Modelling a ceramic foam using locally adaptable morphology

In this paper, a ceramic open foam is modelled using a two‐step procedure. First, a random Laguerre tessellation is fitted to the edge system of the polyurethane foam forming the core of the ceramic foam. In a second phase, a model of the ceramic foam is obtained using dilations with balls of locally varying size. The model fitting is based on geometric characteristics of both polyurethane and ceramic foam estimated from reconstructed tomographic images of these structures.     

Stereological analysis of the spatial Poisson–Voronoi tessellation

Stereological model tests and parameter estimators for the spatial Poisson–Voronoi tessellation are discussed. The tests aim to discriminate the Poisson–Voronoi tessellation from more regular or more irregular tessellations. The power of the model tests under some special parametric alternative hypotheses is investigated by simulation. Among the tests considered, the most powerful test is based on the variance of the section cell areas. Various stereological estimators for the model parameter of the spatial Poisson–Voronoi tessellation are compared with respect to their bias and variance by means of a Monte–Carlo study. Formulae are given for variance prediction. An estimator based on vertex counting is found to be the best. Robustness is investigated by applying the estimators to Voronoi tessellations generated by other point process models.     

基于截面复合曲线约束重构的反求工程参数化建模

提出了基于截面复合曲线约束重构的反求工程参数化建模方法,并对其中的截面数据获取、平面离散曲线分段及整体约束逼近等关键技术进行了系统研究。给出了截面数据获取的点云切片法;设计了拟合误差控制下直线段与圆弧段数据分离的区域生长法;建立了截面复合曲线整体约束逼近的最优化数学模型,并用Lagrange乘子法进行了优化模型求解。最后给出了一基于约束重构的截面复合曲线进行反求工程参数化建模的实例。     

Spatially resolved fluorescence lifetime mapping of enzyme kinetics in living cells

Traditional cuvette‐based enzyme studies lack spatial information and do not allow real‐time monitoring of the effects of modulating enzyme functions in vivo. In order to probe the realistic timescales of steric modifications in enzyme–substrate complexes and functional binding–unbinding kinetics in living cells without losing spatial information, it is imperative to develop sensitive imaging strategies that can report enzyme kinetics in real time over a wide dynamic range of timescales. Here we present a multi‐photon excitation‐based, ultra‐fast photon detection using a streak camera and Laguerre expansion‐based fast deconvolution approach for achieving high spatio‐temporal resolution in monitoring real‐time enzyme kinetics in single cells. In particular, we report spatially resolved, nanosecond‐scale fluorescence dynamics associated with binding–unbinding kinetics of endogenous metabolic co‐factor nicotinamide adenine dinucleotide with enzymes in intact living cells. By monitoring real‐time kinetics of NAD(P)H–enzyme kinetics in primary hepatocytes isolated from young and aged mouse models, we observed that the mechanism of inhibition of mitochondrial respiration at complex I site is mediated by redistribution of free and protein‐bound nicotinamide adenine dinucleotide pools and that this equilibrium redistribution is affected by age‐related modifications in mitochondrial function. We describe unique advantages of Laguerre deconvolution algorithm in comparison with conventional lifetime analysis approaches. Non‐invasive monitoring of metabolic dysfunctions in intact animal models is an attractive strategy for gaining insight into the dynamics of tissue metabolism in health and in various metabolic syndromes such as cancer, diabetes and aging‐induced metabolic dysfunctions. Besides the example demonstrated above, we envisage that the proposed method can find applications in a variety of other situations where intensity‐based approaches fall short owing to spectroscopic artefacts.     

基于SolidWorks的截面草图曲线约束优化技术研究

二维截面曲线重建与正向设计技术相结合是实现复杂外形产品CAD模型重建的重要方法。针对该问题提出了基于SolidWorks软件草图的二维截面曲线约束优化技术,并对截面草图曲线的拟合表达、约束表达和约束优化模型的建立及其求解等关键技术进行了深入研究。应用实例表明,基于SolidWorks的截面草图曲线约束优化方法可以得到在满足约束条件下的数据点列最优逼近曲线,基于该优化曲线可以高效、准确地构建出复杂外形产品的曲面模型。     

Characterization and reconstruction of 3D stochastic microstructures via supervised learning

The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing–structure–property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user‐defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples.     

