Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,an...Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.展开更多
In integrated circuit(IC)manufacturing,fast,nondestructive,and precise detection of defects in patterned wafers,realized by bright-field microscopy,is one of the critical factors for ensuring the final performance and...In integrated circuit(IC)manufacturing,fast,nondestructive,and precise detection of defects in patterned wafers,realized by bright-field microscopy,is one of the critical factors for ensuring the final performance and yields of chips.With the critical dimensions of IC nanostructures continuing to shrink,directly imaging or classifying deep-subwavelength defects by bright-field microscopy is challenging due to the well-known diffraction barrier,the weak scattering effect,and the faint correlation between the scattering cross-section and the defect morphology.Herein,we propose an optical far-field inspection method based on the form-birefringence scattering imaging of the defective nanostructure,which can identify and classify various defects without requiring optical super-resolution.The technique is built upon the principle of breaking the optical form birefringence of the original periodic nanostructures by the defect perturbation under the anisotropic illumination modes,such as the orthogonally polarized plane waves,then combined with the high-order difference of far-field images.We validated the feasibility and effectiveness of the proposed method in detecting deep subwavelength defects through rigid vector imaging modeling and optical detection experiments of various defective nanostructures based on polarization microscopy.On this basis,an intelligent classification algorithm for typical patterned defects based on a dual-channel AlexNet neural network has been proposed,stabilizing the classification accuracy ofλ/16-sized defects with highly similar features at more than 90%.The strong classification capability of the two-channel network on typical patterned defects can be attributed to the high-order difference image and its transverse gradient being used as the network’s input,which highlights the polarization modulation difference between different patterned defects more significantly than conventional bright-field microscopy results.This work will provide a new but easy-to-operate method for detecting and classifying deep-subwavelength defects in patterned wafers or photomasks,which thus endows current online inspection equipment with more missions in advanced IC manufacturing.展开更多
Phenanthrene(Phe)is one of the common polycyclic aromatic hydrocarbons in the environment,and recent studies show that it can cause cardiac developmental toxicity and immunotoxicity.However,it is still unknown whether...Phenanthrene(Phe)is one of the common polycyclic aromatic hydrocarbons in the environment,and recent studies show that it can cause cardiac developmental toxicity and immunotoxicity.However,it is still unknown whether it can affect the hematopoietic development in aquatic organisms.To address this question,zebrafish(Danio rerio)were chronically exposed to Phe at different concentrations.We found that Phe caused structural damage to the renal tubules in the kidney,induced malformed erythrocytes in peripheral blood,and decreased the proportion of myeloid cells in adult zebrafish,suggesting possible negative impacts that Phe posed to hematopoietic development.Then,using in situ hybridization technology,we found that Phe decreased the expression of primitive hematopoietic marker genes,specifically gata1 and pu.1,accompanied by an obstruction of primitive erythrocyte circulation.Furthermore,Phe impaired definitive hematopoiesis,increased aberrations of the transient hematopoietic site(PBI),and reduced the generation of hematopoietic stem cells,ultimately influencing the number of erythrocytes and myeloid cells.The findings suggested that Phe could induce hematopoietic toxicity in zebrafish embryos and pose unknown ecological risks.展开更多
Selective catalytic reduction of NO_(x) with CO(CO-SCR)is a process that purifies both NO and CO pollutants through a catalytic reaction.Specifically,the cleavage of NO on the catalyst surface is crucial for promoting...Selective catalytic reduction of NO_(x) with CO(CO-SCR)is a process that purifies both NO and CO pollutants through a catalytic reaction.Specifically,the cleavage of NO on the catalyst surface is crucial for promoting the reaction.During the reaction,the presence of oxygen vacancies can extract oxygen from NO,thereby facilitating the cleavage of NO on the catalyst surface.Thus,the formation of oxygen vacancies is key to accelerating the CO-SCR reaction,with different types of oxygen vacancies being more conducive to their generation.In this study,Rh/CeCuO_(x) catalysts were synthesized using the co-crystallization and impregnation methods,and asymmetric oxygen vacancies were induced through hydrogen thermal treatment.This structuralmodification was aimed at regulating the behavior of NO on the catalyst surface.The Rh/Ce0.95Cu0.05O_(x)-H_(2) catalyst exhibited the best performance in CO-SCR,achieving above 90%NO conversion at 162℃.Various characterization techniques showed that the H_(2) treatment effectively reduced some of the CuO and Rh_(2)O_(3),creating asymmetric oxygen vacancies that accelerated the cleavage of NO on the catalyst surface,rather than forming difficult-to-decompose nitrates.This study offers a novel approach to constructing oxygen vacancies in new CO-SCR catalysts.展开更多
