Effect of an abrupt change in pulling rate on microstructures of directionally solidified Al2O3-Er3Al5O12 eutectic and off-eutectic composite ceramics

Directionally solidified microstructures of Al₂O₃-Er₃Al₅O₁₂ eutectic and off-eutectic in situ composite ceramics were explored under abrupt-change pulling rate conditions. Corresponding temperature distributions and interface locations were studied. In eutectic composition, fluctuation of eutectic spacing occurred when the pulling rate increased abruptly. A gradually increase or abrupt increase in eutectic spacing was observed when the pulling rate decreased abruptly. In hypoeutectic and hypereutectic compositions, formation of the primary phases were suppressed when the pulling rate increased abruptly from 10?µm/s to 100?µm/s, while primary phases precipitated when the pulling rate decreased abruptly from 100?µm/s to 10?µm/s. The interface altitude decreased after the pulling rate increased abruptly, but increased after the pulling rate decreased abruptly. The liquid composition restriction (around the eutectic composition) at the eutectic interface plays an important role in the suppression of the primary dendrite and coupled eutectic oxides can be obtained in off-eutectic compositions even under higher solidification rate conditions.     

内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

水资源承载力分析研究

水是人们生存必不可少的资源,是生产与生活的基础,但水资源短缺,时间、空间分布不均,利用率低,已成为制约各地经济可持续发展的重要因素之一。本文所选研究区域——昌宁县正处于经济快速发展时期,水资源承载力将会影响其发展,文章综合文献分析和实际调研数据,运用科学的方法进行水资源的承载力分析,结果表明:昌宁县水资源承载力目前与社会经济的发展相适应,但远期将会有所不足,因而要求协调人与自然的矛盾,促进昌宁县的可持续发展。     

古建筑木结构透榫节点力学模型研究

为研究古建筑木结构透榫节点的M-θ力学模型，在分析透榫节点构造特征与受力机理的基础上，建立其数值模型，用透榫节点的试验数据验证了该数值模型的正确性，并分析了节点缝隙、木材横纹弹性模量和大榫头长度对透榫节点受弯承载力的影响。根据受力分析结果，建立以弹性点、屈服点与极限点为特征点的三折线多参数M-θ力学模型，其结果与多数的试验结果基本吻合，并将该力学模型应用于木构架的受力分析。研究结果表明：透榫节点的滞回耗能能力强，节点的变形主要集中在榫头处。当榫头与卯口之间的缝隙增大时，节点的受弯承载力降低。随木材横纹弹性模量的提高和大榫头长度的增加，节点的受弯承载力有一定提高。文章建立的M-θ力学模型能较好反映透榫节点的受力过程，适用于木构架的受力分析，其荷载 位移骨架曲线与试验结果基本吻合。研究成果可为古建筑木结构的维修与保护提供参考。     

Mechanophysical Cues in Extracellular Matrix Regulation of Cell Behavior

The extracellular matrix (ECM) is a macromolecular network that can provide biochemical and structural support for cell adhesion and formation. It regulates cell behavior by influencing biochemical and physical cues. It is a dynamic structure whose components are modified, degraded, or deposited during connective tissue development, giving tissues strength and structural integrity. The physical properties of the natural ECM environment control the design of naturally or synthetically derived biomaterials to guide cell function in tissue engineering. Tissue engineering is an important field that explores physical cues of the ECM to produce new viable tissue for medical applications, such as in organ transplant and organ recovery. Understanding how the ECM exerts physical effects on cell behavior, when cells are seeded in synthetic ECM scaffolds, is of utmost importance. Herein we review recent findings in this area that report on cell behaviors in a variety of ECMs with different physical properties, i.e., topology, geometry, dimensionality, stiffness, and tension.     

Microwave dielectric properties of SrLa[Ga1−x(Mg0.5Ti0.5)x]O4 and SrLa[Ga1−x(Zn0.5Ti0.5)x]O4 (x = 0.2-0.8) ceramics

SrLa[Ga_1−x(R_0.5Ti_0.5)_x]O₄ (R = Mg, Zn) ceramics were prepared by a standard solid state sintering method. The single-phase ceramics with K₂NiF₄-type layered perovskite structure and I4/mmm space group were obtained, indicating that SrLa(R_0.5Ti_0.5) and SrLaGaO₄ can form the unlimited solid solutions. With increasing x for R = Mg and Zn, ε_r increases monotonously, the Qf value first increases and then decreases, while τ_f increases from a negative to a positive value. The optimized microwave dielectric properties were obtained as following: ε_r = 23.3, Qf = 89 400 GHz, τ_f = −0.8 ppm/°C for SrLa[Ga_0.6(Mg_0.5Ti_0.5)_0.4]O₄ and ε_r = 23.3, Qf = 76 200 GHz, τ_f = 0.2 ppm/°C for SrLa[Ga_0.7(Zn_0.5Ti_0.5)_0.3]O₄, indicating that the present solid solution ceramics are the promising candidates as microwave resonator materials for the telecommunication applications.     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。