基于区域划分的多特征纹理图像分割

由于纹理图像的复杂性和多样性,仅依靠传统的单一特征实现纹理图像分割无法满足其对分割精度的要求。本文提出结合区域划分的多特征纹理图像分割方法。首先,依据像素灰度的空间相关性定义多个纹理特征;然后利用区域划分将图像域划分成不同子区域,待分割同质区域由这些子区域拟合而成;通过分别定义多个特征图像的同质区域之间的异质性势能函数和刻画各子区域邻域关系势能函数来定义全局势能函数,并构建非约束吉布斯概率分布,从而建立纹理分割模型;最后,采用M-H算法采样上述概率分布,从而获得最优图像分割结果。分别对模拟纹理图像、遥感图像、自然纹理图像和SAR海冰图像进行了分割实验,并与利用单一特征得到的分割结果进行对比分析,定性和定量的测试结果验证了算法的有效性。     

3D analysis of synaptic vesicle density and distribution after acute foot‐shock stress by using serial section transmission electron microscopy

Behavioural stress has shown to strongly affect neurotransmission within the neocortex. In this study, we analysed the effect of an acute stress model on density and distribution of neurotransmitter‐containing vesicles within medial prefrontal cortex. Serial section transmission electron microscopy was employed to compare two groups of male rats: (1) rats subjected to foot‐shock stress and (2) rats with sham stress as control group. Two‐dimensional (2D) density measures are common in microscopic images and are estimated by following a 2D path in‐section. However, this method ignores the slant of the active zone and thickness of the section. In fact, the active zone is a surface in three‐dimension (3D) and the 2D measures do not accurately reflect the geometric configuration unless the active zone is perpendicular to the sectioning angle. We investigated synaptic vesicle density as a function of distance from the active zone in 3D. We reconstructed a 3D dataset by estimating the thickness of all sections and by registering all the image sections into a common coordinate system. Finally, we estimated the density as the average number of vesicles per area and volume and modelled the synaptic vesicle distribution by fitting a one‐dimensional parametrized distribution that took into account the location uncertainty due to section thickness. Our results showed a clear structural difference in synaptic vesicle density and distribution between stressed and control group with improved separation by 3D measures in comparison to the 2D measures. Our results showed that acute foot‐shock stress exposure significantly affected both the spatial distribution and density of the synaptic vesicles within the presynaptic terminal.     

New methods of Laguerre pole optimization for the ARX model expansion on Laguerre bases

The ARX-Laguerre model is a very important reduced complexity representation of linear system. However a significant reduction of this model is subject to an optimal choice of both Laguerre poles. Therefore we propose in this paper two new methods to estimate, from input/output measurements, the optimal values of Laguerre poles of the ARX-Laguerre model. The first method is based on the Newton-Raphson's iterative technique where we prove that the gradient and the Hessian can be expressed analytically. The second method is based on Genetic Algorithms. Both proposed algorithms are tested on a numerical example and on a heating benchmark.     

Near-field measurement of short-range correlation in optical waves transmitted through random media

Two‐dimensional near‐field images of speckle patterns formed by optical waves transmitted through a disordered porous silica glass sample are measured. The corresponding 2D intensity correlation function, C, is extracted. The subwavelength spatial resolution of near‐field microscopy allows us to resolve in the spatial distribution of C the expected subwavelength oscillations and to follow their dependence on the excitation wavelength. Finally, we deduce the effective refractive index of the material by fitting the theoretical spatial dependence of C to our experimental results.     

基于点云三维重建技术的甲状腺超声穿刺三维导航研究

设计了一种基于超声自动扫描机器人的甲状腺点云三维重建系统,并与甲状腺超声截面穿刺机器人系统相融合,实现并验证了一套甲状腺超声穿刺三维导航的软硬件方案.通过甲状腺自动超声扫查机器人获得了１组带有准确空间位姿信息的甲状腺超声图像,并且通过传统图像算法和深度学习方法分割出甲状腺组织的区域.此后通过点云重建和空间重建方案获得了甲状腺模型,并将超声模型与CT扫查模型及机械臂模型进行空间配准和数据融合,依此在软件界面为医生提供了穿刺手术的多视角三维空间信息,在减轻手术医师负担的同时提升了穿刺手术的精准度和成功率.通过实验分析了扫描控制算法和三维重建算法的可行性和稳定性,并验证了该三维导航系统的导航空间精度和响应速度.     

基于准线-母线的空间孔位姿重建

空间孔位姿重建广泛存在于工业和建筑领域。针对空间孔位姿重建提出一种准线-母线法,其原理为根据孔横断面上的边缘点拟合孔准线,分别过孔柱面其他少量任意点,以假定轴线的方向为方向作孔柱面母线,采用LM(Levenberg-Marquard)法优化各条母线与孔横断面的交点到孔准线距离代数和最小得到孔轴线方向,孔准线中心可作为孔位置。实验表明,该方法需要数据量少、过程简单、精度高,也适用于轴位姿及其他柱面位姿重建。     

Challenges of microtome‐based serial block‐face scanning electron microscopy in neuroscience

Serial block‐face scanning electron microscopy (SBEM) is becoming increasingly popular for a wide range of applications in many disciplines from biology to material sciences. This review focuses on applications for circuit reconstruction in neuroscience, which is one of the major driving forces advancing SBEM. Neuronal circuit reconstruction poses exceptional challenges to volume EM in terms of resolution, field of view, acquisition time and sample preparation. Mapping the connections between neurons in the brain is crucial for understanding information flow and information processing in the brain. However, information on the connectivity between hundreds or even thousands of neurons densely packed in neuronal microcircuits is still largely missing. Volume EM techniques such as serial section TEM, automated tape‐collecting ultramicrotome, focused ion‐beam scanning electron microscopy and SBEM (microtome serial block‐face scanning electron microscopy) are the techniques that provide sufficient resolution to resolve ultrastructural details such as synapses and provides sufficient field of view for dense reconstruction of neuronal circuits. While volume EM techniques are advancing, they are generating large data sets on the terabyte scale that require new image processing workflows and analysis tools. In this review, we present the recent advances in SBEM for circuit reconstruction in neuroscience and an overview of existing image processing and analysis pipelines.     