As the global population ages,osteoporotic bone fractures leading to bone defects are increasingly becoming a significant challenge in the field of public health.Treating this disease faces many challenges,especially ...As the global population ages,osteoporotic bone fractures leading to bone defects are increasingly becoming a significant challenge in the field of public health.Treating this disease faces many challenges,especially in the context of an imbalance between osteoblast and osteoclast activities.Therefore,the development of new biomaterials has become the key.This article reviews various design strategies and their advantages and disadvantages for biomaterials aimed at osteoporotic bone defects.Overall,current research progress indicates that innovative design,functionalization,and targeting of materials can significantly enhance bone regeneration under osteoporotic conditions.By comprehensively considering biocompatibility,mechanical properties,and bioactivity,these biomaterials can be further optimized,offering a range of choices and strategies for the repair of osteoporotic bone defects.展开更多
Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,re...Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.展开更多
Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the e...Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the electronic structure of active sites.This optimization influences the adsorption energy of intermediates,thereby mitigating reaction energy barriers,altering paths,enhancing selectivity,and ultimately improving the catalytic efficiency of electrocatalysts.To elucidate the impact of defects on the electrocatalytic process,we comprehensively outline the roles of various point defects,their synthetic methodologies,and characterization techniques.Importantly,we consolidate insights into the relationship between point defects and catalytic activity for hydrogen/oxygen evolution and CO_(2)/O_(2)/N_(2) reduction reactions by integrating mechanisms from diverse reactions.This underscores the pivotal role of point defects in enhancing catalytic performance.At last,the principal challenges and prospects associated with point defects in current electrocatalysts are proposed,emphasizing their role in advancing the efficiency of electrochemical energy storage and conversion materials.展开更多
To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,t...To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.展开更多
High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,inclu...High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported before.Herein,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese doping.Due to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese ions.The HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.展开更多
Rechargeable magnesium batteries(RMBs)have been considered a promising“post lithium-ion battery”system to meet the rapidly increasing demand of the emerging electric vehicle and grid energy storage market.However,th...Rechargeable magnesium batteries(RMBs)have been considered a promising“post lithium-ion battery”system to meet the rapidly increasing demand of the emerging electric vehicle and grid energy storage market.However,the sluggish diffusion kinetics of bivalent Mg^(2+)in the host material,related to the strong Coulomb effect between Mg^(2+)and host anion lattices,hinders their further development toward practical applications.Defect engineering,regarded as an effective strategy to break through the slow migration puzzle,has been validated in various cathode materials for RMBs.In this review,we first thoroughly understand the intrinsic mechanism of Mg^(2+)diffusion in cathode materials,from which the key factors affecting ion diffusion are further presented.Then,the positive effects of purposely introduced defects,including vacancy and doping,and the corresponding strategies for introducing various defects are discussed.The applications of defect engineering in cathode materials for RMBs with advanced electrochemical properties are also summarized.Finally,the existing challenges and future perspectives of defect engineering in cathode materials for the overall high-performance RMBs are described.展开更多
Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it cha...Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective samples.Additionally,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective regions.This paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these challenges.The network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation network.Specifically,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information effectively.In order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target detection.Moreover,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter number.Finally,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and PVEL-S.SolarCells and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon dataset.Experimental results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.展开更多
The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and...The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and widths were TIG welded,and the microstructures,cracks morphology,and precipitated phases were analyzed using optical microscope,scanning electron microscope,transmission electron microscope,and energy dispersive X-ray spectrometer.The results reveal that the dimensions of casting defects significantly affect the weldability of K4951.Deep defects(greater than 2 mm)lead to rapid crack propagation,while wider defects can moderate the propagation process of cracks.Elemental segregation and the formation of precipitated phases,such as MC carbides,are observed in the fusion zone,contributing to welding cracks.An optimal groove aspect ratio(depth-to-width)between 0.2 and 0.5 minimizes crack formation tendency and enhances tensile strength,resulting in a mixed brittle-ductile fracture mode of joint after high-temperature tensile testing.展开更多
Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simul...Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simultaneously control the growth of perovskite crystals and passivate defects.Here,4-(trifluoromethyl)benzoic anhydride(4-TBA)composed of benzene rings functionalized with carbonyl and trifluoromethyl groups was used as an example additive to study the characteristics of additives used for producing high-quality perovskites and controlling their surface properties.The interaction between4-TBA and perovskite precursor materials was investigated using density functional theory(DFT)simulations.The electron-rich carbonyl group efficiently passivated the under-coordinated lead-ion defects.Additionally,hydrogen bonding between trifluoromethyl and organic cations prevents the generation of cation vacancies.Because of its intrinsic hydrophobicity,the trifluoromethyl group simultaneously improves the moisture and heat stability of the film.4-TBA serves as a universal modifier for various perovskite compositions.The power conversion efficiency(PCE)of inverted perovskite solar cells(PSCs)based on methylammonium(MA)with 4-TBA was improved from 16.15%to 19.28%.Similarly,the PCE of inverted PSCs based on a cesium formamidinium MA(CsFAMA)perovskite film increased from20.72%to 23.58%,upon addition of 4-TBA.Furthermore,the moisture and thermal stability of 4-TBAtreated films and devices was significantly enhanced,along with prolonged device performance.Our work provides guidance on selecting the structure and functional groups that are essential for surface defect passivation and the production of high-quality perovskites.展开更多
BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of th...BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.展开更多
The accepted doping ion in Ti^(4+)-site of PbZr_(y)Ti_(1–y)O_(3)(PZT)-based piezoelectric ceramics is a well-known method to increase mechanical quality factor(Q_(m)),since the acceptor coupled by oxygen vacancy beco...The accepted doping ion in Ti^(4+)-site of PbZr_(y)Ti_(1–y)O_(3)(PZT)-based piezoelectric ceramics is a well-known method to increase mechanical quality factor(Q_(m)),since the acceptor coupled by oxygen vacancy becomes defect dipole,which prevents the domain rotation.In this field,a serious problem is that generally,Qm decreases as the temperature(T)increases,since the oxygen vacancies are decoupled from the defect dipoles.In this work,Q_(m) of Pb_(0.95)Sr_(0.05)(Zr_(0.53)Ti_(0.47))O_(3)(PSZT)ceramics doped by 0.40%Fe_(2)O_(3)(in mole)abnormally increases as T increases,of which the Qm and piezoelectric coefficient(d_(33))at room temperature and Curie temperature(TC)are 507,292 pC/N,and 345℃,respectively.The maximum Qm of 824 was achieved in the range of 120–160℃,which is 62.52%higher than that at room temperature,while the dynamic piezoelectric constant(d_(31))was just slightly decreased by 3.85%.X-ray diffraction(XRD)and piezoresponse force microscopy results show that the interplanar spacing and the fine domains form as temperature increases,and the thermally stimulated depolarization current shows that the defect dipoles are stable even the temperature up to 240℃.It can be deduced that the aggregation of oxygen vacancies near the fine domains and defect dipole can be stable up to 240℃,which pins domain rotation,resulting in the enhanced Q_(m) with the increasing temperature.These results give a potential path to design high Q_(m) at high temperature.展开更多
Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects,...Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.展开更多
The service life of internal combustion engines is significantly influenced by surface defects in cylinder liners.To address the limitations of traditional detection methods,we propose an enhanced YOLOv8 model with Sw...The service life of internal combustion engines is significantly influenced by surface defects in cylinder liners.To address the limitations of traditional detection methods,we propose an enhanced YOLOv8 model with Swin Transformer as the backbone network.This approach leverages Swin Transformer's multi-head self-attention mechanism for improved feature extraction of defects spanning various scales.Integrated with the YOLOv8 detection head,our model achieves a mean average precision of 85.1%on our dataset,outperforming baseline methods by 1.4%.The model's effectiveness is further demonstrated on a steel-surface defect dataset,indicating its broad applicability in industrial surface defect detection.Our work highlights the potential of combining Swin Transformer and YOLOv8 for accurate and efficient defect detection.展开更多
The accuracy and reliability of non-destructive testing(NDT)approaches in detecting interior corrosion problems are critical,yet research in this field is limited.This work describes a novel way to monitor the structu...The accuracy and reliability of non-destructive testing(NDT)approaches in detecting interior corrosion problems are critical,yet research in this field is limited.This work describes a novel way to monitor the structural integrity of steel gas pipelines that uses advanced numerical modeling techniques to anticipate fracture development and corrosion effects.The objective is to increase pipeline dependability and safety through more precise,real-time health evaluations.Compared to previous approaches,our solution provides higher accuracy in fault detection and quantification,making it ideal for pipeline integritymonitoring in real-world applications.To solve this issue,statistical analysis was conducted on the size and directional distribution features of about 380,000 sets of internal corrosion faults,as well as simulations of erosion and wear patterns on bent pipes.Using real defectmorphologies,we developed a modeling framework for typical interior corrosion flaws.We evaluated and validated the applicability and effectiveness of in-service inspection processes,as well as conducted on-site comparison tests.The results show that(1)the length and width of corrosion defects follow a log-normal distribution,the clock orientation follows a normal distribution,and the peak depth follows a Freundlich EX function distribution pattern;(2)pipeline corrosion defect data can be classified into three classes using the K-means clustering algorithm,allowing rapid and convenient acquisition of typical size and orientation characteristics of internal corrosion defects;(3)the applicability range and boundary conditions of various NDT techniques were verified,establishing comprehensive selection principles for internal corrosion defect detection technology;(4)on-site inspection results showed a 31%The simulation and validation platform for typical interior corrosion issues greatly enhances the accuracy and reliability of detection data.展开更多
Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three au...Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three author names were duplicated.The correct author list has been provided in this Correction.The original article[1]has been corrected.展开更多
The cranial mesenchyme,originating from both neural crest and mesoderm,imparts remarkable regional specificity and complexity to postnatal calvarial tissue.While the distinct embryonic origins of the superior and dura...The cranial mesenchyme,originating from both neural crest and mesoderm,imparts remarkable regional specificity and complexity to postnatal calvarial tissue.While the distinct embryonic origins of the superior and dura periosteum of the cranial parietal bone have been described,the extent of their respective contributions to bone and vessel formation during adult bone defect repair remains superficially explored.Utilizing transgenic mouse models in conjunction with high-resolution multiphoton laser scanning microscopy(MPLSM),we have separately evaluated bone and vessel formation in the superior and dura periosteum before and after injury,as well as following intermittent treatment of recombinant peptide of human parathyroid hormone(rhPTH),Teriparatide.Our results show that new bone formation along the dura surface is three times greater than that along the superior periosteal surface following injury,regardless of Teriparatide treatment.Targeted deletion of PTH receptor PTH1R via SMA-CreER and Col 1a(2.3)-CreER results in selective reduction of bone formation,suggesting different progenitor cell pools in the adult superior and dura periosteum.Consistently,analyses of microvasculature show higher vessel density and better organized arterial-venous vessel network associated with a 10-fold more osteoblast clusters at dura periosteum as compared to superior periosteum.Intermittent rhPTH treatment further enhances the arterial vessel ratio at dura periosteum and type H vessel formation in cortical bone marrow space.Taken together,our study demonstrates a site-dependent coordinated osteogenic and angiogenic response,which is determined by regional osteogenic progenitor pool as well as the coupling blood vessel network at the site of cranial defect repair.展开更多
文摘Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.
基金funded by National Natural Science Foundation of China(Grant Nos.52130504,52305577,and 52175509)the Key Research and Development Plan of Hubei Province(Grant No.2022BAA013)+4 种基金the Major Program(JD)of Hubei Province(Grant No.2023BAA008-2)the Interdisciplinary Research Program of Huazhong University of Science and Technology(2023JCYJ047)the Innovation Project of Optics Valley Laboratory(Grant No.OVL2023PY003)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(Grant No.GZB20230244)the fellowship from the China Postdoctoral Science Foundation(2024M750995)。
文摘In integrated circuit(IC)manufacturing,fast,nondestructive,and precise detection of defects in patterned wafers,realized by bright-field microscopy,is one of the critical factors for ensuring the final performance and yields of chips.With the critical dimensions of IC nanostructures continuing to shrink,directly imaging or classifying deep-subwavelength defects by bright-field microscopy is challenging due to the well-known diffraction barrier,the weak scattering effect,and the faint correlation between the scattering cross-section and the defect morphology.Herein,we propose an optical far-field inspection method based on the form-birefringence scattering imaging of the defective nanostructure,which can identify and classify various defects without requiring optical super-resolution.The technique is built upon the principle of breaking the optical form birefringence of the original periodic nanostructures by the defect perturbation under the anisotropic illumination modes,such as the orthogonally polarized plane waves,then combined with the high-order difference of far-field images.We validated the feasibility and effectiveness of the proposed method in detecting deep subwavelength defects through rigid vector imaging modeling and optical detection experiments of various defective nanostructures based on polarization microscopy.On this basis,an intelligent classification algorithm for typical patterned defects based on a dual-channel AlexNet neural network has been proposed,stabilizing the classification accuracy ofλ/16-sized defects with highly similar features at more than 90%.The strong classification capability of the two-channel network on typical patterned defects can be attributed to the high-order difference image and its transverse gradient being used as the network’s input,which highlights the polarization modulation difference between different patterned defects more significantly than conventional bright-field microscopy results.This work will provide a new but easy-to-operate method for detecting and classifying deep-subwavelength defects in patterned wafers or photomasks,which thus endows current online inspection equipment with more missions in advanced IC manufacturing.
