Cascading multi-segment rupture process of the 2023 Turkish earthquake doublet on a complex fault system revealed by teleseismic P wave back projection method

In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.

Adaptive Boundary and Semantic Composite Segmentation Method for Individual Objects in Aerial Images

There are two types of methods for image segmentation.One is traditional image processing methods,which are sensitive to details and boundaries,yet fail to recognize semantic information.The other is deep learning methods,which can locate and identify different objects,but boundary identifications are not accurate enough.Both of them cannot generate entire segmentation information.In order to obtain accurate edge detection and semantic information,an Adaptive Boundary and Semantic Composite Segmentation method(ABSCS)is proposed.This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances.It includes adaptively dividing and modifying the aerial images with the proposed principles and methods,using the deep learning method to semantic segment and preprocess the small divided pieces,using three traditional methods to segment and preprocess original-size aerial images,adaptively selecting traditional results tomodify the boundaries of individual objects in deep learning results,and combining the results of different objects.Individual object semantic segmentation experiments are conducted by using the AeroScapes dataset,and their results are analyzed qualitatively and quantitatively.The experimental results demonstrate that the proposed method can achieve more promising object boundaries than the original deep learning method.This work also demonstrates the advantages of the proposed method in applications of point cloud semantic segmentation and image inpainting.

改进DeepLabV3+算法提取无作物田垄导航线

机器视觉导航是智慧农业的重要部分,无作物田垄的导航线检测是旱地移栽导航的关键。针对无作物田垄颜色信息相近、纹理差距小,传统图像处理方法适用性差、准确率低,语义分割算法检测速度慢、实时性差的问题,该研究提出一种基于改进DeepLabV3+的田垄分割模型。首先对传统DeepLabV3+网络进行轻量化设计,用MobileNetV2网络代替主干网络Xception,以提高算法的检测速度和实时性;接着引入CBAM(convolutional block attention module,CBAM)注意力机制,使模型能够更好地处理垄面边界信息;然后利用垄面边界信息获得导航特征点,对于断垄情况,导航特征点会出现偏差,因此利用四分位数对导航特征点异常值进行筛选,并采用最小二乘法进行导航线拟合。模型评估结果显示,改进后模型的平均像素精确度和平均交并比分别为96.27%和93.18%,平均检测帧率为84.21帧/s,优于PSPNet、U-Net、HRNet、Segformer以及DeepLabV3+网络。在不同田垄环境下,最大角度误差为1.2°,最大像素误差为9,能够有效从不同场景中获取导航线。研究结果可为农业机器人的无作物田垄导航提供参考。

New normalized nonlocal hybrid level set method for image segmentation

This article introduces a new normalized nonlocal hybrid level set method for image segmentation.Due to intensity overlapping,blurred edges with complex backgrounds,simple intensity and texture information,such kind of image segmentation is still a challenging task.The proposed method uses both the region and boundary information to achieve accurate segmentation results.The region information can help to identify rough region of interest and prevent the boundary leakage problem.It makes use of normalized nonlocal comparisons between pairs of patches in each region,and a heuristic intensity model is proposed to suppress irrelevant strong edges and constrain the segmentation.The boundary information can help to detect the precise location of the target object,it makes use of the geodesic active contour model to obtain the target boundary.The corresponding variational segmentation problem is implemented by a level set formulation.We use an internal energy term for geometric active contours to penalize the deviation of the level set function from a signed distance function.At last,experimental results on synthetic images and real images are shown in the paper with promising results.