Out‐of‐focus background subtraction for fast structured illumination super‐resolution microscopy of optically thick samples

We propose a structured illumination microscopy method to combine super resolution and optical sectioning in three‐dimensional (3D) samples that allows the use of two‐dimensional (2D) data processing. Indeed, obtaining super‐resolution images of thick samples is a difficult task if low spatial frequencies are present in the in‐focus section of the sample, as these frequencies have to be distinguished from the out‐of‐focus background. A rigorous treatment would require a 3D reconstruction of the whole sample using a 3D point spread function and a 3D stack of structured illumination data. The number of raw images required, 15 per optical section in this case, limits the rate at which high‐resolution images can be obtained. We show that by a succession of two different treatments of structured illumination data we can estimate the contrast of the illumination pattern and remove the out‐of‐focus content from the raw images. After this cleaning step, we can obtain super‐resolution images of optical sections in thick samples using a two‐beam harmonic illumination pattern and a limited number of raw images. This two‐step processing makes it possible to obtain super resolved optical sections in thick samples as fast as if the sample was two‐dimensional.     

基于宏—细观模型的疲劳裂纹萌生数值模拟

为了研究材料微观特性对结构疲劳寿命的影响,提高结构疲劳寿命预估精度,根据Tanaka-Mura单一微裂纹及裂尖微裂纹萌生寿命预测模型,模拟疲劳载荷下某马氏体钢孔边疲劳裂纹萌生寿命。利用泰森多边形生成法,生成代表多晶结构的二维特征单元。考虑晶粒内相互垂直的多滑移特性以及已起裂裂纹对相邻晶粒裂纹萌生的影响,建立微裂纹起裂与扩展的改进模型。中心孔平板试件疲劳寿命的数值模拟结果与试验值吻合良好,说明给出的改进宏细观疲劳寿命预测模型的有效性。     

A three‐dimensional statistical model for imaged microstructures of porous polymer films

A thresholded Gaussian random field model is developed for the microstructure of porous materials. Defining the random field as a solution to stochastic partial differential equation allows for flexible modelling of nonstationarities in the material and facilitates computationally efficient methods for simulation and model fitting. A Markov Chain Monte Carlo algorithm is developed and used to fit the model to three‐dimensional confocal laser scanning microscopy images. The methods are applied to study a porous ethylcellulose/hydroxypropylcellulose polymer blend that is used as a coating to control drug release from pharmaceutical tablets. The aim is to investigate how mass transport through the material depends on the microstructure. We derive a number of goodness‐of‐fit measures based on numerically calculated diffusion through the material. These are used in combination with measures that characterize the geometry of the pore structure to assess model fit. The model is found to fit stationary parts of the material well.     

基于基准面提取的物料体积在线测量方法

针对测量装置与物料放置底面相对姿态变化影响测量结果的问题,提出一种实时校正及积分基准面提取的物料体积测量方法。该方法通过姿态传感器实时检测激光传感器的姿态,并获取被测物体表面点云,对点云归一化处理,多次迭代拟合确定积分基准面及被测物料边界,进行三维重建,最后提出基于剖分原理的三棱微元逼近的体积计算方法。利用提出的测量方法搭建测量系统,在多种工况下进行实测实验和对比分析,测量结果的平均相对误差为1.69%,表明提出的方法具有较好的适应性及准确性,为物料体积测量提供了新思路。     

基于微观晶相建模的双相钢吸能特性研究

基于Voronoi和概率分布理论,提出材料微观晶相建模方法及其实现流程,建立微观晶相可视化几何模型。通过将微观晶相生成系统和ABAQUS有限元软件相结合,实现了基于微观晶相建模的双相钢有限元仿真,仿真中单相铁素体及马氏体均采用理想弹塑性材料模型,同时,以延性损伤模型模拟材料的破坏行为。以该仿真模型为基础,建立一系列不同晶粒尺寸、不同马氏体体积分数的双相钢微观晶相仿真模型,进行双相钢吸能特性研究,研究表明虽然双相钢吸能量随晶粒尺寸的不同略有差异,但总体均随马氏体体积分数的增加呈现先上升后下降的趋势,最优吸能时双相钢中马氏体体积分数均在2%~5%范围内。实现了双相钢微观尺度下的吸能研究,为轻量化汽车车身安全件的选材提供指导。