Railway turnouts often develop defects such as chipping,cracks,and wear during use.If not detected and addressed promptly,these defects can pose significant risks to train operation safety and passenger security.Despi...Railway turnouts often develop defects such as chipping,cracks,and wear during use.If not detected and addressed promptly,these defects can pose significant risks to train operation safety and passenger security.Despite advances in defect detection technologies,research specifically targeting railway turnout defects remains limited.To address this gap,we collected images from railway inspectors and constructed a dataset of railway turnout defects in complex environments.To enhance detection accuracy,we propose an improved YOLOv8 model named YOLO-VSS-SOUP-Inner-CIoU(YOLO-VSI).The model employs a state-space model(SSM)to enhance the C2f module in the YOLOv8 backbone,proposed the C2f-VSS module to better capture long-range dependencies and contextual features,thus improving feature extraction in complex environments.In the network’s neck layer,we integrate SPDConv and Omni-Kernel Network(OKM)modules to improve the original PAFPN(Path Aggregation Feature Pyramid Network)structure,and proposed the Small Object Upgrade Pyramid(SOUP)structure to enhance small object detection capabilities.Additionally,the Inner-CIoU loss function with a scale factor is applied to further enhance the model’s detection capabilities.Compared to the baseline model,YOLO-VSI demonstrates a 3.5%improvement in average precision on our railway turnout dataset,showcasing increased accuracy and robustness.Experiments on the public NEU-DET dataset reveal a 2.3%increase in average precision over the baseline,indicating that YOLO-VSI has good generalization capabilities.展开更多
The sliding chairs are important components that support the switch rail conversion in the railway turnout.Due to the harsh environmental erosion and the attack from the wheel vibration,the failure rate of the sliding...The sliding chairs are important components that support the switch rail conversion in the railway turnout.Due to the harsh environmental erosion and the attack from the wheel vibration,the failure rate of the sliding chairs accounts for up to 10%of the total failure number in turnout.However,there is little research carried out in the existing literature to diagnose the deterioration states of the sliding chairs.To fill out this gap,by utilizing the images containing the sliding chairs,we propose an improved You Only Look Once version 7(YOLOv7)to identify the state of the sliding chairs.Specifically,to meet the challenge brought by the small inter-class differences among the sliding chair states,we first integrate the Convolutional Block Attention Module(CBAM)into the YOLOv7 backbone to screen the information conducive to state identification.Then,an extra detector for a small object is customized into the YOLOv7 network in order to detect the small-scale sliding chairs in images.Meanwhile,we revise the localization loss in the objective function as the Efficient Intersection over Union(EIoU)to optimize the design of the aspect ratio,which helps the localization of the sliding chairs.Next,to address the issue caused by the varying scales of the sliding chairs,we employ K-means++to optimize the priori selection of the initial anchor boxes.Finally,based on the images collected from real-world turnouts,the proposed method is verified and the results show that our method outperforms the basic YOLOv7 in the state identification of the sliding chairs with 4%improvements in terms of both mean Average Precision@0.5(mAP@0.5)and F1-score.展开更多
For high-speed railways,the smoothness of the railway line significantly affects the operational speed of trains.When the train passes through the turnout on a long-span bridge,the wheel-rail impacts caused by the tur...For high-speed railways,the smoothness of the railway line significantly affects the operational speed of trains.When the train passes through the turnout on a long-span bridge,the wheel-rail impacts caused by the turnout structure irregularities,and the instability arising from the bridge's flexural deformation lead to a strong coupling effect in the vehicle-turnout-bridge system.This significantly affects both ride comfort and operational safety.For addressing this issue,the present study considered a long-span continuous rigid-frame bridge as an example and established a train-turnout-bridge coupled dynamic model of high-speed railway.Utilizing a selfdeveloped dynamic simulation program,the study analysed the dynamic response characteristics when the train passes through the turnouts on the bridge.It also investigated the influence of different span-to-depth ratios of the bridge on the vehicle dynamic response when the train passes through the main line and branch line of turnouts and then proposed a span-to-depth ratio limit value for a long-span continuous rigid-frame bridge.The research findings suggest that the changes in the span-to-depth ratio have a relatively minor impact on the train’s operational performance but significantly affect the dynamic characteristics of the bridge structure.Based on the findings and a comprehensive assessment of safety indicators,it is advisable to establish a span-to-depth ratio limit of 1/4500 for a long-span continuous rigid-frame bridge.展开更多
