Precession electron diffraction using a digital sampling method

A software-based method for collecting precession electron diffraction (PED) patterns is described. The PED patterns are obtained on a computer controlled transmission electron microscope. A series of electron diffraction (ED) patterns are collected as still ED frames at equal intervals, while the electron beam is precessed by one period (360°) around the optical axis. A PED pattern is obtained by combining the different ED frames, which resembles the sampling of a conventional PED pattern. Since intermediate ED frames are collected, it is possible to perform different post-processing strategies on the ED data. This can be used for geometric corrections to obtain accurate integrated intensities. The alignments and data collection are fully automated and controlled by software. The data quality is comparable to what can be achieved using specialized hardware for precession. The PED data can be used for structure solution and refinement with reasonably good R-values.     

Precession electron diffraction using a digital sampling method

A software-based method for collecting precession electron diffraction (PED) patterns is described. The PED patterns are obtained on a computer controlled transmission electron microscope. A series of electron diffraction (ED) patterns are collected as still ED frames at equal intervals, while the electron beam is precessed by one period (360°) around the optical axis. A PED pattern is obtained by combining the different ED frames, which resembles the sampling of a conventional PED pattern. Since intermediate ED frames are collected, it is possible to perform different post-processing strategies on the ED data. This can be used for geometric corrections to obtain accurate integrated intensities. The alignments and data collection are fully automated and controlled by software. The data quality is comparable to what can be achieved using specialized hardware for precession. The PED data can be used for structure solution and refinement with reasonably good R-values.     

跨平台的质谱蛋白回归定量和质量控制的参数方法

各质谱厂商通常使用不同的软件进行蛋白鉴定和定量,导致获得的数据和结果的通用性不佳。另外,目前蛋白质定量的准确性仍有提升空间。因此,开发一个标准化、自动化且定量更准确的蛋白质定量流程具有现实意义。采用肽段保留时间对齐和回归技术,可有效地减少中低丰度肽段鉴定信息缺失带来的影响,提高中低丰度蛋白的定量能力。一个综合考虑信号峰宽分布、保留时间分布以及肽段同位素模式分布等因素的肽段筛选器,可以有效地过滤掉不适宜定量的肽段信号,使肽段离子流色谱（XIC）峰定量面积的计算更为准确。该流程由数据开源转换、保留时间对齐与回归定量、肽段筛选器等模块构成,可准确定量不同平台产出的质谱数据,并明显改善低丰度蛋白的无标定量。经对比,该流程对蛋白质组学动态范围标准蛋白集（UPS2）的定量比MaxQuant和Proteome Discoverer的定量更准确。     

“Ab initio” structure solution from electron diffraction data obtained by a combination of automated diffraction tomography and precession technique

Using a combination of our recently developed automated diffraction tomography (ADT) module with precession electron technique (PED), quasi-kinematical 3D diffraction data sets of an inorganic salt (BaSO₄) were collected. The lattice cell parameters and their orientation within the data sets were found automatically. The extracted intensities were used for “ab initio” structure analysis by direct methods. The data set covered almost the complete set of possible symmetrically equivalent reflections for an orthorhombic structure. The structure solution in one step delivered all heavy (Ba, S) as well as light atoms (O). Results of the structure solution using direct methods, charge flipping and maximum entropy algorithms as well as structure refinement for three different 3D electron diffraction data sets were presented.     

Maximum-likelihood estimation applied to electron microscopic autoradiography

A new method for analysis of electron microscope autoradiographs is described which is based on the maximum-likelihood method of statistics for estimating the intensities of radioactivity in organelle structures. We adopted a Poisson statistical model to describe the autoradiographic grain distributions that we prove results from the underlying Poisson nature of the radioactive decays as well as the additive errors introduced during the formation of grains. Within the model, an interative procedure derived from the expectation-maximization algorithm of mathematical statistics is used to generate the maximum-likelihood estimates. The algorithm has the properties that at every stage of the iteration process the likelihood of the data increases; and for all initial nonzero starting points the algorithm converges to the maximum-likelihood estimates of the organelle intensities. The maximum-likelihood approach differs from the mask-analysis method, and other published quantitative algorithms in the following ways: (1) In deriving estimates of the radioactivity intensities the maximum-likelihood algorithm requires that we obtain the actual locations of the grains as well as the micrograph geometries; each micrograph is digitized so that both the grain locations as well as the geometries of the organelle structures can be used. (2) The maximum-likelihood algorithm iteratively computes the minimum-meansquared-error estimate of the underlying emission locations that resulted in the observed grain distributions, from which intensity estimates are generated; this algorithm does not minimize a chi-squared error statistic. (3) The maximum-likelihood approach is based on a Poisson model and is therefore valid for low-count experiments; there are no minimum constraints on data collection for any single organelle compartment. (4) The maximum-likelihood algorithm requires the form of the point-spread function describing the emission spread; a probability matrix based on the use of overlay masks is not required. (5) The maximum-likelihood algorithm does not change for different organelle geometries; arbitrary geometries are incorporated by maximizing the likelihood-function subject to the geometry constraints. We have performed a preliminary evaluation of the quantitative accuracy of the maximum-likelihood and mask-analysis algorithms. Based on two different phantoms in which we compared the squared error resulting from the two algorithms, we find that the new maximum-likelihood approach provides substantially improved estimates of the radioactivity intensities of the phantoms.     