基金supported by the National Natural Science Foundation of China(Nos.22276117 and 22076108)the Science and Technology Innovation Talent Team Project of Shanxi Province(No.202204051002024).
文摘Phenanthrene(Phe)is one of the common polycyclic aromatic hydrocarbons in the environment,and recent studies show that it can cause cardiac developmental toxicity and immunotoxicity.However,it is still unknown whether it can affect the hematopoietic development in aquatic organisms.To address this question,zebrafish(Danio rerio)were chronically exposed to Phe at different concentrations.We found that Phe caused structural damage to the renal tubules in the kidney,induced malformed erythrocytes in peripheral blood,and decreased the proportion of myeloid cells in adult zebrafish,suggesting possible negative impacts that Phe posed to hematopoietic development.Then,using in situ hybridization technology,we found that Phe decreased the expression of primitive hematopoietic marker genes,specifically gata1 and pu.1,accompanied by an obstruction of primitive erythrocyte circulation.Furthermore,Phe impaired definitive hematopoiesis,increased aberrations of the transient hematopoietic site(PBI),and reduced the generation of hematopoietic stem cells,ultimately influencing the number of erythrocytes and myeloid cells.The findings suggested that Phe could induce hematopoietic toxicity in zebrafish embryos and pose unknown ecological risks.
基金supported by the support of the National Natural Science Foundation of China(Nos.22072141,22176185 and 52304429)the National Key Research and Development Program of China(Nos.2022YFB3504200,2021YFB3501900)+4 种基金the Natural Science Foundation of Jiangxi Province for Distinguished Young Scholars(No.20232ACB213004)Jiangxi Provincial Key Research and Development Program(No.20232BBG70012)Jiangxi Provincial Natural Science Foundation(No.20212BAB213032)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2018263)the Research Projects of Ganjiang Innovation Academy,Chinese Academy of Sciences(No.E355C001).
文摘Selective catalytic reduction of NO_(x) with CO(CO-SCR)is a process that purifies both NO and CO pollutants through a catalytic reaction.Specifically,the cleavage of NO on the catalyst surface is crucial for promoting the reaction.During the reaction,the presence of oxygen vacancies can extract oxygen from NO,thereby facilitating the cleavage of NO on the catalyst surface.Thus,the formation of oxygen vacancies is key to accelerating the CO-SCR reaction,with different types of oxygen vacancies being more conducive to their generation.In this study,Rh/CeCuO_(x) catalysts were synthesized using the co-crystallization and impregnation methods,and asymmetric oxygen vacancies were induced through hydrogen thermal treatment.This structuralmodification was aimed at regulating the behavior of NO on the catalyst surface.The Rh/Ce0.95Cu0.05O_(x)-H_(2) catalyst exhibited the best performance in CO-SCR,achieving above 90%NO conversion at 162℃.Various characterization techniques showed that the H_(2) treatment effectively reduced some of the CuO and Rh_(2)O_(3),creating asymmetric oxygen vacancies that accelerated the cleavage of NO on the catalyst surface,rather than forming difficult-to-decompose nitrates.This study offers a novel approach to constructing oxygen vacancies in new CO-SCR catalysts.
基金supported by the National Natural Science Foundation of China(Nos.82160419 and 82302772)Guizhou Basic Research Project(No.ZK[2023]General 201)。
文摘As the global population ages,osteoporotic bone fractures leading to bone defects are increasingly becoming a significant challenge in the field of public health.Treating this disease faces many challenges,especially in the context of an imbalance between osteoblast and osteoclast activities.Therefore,the development of new biomaterials has become the key.This article reviews various design strategies and their advantages and disadvantages for biomaterials aimed at osteoporotic bone defects.Overall,current research progress indicates that innovative design,functionalization,and targeting of materials can significantly enhance bone regeneration under osteoporotic conditions.By comprehensively considering biocompatibility,mechanical properties,and bioactivity,these biomaterials can be further optimized,offering a range of choices and strategies for the repair of osteoporotic bone defects.
