Modification of the rib operon derived from Bacillus subtilis and its expression in Escherichia coli

A riboflavin operon （rib operon） derived from Bacillus subtilis 368 was modified on structure and the resulting operons were expressed in various strains of Escherichia coli. The results showed that the optimization of the rib operon and the host strain used for expression are two main factors affecting the riboflavin production. Replacing the promoterl and rfn box of the rib operon with a strong constructive promoter spol drastically increased the expression of the rib genes. When E. coli JM109 was used as the host strain, the highest riboflavin production reached 95.3μg/mL （about eight times higher than that of the unmodified r/b operon）. In addition, when tetracycline （20 μg/mL） was used as the selective pressure, compared with the ampicillin resistant transformants, a higher riboflavin yield was obtained in tetracycline resistant host strain.     

KDS-CM： A Cache Mechanism Based on Top-K Data Source for Deep Web Query

Caching is an important technique to enhance the efficiency of query processing. Unfortunately, traditional caching mechanisms are not efficient for deep Web because of storage space and dynamic maintenance limitations. In this paper, we present on providing a cache mechanism based on Top-K data source （KDS-CM） instead of result records for deep Web query. By integrating techniques from IR and Top-K, a data reorganization strategy is presented to model KDS-CM. Also some measures about cache management and optimization are proposed to improve the performances of cache effectively. Experimental results show the benefits of KDS-CM in execution cost and dynamic maintenance when compared with various alternate strategies.     

Research Progress on Artificial Cultivation of Trhicoloma Matsutake and Theory of the Shiro in Changbai Mountains

Study on artificial cultivation of Tricholoma matsutake carried through by the present research group in Changbai Mountains in recent years was briefly reviewed in the paper, and then, the signifycance of cultivation, mechanism of formation, hiberarchy, g     

试用数理统计方法评价考试质量

本文试用正态分布、相关分析等数理统计方法,对考试质量进行评价分析,目的在于开拓数理统计方法的应用领域。     

La2Ce2O7@La2Zr2O7核壳结构纳米粉体的 制备及其抗烧结性能

针对La_2Ce_2O_7抗烧结性能较差,La_2Zr_2O_7的热膨胀系数较低的性能特点,采用水热法合成了La_2Ce_2O_7内核,然后通过共沉淀法成功制备La_2Ce_2O_7@La_2Zr_2O_7核壳结构纳米粉体.将粉体预压成块,分别在1 100℃、1 300℃和1 500℃下进行了不同时间的烧结测试及在1 100～1 500℃烧结6 h以考察温度对其抗烧结性能的影响.采用扫描电镜、透射电镜、能谱仪分析了材料的形貌和成分,并测试了试样的密度和显微硬度.结果表明,La_2Ce_2O_7内核具有立方结构或八面体结构外形,粒径约200 nm. La_2Zr_2O_7壳层为非晶体,形成了包覆效果良好的La_2Ce_2O_7@La_2Zr_2O_7核壳结构.等温烧结时,核壳结构的密度变化率保持在2.1%以内,远低于La_2Ce_2O_7和La_2Zr_2O_7,孔隙和晶粒尺寸分布均匀,无裂纹和烧结现象出现.当烧结温度在1 300℃以内时,核壳结构组织均匀,多孔,密度变化率稳定在10.6%以内,晶粒尺寸约维持在450nm,晶粒长大速率与La_2Zr_2O_7接近,抗烧结性能良好;当烧结温度高于1 300℃时,核壳结构孔隙增大且晶粒迅速长大,致密化加快,晶粒长大速率也变快,与La_2Ce_2O_7接近,出现明显烧结现象;其显微硬度稍高于La_2Ce_2O_7,而远低于La_2Zr_2O_7.     

基于离群点剔除的SVM信用风险评价方法

针对信用评价数据存在离群点和噪声问题, 提出一种基于离群点剔除的支持向量机（SVM）信用风险评价模型. 该模型利用模糊c-均值聚类算法剔除样本离群点, 采用粒子群算法优化支持向量机分类参数, 进而提高支持向量机的分类性能. 将该方法应用于信用风险评价中的结果表明, 相比于其他模型, 该方法分类精度更高.     

粉末冶金多孔材料的平面孔径分布函数

本文根据统计分析原理,使用电子计算机验证多孔材料表面孔径服从瑞利(Rayleigh)分布律: P_R(x)={x/μ~2e~(-x~2/2μ~2-) x≥0 0 x<0     

青少年型喉乳头状瘤和外阴尖锐湿疣的临床和组织病理观察

通过组织病理观察，分析青少年喉乳头瘤的临床行为特征。方法：追踪病史，复习１０例小儿喉乳头状瘤和４例尖锐湿疣的临床和组织病理所见。结果：喉乳头状瘤和尖锐湿疣均为乳头状增生，镜下均以上皮组织增生为主要特征，棘细胞增生增厚，有异型性。喉乳头瘤可见凹空细胞（Ｋｏｉｌｏｃｙｔｅ）呈单个或小灶或片状分布，并多分布于棘层。而形态与喉乳头瘤凹空细胞基本一致的尖锐湿疣的凹空细胞可达基底层甚至全层。结论：结合临床行为，发现喉乳头状瘤标本有凹空细胞的病儿父母多有性病史，且多次复发，病历的标本中多见这一改变     

智能天线LMS算法的分析及实现方案

首先阐述了智能天线的基本原理和结构,然后分析利用LMS算法达到波束集成的原理和过程,并利用软件仿真分析LMS算法的性能,最后设计了LMS算法的硬件实现方案,并分析FPGA、DSP等器件的选择。     

Extracting Result Schema Based on Query Instances in the Deep Web

Deep Web sources contain a large of high-quality and query-related structured date. One of the challenges in the Deep Web is extracting result schemas of Deep Web sources. To address this challenge, this paper describes a novel approach that extracts both result data and the result schema of a Web database. The approach first models the query interface of a Deep Web source and fills in it with a specifically query instance. Then the result pages of the Deep Web sources are formatted in the tree structure to retrieve subtrees that contain elements of the query instance, Next, result schema of the Deep Web source is extracted by matching the subtree＇ nodes with the query instance, in which, a two-phase schema extraction method is adopted for obtaining more accurate result schema. Finally, experiments on real Deep Web sources show the utility of our approach, which provides a high precision and recall.