in photoelectric devices.
基金supported in part by the National Natural Science Foundation of China under Grants 32171909,51705365,52205254The Guangdong Basic and Applied Basic Research Foundation under Grants 2020B1515120050,2023A1515011255+2 种基金The Guangdong Key R&D projects under Grant 2020B0404030001the Scientific Research Projects of Universities in Guangdong Province under Grant 2020KCXTD015The Ji Hua Laboratory Open Project under Grant X220931UZ230.
文摘As computer technology continues to advance,factories have increasingly higher demands for detecting defects.However,detecting defects in a plant environment remains a challenging task due to the presence of complex backgrounds and defects of varying shapes and sizes.To address this issue,this paper proposes YOLO-DD,a defect detectionmodel based on YOLOv5 that is effective and robust.To improve the feature extraction process and better capture global information,the vanilla YOLOv5 is augmented with a new module called Relative-Distance-Aware Transformer(RDAT).Additionally,an Information Gap Filling Strategy(IGFS)is proposed to improve the fusion of features at different scales.The classic lightweight attention mechanism Squeeze-and-Excitation(SE)module is also incorporated into the neck section to enhance feature expression and improve the model’s performance.Experimental results on the NEU-DET dataset demonstrate that YOLO-DDachieves competitive results compared to state-of-the-art methods,with a 2.0% increase in accuracy compared to the original YOLOv5,achieving 82.41% accuracy and38.25FPS(framesper second).Themodel is also testedon a self-constructed fabric defect dataset,and the results show that YOLO-DD is more stable and has higher accuracy than the original YOLOv5,demonstrating its stability and generalization ability.The high efficiency of YOLO-DD enables it to meet the requirements of industrial high accuracy and real-time detection.
基金This research was supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2022R1I1A3063493).
文摘Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.
基金supported by the National Natural Science Foundation of China(51805078)Project of National Key Laboratory of Advanced Casting Technologies(CAT2023-002)the 111 Project(B16009).
文摘Segment Anything Model(SAM)is a cutting-edge model that has shown impressive performance in general object segmentation.The birth of the segment anything is a groundbreaking step towards creating a universal intelligent model.Due to its superior performance in general object segmentation,it quickly gained attention and interest.This makes SAM particularly attractive in industrial surface defect segmentation,especially for complex industrial scenes with limited training data.However,its segmentation ability for specific industrial scenes remains unknown.Therefore,in this work,we select three representative and complex industrial surface defect detection scenarios,namely strip steel surface defects,tile surface defects,and rail surface defects,to evaluate the segmentation performance of SAM.Our results show that although SAM has great potential in general object segmentation,it cannot achieve satisfactory performance in complex industrial scenes.Our test results are available at:https://github.com/VDT-2048/SAM-IS.
基金supported by the Natural Science Foundation of Heilongjiang Province(Grant Number:LH2021F002).
文摘With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.
基金National Natural Science Foundation of China,Grant/Award Number:52271200Scientific and Technological Innovation Foundation of Foshan,Grant/Award Number:BK20BE009+1 种基金the Fundamental Research Funds for the Central Universities,Grant/Award Number:FRF-TP-18-079A1Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2020A1515110460,ORCID:http://orcid.org/0000-0002-0870-2248。
文摘Electrocatalytic water splitting seems to be an efficient strategy to deal with increasingly serious environmental problems and energy crises but still suffers from the lack of stable and efficient electrocatalysts.Designing practical electrocatalysts by introducing defect engineering,such as hybrid structure,surface vacancies,functional modification,and structural distortions,is proven to be a dependable solution for fabricating electrocatalysts with high catalytic activities,robust stability,and good practicability.This review is an overview of some relevant reports about the effects of defect engineering on the electrocatalytic water splitting performance of electrocatalysts.In detail,the types of defects,the preparation and characterization methods,and catalytic performances of electrocatalysts are presented,emphasizing the effects of the introduced defects on the electronic structures of electrocatalysts and the optimization of the intermediates'adsorption energy throughout the review.Finally,the existing challenges and personal perspectives of possible strategies for enhancing the catalytic performances of electrocatalysts are proposed.An in-depth understanding of the effects of defect engineering on the catalytic performance of electrocatalysts will light the way to design high-efficiency electrocatalysts for water splitting and other possible applications.
基金This retrospective study was approved by the Seoul National University Hospital Institutional Review Board(approval number:H-2106-179-1230).The requirement for informed consent was waived.