基金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 and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.
基金supported by the National Natural Science Foundation of China(U21A20281)the Special Fund for Young Teachers from Zhengzhou University(JC23557030,JC23257011)+1 种基金the Key Research Projects of Higher Education Institutions of Henan Province(24A530009)the Project of Zhongyuan Critical Metals Laboratory(GJJSGFYQ202336).
文摘Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the electronic structure of active sites.This optimization influences the adsorption energy of intermediates,thereby mitigating reaction energy barriers,altering paths,enhancing selectivity,and ultimately improving the catalytic efficiency of electrocatalysts.To elucidate the impact of defects on the electrocatalytic process,we comprehensively outline the roles of various point defects,their synthetic methodologies,and characterization techniques.Importantly,we consolidate insights into the relationship between point defects and catalytic activity for hydrogen/oxygen evolution and CO_(2)/O_(2)/N_(2) reduction reactions by integrating mechanisms from diverse reactions.This underscores the pivotal role of point defects in enhancing catalytic performance.At last,the principal challenges and prospects associated with point defects in current electrocatalysts are proposed,emphasizing their role in advancing the efficiency of electrochemical energy storage and conversion materials.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_4084).
文摘To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.52272103 and 52072010)Beijing Natural Science Foundation(Grant Nos.2242029 and JL23004).
文摘High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported before.Herein,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese doping.Due to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese ions.The HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.
基金support of the National Natural Science Foundation of China(Grant No.22225801,22178217 and 22308216)supported by the Fundamental Research Funds for the Central Universities,conducted at Tongji University.
文摘Rechargeable magnesium batteries(RMBs)have been considered a promising“post lithium-ion battery”system to meet the rapidly increasing demand of the emerging electric vehicle and grid energy storage market.However,the sluggish diffusion kinetics of bivalent Mg^(2+)in the host material,related to the strong Coulomb effect between Mg^(2+)and host anion lattices,hinders their further development toward practical applications.Defect engineering,regarded as an effective strategy to break through the slow migration puzzle,has been validated in various cathode materials for RMBs.In this review,we first thoroughly understand the intrinsic mechanism of Mg^(2+)diffusion in cathode materials,from which the key factors affecting ion diffusion are further presented.Then,the positive effects of purposely introduced defects,including vacancy and doping,and the corresponding strategies for introducing various defects are discussed.The applications of defect engineering in cathode materials for RMBs with advanced electrochemical properties are also summarized.Finally,the existing challenges and future perspectives of defect engineering in cathode materials for the overall high-performance RMBs are described.
基金supported in part by the National Natural Science Foundation of China under Grants 62463002,62062021 and 62473033in part by the Guiyang Scientific Plan Project[2023]48–11,in part by QKHZYD[2023]010 Guizhou Province Science and Technology Innovation Base Construction Project“Key Laboratory Construction of Intelligent Mountain Agricultural Equipment”.
文摘Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective samples.Additionally,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective regions.This paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these challenges.The network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation network.Specifically,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information effectively.In order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target detection.Moreover,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter number.Finally,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and PVEL-S.SolarCells and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon dataset.Experimental results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.
基金National Natural Science Foundation of China(52201054,52175368)National Science and Technology Major Projects(J2019-VI-0018-0133)+2 种基金Liaoning Provincial Science and Technology Program(2023-BS-019,2023-MS-020)National Key R&D Program of China(2021YFB3700401)Key Specialized Research and Development Break-Through-Unveiling and Commanding the Special Project Program in Liaoning Province(2021JH15)。
文摘The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and widths were TIG welded,and the microstructures,cracks morphology,and precipitated phases were analyzed using optical microscope,scanning electron microscope,transmission electron microscope,and energy dispersive X-ray spectrometer.The results reveal that the dimensions of casting defects significantly affect the weldability of K4951.Deep defects(greater than 2 mm)lead to rapid crack propagation,while wider defects can moderate the propagation process of cracks.Elemental segregation and the formation of precipitated phases,such as MC carbides,are observed in the fusion zone,contributing to welding cracks.An optimal groove aspect ratio(depth-to-width)between 0.2 and 0.5 minimizes crack formation tendency and enhances tensile strength,resulting in a mixed brittle-ductile fracture mode of joint after high-temperature tensile testing.
