Theoretical hardness of the cubic BC2N

Vickers hardness of the cubic BC₂N has been investigated using the microscopic hardness model, in which the parameters have been obtained using first principles calculations. Ionicities of the chemical bonds in the cubic BC₂N depend on their surrounding chemical environments, which are included in the hardness calculations of the cubic BC₂N using the population ionicity scale. For the four selected configurations of the cubic BC₂N, the theoretical Vickers hardness has been found to lie between 70 and 72 GPa, consistent with the experimental value of 76 GPa. According to our calculations, it should be the cubic BC₂N that ranks second among the superhard materials instead of the cubic BN.     

Evolving Fault-Tolerant Neural Networks

In this paper, genetic algorithm is used to help improve the tolerance of feedforward neural networks against an open fault. The proposed method does not explicitly add any redundancy to the network, nor does it modify the training algorithm. Experiments show that it may profit the fault tolerance as well as the generalisation ability of neural networks.     

Interpretation of the morphology and crystallography of precipitate γ1-Ti4Nb3Al9 in L10-TiAl(Nb)-based intermetallics by invariant line theory

The coherent precipitate γ₁-Ti₄Nb₃Al₉ in the Nb-modified TiAl-based intermetallic compound with a nominal composition of Ti–48 at% Al–10 at% Nb was investigated by transmission electron microscopy. The crystallographic and morphologic characteristics of the precipitating phase have been calculated based on invariant line theory. It is revealed that in the γ-TiAl(Nb)/γ₁-Ti₄Nb₃Al₉ couples, both the morphological and crystallographical characteristics of the precipitate γ₁-Ti₄Nb₃Al₉ could be predicted by the three-dimensional phase transformation invariant line model. The needle direction of [001] at the early stage for coherent precipitate γ₁-Ti₄Nb₃Al₉ and [111] for equilibrium phase γ₁-Ti₄Nb₃Al₉ have both been explained well. The characterization of morphology and crystallography of the precipitate reaction in γ-TiAl/γ₁-Ti₄Nb₃Al₉ system sustain the postulate that precipitates are bounded by unrotated planes (eigenplanes) when three real eigenvalues exist.     

Entrapping multifunctional dendritic nanoparticles into a hydrogel for local therapeutic delivery and synergetic immunochemotherapy

Nano Research - Developing multifunctional nanoparticles to support new therapy models is a promising and challenging task to address the current dilemma on antitumor treatment. Herein, we...     

A two-level strategy for segmenting center of interest from pictures

Segmenting center of interests (COIs) from pictures is an important but highly challenging problem for researchers in computer vision and image processing. The capability of understanding the meanings of pictures by computers can lead to breakthroughs in a wide range of applications including Web image search and online picture-sharing communities. In this paper, a two-level strategy is presented, which consists of a rough segmentation stage and a fine segmentation stage. In the first level, a picture is partitioned into four regions by using a block clustering method based on color and texture features, and the COI within the picture is distinguished from the background according to the principles of photographic composition. This stage aims to determine the approximate region of the target. In the second level, a novel active contour model is established based on shape information and vector method, where the image energy is defined by a hue gradient and the external energy is generated from either a triangular inner force or a supplementary force. This stage tries to extract the boundary of the target accurately. Experimental results on photos downloaded from the Internet show the feasibility and effectiveness of the proposed method.     

Optimization for limited angle tomography in medical image processing

This paper aims to reduce the problems of incomplete data in computed tomography, which happens frequently in medical image process and analysis, e.g., when the high-density region of objects can only be penetrated by X-rays at a limited angular range. As the projection data are available only in an angular range, the incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. Image reconstruction based on total variation (TV) reduces the problem and gives better performance on edge-preserving reconstruction; however, the artificial parameter can only be determined through considerable experimentation. In this paper, an effective TV objective function is proposed to reduce the inverse problem in the limited angle tomography. This novel objective function provides a robust and effective reconstruction without any artificial parameter in the iterative processes, using the TV as a multiplicative constraint. The results demonstrate that this reconstruction strategy outperforms some previous ones.     

无线传感器网络中基于树的动态多路径容错路由协议

多路径路由对无线传感器网络的负载均衡和容错能力等方面都有一定改善作用。在研究一些多路径路由算法的基础上,对分层的无线传感器网络路由进行探索,提出了一种基于树的动态多路径路由的生成方法,快速获得当前节点的主路径与备用路径。仿真结果表明,该方法可有效地均衡网络负载、减少时延、提高网络的可靠性。     

Hybrid Well-balanced WENO Schemes with Different Indicators for Shallow Water Equations

In (J. Comput. Phys. 229: 8105–8129, 2010), Li and Qiu investigated the hybrid weighted essentially non-oscillatory (WENO) schemes with different indicators for Euler equations of gas dynamics. In this continuation paper, we extend the method to solve the one- and two-dimensional shallow water equations with source term due to the non-flat bottom topography, with a goal of obtaining the same advantages of the schemes for the Euler equations, such as the saving computational cost, essentially non-oscillatory property for general solution with discontinuities, and the sharp shock transition. Extensive simulations in one- and two-dimensions are provided to illustrate the behavior of this procedure.     

Myoglobin/gold nanoparticles/carbon spheres 3-D architecture for the fabrication of a novel biosensor

A novel biosensor based on a myoglobin/gold nanoparticles/carbon spheres (Mb-AuNPs-CNs) 3-D architecture bioconjunction has been fabricated for the determination of hydrogen peroxide (H₂O₂). Cyclic voltammetry (CV), Fourier transform infrared (FT-IR) spectroscopy and scanning electron microscopy (SEM) were used to characterize the bioconjunction of the AuNPs-CNs with Mb. Experimental results demonstrate that the AuNPs-CNs hybrid material is more effective in facilitating electron transfer of the immobilized enzyme than CNs alone, which can be attributed to the unique nanostructure and larger surface area of the bioconjunction. The biosensor displayed good performance for the detection of H₂O₂ with a wide linear range from 0.28 μmol/L to 116.5 μmol/L and a detection limit of 0.12 μmol/L. The Michaelis-Menten constant K _M^app value was estimated to be 0.3 mmol/L. The resulting biosensor exhibited fast amperometric response, and good stability, reproducibility, and selectivity to H₂O₂. This article is published with open access at Springerlink.com