文摘Background:The optimal surgical timing and clinical outcomes of ventricular septal defect(VSD)closure in neo-nates remain unclear.We aimed to evaluate the clinical outcomes of VSD closure in neonates(age≤30 days).Methods:We retrospectively reviewed 50 consecutive neonates who underwent VSD closure for isolated VSDs between August 2003 and June 2021.Indications for the procedure included congestive heart failure/failure to thrive and pulmonary hypertension.Major adverse events(MAEs)were defined as the composite of all-cause mortality,reoperation,persistent atrioventricular block,and significant(≥grade 2)valvular dysfunction.Results:The median age and body weight at operation were 26.0 days(interquartile range[IQR],18.8–28.3)and 3.7 kg(IQR,3.3–4.2),respectively.The median follow-up duration was 110.4 months(IQR,56.8–165.0).Seven patients required preoperative respiratory support,andfive had significant(≥grade 2)preoperative valvular dysfunction.One early mortality occurred due to irreversible cardiogenic shock;no late mortality was observed.One reopera-tion was due to hemodynamically significant residual VSD at 103.8 months postoperatively.The overall survival,freedom from reoperation,and freedom from MAE at 15-years were 98.0%,96.3%,and 94.4%,respectively.Pre-operative mechanical ventilation was associated with a longer duration of postoperative mechanical ventilation(p<0.001)and a longer length of intensive care unit stay(p<0.001).Conclusions:VSD closure with favorable outcomes without morbidities is feasible even in neonates.However,neonates requiring preoperative respiratory support may require careful postoperative management considering the long-term postoperative risks.Overall,surgical VSD closure might be indicated earlier in neonates with respiratory compromise.
文摘Background and Objective:The most feared complication of uncorrected secundum Atrial Septal Defect(ASD)is pulmonary arterial hypertension(PAH).Pulmonary vascular resistance(PVR)is crucial in detecting precapil-lary pulmonary hypertension(PH)to guide the need for PAH-specific therapy.There is a change in the cut-off value of PVR according to the recently updated PH guideline.How echocardiographic PVR(PVRecho)correlates to PVR by right heart catheterization(RHC)(PVRcath)according to the new guidelines has not been known.The aim of this study is to determine the reliability of PVRecho in detecting PAH in Uncorrected Ostium Secundum ASD based on the current updated guideline and to help screen the high PVR group.Methods:429 ostium secun-dum ASD in the COngenital HeARt Disease in Adult and Pulmonary Hypertension(COHARD-PH)registry was divided into three groups according to the PVR.PVRecho was calculated using Abbas’Formula and compared the its gold standard,the PVRcath.The correlation between the two methods was analyzed.The Bland-Altman plot was used to analyze the agreement between the two methods.Receiver operating characteristics(ROC)analysis was used to determine the PVRecho cut-off value for high PVR.Results:The majority of the population(63.5%)had high PVR.Female gender dominated the study population(84%).PVR_(echo) was significantly correlated with PVRcath(r=0.6225,p<0.0001).Bland-Altman plot among all groups and in subgroups analysis showed a wide range of agreement.PVRecho underestimated PVRcath 5.124 WU.In subgroup analysis,PVRecho overestimated PVRcath 0.35 WU in those with PVR<2 WU.In the second and third groups,PVR_(echo) underestimated PVRcath 0.52 and 10.77 WU,respectively.Conclusion:PVRecho is reliable in predicting high PVR in uncorrected secun-dum ASD.However,there is a wide range of agreement.PVR_(echo) cut-off value of>1.62 WU showed good dis-criminatory power in determining high PVR.
基金partly supported by the National Natural Science Foundation of China(22078052)the National Key R&D Program of China(2022YFB4101602)the Fundamental Research Funds for the Central Universities(DUT22LAB612)。
文摘Intrinsic topological defect engineering has been proven as a promising strategy to elevate the electrocatalytic activity of carbon materials.However,the controllable construction of high-density and specific topological defects in carbon frameworks to reveal the relationship between reactivity and defect structure remains a challenging task.Herein,the intrinsic pentagon carbon sites that can favor electron overflow and enhance their binding affinity towards the intermediates of catalytic reaction are firstly presented by the work function and the p-band center calculations.To experimentally verify this,the cage-opening reaction of fullerene is proposed and utilized for synthesizing carbon quantum dots with specific pentagon configuration(CQDs-P),subsequently utilizing CQDs-P to modulate the micro-scale defect density of three-dimensional reduced graphene oxide(rGO)viaπ-πinteractions.The multiple spatial-scale rGO-conjugated CQDs-P structure simultaneously possesses abundant pentagon and edge defects as catalytic active sites and long-range-orderedπelectron delocalization system as conductive network.The defects-rich CQDs-P/rGO-4 all-carbon-based catalyst exhibits superb catalytic activity for triiodide reduction reaction with a high photoelectric conversion efficiency of 8.40%,superior to the Pt reference(7.97%).Theoretical calculations suggest that pentagon defects in the carbon frameworks can promote charge transfer and modulate the adsorption/dissociation behavior of the reaction intermediates,thus enhancing the electrocatalytic activity of the catalyst.This work confirms the role of intrinsic pentagon defects in catalytic reactions and provides a new insight into the synthesis of defects-rich carbon catalysts.
