Research on the target coverage algorithms for 3D curved surface

To solve the target covering problems in three-dimensional space, putting forward a deployment strategies of the target points innovatively, and referencing to the differential evolution (DE) algorithm to optimize the location coordinates of the sensor nodes to realize coverage of all the target points in 3-D surface with minimal sensor nodes. Firstly, building the three-dimensional perception model of sensor nodes, and putting forward to the blind area existing in the process of the sensor nodes sensing the target points in 3-D surface innovatively, then proving the feasibility of solving the target coverage problems in 3-D surface with DE algorithm theoretically, and reflecting the fault tolerance of the algorithm.     

Nonlinear FCS-MPC strategy of NPC/H-5 L inverter based on satisfactory optimization algorithm

In the design of the cost function in the nonlinear finite control set model predictive control (FCS-MPC) system, the traditional method based on weighting factors demonstrates some limitations, such as the weighting factors adjusting and heavy predictive calculation due to the increased number of voltage vectors applied in controlling multilevel converters. This paper proposes a simplified FCS-MPC method based on common mode voltage satisfactory optimization, which could considerably reduce the predictive calculation by the optimized switch combination and simplify the cost function design. Moreover, satisfactory optimization is adopted to achieve the accuracy control of common-mode voltage amplitude without adjusting process of weighting factors. The simulation and experimental results verify the feasibility of this control strategy.     

Facet-dependent antibacterial activity of Au nanocrystals

Engineered nanomaterials have attracted significantly attention as one of the most promising antimicrobial agents for against multidrug resistant infections. The toxicological responses of nanomaterials are closely related to their physicochemical properties, and establishment of a structure-activity relationship for nanomaterials at the nano-bio interface is of great significance for deep understanding antibacterial toxicity mechanisms of nanomaterials and designing safer antibacterial nanomaterials. In this study, the antibacterial behaviors of well-defined crystallographic facets of a series of Au nanocrystals, including {100}-facet cubes, {110}-facet rhombic dodecahedra, {111}-facet octahedra, {221}-facet trisoctahedra and {720}-facet concave cubes, was investigated, using the model bacteria Staphylococcus aureus. We find that Au nanocrystals display substantial facet-dependent antibacterial activities. The low-index facets of cubes, octahedra, and rhombic dodecahedra show considerable antibacterial activity, whereas the high-index facets of trisoctahedra and concave cubes remained inert under biological conditions. This result is in stark contrast to the previous paradigm that the high-index facets were considered to have higher bioactivity as compared with low-index facets. The antibacterial mechanism studies have shown that the facet-dependent antibacterial behaviors of Au nanocrystals are mainly caused by differential bacterial membrane damage as well as inhibition of cellular enzymatic activity and energy metabolism. The faceted Au nanocrystals are unique in that they do not induce generation of reactive oxygen species, as validated for most antibiotics and antimicrobial nanostructures. Our findings may provide a deeper understanding of facet-dependent toxicological responses and suggest the complexities of the nanomaterial-cell interactions, shedding some light on the development of high performance Au nanomaterials-based antibacterial therapeutics.     

Ring Airy-Like Beams along Predesigned Parabolic Trajectories

By phase-modulating ring Airy Gaussian beams, ring Airy-like beams propagating along predesigned parabolic trajectories are presented which combine the properties of accelerating beams and abruptly autofocusing beams analytically and numerically for the first time. The enhancement of the quadratic term ratio α shortens the autofocus distance and increases the slope of the beams after autofocusing. Interestingly, the main lobe tends to break into pieces as α increases and the possible reasons have been discussed. Furthermore, the distribution factor β and the radius of the primary r₀ can prominently affect the autofocus distance and the intensity at the focal point but do not change the slope of the beams after the autofocusing. In addition, the self-healing properties are validated to be retainable while RAiG beams via predesigned parabolic trajectories with various α.     

A stochastic control model of investment,production, and consumption on a finite horizon

In this paper, we consider a stochastic control problem on a finite time horizon. The unit price of capital obeys a logarithmic Brownian motion, and the income from production is also subject to the random Brownian fluctuations. The goal is to choose optimal investment and consumption policies to maximize the finite horizon expected discounted hyperbolic absolute risk aversion utility of consumption. A dynamic programming principle is used to derive a time‐dependent Hamilton–Jacobi–Bellman equation. The Leray–Schauder fixed point theorem is used to obtain existence of solution of the HJB equation. At last, we derive the optimal investment and consumption policies by the verification theorem. The main contribution in this paper is the use of PDE technique to the finite time problem for obtaining optimal polices. Copyright © 2014 John Wiley & Sons, Ltd.     

α-Actinin involvement in Z-disk assembly during skeletal muscle C2C12 cells in vitro differentiation

α-Actinin is involved in the assembly and maintenance of muscle fibers. α-Actinin is required to cross-link actin filaments and to connect the actin cytoskeleton to the cell membrane and it is necessary for the attachment of actin filaments to Z-disks in skeletal muscle fibers and to dense bodies in smooth muscle ones. In addition to its mechanical role, sarcomeric α-actinin interacts with proteins involved in a variety of signaling and metabolic pathways.The aim of this work is to monitor Z-disk formation, in order to clear up the role of sarcomeric α-actinin in undifferentiated stage, after 4 days of differentiation (intermediate differentiation stage) and after 7 days of differentiation (fully differentiated stage). For this purpose, C2C12 murine skeletal muscle cells, grown in vitro, were analyzed at three time points of differentiation.Confocal laser scanner microscopy and transmission electron microscopy have been utilized for α-actinin immunolocalization.Both techniques reveal that in undifferentiated cells labeling appears uniformly distributed in the cytoplasm with punctate α-actinin Z-bodies. Moreover, we found that when differentiation is induced, α-actinin links at first membrane-associated proteins, then it aligns longitudinally across the cytoplasm and finally binds actin, giving rise to Z-disks. These findings evidence α-actinin involvement in sarcomeric development, suggesting for this protein an important role in stabilizing the muscle contractile apparatus.     

Blow-up criterion for compressible MHD equations

In this paper, we study the 3D compressible magnetohydrodynamic equations. We obtain a blow up criterion for the local strong solutions just in terms of the gradient of the velocity, similar to the Beal-Kato-Majda criterion (see J.T. Beal, T. Kato and A. Majda (1984) [1]) for the ideal incompressible flow. In addition, initial vacuum is allowed in our case.     

基于ARIMA与神经网络集成的GDP时间序列预测研究

本文深入分析了单整自回归移动平均(ARIMA)模型与神经网络(NN)模型的预测特性和优劣,并在此基础上建立了由ARIMA模型和NN模型集成的GDP时间序列预测模型与算法。其基本思想是充分发挥两种模型在线性空间和非线性空间的预测优势,据此将GDP时间序列的数据结构分解为线性自相关主体和非线性残差两部分,首先用ARIMA模型预测序列的线性主体,然后用NN模型对其非线性残差进行估计,最终集成为整个序列的预测结果。仿真实验表明:集成模型的预测准确率显著高于单一模型的预测准确率,从而证实了集成模型用于GDP预测的有效性。