A multiaxial elastic potential with error-minimizing approximation to rubberlike elasticity

This study is concerned with a new,explicit approach by means of which forms of the large strain elastic potential for multiaxial rubberlike elasticity may be obtained based on data for a single deformation mode.As a departure from usual studies,here for the first time errors may be estimated and rendered minimal for all possible deformation modes and,furthermore,failure behavior may be incorporated.Numerical examples presented are in accurate agreement with Treloar's well-known data.     

Experimental comparison of nonlinear damping performance of toroidal and conventional tuned liquid column dampers

Nonlinear Dynamics - Conventional tuned liquid column dampers (TLCDs) are deficient in multidirectionality. In contrast, toroidal TLCDs are designed to extend the application to multidirectional...     

蛋白质-多糖复合体系在活性物质传递中的应用

蛋白质-多糖复合体系作为生物活性物质传递系统的壁材,有着人工合成聚合物或无机物等其他材料不可比拟的多重优势。本文就蛋白质和多糖之间的连接方式及蛋白质-多糖复合体系形成传递系统的多种形式进行了综述,以及对此领域的发展趋势进行了展望。结合蛋白质和多糖的结构特点,二者之间的链接方式分为非共价结合的物理共聚,和共价结合的美拉德偶联、化学交联、酶催化交联等方式,文中分别对各种连接方式的原理和机理,以及其影响因素做了深入阐述。以蛋白质-多糖复合体系为壁材对活性物质的传递形式大体上分成乳化系统、胶束、纳米凝胶、分子复合物以及壳核结构等系统。不同的活性物质的特征和传递需求,可针对性地选择合适结构的蛋白质和多糖种类以及二者的连接方式和传递系统的形式。并且,随着研究的逐步发展和推进,此领域的发展趋势朝着智能化和靶向性的方向进行。目前活性物质的蛋白质-多糖复合体系的传递系统,还依然面临着系统设计、评价和应用等多方面的挑战,这就要求我们在更全面更深入了解认识其对活性物质影响和功效的基础上,安全合理地设计和深入细致地评价活性成分的传递系统。     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

An effective interference suppression algorithm for visible light communication system based on DBSCAN

In order to improve the signal-to-noise ratio and mitigate the damage of noise to the communication quality,an effective interference suppression algorithm,which is based on the improved density-based spatial clustering of applications with noise algorithms,is proposed for visible light communication systems using the complementary metal–oxide–semiconductor image sensor as the receiver.Experimental results show that the algorithm can learn the region where the payload data is located,filter out the noise data,and greatly decrease the interference.The effect of the algorithm is also studied through bit error ratio performance.