Fe-Al-V三元系富铁角热力学优化

采用CALPHAD方法对Fe-Al-V三元系富铁角进行热力学优化,并首次提出采用三亚点阵模型描述三元金属间化合物L21相,即(Fe)2(Al,Fe)1(Fe,V)1。基于可靠的边界二元系热力学描述,结合Fe-Al-V三元系富铁角试验数据,通过优化获得了一套自洽准确的热力学模型参数。优化的模型参数可较满意地重现Fe-Al-V三元系富铁角的相平衡关系,弥补了商业数据库无法对其进行描述的不足,为钒微合金化轻质钢的设计开发提供可靠的理论基础。

Automatic Road Tunnel Crack Inspection Based on Crack Area Sensing and Multiscale Semantic Segmentation

The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of roadtunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combinedwith a deep neural network model is an effective means to realize the localization and identification of crackdefects on the surface of road tunnels.We propose a complete set of automatic inspection methods for identifyingcracks on the walls of road tunnels as a solution to the problem of difficulty in identifying cracks during manualmaintenance. First, a set of equipment applied to the real-time acquisition of high-definition images of walls inroad tunnels is designed. Images of walls in road tunnels are acquired based on the designed equipment, whereimages containing crack defects are manually identified and selected. Subsequently, the training and validationsets used to construct the crack inspection model are obtained based on the acquired images, whereas the regionscontaining cracks and the pixels of the cracks are finely labeled. After that, a crack area sensing module is designedbased on the proposed you only look once version 7 model combined with coordinate attention mechanism (CAYOLOV7) network to locate the crack regions in the road tunnel surface images. Only subimages containingcracks are acquired and sent to the multiscale semantic segmentation module for extraction of the pixels to whichthe cracks belong based on the DeepLab V3+ network. The precision and recall of the crack region localizationon the surface of a road tunnel based on our proposed method are 82.4% and 93.8%, respectively. Moreover, themean intersection over union (MIoU) and pixel accuracy (PA) values for achieving pixel-level detection accuracyare 76.84% and 78.29%, respectively. The experimental results on the dataset show that our proposed two-stagedetection method outperforms other state-of-the-art models in crack region localization and detection. Based onour proposedmethod, the images captured on the surface of a road tunnel can complete crack detection at a speed often frames/second, and the detection accuracy can reach 0.25 mm, which meets the requirements for maintenanceof an actual project. The designed CA-YOLO V7 network enables precise localization of the area to which a crackbelongs in images acquired under different environmental and lighting conditions in road tunnels. The improvedDeepLab V3+ network based on lightweighting is able to extract crack morphology in a given region more quicklywhile maintaining segmentation accuracy. The established model combines defect localization and segmentationmodels for the first time, realizing pixel-level defect localization and extraction on the surface of road tunnelsin complex environments, and is capable of determining the actual size of cracks based on the physical coordinatesystemafter camera calibration. The trainedmodelhas highaccuracy andcanbe extendedandapplied to embeddedcomputing devices for the assessment and repair of damaged areas in different types of road tunnels.

A Coastal Zone Segmentation Variational Model and Its Accelerated ADMM Method

Effective and efficient SAR image segmentation has a significant role in coastal zone interpretation. In this paper, a coastal zone segmentation model is proposed based on Potts model. By introducing edge self-adaption parameter and modifying noisy data term, the proposed variational model provides a good solution for the coastal zone SAR image with common characteristics of inherent speckle noise and complicated geometrical details. However, the proposed model is difficult to solve due to to its nonlinear, non-convex and non-smooth characteristics. Followed by curve evolution theory and operator splitting method, the minimization problem is reformulated as a constrained minimization problem. A fast alternating minimization iterative scheme is designed to implement coastal zone segmentation. Finally, various two-stage and multiphase experimental results illustrate the advantage of the proposed segmentation model, and indicate the high computation efficiency of designed numerical approximation algorithm.

Shield Excavation Analysis: Ground Settlement & Mechanical Responses in Complex Strata

