钢液定氧测头响应时间和热平衡态

本文分别研究了ＺｒＯ２（ＭｇＯ）固体电解质管头壁厚，参比电极量对定氧测头响应时间的影响，得出了以ＺｒＯ２管头壁厚为０．６０－０．８０ｍｍ，Ｃｒ／Ｃｒ２Ｏ３参比电极加入量为４０－６０ｍｇ所组成的定氧测头响应速度最快，同时采用了“双偶法”对定氧测头在工作过程中的热平衡态进行了研究。结果表明：氧浓差电池中的传热是响应过程的控速步骤，氧电势曲线上峰值的产生是起源于电池中的热平衡态。     

基于强跟踪滤波器估计的最优融合方法

在分布式雷达数据处理模式中 ,数据融合是获得较精确的目标轨迹的主要环节。为克服卡尔曼滤波器对初始值敏感、鲁棒性差和对机动目标跟踪性能差的缺陷 ,通过利用各传感器的观测数据 ,采用强跟踪滤波器对目标进行跟踪 ,以改善目标状态估计的精度。对判定源于同一目标的状态估计值 ,给出了一种估计状态线进行性组合的最优融合准则。得出了实际数据的实验结果。     

可编程控制器调速器

本文以联合研制成功的水电站可编程控制调速器为对象，详细介绍其硬件与软件构成及工作原理。同时，对多种调节模式等方面也进行了一些探索。     

高含固量聚苯乙烯－聚丙烯酸酯复合乳胶的合成及表征

本文采用种子乳液聚合技术，合成聚苯乙烯－聚丙烯酸酯复合乳液，用ＴＥＭ电镜观察其乳液的形态，用ＧＰＣ方法测定了乳胶聚合物的化学组成。     

AC=BD在微分方程中的应用

利用AC＝BD的思想，将变系数广义KdV方程约化成常微分方程，求出了KdV方程的Lax对。     

九十年代计算机网络发展趋势

本文详细介绍了国外计算机网络发展的最新技术，并阐明了计算机网络发展的五种趋势．     

Frequent mtDNA mutations and its role in gastric carcinogenesis

In order to disclose the relationship between mutations of mitochondrial DNA (mtDNA) and gastric carcinogenesis, we screened the entire mtDNA sequence in 30 cases of human gastric cancer and matched normal tissues by using denaturing high-performance liquid chromatography (DHPLC) and DNA sequencing. Our data showed that high frequency (66.7%, 20/30) of mitochondrial genome mutation occurred in gastric cancer. Among these variants, 17 cases (56.7%, 17/30) were identified to be somatic mutation. High level mutant frequency was found in ND4, ND5 coding genes and D-loop control region, which was 36.7%, 26.7% and 30% respectively. Comparing with complexes Ⅲ, Ⅳ and Ⅴof the electron transport chain, we found that variants appeared to be more frequent in the subunit genes of complexⅠ. Most of mutations were base substitutions (85.4%, 41/48). Our results suggested that mutations of subunit genes encoding complexⅠ, especially ND3, ND4 and ND5 genes, might contribute to human gastric carcinogenesis.     

高效凝胶渗透色谱测定硅油分子量及其分布

采用ＨＰＧＰＣ与蒸汽压渗透（ＶＰＯ）结合的方法研究了甲基苯基硅油等分子量及其分布测定方法。     

浅谈运动疗法在康复医疗中的应用

简述了运动疗法在康复医疗中的地位、作用及应用，并介绍了常见的运动疗法。     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-