安培环路定理的拓扑学描述

近年来拓扑学在量子力学中得到了广泛的运用.本文将安培环路定理积分式重新表达为一矢量场在轮胎参数面上的第一类陈数积分.数值模拟展示了该积分值为一整数即第一陈数,其代表矢量场的整体性质:当经历连续变换时,矢量场的局部数值发生改变但整体积分值即陈数仍保持不变;若陈数发生改变,则表明矢量场变换的连续性条件发生破坏,矢量场出现奇点.进一步通过高斯映射将该矢量场从参数轮胎面映射到单位球面上,并给出了第一陈数的直观几何意义.理论和数值结果揭示了安培环路定理的拓扑学本质,表明拓扑概念在经典物理学中也会有广泛应用.     

贝叶斯优化卷积神经网络公共场所异常声识别*

针对公共场所异常声的感知和识别问题,提出一种基于贝叶斯优化卷积神经网络的识别方法。提取声信号的Gammatone倒谱系数、倍频程功率谱、短时能量和谱质心,组合成声信号的特征图。构建卷积神经网络作为分类器,利用递增的卷积核设置和池化操作处理不同尺度的特征。基于贝叶斯优化算法优化卷积神经网络的模型参数,对包括火苗噼啪声、婴儿啼哭声、烟花燃放声、玻璃破碎声和警报声的5种公共场所异常声进行识别。该方法的识别结果与基于不同的特征提取和分类器方案得到的识别结果进行比较,结果表明该方法的识别效果优于其他特征提取和分类器方案的识别效果。最后分析了该方法在不同信噪比噪声干扰下的识别结果,验证了该方法的有效性。     

MOEPGA: A novel method to detect protein complexes in yeast protein–protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm

The identification of protein complexes in protein–protein interaction (PPI) networks has greatly advanced our understanding of biological organisms. Existing computational methods to detect protein complexes are usually based on specific network topological properties of PPI networks. However, due to the inherent complexity of the network structures, the identification of protein complexes may not be fully addressed by using single network topological property. In this study, we propose a novel MultiObjective Evolutionary Programming Genetic Algorithm (MOEPGA) which integrates multiple network topological features to detect biologically meaningful protein complexes. Our approach first systematically analyzes the multiobjective problem in terms of identifying protein complexes from PPI networks, and then constructs the objective function of the iterative algorithm based on three common topological properties of protein complexes from the benchmark dataset, finally we describe our algorithm, which mainly consists of three steps, population initialization, subgraph mutation and subgraph selection operation. To show the utility of our method, we compared MOEPGA with several state-of-the-art algorithms on two yeast PPI datasets. The experiment results demonstrate that the proposed method can not only find more protein complexes but also achieve higher accuracy in terms of fscore. Moreover, our approach can cover a certain number of proteins in the input PPI network in terms of the normalized clustering score. Taken together, our method can serve as a powerful framework to detect protein complexes in yeast PPI networks, thereby facilitating the identification of the underlying biological functions.     

Modeling the Effect of Injection Molding Process Parameters on Warpage Using Neural Network Theory

A back propagation artificial neural network (BPANN) prediction model for warpage of injection-molded polypropylene was developed based on an orthogonal design method. The BPANN model was trained by the input and output data obtained from the moldflow software platform simulations. It is proved that the BPANN model can predict the warpage with reasonable accuracy. Utilizing the BPANN model, the effects of the process parameters, packing pressure (Pp), melt temperature (T_me), mold temperature (T_mo), packing time (t_p), cooling time (t_c), and fill pressure (p_f), on the warpage were investigated. The most important process parameter affecting the warpage was Pp, and the second most important was T_me. The rest of the process parameters, T_mo, t_p, t_c, and p_f, were found to be relatively less influential. Warpage increased with elevating T_mo. In contrast, an increase in Pp and T_me caused the warpage to decrease.     

Synthesis and Characterization of a New Metal-organic Framework with Nou Topology

A new compound, [H2N(CH3)2]2[Zn(btec)].H2O(1, H4 btec = 1,2,4,5-benzenetetracarboxylic acid) has been solvothermally synthesized and structurally characterized by singlecrystal X-ray diffraction. The crystal structure is of monoclinic, space group P21/c with a = 9.5741(3), b = 14.5044(4), c = 13.7329(5) , β = 100.582(4)°, V = 1874.61(10) 3, C14H20N2O9 Zn, Mr = 425.7, Z = 4, Dc = 1.387 g/cm3, μ = 1.349 mm-1, F(000) = 776, R = 0.0560 and w R = 0.1684 for 2834 observed reflections(I 2σ(I)). Compound 1 based on μ4-btec and tetrahedral building unit features a three-dimensional(3D) anionic framework with mixed connected nou topology. The luminescent property and thermogravimetric analysis of compound 1 are investigated.     