This study delves into the effects of shield tunneling in complex coastal strata, focusing on how this constructionmethod impacts surface settlement, the mechanical properties of adjacent rock, and the deformation of tunnelsegments. It investigates the impact of shield construction on surface settlement, mechanical characteristics ofnearby rock, and segment deformation in complex coastal strata susceptible to construction disturbances. Utilizingthe Fuzhou Binhai express line as a case study, we developed a comprehensive numerical model using theABAQUS finite element software. The model incorporates factors such as face force, grouting pressure, jack force,and cutterhead torque. Its accuracy is validated against field monitoring data from engineering projects. Simulationswere conducted to analyze ground settlement and mechanical changes in adjacent rock and segments acrossfive soil layers. The results indicate that disturbances are most significant near the excavation zone of the shieldmachine, with a prominent settlement trough forming and stabilizing around 2.0–3.0 D from the excavation. Theexcavation face compresses the soil, inducing lateral expansion. As grouting pressure decreases, the segmentexperiences upward buoyancy. In mixed strata, softer layers witness increased cutting, intensifying disturbancesbut reducing segment floatation. These findings offer valuable insights for predicting settlements, ensuring segmentand rock safety, and optimizing tunneling parameters.

Study of the segmentation of active fault by the boundary element method──analysis of the Xianshuihe fault zone

On the basis of the recent geological surveys and the relevant studies of the Xianshuihe fault zone, this paper analyzes the seismogenic mechanism of some faults and characteristic morphology on the fault zone by the boundary element method and discusses the fault segmentation and the related distribution of the earthquake ruptures. The main conclusions are: For the first order segmentation, the Xianshuihe fault zone can be divided into three major segments (the northwestern Luhuo-Qianning segment, the middle linking fracture region and the southeastern Kangding segment). Among them, the differences are not only in geometry and structure, but also in mechanical property and dynamics. Some of the characteristic morphologies on the Xianshuihe fault zone reflect the effects in cumulative deformation due to long-term fault movement, and reveal the fault segmentation in different orders. Such morphologies control, to some extent, the developments and the distributions of the earthquake ruptures on the fault zone.

BSN:Photometric Light Curve Analysis of Two Contact Binary Systems LS Del and V997 Cyg

The light curve analyses and orbital period variations for two contact binary stars,LS Del and V997 Cyg,are presented in this work which was conducted in the frame of the Binary Systems of South and North project Ground-based photometric observations were performed at two observatories in France.We used the Transiting Exoplanet Survey Satellite(TESS)data for extracting times of minima and light curve analysis of the targe systems.The O-C diagram for both systems displays a parabolic trend.LS Del and V997 Cyg’s orbital periods are increasing at rates of dP/dt=7.20×10^(-08)days yr^(-1)and dP/dt=2.54×10^(-08)days yr^(-1),respectively Therefore,it can be concluded that mass is being transferred from the less massive star to the more massive component with a rate of dM/dt=-1.96×10^(-7)M_(⊙)yr^(-1)for the LS Del system,and dM/dt=-3.83×10^(-7)M_(⊙)yr-1for V997 Cyg.The parameters of a third possible object in the system are also considered.The PHysics Of Eclipsing BinariEs Python code was used to analyze the light curves.The light curve solutions needed a cold starspot due to the asymmetry in the LS Del system’s light curve maxima.The mass ratio fill-out factor,and star temperature all indicate that both systems are contact binary types in this investigation.Two methods were applied to estimate the absolute parameters of the systems:one method relied on the parallax of Gaia DR3,and the other used a P-M relationship.The positions of the systems are also depicted on the M-L,M-R q-L_(ratio),and logM_(tot)-logJ_(0)diagrams.We recommend that further observations and investigations be done on the existence of a fourth body in this system.

A Study on Reconstruction of Surface Wind Speed in China Due to Various Climate Variabilities

Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.

基于改进的V-Net模型肺结节分割算法的研究

由于CT图像是三维图像,在原始的V-Net模型分割中,易出现结节漏检和边界分割不清晰,以及损失函数Dice训练时不稳定等问题。根据这些问题,提出3D多尺度SE V-Net,简称MSEV-Net网络,同时通过联合损失函数来提高训练的稳定性。该网络模型在V-Net网络的基础上,使用多尺度卷积模块来替换原有的5×5×5卷积,同时在残差连接后加入SE通道注意力模块,通过不同尺度的特征融合和学习不同通道之间的关系,解决肺结节小不易分割的问题。同时在V-Net网络残差连接基础上加一条短跳跃连接,使得整个网络更好利用全局特征。联合损失函数选择Dice和交叉熵损失函数进行融合,可以很好地解决训练不稳定问题。提出的MSEV-Net网络模型和联合损失函数在平均分割准确率PA达到0.998,DSC达到0.837。实验结果表明,该方法在提高肺结节分割精度方面具有一定的效果。

