Synthesis of Acrylamide Molecularly Imprinted Polymers Immobilized on Graphite Oxide through Surface-Initiated Atom Transfer Radical Polymerization

A novel acrylamide (AA) molecularly imprinted polymer was synthesized by atom transfer radical polymerization (ATRP) on graphite oxide (GO) particles. Propionamide (PAM) was used as a dummy template molecule, hydroxy ethyl acrylate (HEA) as a functional monomer, ethylene glycol dimethacrylate (EDMA) as a crosslinking agent, and acetonitrile as both solvent and dispersion medium. Scanning electron microscopy (SEM) images and infrared spectroscopy (IR) confirmed that the molecularly imprinted polymers (MIP) were successfully grafted onto the surface of the GO particles. The corresponding adsorption kinetic curves and adsorption isotherms showed that the AA adsorption reached equilibrium after 5 h, with large amounts of AA being adsorped in the first 100 min. The maximum AA adsorption capacity was 123.48 µmol g^?1 according to Scatchard analysis, which indicated that the MIP possesses good AA adsorption capacity. This MIP-GO material was used to selectively determine AA in fried food samples.     

界面态电荷对n沟6H-SiC MOSFET场效应迁移率的影响

针对界面态密度在禁带中的不均匀分布，分析了界面态电荷对n沟6H碳化硅MOSFET场效应迁移率的影响.分析结果显示，界面态电荷使n沟碳化硅器件的场效应迁移率明显降低.并给出了实验测定的场效应迁移率和反型层载流子迁移率的比值与界面态密度之间关系. 关键词： 碳化硅 界面态 反型层迁移率 场效应迁移率     

用自适应谐振网络进行图像纹理的分类与识别

分析了自适应谐振（ＡＲＴ２）神经网络模型的模式分类能力，并利用该网络来进行图像纹理的分类和识别，对６类自然景物的纹理图片分类和识别的结果验证了方法的有效性，对心脏超声图片的分类也取得一些初步成果．     

SiC/SiO2界面粗糙散射对沟道迁移率影响的Monte Carlo研究

提出了一种SiC反型层表面粗糙散射的指数模型,并对6H-SiC反型层迁移率进行了单电子的Monte Carlo模拟,模拟中考虑了沟道区的量子化效应.模拟结果表明,采用表面粗糙散射的指数模型能够使SiC反型层迁移率的模拟结果和实验值符合得更好.模拟结果还反映出有效横向电场较高时表面粗糙散射的作用会变得更显著,电子的屏蔽效应降低了粗糙散射对沟道迁移率的影响,温度升高会引起沟道迁移率降低. 关键词： 6H-SiC 反型层迁移率 表面粗糙散射 指数模型     

Algebraic Multigrid Preconditioning for Finite Element Solution of Inhomogeneous Elastic Inclusion Problems in Articular Cartilage

In studying biomechanical deformation in articular cartilage, the presence of cells (chondrocytes) necessitates the consideration of inhomogeneous elasticity problems in which cells are idealized as soft inclusions within a stiff extracellular matrix. An analytical solution of a soft inclusion problem is derived and used to evaluate iterative numerical solutions of the associated linear algebraic system based on discretization via the finite element method, and use of an iterative conjugate gradient method with algebraic multigrid preconditioning (AMG-PCG). Accuracy and efficiency of the AMG-PCG algorithm is compared to two other conjugate gradient algorithms with diagonal preconditioning (DS-PCG) or a modified incomplete LU decomposition (Euclid-PCG) based on comparison to the analytical solution. While all three algorithms are shown to be accurate, the AMG-PCG algorithm is demonstrated to provide significant savings in CPU time as the number of nodal unknowns is increased. In contrast to the other two algorithms, the AMG-PCG algorithm also exhibits little sensitivity of CPU time and number of iterations to variations in material properties that are known to significantly affect model variables. Results demonstrate the benefits of algebraic multigrid preconditioners for the iterative solution of assembled linear systems based on finite element modeling of soft elastic inclusion problems and may be particularly advantageous for large scale problems with many nodal unknowns.     

Sparse representation-based classification algorithm for optical Tibetan character recognition

A sparse representation-based two-phase classification algorithm is proposed for off-line handwritten Tibetan character recognition. The first phase realizes coarse classification with the K-NN classifier by finding the K nearest neighbours of a test sample in the dictionary constructed by K-SVD with samples of all classes, and the classes of these neighbours are regarded as the candidate classes of the test sample. The second phase performs fine classification with the sparse representation classifier by sparsely representing the test sample with all elements of the dictionary constructed by K-SVD with samples of all candidate classes, and the test sample is finally classified into the candidate class with the maximal contribution in sparse representation. Experiments on the Tibetan off-line handwritten character database show that an optimal recognition rate of 97.17% has been reached and it is 2.12% higher than that of K-NN.     

Singularity spectrum of fractal signals from wavelet analysis: Exact results

The multifractal formalism for singular measures is revisited using the wavelet transform. For Bernoulli invariant measures of some expanding Markov maps, the generalized fractal dimensions are proved to be transition points for the scaling exponents of some partition functions defined from the wavelet transform modulus maxima. The generalization of this formalism to fractal signals is established for the class of distribution functions of these singular invariant measures. It is demonstrated that the Hausdorff dimensionD(h) of the set of singularities of Hölder exponenth can be directly determined from the wavelet transform modulus maxima. The singularity spectrum so obtained is shown to be not disturbed by the presence, in the signal, of a superimposed polynomial behavior of ordern, provided one uses an analyzing wavelet that possesses at leastN>n vanishing moments. However, it is shown that aC behavior generally induces a phase transition in theD(h) singularity spectrum that somewhat masks the weakest singularities. This phase transition actually depends on the numberN of vanishing moments of the analyzing wavelet; its observation is emphasized as a reliable experimental test for the existence of nonsingular behavior in the considered signal. These theoretical results are illustrated with numerical examples. They are likely to be valid for a large class of fractal functions as suggested by recent applications to fractional Brownian motions and turbulent velocity signals.     

The optimum bandwidth of chirp signals in ultrasonic applications

A new formula for the pulse-compression ratio achievable with linear FM pulses (chirp signals) in ultrasonic applications is derived. The calculations take into account the frequently omitted effects of the transfer function of an ultrasonic transducer. For a squared-cosine type transducer spectrum, the optimum chirp signal bandwidth is 1.14 times the 6 dB bandwidth of the transducer. The pulse-compression ratio is 2.24 dB lower than in the case of an ideal broadband transducer. Measurements show a close agreement with the presented theory.     

New formulation of restricted growth processes

We present a new formulation of a class of growth models-those which evolve according to an exclusion process. This formulation is based upon a transformation of the probability distribution function which involves Grassmann variables. This method is very general and enables one to derive an exact stochastic differential equation for the model of interest. We describe this method using the traffic model as an example.     

微合金化元素对Fe—A1界面结合的第一性原理研究

利用第一性原理中的DFT理论研究了Fe／A1界面的能量学和电子结构，讨论了替位型掺杂的元素Zn、Mn、Ni在Fe／A1界面处的作用．结果表明：元素Zn、Mn、Ni都会优先替换界面处的Fe原子，使得界面结合能增加，体系更稳定，有利于界面的结合；跨界面的Fe原子与Al原子之间的电荷布居、键长以及差分电荷密度图的计算表明：掺杂后有利于跨界面的Fe-Al间成键，从而加强了Al层与Fe基体的结合，且结合强度由强到弱依次为：掺Zn〉掺Mn〉掺Ni；与实验比较吻合．最后对掺杂Zn的增韧机理加以解释．