基金Intelligent Manufacturing and Robot Technology Innovation Project of Beijing Municipal Commission of Science and Technology and Zhongguancun Science and Technology Park Management Committee,Grant/Award Number:Z221100000222016National Natural Science Foundation of China,Grant/Award Number:62076014Beijing Municipal Education Commission and Beijing Natural Science Foundation,Grant/Award Number:KZ202010005004。
文摘Non-destructive detection of wire bonding defects in integrated circuits(IC)is critical for ensuring product quality after packaging.Image-processing-based methods do not provide a detailed evaluation of the three-dimensional defects of the bonding wire.Therefore,a method of 3D reconstruction and pattern recognition of wire defects based on stereo vision,which can achieve non-destructive detection of bonding wire defects is proposed.The contour features of bonding wires and other electronic components in the depth image is analysed to complete the 3D reconstruction of the bonding wires.Especially to filter the noisy point cloud and obtain an accurate point cloud of the bonding wire surface,a point cloud segmentation method based on spatial surface feature detection(SFD)was proposed.SFD can extract more distinct features from the bonding wire surface during the point cloud segmentation process.Furthermore,in the defect detection process,a directional discretisation descriptor with multiple local normal vectors is designed for defect pattern recognition of bonding wires.The descriptor combines local and global features of wire and can describe the spatial variation trends and structural features of wires.The experimental results show that the method can complete the 3D reconstruction and defect pattern recognition of bonding wires,and the average accuracy of defect recognition is 96.47%,which meets the production requirements of bonding wire defect detection.
基金supported by the National Natural Science Foundation of China(Grant No.52370109)China Postdoctoral Science Foundation(2022M710830)+4 种基金Venture and Innovation Support Program for Chongqing Overseas Returnees(cx2022005)the Natural Science Foun-dation Project of CQ CSTC(CSTB2022NSCQ-MSX1267)Research Project of Chongqing Education Commission Foundation(KJQN201800826)Science and Technology Research Program of Chongqing Municipal Education Commission of China(KJZD-K202100801)Post-doctoral Program Funded by Chongqing,and Chongqing Technology and Business University,China(CXQT21023).
文摘Good crystallinity can reduce the charge recombination centers caused by defects,whilst structures with strong polycondensation have high charge mobility,leading to more charge transfer to the material surface for reaction.Much effort has been put into the preparation of a highly efficient g-C_(3)N_(4) with defects to improve its application potential under the premise in high crystallinity.Hence,this review paper emphasizes the importance to balance the defect and crystallinity of g-C_(3)N_(4).In addition,detailed discussion on the relationship between defects and activity of g-C_(3)N_(4) was carried out based on its applications in environmental purification(e.g.,VOCs oxidation,NO_(x) oxidation,H_(2)O_(2) evolution,sterilization,pesticide oxidation)and energy conversion(H_(2) evolution,N_(2) fixation and CO_(2) reduction).Lastly,the challenge in developing more efficient defective g-C_(3)N_(4) photocatalytic materials is summarized.
基金supported by the Science and Technology Development Fund,Macao SAR(File no.FDCT-0082/2021/A2,0010/2022/AMJ,006/2022/ALC)UM's research fund(File no.MYRG2022-00241-IAPME,MYRGCRG2022-00009-FHS)+2 种基金the research fund from Wuyi University(EF38/IAPME-XGC/2022/WYU)the Natural Science Foundation of China(61935017,62175268)Science,Technology and Innovation Commission of Shenzhen Municipality(Project Nos.JCYJ20220530113015035,JCYJ20210324120204011,and KQTD2015071710313656).
文摘Metal halide perovskites,particularly the quasi-two-dimensional perovskite subclass,have exhibited considerable potential for next-generation electroluminescent materials for lighting and display.Nevertheless,the presence of defects within these perovskites has a substantial influence on the emission efficiency and durability of the devices.In this study,we revealed a synergistic passivation mechanism on perovskite films by using a dual-functional compound of potassium bromide.The dual functional potassium bromide on the one hand can passivate the defects of halide vacancies with bromine anions and,on the other hand,can screen the charged defects at the grain boundaries with potassium cations.This approach effectively reduces the probability of carriers quenching resulting from charged defects capture and consequently enhances the radiative recombination efficiency of perovskite thin films,leading to a significant enhancement of photoluminescence quantum yield to near-unity values(95%).Meanwhile,the potassium bromide treatment promoted the growth of homogeneous and smooth film,facilitating the charge carrier injection in the devices.Consequently,the perovskite light-emitting diodes based on this strategy achieve a maximum external quantum efficiency of~21%and maximum luminance of~60,000 cd m^(-2).This work provides a deeper insight into the passivation mechanism of ionic compound additives in perovskite with the solution method.
基金This research was financially supported by the Ministry of Trade,Industry,and Energy(MOTIE),Korea,under the“Project for Research and Development with Middle Markets Enterprises and DNA(Data,Network,AI)Universities”(AI-based Safety Assessment and Management System for Concrete Structures)(ReferenceNumber P0024559)supervised by theKorea Institute for Advancement of Technology(KIAT).
文摘Time-series data provide important information in many fields,and their processing and analysis have been the focus of much research.However,detecting anomalies is very difficult due to data imbalance,temporal dependence,and noise.Therefore,methodologies for data augmentation and conversion of time series data into images for analysis have been studied.This paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to noise.The method of data augmentation is set as the addition of noise.It involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the model.In addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into images.It enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the data.For anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat maps.It allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies occur.The performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to images.Additionally,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training time.The proposed method can provide an important springboard for research in the field of anomaly detection using time series data.Besides,it helps solve problems such as analyzing complex patterns in data lightweight.