다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

We propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by the gradient. We minimize an energy which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a "mean-curvature flow"-like evolving the active contour, which will stop on the desired boundary. However, the stopping term does not depend on the gradient of the image, as in the classical active contour models, but is instead related to a particular segmentation of the image. We give a numerical algorithm using finite differences. Finally, we present various experimental results and in particular some examples for which the classical snakes methods based on the gradient are not applicable. Also, the initial curve can be anywhere in the image, and interior contours are automatically detected.

/pdf/active-contours-without-edges-2tt3qz9lq0.pdf

Active contours without edges

Inpainting, the technique of modifying an image in an undetectable form, is as ancient as art itself. The goals and applications of inpainting are numerous, from the restoration of damaged paintings and photographs to the removal/replacement of selected objects. In this paper, we introduce a novel algorithm for digital inpainting of still images that attempts to replicate the basic techniques used by professional restorators. After the user selects the regions to be restored, the algorithm automatically fills-in these regions with information surrounding them. The fill-in is done in such a way that isophote lines arriving at the regions' boundaries are completed inside. In contrast with previous approaches, the technique here introduced does not require the user to specify where the novel information comes from. This is automatically done (and in a fast way), thereby allowing to simultaneously fill-in numerous regions containing completely different structures and surrounding backgrounds. In addition, no limitations are imposed on the topology of the region to be inpainted. Applications of this technique include the restoration of old photographs and damaged film; removal of superimposed text like dates, subtitles, or publicity; and the removal of entire objects from the image like microphones or wires in special effects.

Image inpainting

We analyze overlapping Schwarz waveform relaxation for the heat equation in n spatial dimensions. We prove linear convergence of the algorithm on unbounded time intervals and superlinear convergence on bounded time intervals. In both cases the convergence rates are shown to depend on the size of the overlap. The linear convergence result depends also on the number of subdomains because it is limited by the classical steady state result of overlapping Schwarz for elliptic problems. However the superlinear convergence result is independent of the number of subdomains. Thus overlapping Schwarz waveform relaxation does not need a coarse space for robust convergence independent of the number of subdomains, if the algorithm is in the superlinear convergence regime. Numerical experiments confirm our analysis. We also briefly describe how our results can be extended to more general parabolic problems.

/pdf/overlapping-schwarz-waveform-relaxation-for-the-heat-2xfuwuurr6.pdf

Overlapping Schwarz Waveform Relaxation for the Heat Equation in n-Dimensions

The Poisson–Boltzmann theory has become widely accepted in modeling electrostatic solvation interactions in biomolecular calculations. However the standard practice of atomic point charges in molecular mechanics force fields introduces singularity into the Poisson–Boltzmann equation. The finite-difference/finite-volume discretization approach to the Poisson–Boltzmann equation alleviates the numerical difficulty associated with the charge singularity but introduces discretization error into the electrostatic potential. Decomposition of the electrostatic potential has been explored to remove the charge singularity explicitly to achieve higher numerical accuracy in the solution of the electrostatic potential. In this study, we propose an efficient method to overcome the charge singularity problem. In our framework, two separate equations for two different potentials in two different regions are solved simultaneously, i.e., the reaction field potential in the solute region and the total potential in the solvent region. The proposed method can be readily implemented with typical finite-difference Poisson–Boltzmann solvers and return the singularity-free reaction field potential with a single run. Test runs on 42 small molecules and 4 large proteins show a very high agreement between the reaction field energies computed by the proposed method and those by the classical finite-difference Poisson–Boltzmann method. It is also interesting to note that the proposed method converges faster than the classical method, though additional time is needed to compute Coulombic potential on the dielectric boundary. The higher precision, accuracy, and efficiency of the proposed method will allow for more robust electrostatic calculations in molecular mechanics simulations of complex biomolecular systems.

On removal of charge singularity in Poisson-Boltzmann equation.

We first introduce a surface normal estimation procedure for point clouds capable of handling geometric singularities in the data, such as edges and corners. Our formulation is based on recasting the popular Principal Component Analysis (PCA) method as a constrained nonlinear least squares (NLSQ) problem. In contrast to traditional PCA, the new formulation assigns appropriate weights to neighboring points automatically during the optimization process in order to minimize the contributions of points located across singularities. We extend this strategy to point cloud denoising by combining normal estimation, point projection, and declustering into one NLSQ formulation. Finally, we propose a point cloud segmentation technique based on surface normal estimates and local point connectivity. In addition to producing consistently oriented surface normals, the process segments the point cloud into disconnected components that can each be segmented further into piecewise smooth components as needed.

Point Cloud Segmentation and Denoising via Constrained Nonlinear Least Squares Normal Estimates

A direct imaging algorithm for point and extended targets is presented. The algorithm is based on a physical factorization of the response matrix of a transducer array. The factorization is used to transform a passive target problem to an active source problem and to extract principal components (tones) in a phase consistent way. The multitone imaging function can superpose multiple tones (spatial diversity/aperture of the array) and frequencies (bandwidth of the probing signal) based on phase coherence. The method is a direct imaging algorithm that is simple and efficient since no forward solver or iteration is needed. Robustness of the algorithm with respect to noise is demonstrated via numerical examples.

/pdf/a-phase-and-space-coherent-direct-imaging-method-1kzy42rcsz.pdf

A phase and space coherent direct imaging method.

In this paper we study the response matrix obtained from the interelement response of an active array of transducers that can send out signals and record reflected signals. In particular we analyze the eigenvalues and eigenvectors of the response matrix corresponding to the acoustic field reflected by an extended target, the size of which is comparable to the wavelength. We show that the eigenvalues are not well separated for a single extended target in general. However, when both the size of the target and the size of the active array are small compared to the distance from the array to the target, it is shown that the eigenvalues are well separated and that the leading eigenvalues and eigenvectors can be characterized in terms of the location and dimension of the target. Numerical experiments are presented to verify the analysis.

/pdf/analysis-of-the-response-matrix-for-an-extended-target-ot35ixy7az.pdf

Hongkai Zhao

Papers

Overlapping Schwarz Waveform Relaxation for the Heat Equation in n-Dimensions

On removal of charge singularity in Poisson-Boltzmann equation.

Point Cloud Segmentation and Denoising via Constrained Nonlinear Least Squares Normal Estimates

A phase and space coherent direct imaging method.

Analysis of the Response Matrix for an Extended Target