基于地脉动H/V谱比法的红土场地卓越周期

为研究地脉动H/V谱比法在确定红土场地卓越周期中的适用性,对不同类别红土场地开展系统的地脉动测试。首先利用地脉动H/V谱比法中水平分量的不同组合方式处理地脉动测试数据,得到HVSR曲线;然后分析HVSR曲线,获取场地卓越周期,进而确定场地类别,划分场地岩土类型;最后结合钻孔勘探信息,验证了地脉动H/V谱比法在确定红土场地卓越周期中具有良好的适用性,且H/V谱比法中采用东西和南北向水平分量的矢量和组合方式可更加简便和准确地获取场地卓越周期。

Segmentation of Bacteria Image Based on Level Set Method

In biology ferment engineering,accurate statistics of the quantity of bacteria is one of the most important subjects. In this paper,the quantity of bacteria which was observed traditionally manuauy can be detected automatically. Image acquisition and processing system is designed to accomplish image preprocessing,image segmentation and statistics of the quantity of bacteria. Segmentation of bacteria images is successfully realized by means of a region-based level set method and then the quantity of bacteria is computed precisely,which plays an important role in optimizing the growth conditions of bacteria.

矮腿小倾角V形刚构桥梁设计方法

文中首先对矮腿小倾角V形刚构桥梁特点进行简单阐述,随后以某桥梁工程项目为例,对其设计方法进行深入研究,主要分析项目设计方案模型、设计参数、设计重点以及设计效果等内容。结果表明,矮腿小倾角V形刚构桥梁设计方法在实际应用中具有良好的可行性与安全性。

微动H/V谱比法提取基岩面埋深的方法技术研究与应用

基岩面埋深是公路工程建设中的重要参考依据。本文通过福建地区两个探测实例,研究了微动H/V谱比法探测基岩面埋深的方法技术,介绍了微动H/V(Horizontal to Vertical)谱比法提取基岩面埋深的方法原理。首先对微动单个三分量检波器采集地震记录进行处理和分析,获取了测点的峰值频率F 0。在钻孔较多的情况下,可根据钻孔的中风化岩深度与峰值频率F 0的幂函数拟合,得到了该区的经验参数a和b,从而可以计算整个测区每个测点的中风化岩深度三维分布。在钻孔较少的情况下,可根据测区内部分钻孔的孔内剪切波值计算该区的覆盖层平均横波速度,进而根据经验公式计算覆盖层厚度和基岩面三维埋深分布。两个探测实例研究结果表明:微动H/V谱比法是一种快速获取公路工程三维基岩面的方法,在一定条件下,相对误差能够控制在5%左右,能够满足工程勘察的需求。微动谱比法具有简便性和易操作性,点位可随机布置,几乎不受场地条件限制,能够取得较好的地质效果,可推广应用。

温度对丙烷选择氧化催化剂Mo-V-Te-Ox催化性能的影响分析

本文采用三氧化钼、水合硫酸氧钒和二氧化锑为主要原料,并添加氧化铈助剂,在不同温度下进行水热合成,并结合微波干燥和常规加热干燥,通过程序升温焙烧活化制备了复合氧化物Mo-V-Te-Ox催化剂。通过自建的气固相微型反应装置和气相色谱的联用对催化剂样品进行了活性评价。