Hyperuricemia is a high-risk factor for the development of gout and renal fibrosis,but the adverse effects of hyperuricemia on the liver have been seriously neglected.This research investigated the ameliorating effect...Hyperuricemia is a high-risk factor for the development of gout and renal fibrosis,but the adverse effects of hyperuricemia on the liver have been seriously neglected.This research investigated the ameliorating effect of Lacticaseibacillus rhamnosus Fmb14 on hyperuricemia induced liver dysfunction both in vitro and in vivo.Cell free extracts of high dose L.rhamnosus Fmb14 treatment reduced the death rate of HepG2 cell lines from 24.1%to 14.9%by inhibiting NLRP3 recruitment,which was mainly activated by reactive oxygen species release and mitochondrial membrane potential disorder.In purine dietary induced hyperuricemia(PDIH)mice model,liver oedema and pyroptosis were ameliorated after L.rhamnosus Fmb14 administration through downregulating the expression levels of NLRP3,caspase-1 and gasdermin-D from 1.61 to 0.86,3.15 to 1.01 and 5.63 to 2.02,respectively.L.rhamnosus Fmb14 administration restored mitochondrial inner membrane protein(MPV17)and connexin 43 from 2.83 and 0.73 to 0.80 and 0.98 respectively in PDIH mice,indicating that dysbiosis of mitochondrial membrane potential was restored in liver.Intriguingly,PDIH pyroptosis stimulates the process of apoptosis,which leads to severe leakage of hepatocytes,and both of pyroptosis and apoptosis were decreased after L.rhamnosus Fmb14 treatment.Therefore,L.rhamnosus Fmb14 is a promising biological resource to maintain homeostasis of the liver in hyperuricemia and the prevention of subsequent complications.展开更多
Objective To identify nivolumab resistance-related genes in patients with head and neck squamous cell carcinoma(HNSCC)using single-cell and bulk RNA-sequencing data.Methods The single-cell and bulk RNA-sequencing data...Objective To identify nivolumab resistance-related genes in patients with head and neck squamous cell carcinoma(HNSCC)using single-cell and bulk RNA-sequencing data.Methods The single-cell and bulk RNA-sequencing data downloaded from the Gene Expression Omnibus database were analyzed to screen out differentially expressed genes(DEGs)between nivolumab resistant and nivolumab sensitive patients using R software.The Least Absolute Shrinkage Selection Operator(LASSO)regression and Recursive Feature Elimination(RFE)algorithm were performed to identify key genes associated with nivolumab resistance.Functional enrichment of DEGs was analyzed with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses.The relationships of key genes with immune cell infiltration,differentation trajectory,dynamic gene expression profiles,and ligand-receptor interaction were explored.Results We found 83 DEGs.They were mainly enriched in T-cell differentiation,PD-1 and PD-L1 checkpoint,and T-cell receptor pathways.Among six key genes identified using machine learning algorithms,only PPP1R14A gene was differentially expressed between the nivolumab resistant and nivolumab sensitive groups both before and after immunotherapy(P<0.05).The high PPP1R14A gene expression group had lower immune score(P<0.01),higher expression of immunosuppressive factors(such as PDCD1,CTLA4,and PDCD1LG2)(r>0,P<0.05),lower differentiation of infiltrated immune cells(P<0.05),and a higher degree of interaction between HLA and CD4(P<0.05).Conclusions PPP1R14A gene is closely associated with resistance to nivolumab in HNSCC patients.Therefore,PPP1R14A may be a target to ameliorate nivolumab resistance of HNSCC patients.展开更多
In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion ...In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion technology based on pre-stack seismic data, pre-stack P-and S-wave inversion results,and post-stack attributes.This method not only can keep the fluid information contained in pre-stack seismic data but also make use of the high SNR characteristics of post-stack data.First,we use a one-step recursive method to get the optimal attribute combination from a number of attributes.Second,we use a probabilistic neural network method to train the nonlinear relationship between log curves and seismic attributes and then use the trained samples to find the natural gamma ray distribution in the Su-14 well block and improve the resolution of seismic data.Finally,we predict the effective reservoir distribution in the Su-14 well block.展开更多
[ Objective] The aim was to observe the ultrastructure of different callus structures in Heiya No. 14 by transmission electron microscopy. [Methods] Sample preparation and observation were both carried out by conventi...[ Objective] The aim was to observe the ultrastructure of different callus structures in Heiya No. 14 by transmission electron microscopy. [Methods] Sample preparation and observation were both carried out by conventional transmission electron microscopy. [ Results] It was showed by transmission electron microscopy that the initial callus cells had a large central vacuole, which squeezed its cytoplasm to be a thin layer around the brim of cell, Meanwhile the nuclear was also squeezed to distribute in the corner of cell, but its nucleolus could be still observed; Compared embryogenic callus with initial callus, its cell wall became thick, and many starch grains and chloroplasts including starch grains could be observed in the cytoplasm area of cell membrane; In non-embryoenic callus, no organelles except for the vacuole could be observed; In browning callus, there was almost no organelles in cells. [ Conclusion] There are significant differences in different types of flax callus at the cell ultrastructure level, which can be as an index for reflecting the differentiation ability of callus cell.展开更多
