The adoption of Docker containers has revolutionized software deployment by providing a lightweight and efficient way to isolate applications in data centers. However, securing these containers, especially when handli...The adoption of Docker containers has revolutionized software deployment by providing a lightweight and efficient way to isolate applications in data centers. However, securing these containers, especially when handling sensitive data, poses significant challenges. Traditional Linux Security Modules (LSMs) such as SELinux and AppArmor have limitations in providing fine-grained access control to files within containers. This paper presents a novel approach using eBPF (extended Berkeley Packet Filter) to implement a LSM that focuses on file-oriented access control within Docker containers. The module allows the specification of policies that determine which programs can access sensitive files, providing enhanced security without relying solely on the host operating system’s major LSM.展开更多
针对蔡司快速超高分辨激光共聚焦显微镜(LSM 900 with Airyscan2)的成像性能优化问题,该研究系统探究了激光功率、探测器增益、像素驻留时间、平均采样次数及Airyscan成像模式选择等关键参数对分辨率、信噪比(SNR)及成像速度的协同影响...针对蔡司快速超高分辨激光共聚焦显微镜(LSM 900 with Airyscan2)的成像性能优化问题,该研究系统探究了激光功率、探测器增益、像素驻留时间、平均采样次数及Airyscan成像模式选择等关键参数对分辨率、信噪比(SNR)及成像速度的协同影响。通过设计多组对比实验,量化了不同参数组合下的成像性能指标,提出了一套兼顾高分辨率、高信噪比与快速成像的优化策略。结果显示,在Airyscan SR模式下,通过平衡激光功率(0.1%~50%)、探测器增益(550~850 V)及像素驻留时间(0.5~4.0μs)、平均采样次数(0~8次),可实现xy方向分辨率≤120 nm。该研究为超分辨成像参数优化提供了可操作的参数优化框架,对生物医学超分辨成像研究具有重要参考价值。展开更多
The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during o...The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during optimization makes the results highly dependent on the initial design.Although topological derivatives are often introduced to enable hole nucleation,their conversion into effective shape derivatives remains challenging,limiting topological evolution.To address this,a level set topology optimization method with autonomous hole formation(LSM-AHF)is proposed,integrating the material removal mechanism of the SIMP(Solid Isotropic Material with Penalization)method into the LSM framework.First,an initial structure is generated by adjusting the judgment threshold,and a binary thresholding algorithm is subsequently employed to obtain a clear and well-defined geometry.The structural boundaries of this geometry are then identified and used to construct a signed distance field,which serves as the initial level set function.To ensure smooth transitions across material interfaces and enhance numerical stability,Gaussian filtering is subsequently applied to the distance field.Numerical results demonstrate that LSMAHF effectively enables hole nucleation without manual initialization and improves topology change,addressing the respective limitations of conventional LSM and SIMP methods.展开更多
Additive manufacturing(AM)has revolutionized modern manufacturing,but the application of magnesium(Mg)alloys in laser-based AM remains underexplored due to challenges such as oxidation,low boiling point,and thermal ex...Additive manufacturing(AM)has revolutionized modern manufacturing,but the application of magnesium(Mg)alloys in laser-based AM remains underexplored due to challenges such as oxidation,low boiling point,and thermal expansion,which lead to defects like porosity and cracking.This study provides a comprehensive analysis of microstructure changes in WE43 magnesium(Mg)alloy after laser surface melting(LSM),examining grain morphology,orientation,size,microsegregation,and defects under various combinations of laser power,scan speed,and spot size.Ourfindings reveal that variations in laser power and spot size exert a more significant influence on the depth and aspect ratio of the keyhole melt pool compared to laser scan speed.Critically,we demonstrate that laser energy density,while widely used as a quantitative metric to describe the combined effects of process parameters,exhibits significant limitations.Notable variations in melt pool depth,normalized width,and microstructure with laser energy density were observed,as reflected by low R²values.Additionally,we underscore the importance of assessing the temperature gradient across the width of the melt pool,which determines whether conduction or keyhole melting modes dominate.These modes exhibit distinct heatflow mechanisms and yield fundamentally different microstructural outcomes.Furthermore,we show that the microstructure and grain size in conduction mode exhibit a good correlation with the temperature gradient(G)and solidification rate(R).This research provides a framework for achieving localized microstructural control in LSM,providing insights to optimize process parameters for laser-based 3D printing of Mg alloys,and advancing the integration of Mg alloys into AM technologies.展开更多
The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across divers...The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across diverse geological settings.Large-scale models(LSMs),with vast parameter spaces and extensive training datasets,excel in solving complex visual problems.This study explores the potential of using one such LSM,Segment anything model(SAM),to identify facet-type discontinuities across several outcrops via interactive prompting.The findings demonstrate that SAM effectively segments two-dimensional(2D)discontinuities,with its generalization capability validated on a dataset of 2426 identified discontinuities across 170 outcrops.The model achieves 0.78 mean IoU and 0.86 average precision using 11-point prompts.To extend to three dimensions(3D),a framework integrating SAM with Structure-from-Motion(SfM)was proposed.By utilizing the inherent but often overlooked relationship between image pixels and point clouds in SfM,the identification process was simplified and generalized across photogrammetric devices.Benchmark studies showed that the framework achieved 0.91 average precision,identifying 87 discontinuities in Dataset-3D.The results confirm its high precision and efficiency,making it a valuable tool for data annotation.The proposed method offers a practical solution for geological investigations.展开更多
文摘The adoption of Docker containers has revolutionized software deployment by providing a lightweight and efficient way to isolate applications in data centers. However, securing these containers, especially when handling sensitive data, poses significant challenges. Traditional Linux Security Modules (LSMs) such as SELinux and AppArmor have limitations in providing fine-grained access control to files within containers. This paper presents a novel approach using eBPF (extended Berkeley Packet Filter) to implement a LSM that focuses on file-oriented access control within Docker containers. The module allows the specification of policies that determine which programs can access sensitive files, providing enhanced security without relying solely on the host operating system’s major LSM.
