Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Supramolecular Glyco‐nanoparticles Toward Immunological Applications

Glyco‐mimicking nanoparticles (glyco‐NPs) with Förster resonance energy transfer (FRET) donor and acceptor groups formed via dynamic covalent bond of benzoboroxole and sugar from two complementary polymers are prepared. The glyco‐NPs are proved to be quite stable under physiological conditions but sensitive to pH. So the glyco‐NPs can be internalized by dendritic cells with integrity and nontoxicity and then dissociate within the acidic organelles. This particle dissociation is directly observed and visualized in vitro, for the first time via the FRET measurements and fluorescent microscopy. This feature makes controlled release of drug or protein by glyco‐NPs possible, i.e., when model antigen Ovalbumin is loaded in the glyco‐NPs, the released Ovalbumin in dendritic cells stimulates T cells more efficiently than the free Ovalbumin itself as a result of the enhanced antigen processing and presentation. Thus, the results enlighten a bright future of the glyco‐NPs in immunotherapy.     

Structural dependence of microwave dielectric properties of spinel structured Mg2(Ti1-xSnx)O4 solid solutions: Crystal structure refinement,Raman spectra study and complex chemical bond theory

Mg₂(Ti_1-xSn_x)O₄ (x?=?0–1) ceramics were prepared through conventional solid-state method. This paper focused on the dependence of microwave dielectric properties on crystal structural characteristics via crystal structure refinement, Raman spectra study and complex chemical bond theory. XRD spectrums delineated the phase information of a spinel structure, and structural characteristic of these compositions were achieved with the help of Rietveld refinements. Raman spectrums were used to depict the correlations between vibrational phonon modes and dielectric properties. The variation of permittivity is ascribed to the Mg₂(Ti_1-xSn_x)O₄ average bond covalency. The relationship among the B-site octahedral bond energy, tetrahedral bond energy and temperature coefficient are discussed by defining on the change rate of bond energy and the contribution rate of octahedral bond energy. The quality factor is affected by systematic total lattice energy, and the research of XPS patterns illustrated that oxygen vacancies can be effectively restrained in rich oxygen sintering process. Obviously, the microwave dielectric properties of Mg₂(Ti_1-xSn_x)O₄ compounds were obtained (${\epsilon }_r$= 12.18, $Q\times f$?=?170,130?GHz, ${\tau }_f$?=??53.1?ppm/°C, x?=?0.2).     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

太赫兹脉冲焦平面成像技术的发展与应用

作为太赫兹技术中的重要组成部分,太赫兹脉冲焦平面成像一经问世就引起了行业内的广泛关注,人们引入了各种方法去提升此成像技术的测量性能,同时也尝试将此成像技术应用于不同的工业和基础研究领域。本文综述了近年来人们对太赫兹脉冲焦平面成像的技术改良和应用研究,包括提升成像系统的空间分辨率、信噪比、信息获取能力,以及将此成像技术应用于光谱识别检测、超表面器件功能验证、太赫兹特殊光束测量、太赫兹表面波观测等,希望该综述能够推动太赫兹脉冲焦平面成像的进一步技术革新和应用拓展。