文摘Railway turnouts often develop defects such as chipping,cracks,and wear during use.If not detected and addressed promptly,these defects can pose significant risks to train operation safety and passenger security.Despite advances in defect detection technologies,research specifically targeting railway turnout defects remains limited.To address this gap,we collected images from railway inspectors and constructed a dataset of railway turnout defects in complex environments.To enhance detection accuracy,we propose an improved YOLOv8 model named YOLO-VSS-SOUP-Inner-CIoU(YOLO-VSI).The model employs a state-space model(SSM)to enhance the C2f module in the YOLOv8 backbone,proposed the C2f-VSS module to better capture long-range dependencies and contextual features,thus improving feature extraction in complex environments.In the network’s neck layer,we integrate SPDConv and Omni-Kernel Network(OKM)modules to improve the original PAFPN(Path Aggregation Feature Pyramid Network)structure,and proposed the Small Object Upgrade Pyramid(SOUP)structure to enhance small object detection capabilities.Additionally,the Inner-CIoU loss function with a scale factor is applied to further enhance the model’s detection capabilities.Compared to the baseline model,YOLO-VSI demonstrates a 3.5%improvement in average precision on our railway turnout dataset,showcasing increased accuracy and robustness.Experiments on the public NEU-DET dataset reveal a 2.3%increase in average precision over the baseline,indicating that YOLO-VSI has good generalization capabilities.
基金supported by the National Key R&D Program of China(2021YFF0501102)the National Natural Science Foundation of China(52372308,U2368202,U1934219,52202392,52022010,U22A2046,52172322,and 62271486).
文摘The sliding chairs are important components that support the switch rail conversion in the railway turnout.Due to the harsh environmental erosion and the attack from the wheel vibration,the failure rate of the sliding chairs accounts for up to 10%of the total failure number in turnout.However,there is little research carried out in the existing literature to diagnose the deterioration states of the sliding chairs.To fill out this gap,by utilizing the images containing the sliding chairs,we propose an improved You Only Look Once version 7(YOLOv7)to identify the state of the sliding chairs.Specifically,to meet the challenge brought by the small inter-class differences among the sliding chair states,we first integrate the Convolutional Block Attention Module(CBAM)into the YOLOv7 backbone to screen the information conducive to state identification.Then,an extra detector for a small object is customized into the YOLOv7 network in order to detect the small-scale sliding chairs in images.Meanwhile,we revise the localization loss in the objective function as the Efficient Intersection over Union(EIoU)to optimize the design of the aspect ratio,which helps the localization of the sliding chairs.Next,to address the issue caused by the varying scales of the sliding chairs,we employ K-means++to optimize the priori selection of the initial anchor boxes.Finally,based on the images collected from real-world turnouts,the proposed method is verified and the results show that our method outperforms the basic YOLOv7 in the state identification of the sliding chairs with 4%improvements in terms of both mean Average Precision@0.5(mAP@0.5)and F1-score.
基金supported by the National Key R&D Program of China(2022YFB2602900)the 111 Project(B20040)the China Railway Science and Technology Research and Development Program Project(N2023T011-A(JB)).
文摘For high-speed railways,the smoothness of the railway line significantly affects the operational speed of trains.When the train passes through the turnout on a long-span bridge,the wheel-rail impacts caused by the turnout structure irregularities,and the instability arising from the bridge's flexural deformation lead to a strong coupling effect in the vehicle-turnout-bridge system.This significantly affects both ride comfort and operational safety.For addressing this issue,the present study considered a long-span continuous rigid-frame bridge as an example and established a train-turnout-bridge coupled dynamic model of high-speed railway.Utilizing a selfdeveloped dynamic simulation program,the study analysed the dynamic response characteristics when the train passes through the turnouts on the bridge.It also investigated the influence of different span-to-depth ratios of the bridge on the vehicle dynamic response when the train passes through the main line and branch line of turnouts and then proposed a span-to-depth ratio limit value for a long-span continuous rigid-frame bridge.The research findings suggest that the changes in the span-to-depth ratio have a relatively minor impact on the train’s operational performance but significantly affect the dynamic characteristics of the bridge structure.Based on the findings and a comprehensive assessment of safety indicators,it is advisable to establish a span-to-depth ratio limit of 1/4500 for a long-span continuous rigid-frame bridge.
基金Grant support was received from the National Natural Science Foundation of China(32072182).
