Convergence of compressible Euler-Poisson system to incompressible Euler equations

In this paper, we study the quasi-neutral limit of compressible Euler-Poisson equations in plasma physics in the torus T^d. For well prepared initial data the convergence of solutions of compressible Euler-Poisson equations to the solutions of incompressible Euler equations is justified rigorously by an elaborate energy methods based on studies on an λ-weighted Lyapunov-type functional. One main ingredient of establishing uniformly a priori estimates with respect to λ is to use the curl-div decomposition of the gradient.     

Luminescence decay of distant donor-acceptor pairs in phosphorous-doped ZnTe

Luminescence decay of isolated donor-acceptor pairs has been measured over the range of pair distance R ～ 180 Å in phosphorous-doped ZnTe. Analysis of the recombination rate as a function of the pair distance suggests an asymptotic behaviour of the acceptor envelope function of the type exp(-r/a_A), with $\text{a}{}_{\mathrm{A}}\text{= 40 ± 10}\text{A}\text{?}$. This effective Bohr radius would correspond to an hydrogenic mass $\text{m}{}^1\text{= (0.13 ± 0.03)}\text{m}{}_{\mathrm{o}}$, which is close to the light hole mass as measured from cyclotron resonance experiments, $\text{m}{}^1\text{= (0.154 ± 0.005)}\text{m}{}_{\mathrm{o}}$. A discussion on the validity of the isolated donor-acceptor pair model is also given.     

羊八井50m2RPC实验及初步测试结果

介绍了羊八井50m²电阻板室(RPC)地毯实验的结构、安装和对其性能的初步测试.测试的结果表明RPC完全能够很好地在海拔4300m,气压594mbar的羊八井宇宙线观测站正常地运行.     

近场光学扫描显微镜图象的行噪音处理

在近场光学扫描显微镜以及其他一些以扫描方式工作的系统中,由于各种原因,致使系统的扫描图象带有较大的行噪音.在这种情况下,采用传统的求平均法以及傅里叶滤波法去除行噪音效果不佳.本文提出了在空间域的自适应迭代处理和小波分析结合处理行噪音的方法.由于小波分析可以在时-频域局部化,而且时窗和频窗的宽度可以调节,故而可以检测到行噪音信号,并实现噪音的定位,实验证明效果较好.     

A modified integral equation method of the semilinear backward heat problem

The paper is concerned with the non-linear backward heat equation in the rectangle domain. The problem is severely ill-posed. We shall use a modified integral equation method to regularize the nonlinear problem. The error estimates of Hölder type of the regularized solutions are obtained. Numerical results are presented to illustrate the accuracy and efficiency of the method. This work is a generalization of many earlier papers, including the recent paper [D.D. Trong, N.H. Tuan, Regularization and error estimate for the nonlinear backward heat problem using a method of integral equation, Nonlinear Anal. 71 (9) (2009) 4167-4176].     

High pressure effect on the crystal and magnetic structure of Pr0.1Sr0.9MnO3 manganite

The crystal and magnetic structure of Pr_0.1Sr_0.9MnO₃ manganite has been studied by the neutron diffraction at high pressures up to 5 GPa in the temperature range 10?C295 K. At normal pressure and decreasing temperature the appearance of the C-type (T _N = 220 K) and G-type (T _N = 180 K) antiferromagnetic states occurs, which is accompanied by a structural phase transition from the cubic structure (Pm $ \bar 3 $ m space group) to the tetragonal structure (I4/mcm space group). It is shown that the temperature of the transition to the C-type antiferromagnetic phase increases with pressure with the pressure coefficient dT _N/dP = 4.0(5) K/GPa and the temperature of the transition to the G-type antiferromagnetic phase weakly depends on pressure.     

不完备信息下的灰色粗糙集成决策模型侯亚林

In this paper, for multiple attribute decision-making problem in which attribute values are interval grey numbers and some of them are null values, a decision model based on grey rough sets integration with incomplete information is proposed. We put forward incidence degree coefficient formula for grey interval, by information entropy theory and analysis technique, the method and principle is presented to fill up null values. We also establish the method of grey interval incidence cluster. Because grey system theory and Rough set theory are complementary each other, decision table with preference information is obtained by the result of grey incidence cluster. An algorithm for inducing decision rules based on rough set theory and the dominance relationship is presented. In some extent, this algorithm can deal with decision-making problem in which the attribute values are interval grey numbers and some of them are null values. Contrasted with classical model of cluster decision-making, the algorithm has an advantage of flexibility and compatibility to new information.     

Pressure-induced structural transformations,orbital order and antiferromagnetism in La<Subscript>0.75</Subscript>Ca<Subscript>0.25</Subscript>MnO<Subscript>3</Subscript>

High pressure evolution of structural, vibrational and magnetic properties of La_0.75Ca_0.25MnO₃ was studied by means of X-ray diffraction and Raman spectroscopy up to 39 GPa, and neutron diffraction up to 7.5 GPa. The stability of different magnetic ground states, orbital configurations and structural modifications were investigated by LDA + U electronic structure calculations. A change of octahedral tilts corresponding to the transformation of orthorhombic crystal structure from the Pnma symmetry to the Immaone occurs above P ~ 6 GPa. At the same time, the evolution of the orthorhombic lattice distortion evidences an appearance of the e _g d _{x² ? z²} orbital polarization at high pressures. The magnetic order in La_0.75Ca_0.25MnO₃ undergoes a continuous transition from the ferromagnetic 3D metallic (FM) ground state to the A-type antiferromagnetic (AFM) state of assumedly 2D pseudo-metallic character under pressure, that starts at about 1 GPa and extends possibly to 20–30 GPa.     

An efficient rough feature selection algorithm with a multi-granulation view

Feature selection is a challenging problem in many areas such as pattern recognition, machine learning and data mining. Rough set theory, as a valid soft computing tool to analyze various types of data, has been widely applied to select helpful features (also called attribute reduction). In rough set theory, many feature selection algorithms have been developed in the literatures, however, they are very time-consuming when data sets are in a large scale. To overcome this limitation, we propose in this paper an efficient rough feature selection algorithm for large-scale data sets, which is stimulated from multi-granulation. A sub-table of a data set can be considered as a small granularity. Given a large-scale data set, the algorithm first selects different small granularities and then estimate on each small granularity the reduct of the original data set. Fusing all of the estimates on small granularities together, the algorithm can get an approximate reduct. Because of that the total time spent on computing reducts for sub-tables is much less than that for the original large-scale one, the algorithm yields in a much less amount of time a feature subset (the approximate reduct). According to several decision performance measures, experimental results show that the proposed algorithm is feasible and efficient for large-scale data sets.