α‐Diamine Nickel Catalysts with Nonplanar Chelate Rings for Ethylene Polymerization

A series of novel α‐diamine nickel complexes, (ArNH‐C(Me)‐(Me)C‐NHAr)NiBr₂, 1 : Ar=2,6‐diisopropylphenyl, 2 : Ar=2,6‐dimethylphenyl, 3 : Ar=phenyl), have been synthesized and characterized. X‐ray crystallographic analysis showed that the coordination geometry of the α‐diamine nickel complexes is markedly different from conventional α‐diimine nickel complexes, and that the chelate ring (N‐C‐C‐N‐Ni) of the α‐diamine nickel complex is significantly distorted. The α‐diamine nickel catalysts also display different steric effects on ethylene polymerization in comparison to the α‐diimine nickel catalyst. Increasing the steric hindrance of the α‐diamine ligand by substitution of the o‐methyl groups with o‐isopropyl groups leads to decreased polymerization activity and molecular weight; however, catalyst thermal stability is significantly enhanced. Living polymerizations of ethylene can be successfully achieved using 1 /Et₂AlCl at 35 °C or 2 /Et₂AlCl at 0 °C. The bulky α‐diamine nickel catalyst 1 with isopropyl substituents can additionally be used to control the branching topology of the obtained polyethylene at the same level of branching density by tuning the reaction temperature and ethylene pressure.     

Molecular structure and properties of click hydrogels with controlled dangling end defect

In this study, controlled amount of dangling ends is introduced to the two series of poly(ethylene glycol)‐based hydrogel networks with three and four crosslinking functionality by using click chemistry. The structure of the gels with regulated defect percentage is confirmed by comparing the results of low‐field NMR characterization and Monte Carlo simulation. The mechanical properties of these gels were characterized by tensile stress–strain behaviors of the gels, and the results are analyzed by Gent model and Mooney–Rivlin model. The shear modulus of the swollen gels is found to be dependent on the functionality of the network, and decreases with the defect percentage. Furthermore, the value of shear modulus well obeys the Phantom model for all the gels with varied percentage of the defects. The maximum extension ratio, obtained from the fitting of Gent model, is also found to be dependent on the functionality of the network, and does not change with the defect percentage, except at very high defect percentage. The value of the maximum extension ratio is between that predicted from Phantom model and the Affine model. This indicates that at the large deformation, the fluctuation of the crosslinking points is suppressed for some extend but still exists. Polymer volume fractions at various defect percentages obtained from prediction of Flory–Rehner model are found to be in well agreement with the swelling experiment. All these results indicate that click chemistry is a powerful method to regulate the network structure and mechanical properties of the gels. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1227–1236     

Polymer networks functionalized with low-valent phosphorus cations

In this work, we show that polymer networks composed of tertiary alkyl phosphines can be cleanly functionalized with phosphino-phosphonium or triphosphenium cations. Methods for functionalizing the polymers range from halide abstraction of commercially available reagents, to ligand exchange from simple to make reported compounds, and finally, macromolecular ligand design guided by observations made at the molecular level to accommodate the formation of kinetically favored triphosphenium cation functionalized networks. The synthesis, comprehensive characterization, and comparison of the new polymers to molecular analogues is outlined. It is shown the addition of the low valent phosphorus centers to the polymer network has the effect of tuning material physical properties.     

Graph-like compacta: Characterizations and Eulerian loops

A compact graph-like space is a triple $\left(X,V,E\right)$, where $X$ is a compact, metrizable space, $V\subseteq X$ is a closed zero-dimensional subset, and $E$ is an index set such that $X⧹V\cong \text{◂+▸}E\times \left(0,1\right)$. New characterizations of compact graph-like spaces are given, connecting them to certain classes of continua, and to standard subspaces of Freudenthal compactifications of locally finite graphs. These are applied to characterize Eulerian graph-like compacta.