像势对量子阱中类氢杂质结合能的影响

在有效质量近似下，利用变分方法研究了像势对量子阱中类氢杂质结合能的影响。计算中考虑到了阱和垒中电子有效质量的不同。数值计算结果表明：阱和垒中质量的不连续只对阱宽较窄的区域有影响，而像势则在整个区域都有影响．对于阱和垒中介电常数之比较大和阱宽较小的量子阱，考虑像势对阱中杂质结合能的修正是非常必要的     

稳定性理论中的两个问题

本文讨论了吸引性与稳定性的关系,完善了稳定性的数学理论及应用一文中关于周期系统稳定与一致稳定等价的证明。     

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。     

弗里德曼空间和宇宙论

利用弗里德曼空间理论，讨论了宇宙学中的一些问题，主要内容：（１）弗里德曼空间的度规张量；（２）弗里德曼空间的能量动量张量；（３）弗里德曼空间的演化和温度的关系；（４）红向移动的理论公式．     

太行山长城岭南山东北坡植被的研究

本文研究了太行山长城岭南山东北坡的植被分布及其特征。结果表明,从山麓至山顶,由于气候条件随海拨的逐渐升高而产生了明显的垂直变化,从而导致了植被分布的垂直变化。从山麓至山顶依次分布有落叶阔叶林、针阔混交林、针叶林和落叶阔叶灌丛等四个植被型、并因人为干扰落叶阔叶林正向针阔叶混交林和针叶林方向演替。     

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-