新时期体育教学与运动训练异同性的再研究

新时期是知识经济的时代。本文结合新世纪初的时代背景特征，从体育教学和运动训练的目的任务、实施内容、实施方法、发展趋势等方面进行异同性的比较研究，旨在对21世纪初的体育教学和运动训练重新认识和定位，为体育工作者提供参考。     

房屋改造工程设计及施工要点分析

通过分析多项工程的加固改造设计和施工要点,提出了多种扩建改造加固的方法和处理加固设计中常见疑难问题的措施.     

论会计能力模块课程体系的设计与实施

针对会计教学改革的不断深入，提出了会计能力模块课程体系的设计思路，论述了会计能力模块开发的现实性，模块设计的原则，类型及教学研究与实施方法。     

高等学校学科知识联盟

借用企业知识联盟的一些思想,阐述了高校学科知识联盟的形式、意义以及构建方法。     

沪杭高新技术产业发展交流分析

高新技术是高科技与新技术的组合,相对于一般传统技术而言的新兴尖端技术,它包含了以电子信息技术、生物技术、新材料技术、新能源技术和航天技术等为代表的高新技术群.     

Tissue-specific and reversible RNA interference in transgenic mice

Genetically engineered mice provide powerful tools for understanding mammalian gene function. These models traditionally rely on gene overexpression from transgenes or targeted, irreversible gene mutation. By adapting the tetracycline (tet)-responsive system previously used for gene overexpression, we have developed a simple transgenic system to reversibly control endogenous gene expression using RNA interference (RNAi) in mice. Transgenic mice harboring a tet-responsive RNA polymerase II promoter driving a microRNA-based short hairpin RNA targeting the tumor suppressor Trp53 reversibly express short hairpin RNA when crossed with existing mouse strains expressing general or tissue-specific 'tet-on' or 'tet-off' transactivators. Reversible Trp53 knockdown can be achieved in several tissues, and restoring Trp53 expression in lymphomas whose development is promoted by Trp53 knockdown leads to tumor regression. By leaving the target gene unaltered, this approach permits tissue-specific, reversible regulation of endogenous gene expression in vivo, with potential broad application in basic biology and drug target validation.     

中立型时滞双曲微分方程的振动准则

建立了一类中立型非线性时滞双曲微分方程的若干新的振动准则,结论推广和改进了一些文献中的定理.     

流形上微分方程求解的渐近展开方法

文章陈述了流形上微分方程、渐近级数和渐近展开等概念和相关命题,然后给出了例子,用渐近展开方法求解了微分方程。     

利用DA算法实现大规模FIR滤波器

分布式算法是一种广泛地应用在可编程逻辑序列（FPCA）和ASIC设计中计算乘积和的算法。DA算法的处理速度仅与输入的位宽有关，对于大规模乘积和的运算，其计算速度有着明显的优势。当输入位宽过大时，可以将DA算法改进成并串结构以获得更快的处理速度。该文对在FPCA中利用DA算法实现大规模FIR滤波器，提出了具体的实现方案。     

An efficient algorithm to generate candidates in discovering frequent episodes

0 IntroductionData mining is widely used in many research fieldssuch as decision supporting systems[1], bio-informationanalysis[2]and knowledge engineering[3-5]. Most data col-lected from scientific experiments or telecommunicationnetworks have inherent sequential nature inthemand canthus be abstractly viewed as a sequence of events . Onebasic problemin miningsuchevent sequencesis discoveryof recurrent combinations of events , which are calledepisodes. Once frequent episodes are discovered,rul…