基金supported by a Research Grant of Pukyong National University(2023)。
文摘Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simultaneously control the growth of perovskite crystals and passivate defects.Here,4-(trifluoromethyl)benzoic anhydride(4-TBA)composed of benzene rings functionalized with carbonyl and trifluoromethyl groups was used as an example additive to study the characteristics of additives used for producing high-quality perovskites and controlling their surface properties.The interaction between4-TBA and perovskite precursor materials was investigated using density functional theory(DFT)simulations.The electron-rich carbonyl group efficiently passivated the under-coordinated lead-ion defects.Additionally,hydrogen bonding between trifluoromethyl and organic cations prevents the generation of cation vacancies.Because of its intrinsic hydrophobicity,the trifluoromethyl group simultaneously improves the moisture and heat stability of the film.4-TBA serves as a universal modifier for various perovskite compositions.The power conversion efficiency(PCE)of inverted perovskite solar cells(PSCs)based on methylammonium(MA)with 4-TBA was improved from 16.15%to 19.28%.Similarly,the PCE of inverted PSCs based on a cesium formamidinium MA(CsFAMA)perovskite film increased from20.72%to 23.58%,upon addition of 4-TBA.Furthermore,the moisture and thermal stability of 4-TBAtreated films and devices was significantly enhanced,along with prolonged device performance.Our work provides guidance on selecting the structure and functional groups that are essential for surface defect passivation and the production of high-quality perovskites.
文摘BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.
基金National Natural Science Foundation of China(U2241242)National Key R&D Program of China(2023YFB3812000,2021YFA0716502)。
文摘The accepted doping ion in Ti^(4+)-site of PbZr_(y)Ti_(1–y)O_(3)(PZT)-based piezoelectric ceramics is a well-known method to increase mechanical quality factor(Q_(m)),since the acceptor coupled by oxygen vacancy becomes defect dipole,which prevents the domain rotation.In this field,a serious problem is that generally,Qm decreases as the temperature(T)increases,since the oxygen vacancies are decoupled from the defect dipoles.In this work,Q_(m) of Pb_(0.95)Sr_(0.05)(Zr_(0.53)Ti_(0.47))O_(3)(PSZT)ceramics doped by 0.40%Fe_(2)O_(3)(in mole)abnormally increases as T increases,of which the Qm and piezoelectric coefficient(d_(33))at room temperature and Curie temperature(TC)are 507,292 pC/N,and 345℃,respectively.The maximum Qm of 824 was achieved in the range of 120–160℃,which is 62.52%higher than that at room temperature,while the dynamic piezoelectric constant(d_(31))was just slightly decreased by 3.85%.X-ray diffraction(XRD)and piezoresponse force microscopy results show that the interplanar spacing and the fine domains form as temperature increases,and the thermally stimulated depolarization current shows that the defect dipoles are stable even the temperature up to 240℃.It can be deduced that the aggregation of oxygen vacancies near the fine domains and defect dipole can be stable up to 240℃,which pins domain rotation,resulting in the enhanced Q_(m) with the increasing temperature.These results give a potential path to design high Q_(m) at high temperature.
文摘Rail defects can pose significant safety risks in railway operations, raising the need for effective detection methods. Acoustic Emission (AE) technology has shown promise for identifying and monitoring these defects, and this study evaluates an advanced on-vehicle AE detection approach using bone-conduct sensors—a solution to improve upon previous AE methods of using on-rail sensor installations, which required extensive, costly on-rail sensor networks with limited effectiveness. In response to these challenges, the study specifically explored bone-conduct sensors mounted directly on the vehicle rather than rails by evaluating AE signals generated by the interaction between rails and the train’s wheels while in motion. In this research, a prototype detection system was developed and tested through initial trials at the Nevada Railroad Museum using a track with pre-damaged welding defects. Further testing was conducted at the Transportation Technology Center Inc. (rebranded as MxV Rail) in Colorado, where the system’s performance was evaluated across various defect types and train speeds. The results indicated that bone-conduct sensors were insufficient for detecting AE signals when mounted on moving vehicles. These findings highlight the limitations of contact-based methods in real-world applications and indicate the need for exploring improved, non-contact approaches.
