Analytical study of surface wave multiple refraction in boundary of a scalar impedance surface with a tensor impedance surface

In this paper, the multiple refraction phenomenon is investigated on the boundary of a scalar impedance surface (SIS) and a tensor impedance surface (TIS). When a surface wave (SW) propagates on the SIS and radiates to the boundary of the TIS, the propagation direction of it is changed and the refraction phenomenon is accrued. The method that is proposed in this paper can predict the multiple refraction for the SW. Moreover, another analytical method is introduced for designing the proposed structure which the double refraction (DR) occurs at arbitrary angles on it. Using it, a sample of the structure is designed by printed circuits in 15.2GHz and the results are verified by the full‐wave simulation and measurement. The results are shown that in the structure, DR is occurred in 2° and 22° as predicted. The proposed method can provide many applications such as design of SW power dividers based on the TISs, impedance surface based waveguides, holographic antennas, and feeding of array antennas.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

Shape from focus based on 3D structure tensor using optical microscopy

Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape.     

A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

A large-scale dynamically weighted directed network (DWDN) involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications, like in a terminal interaction pattern analysis system (TIPAS). It can be represented by a high-dimensional and incomplete (HDI) tensor whose entries are mostly unknown. Yet such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN. A latent factorization-of-tensors (LFT) model proves to be highly efficient in extracting such knowledge from an HDI tensor, which is commonly achieved via a stochastic gradient descent (SGD) solver. However, an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale DWDNs. To address this issue, this work proposes a proportional-integral-derivative (PID)-incorporated LFT model. It constructs an adjusted instance error based on the PID control principle, and then substitutes it into an SGD solver to improve the convergence rate. Empirical studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models, the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.      

爆炸排淤填石法中淤泥的本构模型

以爆炸排淤填石法为背景 ,对不同应变率阶段淤泥的本构模型进行了分析 ,利用ANSYS/LS-DYNA动态有限元分析程序对所选择的模型进行验证和确认。计算和分析结果表明 :在形成爆炸空腔的高应变率阶段 ,淤泥表现为理想不可压缩流体的性质 ;在小药量小抵抗线条件下 ,甚至在淤泥自重作用下的较低应变率变形阶段 ,其黏性效应也可以忽略不计。     

边界单元法在露天矿边坡疏干排水工程中的应用

该文首先讨论了边界无法处理渗流问题的计算原理,针对露天矿山边坡裂隙岩体的渗透特性,建立二维渗流模型,采用边界元数值方法模拟分析各向异性岩体地下水在排水孔疏于过程中的渗流场分布特征,并应用于露天矿现场实例之中。     

一种新型钢丝绳夹具的设计

基于钢丝绳的结构特点及受载情况,设计制作了一种新型钢丝绳夹具。该夹具夹紧过程既方便快捷又安全高效,尤其适用于大张力钢丝绳施工、测试及锚定前的夹紧过程中。     

裂隙岩体渗透张量的确定和修正

分析了实验室法、现场测试法、裂隙采样测量法和反演法确定裂隙岩体渗透张量的优缺点。提出了用单孔压水试验修正裂隙采样测量裂隙岩体渗透张量的确定方法，并采用该方法对某大型磁铁矿边坡进行了岩体渗透张量的测定。试验表明，该方法能较好刻画裂隙岩体渗透特性的各向异性，更好地消除裂隙非贯通性和充填物的影响以及压水试验尺寸的效应影响。     

龙滩水电站左岸高边坡裂隙岩体渗透张量遗传反演

应用遗传算法对龙滩水电站工程左岸高边坡地区岩体渗透性参数作了反演 ,计算结果精度较好 ,与实际地质资料分析结论基本一致 ,表明遗传反演方法在实际工程中应用是可行的     

温度饱和水下的裂隙岩体力学特性研究*

在理论上，利用O‘Connell的饱和水裂隙岩体等效弹性模量与岩石模量的关系式，并由式中的裂隙密度概念意义，建立了温度作用下的裂隙密度与Oda提出的裂隙张量之间的关系式；在试验的基础上，给出了温度、饱和水下的单裂隙岩体应力－应变、抗压强度回归拟合关系表达式。并通过试验与拟合结果对以加以验证，其裂隙岩体力学模型可为裂隙岩体THM耦合分析提供合理的依据。