Synthesis,characterization, and thermal properties of phosphorus‐containing,wholly aromatic thermotropic copolyesters

A series of phosphorus‐containing, wholly aromatic thermotropic copolyesters from acetylated 2‐(6‐oxide‐6H‐dibenz〈c,e〉〈1,2〉oxa phosphorin‐6‐yl)‐1,4‐dihydroxy phenylene, p‐acetoxybenzoic acid, terephthalic acid, and isophthalic acid were prepared by melting polycondensation. The structure and basic properties of the polymers, such as the glass‐transition temperature (T_g), melting temperature (T_m), thermal stability, crystallinity, and liquid crystallinity, were investigated with Fourier transform infrared, elemental analysis, differential scanning calorimetry (DSC), thermogravimetric analysis, wide‐angle X‐ray diffraction, and hot‐stage polarizing optical microscopy. The copolyesters had relatively high T_g values ranging from 183 to 192°C. The T_m values obtained from DSC curves for samples P‐20 and P‐25 were 290 and 287°C, respectively (where the number in the sample name indicates the molar fraction of the phosphorus‐containing monomer in the reactants). The initial flow temperatures of other samples observed with hot‐stage polarizing microscopy were 271–290°C. The 5% degradation temperatures in nitrogen ranged from 431 to 462°C, and the char yields at 640°C were 41–52%. All the copolyesters, except P‐40, were thermotropic and nematic. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 1278–1284, 2002     

混合材对碱—碳酸盐反应的影响

利用快速测长法研究了混合材对碱—碳酸盐反应的影响。通过试验证明混合材能减缓碱—碳酸盐反应的速度,但不能有效地抑制碱—碳酸盐反应,并初步探讨了混合材不能有效地抑制碱—碳酸盐反应的机理。     

An efficient KPCA algorithm based on feature correlation evaluation

Classic kernel principal component analysis (KPCA) is less computationally efficient when extracting features from large data sets. In this paper, we propose an algorithm, that is, efficient KPCA (EKPCA), that enhances the computational efficiency of KPCA by using a linear combination of a small portion of training samples, referred to as basic patterns, to approximately express the KPCA feature extractor, that is, the eigenvector of the covariance matrix in the feature extraction. We show that the feature correlation (i.e., the correlation between different feature components) can be evaluated by the cosine distance between the kernel vectors, which are the column vectors in the kernel matrix. The proposed algorithm can be easily implemented. It first uses feature correlation evaluation to determine the basic patterns and then uses these to reconstruct the KPCA model, perform feature extraction, and classify the test samples. Since there are usually many fewer basic patterns than training samples, EKPCA feature extraction is much more computationally efficient than that of KPCA. Experimental results on several benchmark data sets show that EKPCA is much faster than KPCA while achieving similar classification performance.     

关于煤化工前途的思考

对煤化工存在的问题做了分析,提出加大科研投入,获取自主知识产权,解决煤化工装置大型化、国产化,坑口气化,煤层气开发利用等煤化工重点问题,适合我国国情的煤化工将有良好的发展前景。     

时间Petri网与CAGA算法相结合的并行测试研究

在并行测试的研究中对于任务的测试次序一直是个研究重点及难题。用时间Petri网建立关于并行测试系统的模型,并首次用元胞遗传算法(CAGA)对模型中的变迁序列进行搜索,快速得到最好的测试序列。通过仿真结果表明,该算法展示了很好的收敛效果,并且与已有的研究成果相比更具优势。     

天线姿态监控管理系统中管控主机的设计

随着移动网络的发展,电信运营商加强对信号基站的部署,同时特别关注天线的姿态及信号的覆盖情况,需求一种能够提供远程集中管理的系统方案。设计了一种管控主机,能够连接天线姿态传感器获取天线的姿态,同时可以集中管理不同型号的电调,结合天线姿态监控管理系统实现对基站天线姿态的远程监控,使运维人员可以随时随地了解天线姿态情况,给日常运维带来便捷,提高了工作效率。     

K_2O－CaO－Al_2O_3－SiO_2系统自释釉瓷化学组成的研究

本文从酸度系数着手，证实了Ｋ２Ｏ－ＣａＯ－Ａｌ４Ｏ久－ＳｉＯ２系统中存在自释釉组成，限定了其组成范围，０．６７％＜Ｋ２Ｏ＜１．２８％，１０．６４％＜ＣａＯ＜１３．６２％，１１．５３％＜Ａｌ４Ｏ３＜１５．３２％，７２．７３％＜ＳｉＯ２＜７４．０４％，并讨论了自释釉瓷的性能。     

新型可见光固化口腔正畸粘合剂研制

介绍了一种新型可见光固化正畸粘合剂的组成、性能及正畸粘接的工艺。此粘合剂由一种单组分液体底胶和单组分糊剂组成。与化学固化粘合剂相比,其操作使用方便,固化时间短。这种新型粘合剂的粘接强度完全满足了正畸粘合剂的要求。