超高压变质作用：地球科学的新热点

超高压质作用是变质压力达2.5Gpa 以上的超深变质作用。以出现柯石英、金刚石等超高压变质矿物为标志。我国大别苏鲁是世界上出露最好、延伸最长的超高压变质带。代表中晚三叠纪扬子陆块向中朝陆块深俯冲过程中巨量陆壳物质曾经进入地幔深度达150Km.超高压变质的形成和折返、隆升岩石记录的精细研究，可以获得变质的PT轨迹，进而重塑“先挤压、后拉张”的构造演化模型。超高压变质作用的研究为板块构造理论在大陆的应用，展开新前景，已经成为地球科学的新热点之一。     

辐射场与太阳帆之间的相互作用

用分子动力理论导出了辐射场施于静止帆和运动帆的压强,并从动力学观点讨论了辐射场与帆之间的能量转换效率,同时指出了文[1]存在的一些问题.     

竹纤维制取工艺中梳针选用的探讨

为了提高和改善竹纤堆制取中梳理工序的效果，探讨了梳针组合梳理竹纤维的方法，通过对最终制成纤雏的长度、线密度、强度等物理性能的测试，比较了各方法制取竹纤维的效果，时各梳理效果的不同进行了分析，并得出了最佳组合梳理方案应为采用20-10、20-15、22—10三种梳针依次梳理。并证明组合梳理是一种很有效的梳理方法。     

对信息时代艺术创作的思考

在利用信息化的语言诠释艺术理念的今天,艺术是否依然能够保留其原始的内涵和质朴的特征成为人们关注的热点.本文通过分析新时代艺术的若干特点,指出经典艺术面临的挑战.倡导艺术家积极应对信息化浪潮的冲击,用新的思维方式推动新世纪中华传统文艺的复兴.     

Suppression of Notch signalling by the COUP-TFII transcription factor regulates vein identity

Arteries and veins are anatomically, functionally and molecularly distinct. The current model of arterial-venous identity proposes that binding of vascular endothelial growth factor to its heterodimeric receptor--Flk1 and neuropilin 1 (NP-1; also called Nrp1)--activates the Notch signalling pathway in the endothelium, causing induction of ephrin B2 expression and suppression of ephrin receptor B4 expression to establish arterial identity. Little is known about vein identity except that it involves ephrin receptor B4 expression, because Notch signalling is not activated in veins; an unresolved question is how vein identity is regulated. Here, we show that COUP-TFII (also known as Nr2f2), a member of the orphan nuclear receptor superfamily, is specifically expressed in venous but not arterial endothelium. Ablation of COUP-TFII in endothelial cells enables veins to acquire arterial characteristics, including the expression of arterial markers NP-1 and Notch signalling molecules, and the generation of haematopoietic cell clusters. Furthermore, ectopic expression of COUP-TFII in endothelial cells results in the fusion of veins and arteries in transgenic mouse embryos. Thus, COUP-TFII has a critical role in repressing Notch signalling to maintain vein identity, which suggests that vein identity is under genetic control and is not derived by a default pathway.     

《微机组装与维修》课程教学设计理念与实践

在分析总结<微机组装与维修>课程教学工作的基础上,提出了该课程的"课程-专题-知识点"教学链的概念,并对该教学链进行了详细的分析和设计,最后陈述了实际教学过程中的效果.     

An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis

Using advanced gene targeting methods, generating mouse models of cancer that accurately reproduce the genetic alterations present in human tumors is now relatively straightforward. The challenge is to determine to what extent such models faithfully mimic human disease with respect to the underlying molecular mechanisms that accompany tumor progression. Here we describe a method for comparing mouse models of cancer with human tumors using gene-expression profiling. We applied this method to the analysis of a model of Kras2-mediated lung cancer and found a good relationship to human lung adenocarcinoma, thereby validating the model. Furthermore, we found that whereas a gene-expression signature of KRAS2 activation was not identifiable when analyzing human tumors with known KRAS2 mutation status alone, integrating mouse and human data uncovered a gene-expression signature of KRAS2 mutation in human lung cancer. We confirmed the importance of this signature by gene-expression analysis of short hairpin RNA-mediated inhibition of oncogenic Kras2. These experiments identified both a pattern of gene expression indicative of KRAS2 mutation and potential effectors of oncogenic KRAS2 activity in human cancer. This approach provides a strategy for using genomic analysis of animal models to probe human disease.     

基于统计模型的时-空相关海杂波仿真

工作于海洋环境下的雷达面临较严重的海杂波的影响,海杂波统计模型的研究对最优检测算法设计和雷达性能预估有重要作用。基于海杂波的复合散射理论,分析了海杂波非高斯幅度分布的特性、时间相关性及空间相关性。讨论了采用球不变随机过程产生时间和空间相关的海杂波仿真方法。对算法中散斑分量和纹理分量的参数估计,时间相关性和空间相关性的引入方法进行了分析。设定仿真环境仿真产生了具有时间和空间相关性的非高斯型海杂波数据,结果表明采用该方法的有效性。     

拟Banach空间上的凸性模与特殊鞅不等式

在拟Banach空间上引入了他凸性模，它是一致凸性模的推广，并证明了重赋拟范定理，在此基础上研究了取值于拟Banach空间的一类特殊鞅不等式与该空间的q一致TC可凸性的关系，从而用特殊鞅不等式刻画了空间的q一致化可凸性．     

基于SVM的句子组块识别

阐述了基于统计的SVM（支持向量机）模型的汉语句子组块识别. SVM模型使用已进行组块标注的语料，通过多种特征参数选择和多分类划分，对数据进行统计学习得到训练模型后实现. 给出模型的算法和识别结果，分析了统计模型的特点.