Crystallographic image processing approach to crystal structure determination

It is shown that the crystallographic image-processing technique based on the weak-phase object approximation and on the combination of high-resolution electron microscopy and electron diffraction is applicable to crystal structure determination. The technique consists of two stages: image deconvolution and phase extension. In the first stage an image taken at an arbitrary defocus condition can be transformed into the structure image with the resolution limited by the resolution of the electron microscope. In the second stage the image resolution is enhanced to the diffraction resolution limit so that most unoverlapped atoms can be resolved individually in the final image. Although the experimental diffraction intensities are available for the image deconvolution, they must be corrected for the phase extension. The proposed empirical method of electron diffraction intensity correction seems effective for obtaining a set of corrected diffraction intensities which are approximately equal to square structure factors.
When the crystal structure under examination belongs to a known typical type, it is easy to propose the structure model by referring to the deconvoluted image which reveals the low-resolution structure, and the high-resolution structure can also be determined by image simulation.     

面向大规模定制的产品族结构与配置管理

在大规模定制环境下，现有的产品数据管理方法和工具在管理产品族数据时，将导致物料清单结构冗余和管理的低效率。为了满足大规模定制环境下产品族数据高效管理的需求，提出了一种基于类物料清单的产品族结构与配置管理的新方法，建立了产品族结构模型，并在此基础上研究了相应的产品变量配置生成机理。最后，给出了该模型和配置生成机理应用于摩托车产品族的结构与配置管理的实例。     

Adaptive Gregory Patch Approximation to Z-Map Data

A method is proposed for Gregory surface approximation to 3D array data points. Surface approximation is the process of constructing a compact representation to model an object surface based on a fairly large number of measured 3D data points. Based on an adaptive subdivision technique, the proposed method begins with a rough initialisation of the surface and progressively refines it in successive steps in the regions where the data is poorly approximated. The method has been implemented using piecewise bicubic Gregory patches with G 1 continuity. An advantage of this approach is that the refinement is essentially local, reducing the computational requirements that permit the processing of a large number of data points This method, combined with the inverse offsetting method, can be used to obtain an offset surface without self-interference. The offset surface can be used to generate gouging-free CL tool paths for machining compound surfaces on milling machines.     

A quantitative analysis of the cone-angle dependence in precession electron diffraction

Precession electron diffraction (PED) is a technique which is gaining increasing interest due to its ease of use and reduction of the dynamical scattering problem in electron diffraction. To further investigate the usefulness of this technique, we have performed a systematic study of the effect of precession angle on the mineral andalusite where the semiangle was varied from 6.5 to 32 mrad in five discrete steps. The purpose of this study was to determine the optimal conditions for the amelioration of kinematically forbidden reflections, and the measurement of valence charge density. We show that the intensities of kinematically forbidden reflections decay exponentially as the precession semiangle () is increased. We have also determined that charge density effects are best observed at moderately low angles (6.5–13 mrad) even though PED patterns become more kinematical in nature as the precession angle is increased further.     

Detection of suspicious objects on the basis of analysis of human X-ray images

A new approach is proposed for detection of suspicious objects in X-ray images for security assurance. The approach is based on using the statistical model of the image for detecting anomalies. The model is designed with the use of the “bag-of-words” with context definition of the word coordinates in the image during statistical pattern formation. It is experimentally demonstrated that this approach ensures adequate approximation of the result of detection of suspicious objects by humans.     

Interpretation of O K-edge EELS in zircon using a structural variation approach

This work describes an approach to interpret the near-edge fine structure of electron energy-loss spectroscopy (EELS) of O K-edge in zircon using a structural variation method. The positions and intensities of several peaks in the O K-edge EELS spectrum are assigned to specific structural parameters. It suggests that the near-edge structures in EELS can be used to measure atomic structure changes.     