基金supported by the Scientific and technological key project in Henan Province 22210224002the Natural Science Foundation of Henan Polytechnic University B2021-38.
文摘The service life of internal combustion engines is significantly influenced by surface defects in cylinder liners.To address the limitations of traditional detection methods,we propose an enhanced YOLOv8 model with Swin Transformer as the backbone network.This approach leverages Swin Transformer's multi-head self-attention mechanism for improved feature extraction of defects spanning various scales.Integrated with the YOLOv8 detection head,our model achieves a mean average precision of 85.1%on our dataset,outperforming baseline methods by 1.4%.The model's effectiveness is further demonstrated on a steel-surface defect dataset,indicating its broad applicability in industrial surface defect detection.Our work highlights the potential of combining Swin Transformer and YOLOv8 for accurate and efficient defect detection.
基金The“13th Five-Year Plan”National Science and Technology Major Project,2016ZX05052,Changchao QiThe China National Petroleum Corporation Science and Technology Project,2021DJ6505,Changchao Qi.
文摘The accuracy and reliability of non-destructive testing(NDT)approaches in detecting interior corrosion problems are critical,yet research in this field is limited.This work describes a novel way to monitor the structural integrity of steel gas pipelines that uses advanced numerical modeling techniques to anticipate fracture development and corrosion effects.The objective is to increase pipeline dependability and safety through more precise,real-time health evaluations.Compared to previous approaches,our solution provides higher accuracy in fault detection and quantification,making it ideal for pipeline integritymonitoring in real-world applications.To solve this issue,statistical analysis was conducted on the size and directional distribution features of about 380,000 sets of internal corrosion faults,as well as simulations of erosion and wear patterns on bent pipes.Using real defectmorphologies,we developed a modeling framework for typical interior corrosion flaws.We evaluated and validated the applicability and effectiveness of in-service inspection processes,as well as conducted on-site comparison tests.The results show that(1)the length and width of corrosion defects follow a log-normal distribution,the clock orientation follows a normal distribution,and the peak depth follows a Freundlich EX function distribution pattern;(2)pipeline corrosion defect data can be classified into three classes using the K-means clustering algorithm,allowing rapid and convenient acquisition of typical size and orientation characteristics of internal corrosion defects;(3)the applicability range and boundary conditions of various NDT techniques were verified,establishing comprehensive selection principles for internal corrosion defect detection technology;(4)on-site inspection results showed a 31%The simulation and validation platform for typical interior corrosion issues greatly enhances the accuracy and reliability of detection data.
文摘Correction to:Nano-Micro Lett.(2025)17:24 https://doi.org/10.1007/s40820-024-01515-0 Following publication of the original article[1],the authors reported the author list needed to be updated because the last three author names were duplicated.The correct author list has been provided in this Correction.The original article[1]has been corrected.
基金National Institutes of Health R01AR067859,R01DE019902,R21DE026256,R01DE029790,R01AR083224,R21AR076056,and P30AR069655。
文摘The cranial mesenchyme,originating from both neural crest and mesoderm,imparts remarkable regional specificity and complexity to postnatal calvarial tissue.While the distinct embryonic origins of the superior and dura periosteum of the cranial parietal bone have been described,the extent of their respective contributions to bone and vessel formation during adult bone defect repair remains superficially explored.Utilizing transgenic mouse models in conjunction with high-resolution multiphoton laser scanning microscopy(MPLSM),we have separately evaluated bone and vessel formation in the superior and dura periosteum before and after injury,as well as following intermittent treatment of recombinant peptide of human parathyroid hormone(rhPTH),Teriparatide.Our results show that new bone formation along the dura surface is three times greater than that along the superior periosteal surface following injury,regardless of Teriparatide treatment.Targeted deletion of PTH receptor PTH1R via SMA-CreER and Col 1a(2.3)-CreER results in selective reduction of bone formation,suggesting different progenitor cell pools in the adult superior and dura periosteum.Consistently,analyses of microvasculature show higher vessel density and better organized arterial-venous vessel network associated with a 10-fold more osteoblast clusters at dura periosteum as compared to superior periosteum.Intermittent rhPTH treatment further enhances the arterial vessel ratio at dura periosteum and type H vessel formation in cortical bone marrow space.Taken together,our study demonstrates a site-dependent coordinated osteogenic and angiogenic response,which is determined by regional osteogenic progenitor pool as well as the coupling blood vessel network at the site of cranial defect repair.