基金supported by the National Natural Science Foundation of China[52475096]Guangxi Natural Science Fund for Distinguished Young Scholars[2025GXNSFFA069009]+2 种基金Bagui Outstanding Youth Program of Guangxi,ChinaNatural Science and Technology Innovation Development Doubling Plan Project of Guangxi University,China[2024BZRC010]Innovation Project of Guangxi Graduate Education,China[YCBZ2025014].
文摘The level set method(LSM)is renowned for producing smooth boundaries and clear geometric representations,facilitating integration with CAD environments.However,its inability to autonomously generate new holes during optimization makes the results highly dependent on the initial design.Although topological derivatives are often introduced to enable hole nucleation,their conversion into effective shape derivatives remains challenging,limiting topological evolution.To address this,a level set topology optimization method with autonomous hole formation(LSM-AHF)is proposed,integrating the material removal mechanism of the SIMP(Solid Isotropic Material with Penalization)method into the LSM framework.First,an initial structure is generated by adjusting the judgment threshold,and a binary thresholding algorithm is subsequently employed to obtain a clear and well-defined geometry.The structural boundaries of this geometry are then identified and used to construct a signed distance field,which serves as the initial level set function.To ensure smooth transitions across material interfaces and enhance numerical stability,Gaussian filtering is subsequently applied to the distance field.Numerical results demonstrate that LSMAHF effectively enables hole nucleation without manual initialization and improves topology change,addressing the respective limitations of conventional LSM and SIMP methods.
文摘Additive manufacturing(AM)has revolutionized modern manufacturing,but the application of magnesium(Mg)alloys in laser-based AM remains underexplored due to challenges such as oxidation,low boiling point,and thermal expansion,which lead to defects like porosity and cracking.This study provides a comprehensive analysis of microstructure changes in WE43 magnesium(Mg)alloy after laser surface melting(LSM),examining grain morphology,orientation,size,microsegregation,and defects under various combinations of laser power,scan speed,and spot size.Ourfindings reveal that variations in laser power and spot size exert a more significant influence on the depth and aspect ratio of the keyhole melt pool compared to laser scan speed.Critically,we demonstrate that laser energy density,while widely used as a quantitative metric to describe the combined effects of process parameters,exhibits significant limitations.Notable variations in melt pool depth,normalized width,and microstructure with laser energy density were observed,as reflected by low R²values.Additionally,we underscore the importance of assessing the temperature gradient across the width of the melt pool,which determines whether conduction or keyhole melting modes dominate.These modes exhibit distinct heatflow mechanisms and yield fundamentally different microstructural outcomes.Furthermore,we show that the microstructure and grain size in conduction mode exhibit a good correlation with the temperature gradient(G)and solidification rate(R).This research provides a framework for achieving localized microstructural control in LSM,providing insights to optimize process parameters for laser-based 3D printing of Mg alloys,and advancing the integration of Mg alloys into AM technologies.
基金support in dataset preparation.This study was funded by National Natural Science Foundation of China(Nos.42422704 and 52379109)Opening the fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(No.SKLGP2024K028)Science and Technology Research and Design Projects of China State Construction Engineering Corporation Ltd.(No.CSCEC-2024-Q-68).
文摘The identification of rock mass discontinuities is critical for rock mass characterization.While high-resolution digital outcrop models(DOMs)are widely used,current digital methods struggle to generalize across diverse geological settings.Large-scale models(LSMs),with vast parameter spaces and extensive training datasets,excel in solving complex visual problems.This study explores the potential of using one such LSM,Segment anything model(SAM),to identify facet-type discontinuities across several outcrops via interactive prompting.The findings demonstrate that SAM effectively segments two-dimensional(2D)discontinuities,with its generalization capability validated on a dataset of 2426 identified discontinuities across 170 outcrops.The model achieves 0.78 mean IoU and 0.86 average precision using 11-point prompts.To extend to three dimensions(3D),a framework integrating SAM with Structure-from-Motion(SfM)was proposed.By utilizing the inherent but often overlooked relationship between image pixels and point clouds in SfM,the identification process was simplified and generalized across photogrammetric devices.Benchmark studies showed that the framework achieved 0.91 average precision,identifying 87 discontinuities in Dataset-3D.The results confirm its high precision and efficiency,making it a valuable tool for data annotation.The proposed method offers a practical solution for geological investigations.
