Factors influencing magnetic polymer microspheres prepared by dispersion polymerization

Magnetic iron oxide (Fe₃O₄) was prepared by a coprecipitation method. Core–shell composite magnetic polymer microspheres with carboxyl groups were synthesized by the dispersion polymerization of styrene and acrylic acid in the presence of magnetic oxide, and dibenzoyl peroxide was used as an initiator. The synthesized magnetic polymer microspheres were characterized with X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, and so forth. The results indicated that the product was single‐phase Fe₃O₄, and its average size was about 10 nm. The configuration of the microspheres, which contained carboxyl groups, was spherical, and the average size was about 2 μm. The results of vibrating sample magnetometry tests showed that the magnetic powders produced by different surfactants had different saturation magnetizations. When poly(ethylene glycol) with a weight‐average molecular weight of 4000 was used as a surfactant, the saturation magnetization of the samples reached 69.2 emu/g. The factors that affected the shape, magnetism, size, and distribution of the microspheres were also studied. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

An SVD-based adaptive robust speech steganography using MDCT coefficient

Multimedia Tools and Applications - Speech is one of the essential ways of communication. The study of speech steganography provides great value in information security. To improve imperceptibility...     

Oxidation behavior and mechanism of aluminum oxynitride (AlON) at elevated temperatures

The oxidation behavior and mechanism of aluminum oxynitride (AlON) powder exposed to air at elevated temperatures between 800°C and 1300°C was investigated by X-ray diffractometry (XRD), scanning electron microscope (SEM), electron spin resonance (ESR), nuclear magnetic resonance (NMR), and simultaneous thermogravimetry, differential thermal analysis, and mass spectrometry techniques (TG-DTA-MS). The weight of AlON gradually increases to a maximum value at 1150°C and then decreases with further heating. Meanwhile, AlON powder undergoes chemical changes, as evidenced by lattice expansion, and turns eventually into alumina. ESR spectra reveal the occurrence of lone pair electrons in the oxidized products and the intensity of corresponding resonance signal increases before disappearing with the increase in temperature. Combined with the results of NMR and TG-DTA-MS, the measured data suggest that Al-N in [AlO₃N] tetrahedron and [AlO₅N] octahedron are gradually oxidized into Al-O-N group with lone pair electrons, which causes continuous weight gain and lattice expansion. Further oxidation at higher temperatures results in alumina and N₂.     

叔胺萃取分离精炼铂的新工艺

用三烷基胺（Ｎ２３５）萃取分离铂，考察了稀释剂、改质剂浓度、料液酸度对分配系数的影响，从复杂的工业料液中，用Ｎ２３５萃取、洗涤、反萃、再生及精炼铂的工艺技术。     

SiO_2/Al_2O_3 RATIO OF HYDRATED SODIUM ALUMINOSILICATE IN ALUMINA PRODUCTION

ＳｉＯ２／Ａｌ２Ｏ３ＲＡＴＩＯＯＦＨＹＤＲＡＴＥＤＳＯＤＩＵＭＡＬＵＭＩＮＯＳＩＬＩＣＡＴＥＩＮＡＬＵＭＩＮＡＰＲＯＤＵＣＴＩＯＮ①ＤｅｎｇＨｏｎｇｍｅｉ，ＺｅｎｇＷｅｎｍｉｎｇ，ＣｈｅｎＮｉａｎｙｉＳｈａｎｇｈａｉＩｎｓｔｉｔｕｔｅｏｆＭｅｔａｌｕ...     

用于腺苷检测的基于级联扩增核酸适体电化学传感界面的构建研究

该文报道了一种基于酶级联扩增的电化学核酸适体检测腺苷的新方法。当腺苷存在时,滚环扩增的引物通过E.coli DNA连接酶的作用与通过巯基组装在金电极上的固定探针连接。在pHi29 DNA聚合酶的作用下,滚环扩增反应进行并产生一条与环形探针完全互补的长的单链,然后将大量金纳米粒子标记的核酸探针与滚环扩增的产物杂交。该传感界面电化学行为的结果表明,通过酶级联扩增的方法提高了检测腺苷的阻抗响应灵敏度,且选择性和重现性良好。用于腺苷的检测时,其线性范围为2.0μmol/L~100μmol/L,最低检测浓度为2.0μmol/L,表明该传感界面的设计可作为一种通用方法而有望用于其它目标物的检测。     

Parallel computation of determinants of matrices with multivariate polynomial entries

In this paper we present an extension to the work of Björck et al. for computing the determinants of matrices with univariate or bivariate polynomials as entries to multivariate case. The algorithm supports parallel computation and has been implemented on a multi-core cluster computer system. We show how to use our approach to calculate two unsolved problems, which arise from computational geometry optimization and electric power engineering, and analyze the time complexity as well as bits complexity.     

Supervised classification of share price trends

Share price trends can be recognized by using data clustering methods. However, the accuracy of these methods may be rather low. This paper presents a novel supervised classification scheme for the recognition and prediction of share price trends. We first produce a smooth time series using zero-phase filtering and singular spectrum analysis from the original share price data. We train pattern classifiers using the classification results of both original and filtered time series and then use these classifiers to predict the future share price trends. Experiment results obtained from both synthetic data and real share prices show that the proposed method is effective and outperforms the well-known K-means clustering algorithm.     

基于Web的计算机课程作业管理系统设计和实现

本文所阐述的基于Web的作业管理系统．利用网络编程．实现在一个平台上进行作业的上交、批改、以及成绩的统计和查询等操作．为教学的进行提供了有效便捷的手段。