服装衣身合体性评价中的模糊数学方法

探讨了进行服装衣身合体性评价的模糊数学方法，建立了其理论隶属函数，对于进一步探讨衣身、衣袖合体配伍性评价提供了理论基础。     

四硫代钼酸铵与四硫代钨酸铵合成方法改进的研究

对钼酸铵与硫化氢反应合成四硫代钼酸铵、钨酸与硫化氢反应合成四硫代钨酸铵的方法进行了改进。结果表明，采用改进后的方法，反应时间分别为７小时和１１小时。比文献值￣［１１］缩短了许多。产率分别为９１．１％和５２．１％，均高于文献值￣［１］。     

多功能示教板的制作及在体育教学中的应用

通过多功能示教板的制作及应用 ,教师在教学过程中 ,改进教学方法 ,提高教学质量 ,使教学更加直观、立体、形象 ,增强了学生学习的兴趣     

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     

Isolation and purification of BVⅠ-2H from bee venom and analysis of its biological action

The medical use of bee venom for rheumatoid arthritis ( RA ) has a very long tradition. In this study, isolation and purification of polypeptides from bee venom were carried out on sephadex chromatography, heparin sepharose CL-6B chromatography and HPLC. Several fractions were extracted, and their effects on activation of splenocyte and THP-1 cell were studied. The inhibitory fraction was selected for further studies. Finally, BVⅠ-2H that the HPLC elution profiles was a single peak was isolated by C8 column. ESI- MS detection results showed that BVⅠ-2H was a fraction of bee venom, and the molecular weight of the major component was 644.8. BVⅠ-2H could inhibit ConA-induced splenocyte proliferation, IL-1 production and interfere with splenocyte cycle in mice. Moreover, BVⅠ-2H could inhibit PMA-induced TNFα production in THP-1 cells, which was due to its inhibitory effects on TNFα mRNA expression and protein phosphorylation of IκBα. Our studies indicated that BVⅠ-2H was one of the anti-inflammatory components of bee venom.     

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。     

作物高产性的光合碳同化生理限制因子分析

对影响作物高产的光合作用碳同化的生理限制因子进行了分析，提出内外因子结合考虑是提高作物的光合效率和产量的关键．     

多部图λκ_n(g)的G-设计,G为有1条悬边的4长圈

设λkn(g)是一个λ重完全n部图,G为一个不带孤立点的简单图,一个(λkn(g),G)-设计是将λkn(g)划分成边互不相交的子图,使得每一个子图都和G同构．在此基础上讨论了G为有1条悬边4长圈时多重完全多部图的G-设计的存在性．并给出其存在谱．     

Discovering Frequent Subtrees from XML Data Using Neural Networks

By rapid progress of network and storage technologies, a huge amount of electronic data such as Web pages and XML has been available on Internet. In this paper, we study a data-mining problem of discovering frequent ordered sub-trees in a large collection of XML data, where both of the patterns and the data are modeled by labeled ordered trees. We present an efficient algorithm of Ordered Subtree Miner （OSTMiner） based on two- layer neural networks with Hebb rule, that computes all ordered sub-trees appearing in a collection of XML trees with frequent above a user-specified threshold using a special structure EM-tree. In this algo- rithm, EM-tree is used as an extended merging tree to supply scheme information for efficient pruning and mining frequent sub-trees. Experiments results showed that OSTMiner has good response time and scales well.     

粗可能性测度

给定模糊可测空间(X，A)及(X，A)上的可能性测度，通过应用粗集理论，将可能性测度Ⅱ和模糊糊积分分别扩充至P(X)和F(X)上，从而引入粗可能性测度的概念。