肝粘贴悬吊法、W型悬吊肝左叶、前腹壁肝脏V型悬吊法在腹腔镜胃癌根治术中的应用

目的 探讨肝粘贴悬吊法、W型悬吊肝左叶、前腹壁肝脏V型悬吊法在腹腔镜胃癌根治术中应用。方法 2018年10月~2022年10月我院行腹腔镜胃癌根治术的胃癌病人79例,根据悬吊方法不同分为A组(26例)、B组(26例)和C组(27例)三组。A组采用肝粘贴悬吊法,B组采用W型悬吊肝左叶法,C组采用前腹壁肝脏V型悬吊法,三组均随访至术后6个月。比较三组手术指标、并发症发生率以及术前、术后7天的肝功能变化情况。结果 B组肝悬吊时间[(16.23±2.52)分钟]和手术时间[(318.48±30.62)分钟],大于A组的(2.64±0.61)分钟和(233.64±20.67)分钟,同时也大于C组的(12.43±1.56)分钟和(270.81±25.77)分钟,C组肝悬吊时间[(12.43±1.56)分钟]和手术时间[(270.81±25.77)分钟]大于A组的(2.64±0.61)分钟和(233.64±20.67)分钟。B组出血量[(224.51±20.27)ml]和术中输血例数(5例)、C组出血量[(223.54±21.87)ml]和术中输血例数(7例)低于A组出血量[(324.54±30.51)ml]和术中输血例数(15例),差异有统计学意义(P<0.05)。术后7天B组血清丙氨酸氨基转移酶(ALT)为(27.52±3.62) U/L,门冬氨酸氨基转移酶(AST)为(25.75±3.95) U/L,白蛋白(ALB)为(31.65±3.18) g/L,C组分别为(26.54±3.73) U/L、(26.34±3.82) U/L和(32.06±3.09) g/L,均较术前升高,且B、C组术后血清ALT、AST、ALB水平高于A组,差异有统计学意义(P<0.05);A组术后肝脏裂伤发生率(11.54%)、出血发生率(7.69%)较高,B组术中壁腹膜出血发生率(11.54%)较高,三组并发症发生率比较差异无统计学意义(P>0.05)。结论 肝粘贴悬吊法操作简单、省时,但不适用于左肝肥厚者,术后脱胶可能引起肝表面撕裂出血;W型悬吊效果良好,耗时稍长,适用于肥胖、肝左叶肥大病人;V型加纱布悬吊效果适中,耗时适中。

基于YOLOv5算法的圆心定位方法

准确地获取图像中圆形目标的圆心是目标识别和定位中的关键问题。目前圆心定位主要采用最小二乘拟合圆以及HOUGH变换方法,但这些方法在不同程度上存在着鲁棒性不强、对环境光线要求高、需提前调试参数确定阈值、复杂背景下效果急剧变差等局限性。针对该问题,提出一种综合运用YOLOv5算法、Grabcut算法和灰度质心法进行图像分类、图像分割和灰度重心算法求取圆心坐标。该方法使用YOLOv5对图像中的圆形目标进行粗定位,再通过图像分割方法分割出圆形目标,最后使用加权型的灰度重心算法准确定位出圆心坐标,实现对圆形标志的可靠定位。用多个实验比较了该算法与现有算法的精度和稳定性,实验表明,该算法与现有算法相比,在干扰及形变的情况下圆心定位平均相对误差保持在0.5pixel以内,而在干扰、强形变及目标残缺的情况下仍能保持在7 pixel以内,该算法不仅提高了圆形目标圆心检测的鲁棒性和准确性,而且具有良好的抗干扰性。

基于分段隔磁桥的V型转子永磁电机的振动噪声削弱方法

电动汽车用V型转子永磁电机中的电磁噪声是电动汽车噪声的主要来源,影响到乘车人的舒适度问题。本文以1台额定功率104 kW的电动汽车用V型永磁电机为研究对象,分析电机电磁噪声产生的原因,提出一种在转子中开设分段隔磁桥的方案以降低电机的振动噪声,并与不分段隔磁桥、双层分段隔磁桥方案进行比较。在Maxwell中建立仿真计算模型,并采用有限元法对多个优化方案的电机模型进行电磁性能、振动、噪声的分析比较,并通过样机的振动噪声试验证明了计算方法的正确性及准确性。结果表明,考虑到制作工艺等问题,采用单层分段隔磁桥能够在几乎不影响电磁性能的情况下,有效地减弱电机的电磁噪声。