文摘Hyperuricemia is a high-risk factor for the development of gout and renal fibrosis,but the adverse effects of hyperuricemia on the liver have been seriously neglected.This research investigated the ameliorating effect of Lacticaseibacillus rhamnosus Fmb14 on hyperuricemia induced liver dysfunction both in vitro and in vivo.Cell free extracts of high dose L.rhamnosus Fmb14 treatment reduced the death rate of HepG2 cell lines from 24.1%to 14.9%by inhibiting NLRP3 recruitment,which was mainly activated by reactive oxygen species release and mitochondrial membrane potential disorder.In purine dietary induced hyperuricemia(PDIH)mice model,liver oedema and pyroptosis were ameliorated after L.rhamnosus Fmb14 administration through downregulating the expression levels of NLRP3,caspase-1 and gasdermin-D from 1.61 to 0.86,3.15 to 1.01 and 5.63 to 2.02,respectively.L.rhamnosus Fmb14 administration restored mitochondrial inner membrane protein(MPV17)and connexin 43 from 2.83 and 0.73 to 0.80 and 0.98 respectively in PDIH mice,indicating that dysbiosis of mitochondrial membrane potential was restored in liver.Intriguingly,PDIH pyroptosis stimulates the process of apoptosis,which leads to severe leakage of hepatocytes,and both of pyroptosis and apoptosis were decreased after L.rhamnosus Fmb14 treatment.Therefore,L.rhamnosus Fmb14 is a promising biological resource to maintain homeostasis of the liver in hyperuricemia and the prevention of subsequent complications.
基金supported by the National Innovation and Enterpreneurship Training Program for College Students(202210367002)the Key Laboratory Open Project of An-hui Province(AHCM2022Z004).
文摘Objective To identify nivolumab resistance-related genes in patients with head and neck squamous cell carcinoma(HNSCC)using single-cell and bulk RNA-sequencing data.Methods The single-cell and bulk RNA-sequencing data downloaded from the Gene Expression Omnibus database were analyzed to screen out differentially expressed genes(DEGs)between nivolumab resistant and nivolumab sensitive patients using R software.The Least Absolute Shrinkage Selection Operator(LASSO)regression and Recursive Feature Elimination(RFE)algorithm were performed to identify key genes associated with nivolumab resistance.Functional enrichment of DEGs was analyzed with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses.The relationships of key genes with immune cell infiltration,differentation trajectory,dynamic gene expression profiles,and ligand-receptor interaction were explored.Results We found 83 DEGs.They were mainly enriched in T-cell differentiation,PD-1 and PD-L1 checkpoint,and T-cell receptor pathways.Among six key genes identified using machine learning algorithms,only PPP1R14A gene was differentially expressed between the nivolumab resistant and nivolumab sensitive groups both before and after immunotherapy(P<0.05).The high PPP1R14A gene expression group had lower immune score(P<0.01),higher expression of immunosuppressive factors(such as PDCD1,CTLA4,and PDCD1LG2)(r>0,P<0.05),lower differentiation of infiltrated immune cells(P<0.05),and a higher degree of interaction between HLA and CD4(P<0.05).Conclusions PPP1R14A gene is closely associated with resistance to nivolumab in HNSCC patients.Therefore,PPP1R14A may be a target to ameliorate nivolumab resistance of HNSCC patients.
基金The National Natural Science Foundation of China and China Petroleum&Chemical Corporation Co-funded Project(Grant Nos 40839905 and 40739907)
文摘In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion technology based on pre-stack seismic data, pre-stack P-and S-wave inversion results,and post-stack attributes.This method not only can keep the fluid information contained in pre-stack seismic data but also make use of the high SNR characteristics of post-stack data.First,we use a one-step recursive method to get the optimal attribute combination from a number of attributes.Second,we use a probabilistic neural network method to train the nonlinear relationship between log curves and seismic attributes and then use the trained samples to find the natural gamma ray distribution in the Su-14 well block and improve the resolution of seismic data.Finally,we predict the effective reservoir distribution in the Su-14 well block.
基金Supported by Harbin Postdoctoral Foundation(LRB08-491)~~
文摘[ Objective] The aim was to observe the ultrastructure of different callus structures in Heiya No. 14 by transmission electron microscopy. [Methods] Sample preparation and observation were both carried out by conventional transmission electron microscopy. [ Results] It was showed by transmission electron microscopy that the initial callus cells had a large central vacuole, which squeezed its cytoplasm to be a thin layer around the brim of cell, Meanwhile the nuclear was also squeezed to distribute in the corner of cell, but its nucleolus could be still observed; Compared embryogenic callus with initial callus, its cell wall became thick, and many starch grains and chloroplasts including starch grains could be observed in the cytoplasm area of cell membrane; In non-embryoenic callus, no organelles except for the vacuole could be observed; In browning callus, there was almost no organelles in cells. [ Conclusion] There are significant differences in different types of flax callus at the cell ultrastructure level, which can be as an index for reflecting the differentiation ability of callus cell.
