Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating land...Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating landslides.However,DDA fails to accurately capture the degradation in shear strength of rock joints commonly observed in high-speed landslides.In this study,DDA is modified by incorporating simplified joint shear strength degradation.Based on the modified DDA,the kinematics of the Baige landslide that occurred along the Jinsha River in China on 10 October 2018 are reproduced.The violent starting velocity of the landslide is considered explicitly.Three cases with different violent starting velocities are investigated to show their effect on the landslide movement process.Subsequently,the landslide movement process and the final accumulation characteristics are analyzed from multiple perspectives.The results show that the violent starting velocity affects the landslide motion characteristics,which is found to be about 4 m/s in the Baige landslide.The movement process of the Baige landslide involves four stages:initiation,high-speed sliding,impact-climbing,low-speed motion and accumulation.The accumulation states of sliding masses in different zones are different,which essentially corresponds to reality.The research results suggest that the modified DDA is applicable to similar high-level rock landslides.展开更多
针对转向架构架磁粉探伤缺陷识别环节人工目测效率低的现状,提出一种基于YOLO-CET(You Only Look Once based on CoTNet-Efficient-Transformer blocks)的探伤图像缺陷自动识别算法,实现对构架表面真伪缺陷的智能识别。以YOLOv5(You Onl...针对转向架构架磁粉探伤缺陷识别环节人工目测效率低的现状,提出一种基于YOLO-CET(You Only Look Once based on CoTNet-Efficient-Transformer blocks)的探伤图像缺陷自动识别算法,实现对构架表面真伪缺陷的智能识别。以YOLOv5(You Only Look Once version 5)为基础模型,在骨干特征提取网络引入轻量化CoTNet(Contextual Transformer Networks)网络层,实现缺陷特征的多尺度融合与提取。加入高效通道注意力机制,在不增加网络计算量的同时提高模型的鲁棒性和泛化性。增加一个小尺寸缺陷检测头用于减轻不同尺寸特征带来的尺度方差影响,同时引入视觉自注意力模块,增强小目标缺陷的抓取识别能力。利用自建的构架表面缺陷探伤数据集进行测试,结果表明,与YOLOv5相比,所提出的YOLO-CET使检测平均精度提升33.8%,F1-Score提升0.26,浮点运算量仅增加1.5 B,该模型可实现缺陷的自动检测,有效解决背景误判、细小缺陷漏检等问题。展开更多
CD38 is known to play roles in various inflammatory pathways.However,whether it has a protective or detrimental effect during bacterial septicemia remains disputed.Herein,this study aimed to determine the potential ef...CD38 is known to play roles in various inflammatory pathways.However,whether it has a protective or detrimental effect during bacterial septicemia remains disputed.Herein,this study aimed to determine the potential effect of CD38 on renal injury in septicemia.Escherichia coli(E.coli)was used to induce sepsis-associated renal injury in mice.WT and CD38-/-mice were stimulated with E.coli.After three hours,the serum was collected to detect renal function.Function mRNA expressions inflammatory cytokines in kidneys were quantified by real-time PCR.Hematoxylin and eosin staining were used to observe the histomorphology of kidney.The expression of TLR4,NF-κB,MAPK and cytokines were detected by Western Blot.Our results demonstrated that 3×10^(8) cfu/mL E.coli is the appropriate dose to induce sepsis mice model.Compared to WT sepsis mice,CD38-/-mice showed aggravated kidney injuries with impaired renal function,increased inflammation and apoptosis after E.coli stimulation.Interestingly,CD38 deficiency also led to elevated expression of TLR4 and increased phosphorylation of NF-κB p65/p105 and ERK1/2.To sum up,our results suggested that CD38 deficiency could aggravate E.coli-induced renal injury through activating ERK1/2-NF-κB signaling pathway.展开更多
基金supported by the National Natural Science Foundations of China(grant numbers U22A20601 and 52209142)the Opening fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(grant number SKLGP2022K018)+1 种基金the Science&Technology Department of Sichuan Province(grant number 2023NSFSC0284)the Science and Technology Major Project of Tibetan Autonomous Region of China(grant number XZ202201ZD0003G)。
文摘Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating landslides.However,DDA fails to accurately capture the degradation in shear strength of rock joints commonly observed in high-speed landslides.In this study,DDA is modified by incorporating simplified joint shear strength degradation.Based on the modified DDA,the kinematics of the Baige landslide that occurred along the Jinsha River in China on 10 October 2018 are reproduced.The violent starting velocity of the landslide is considered explicitly.Three cases with different violent starting velocities are investigated to show their effect on the landslide movement process.Subsequently,the landslide movement process and the final accumulation characteristics are analyzed from multiple perspectives.The results show that the violent starting velocity affects the landslide motion characteristics,which is found to be about 4 m/s in the Baige landslide.The movement process of the Baige landslide involves four stages:initiation,high-speed sliding,impact-climbing,low-speed motion and accumulation.The accumulation states of sliding masses in different zones are different,which essentially corresponds to reality.The research results suggest that the modified DDA is applicable to similar high-level rock landslides.
文摘针对转向架构架磁粉探伤缺陷识别环节人工目测效率低的现状,提出一种基于YOLO-CET(You Only Look Once based on CoTNet-Efficient-Transformer blocks)的探伤图像缺陷自动识别算法,实现对构架表面真伪缺陷的智能识别。以YOLOv5(You Only Look Once version 5)为基础模型,在骨干特征提取网络引入轻量化CoTNet(Contextual Transformer Networks)网络层,实现缺陷特征的多尺度融合与提取。加入高效通道注意力机制,在不增加网络计算量的同时提高模型的鲁棒性和泛化性。增加一个小尺寸缺陷检测头用于减轻不同尺寸特征带来的尺度方差影响,同时引入视觉自注意力模块,增强小目标缺陷的抓取识别能力。利用自建的构架表面缺陷探伤数据集进行测试,结果表明,与YOLOv5相比,所提出的YOLO-CET使检测平均精度提升33.8%,F1-Score提升0.26,浮点运算量仅增加1.5 B,该模型可实现缺陷的自动检测,有效解决背景误判、细小缺陷漏检等问题。
基金supported by the National Natural Sciences Foundation of China (NSFC) grant numbers [31960165&81760288]
文摘CD38 is known to play roles in various inflammatory pathways.However,whether it has a protective or detrimental effect during bacterial septicemia remains disputed.Herein,this study aimed to determine the potential effect of CD38 on renal injury in septicemia.Escherichia coli(E.coli)was used to induce sepsis-associated renal injury in mice.WT and CD38-/-mice were stimulated with E.coli.After three hours,the serum was collected to detect renal function.Function mRNA expressions inflammatory cytokines in kidneys were quantified by real-time PCR.Hematoxylin and eosin staining were used to observe the histomorphology of kidney.The expression of TLR4,NF-κB,MAPK and cytokines were detected by Western Blot.Our results demonstrated that 3×10^(8) cfu/mL E.coli is the appropriate dose to induce sepsis mice model.Compared to WT sepsis mice,CD38-/-mice showed aggravated kidney injuries with impaired renal function,increased inflammation and apoptosis after E.coli stimulation.Interestingly,CD38 deficiency also led to elevated expression of TLR4 and increased phosphorylation of NF-κB p65/p105 and ERK1/2.To sum up,our results suggested that CD38 deficiency could aggravate E.coli-induced renal injury through activating ERK1/2-NF-κB signaling pathway.