Precession technique and electron diffractometry as new tools for crystal structure analysis and chemical bonding determination

We have developed a new fast electron diffractometer working with high dynamic range and linearity for crystal structure determinations. Electron diffraction (ED) patterns can be scanned serially in front of a Faraday cage detector; the total measurement time for several hundred ED reflections can be tens of seconds having high statistical accuracy for all measured intensities (1-2%). This new tool can be installed to any type of TEM without any column modification and is linked to a specially developed electron beam precession "Spinning Star" system. Precession of the electron beam (Vincent-Midgley technique) reduces dynamical effects allowing also use of accurate intensities for crystal structure analysis. We describe the technical characteristics of this new tool together with the first experimental results. Accurate measurement of electron diffraction intensities by electron diffractometer opens new possibilities not only for revealing unknown structures, but also for electrostatic potential determination and chemical bonding investigation. As an example, we present detailed atomic bonding information of CaF(2) as revealed for the first time by precise electron diffractometry.     

Rotating machine fault diagnosis using dimension reduction with linear local tangent space alignment

A novel fault diagnosis method using dimension reduction with linear local tangent space alignment is proposed in this paper. With this method, the mixed-domain feature set is first constructed to completely characterize the property of each fault by combining Empirical Mode Decomposition (EMD) with the Autoregression (AR) model coefficients. Then, Linear Local Tangent Space Alignment (LLTSA) is used to automatically compress the high-dimensional eigenvectors of training and test samples into the low-dimensional eigenvectors which have better discrimination. By using the tangent space in the neighborhood of a data point to represent the local geometry, and aligning those local tangent spaces in the low-dimensional space (which is linearly mapped from the raw high-dimensional space), LLTSA can not only gain a perfect approximation of low-dimensional intrinsic geometric structure within the high-dimensional observation data, but can also enhance local within-class relations. Finally, the Littlewoods-Paley wavelet support vector machine (LPWSVM) is proposed to perform fault classification with the obtained low-dimensional eigenvectors. Compared with the existing methods, the proposed approach has improved the fault diagnosis precision. The experiments on deep groove ball bearings fault diagnosis demonstrated the advantage and effectiveness of the proposed fault diagnosis approach.     

Constrained H2 approximation of multiple input-output delay systems using genetic algorithm

The paper presents a constrained H2 approximation method for multiple input-output delay systems by using a genetic algorithm. The H2 error between the original and the approximate models is minimized subject to constraints on the H(infinity) error between them and the matching of their steady-state under step inputs. In particular, the H2 error is used as the objective (fitness) function for minimization with the best parameters of the approximate model obtained by repeating the genetic operations on the population incorporated a parameter search space expansion scheme. The effectiveness of the proposed method is demonstrated by numerical examples. It is shown that the approximate models obtained by this approach have better approximation performance in both the H2 and H(infinity) norms, as well as the steady-state response, than those obtained by a previous gradient-based minimization approach.     

克里金模型及其在全局优化设计中的应用

介绍了克里金模型的基本理论,并采用以克里金模型为近似模型的贝叶斯分析算法,对函数关系复杂、难以计算情况下的全局优化问题进行求解.该算法使用实验设计的方法选取初始样本点,通过样点填充准则找到新的样本点来更新克里金模型,不断循环,从而找到全局最优点.通过实例计算证明,与传统优化算法相比,此方法计算速度快、精度良好.     

CIM环境下连续生产过程通用虚拟生产调度系统

介绍了一种通用的面向连续生产过程分析和调度的原型系统,以及实现这类系统的一些思想、技术和方法。提出了一种连续生产装置抽象模型,并基于此模型通过面向对象编程方法,建立了通用的生产装置分析调度平台。这个平台的主体是一个复杂的生产装置分析调度对象类。     

双参数威布尔分布的参数区间估计的直接方法

提出一种完全不同于现成方法的、以两个抽样分布为基础的估计双参数威布尔分布的形状参数和尺度参数的置信限的方法。该法直接用样本观察值进行估计，虽然采用了一阶近似对其中一个抽样分布作了简化处理，但算例表明，即使样本很小，估算结果也有足够精度，明显优于某些现成方法，而且理论证明，用该法估计的结果偏于安全。该法简便，尤适于工程应用。     

基于矩阵逼近的模型修正方法的研究

提出一种新的以试验振动和参数辨识的数据为参数,进行有限元分析模型修正的方法。该方法基于矩阵最佳逼近理论,运用Ｂａｙｅｓ估计原理来处理试验结果误差带来的试验模态可信度问题,求取分析模对试验获得的不完备模态的谱点的最佳逼近结果,最后获得质量阵的最小修正模型。     

反求工程中基于点云数据集的CAD建模研究

提出了一种新的基于神经网络的点云数据重构CAD光顺造型的新算法。首先对点云数据平滑处理;然后进行特征线提取,并以特征线为基础对曲面进行分割。该方法能直接从神经网络的权值矩阵得到曲线的控制顶点／曲面的控制网格,通过神经网络的权值约束实现曲线段／曲面片之间的光滑拼接。同时对恢复的隐式表面的初始逼近网格自适应性优化。实验效果表明,该方法能够得到精确的逼近结果,同时能满足反求工程的实时需求.