Configurational statistics of copolymers prepared by complex-radical polymerization

Radical copolymerization is considered theoretically taking into account the effect of complexing on the configurational statistics of macromolecules formed. Akinetic model has been developed that considers, apart from the ordinary addition of single monomer units to a propagating chain, the possible addition of monomer unit pairs along with a complexing agent in the form of a ternary complex. Within the framework of this model, the problem of calculating the probabilities of formation of any sequences of monomer units (taking into account their microtacticity) in a macromolecule has been rigorously solved as well as the problem of finding the composition distribution of the copolymer formed. It has been shown that this distribution is described by a conventional Gauss law and the appropriate parameters are given. Possible generalizations of the suggested approach are indicated.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

Group‐in‐a‐Box Meta‐Layouts for Topological Clusters and Attribute‐Based Groups: Space‐Efficient Visualizations of Network Communities and Their Ties

An important part of network analysis is understanding community structures like topological clusters and attribute‐based groups. Standard approaches for showing communities using colour, shape, rectangular bounding boxes, convex hulls or force‐directed layout algorithms remain valuable, however our Group‐in‐a‐Box meta‐layouts add a fresh strategy for presenting community membership, internal structure and inter‐cluster relationships. This paper extends the basic Group‐in‐a‐Box meta‐layout, which uses a Treemap substrate of rectangular regions whose size is proportional to community size. When there are numerous inter‐community relationships, the proposed extensions help users view them more clearly: (1) the Croissant–Doughnut meta‐layout applies empirically determined rules for box arrangement to improve space utilization while still showing inter‐community relationships, and (2) the Force‐Directed layout arranges community boxes based on their aggregate ties at the cost of additional space. Our free and open source reference implementation in NodeXL includes heuristics to choose what we have found to be the preferable Group‐in‐a‐Box meta‐layout to show networks with varying numbers or sizes of communities. Case study examples, a pilot comparative user preference study (nine participants), and a readability measure‐based evaluation of 309 Twitter networks demonstrate the utility of the proposed meta‐layouts.     

4D MRI Flow Coupled to Physics‐Based Fluid Simulation for Blood‐Flow Visualization

Modern MRI measurements deliver volumetric and time‐varying blood‐flow data of unprecedented quality. Visual analysis of these data potentially leads to a better diagnosis and risk assessment of various cardiovascular diseases. Recent advances have improved the speed and quality of the imaging data considerably. Nevertheless, the data remains compromised by noise and a lack of spatiotemporal resolution. Besides imaging data, also numerical simulations are employed. These are based on mathematical models of specific features of physical reality. However, these models require realistic parameters and boundary conditions based on measurements. We propose to use data assimilation to bring measured data and physically‐based simulation together, and to harness the mutual benefits. The accuracy and noise robustness of the coupled approach is validated using an analytic flow field. Furthermore, we present a comparative visualization that conveys the differences between using conventional interpolation and our coupled approach.     

海上溢油漂移扩散的数值模拟

该文基于三维自由水面垂向分层动网格的Euler-Lagrangian模式,采用VC方式(Vertex-Centered)的非结构化有限体积方法离散三维浅水方程,模拟渤海的潮汐水流运动过程。以此为水动力背景场,采用油、水分离的Lagrangian粒子追踪模型,对渤海海域发生的溢油漂移扩散问题进行模拟。其油品的蒸发、乳化和溶解等风化作用以引入综合衰减系数的方式考虑。模型对油膜的漂移路径、厚度和面积进行了实时模拟和预测,用多个测站的同步连续实测值对水动力模式进行了参数率定与模型验证,油膜输运扩散的计算结果也与相关报告数据进行了对比,均吻合良好,说明模型具有较高的可靠性与重现性。     

三维激光扫描技术在引水隧洞检修中的应用

三维激光扫描技术是国际上近年发展的一项集光、电和计算机技术于一体的新技术,利用该技术可以快速、精确地获取空间数据。锦屏二级水电站引水隧洞放空检修时发现少数洞内存在混凝土破损情况,但受时间与费用等因素限制,难于以采用常规手段详细检查混凝土表面缺陷与变形等问题。通过采用三维激光扫描技术对隧洞进行全断面扫描,及时探查了混凝土表面的缺陷并进行了处理,确保了工程安全运行;同时,还得到混凝土表面的三维坐标信息,建立了混凝土表面缺陷基准数据库,可为后续进一步分析混凝土表面缺陷的变化情况提供参考。     

Real-time facial animation on mobile devices

We present a performance-based facial animation system capable of running on mobile devices at real-time frame rates. A key component of our system is a novel regression algorithm that accurately infers the facial motion parameters from 2D video frames of an ordinary web camera. Compared with the state-of-the-art facial shape regression algorithm [1], which takes a two-step procedure to track facial animations (i.e., first regressing the 3D positions of facial landmarks, and then computing the head poses and expression coefficients), we directly regress the head poses and expression coefficients. This one-step approach greatly reduces the dimension of the regression target and significantly improves the tracking performance while preserving the tracking accuracy. We further propose to collect the training images of the user under different lighting environments, and make use of the data to learn a user-specific regressor, which can robustly handle lighting changes that frequently occur when using mobile devices.