Expression of green fluoscrescent protein gene in Sclerotinia sclerotiorum

Protoplasts of the pathogenic plant fungus,Sclerotinia sclerotiorum,were transformed using the pPGF plasmid,which contains green fluorescent protein gene,under the control of Aspergillus nidulans regulatory sequences. The pPGF plasmid was introduced by PEG/CaCl2 treatment. Positive transformants were harvested with hygromycin B (HYG) resistance as selective marker,and then were observed with green fluorescence phenomena in response to blue light,which suggested that GFP gene was cloned into genome DNA of S. sclerotiorum. The transformants were verified mitotically stable by Southern blotting analysis and passage culturing. This study is developed as an initial step for further research into infection mechanisms of S. sclerotiorum to plants and interactions with bio-control fungus.     

Novel fluorescence sensor based on covalent immobilization of 3-amino-9-ethylcarbazole via electrostatically assembled gold nanoparticle layer

A novel technique of immobilizing indicator dyes by electrostatic adsorption and covalent bonding to fabricate optical sensors was developed. 3-Amino-9-ethylcarbazole (AEC) was attached to the outmost surface of quartz glass slide via aminosilanizing the slide, crosslinking chitosan, adsorbing Au nanoparticle, self-assembling HS(CH₂)₁₁OH, and coupling AEC. Thus, an AEC-immobilized optical sensor was obtained. The sensor exhibits a wide linear response range from 7.0×10⁻⁷ to 1.0×10⁻⁴ mol/L and a correlation coefficient of 0.995 9 for the detection of 2-nitrophenol. The detection limit and response time of the sensor are 1.0×10⁻⁷ mol/L and less than 10 s, respectively. The fluorescence intensity of the used sensor can be restored to the blank value by simply rinsing with blank buffer. A very effective matrix for immobilizing indicator dye is provided by the proposed technique, which is adaptable to other indicator dyes with amino groups besides AEC. Foundation item: Project(20775010) supported by the National Natural Science Foundation of China; Project(208095) supported by the Key Project of Ministry of Education, China; Project(07A006) supported by the Scientific Research Fund of Hunan Provincial Education Department, China; Project(07JJ3020) supported by Hunan Provincial Natural Science Foundation of China     

基于灰度合成的图像素描效果生成算法

提出一种采用灰度合成的图像素描效果快速生成算法,实现真实感图像的艺术化生成.不同于已有算法只是利用经典的边缘检测方法来提取图像的边缘特征,本算法通过灰度信息分布来控制素描图像的细节特征,通过灰度合成得到图像边缘特征的加强和柔化,形成素描效果.算法首先得到输入图像的灰度反色图,并对其进行高斯模糊滤波,平滑边缘特征.然后采用灰度合成将滤波后的反色图和输入图像的灰度图进行合成,并同时起到对混合的图像的亮度进行自适应调整的作用,形成图像素描艺术风格.实验结果表明,算法在突出边缘特征的同时,能够较好地保持输入图像的细节特征,并实现素描效果.     

低固相含量液流中磨蚀翼型空化特性研究

针对水力机械内部空蚀及泥沙磨损联合作用破坏问题,探索空化促进磨损破坏的方式.在闭式循环装置的收缩-扩散实验段中,采用激光-CCD系统获取低固相含量下空化场中翼型表面多个断面的空穴结构分布,分析了空穴结构空间分布规律及其初生、发展、脱落、溃灭的周期性行为特征.针对空穴结构分布,采用了一种基于统计原理的图像处理方法,获得了空泡云平均值及标准差值的灰度分布,前者为流场中各位置的空化程度,后者为各位置空泡云体积变化率的分布.结合已有的空蚀磨损研究成果认为,水力机械内部空化促进颗粒磨损的方式取决于空穴结构及其体积变化率在流场中的分布规律.     

结合图像属性的MSD-FICA盲水印算法

基于图像高频子分量相互独立的属性,再结合图像低频能量不易丢失的特点,该文设计了多分辨率子带分解的快速独立分量分析(MSD-FICA)盲水印算法,借鉴了经典的量化调制水印(QIM)算法思想,对原始图像小波分解后的高频成分(水平、垂直、对角小波系数)进行排序,取中频成分。嵌入水印是对中频分量系数和低频分量系数同时嵌入,水印的提取采用快速独立分量分析(FICA)算法,先用主成分分析进行预处理,然后用FICA盲提取水印。实验表明,该算法能有效地提取出水印,并能抵抗一定的压缩、滤波、噪声攻击。     

茶饮料中糖精钠的测定

建立了茶饮料中糖精钠的荧光分光光度测定方法。样品前处理采用盐酸酸化,加入氯化钠,乙醚萃取后再用2 g/L碳酸钠溶液洗涤乙醚萃取层,加热除去乙醚定容后用荧光光度计测定。测试条件为：激发波长265 nm,发射波长475 nm。方法检测限为2 mg/kg,线性范围在2～60 mg/kg之间,变异系数为1.97%,回收率96.8%。     

医学CT断层图像三维重建的Matlab实现方法

介绍了运用Matlab软件进行CT断层图像的三维重建的原理及实现方法。运用计算机图形学和图像处理技术将计算机断层扫描（CT）等成像设备得到的人体断层二维图像序列,在计算机中重建成三维图像数据,并在屏幕上形象逼真地显示人体器官的立体视图。可以对重构出的器官图像进行诸如旋转、缩放等操作,重建方法简单,显示效果良好。     

微粒群优化和区域生长结合的彩色图像分割算法

提出了一种微粒群优化和区域生长相结合的彩色图像分割算法,以彩色图像直方图中自适应搜索到的峰值作为像素种子。由于搜索像素种子点是按密度进行,计算量小,大幅度提高了算法的计算速度,同时克服了传统区域生长方法不能自动选择种子且容易导致过分割的局限性。实验表明：该方法提高了图像分割速度,并可以准确地分割出目标,是一种有效的图像分割方法。     

层状磷酸锆的制备及插层研究

具有层状结构的磷酸锆α-Zr（HPO4）2·H2O通过粉末X-射线衍射（XRD）,振动光谱（红外IR和拉曼光谱Raman）,热分析仪（TG）,透射电子显微镜（TEM）,扫描电子显微镜（SEM）和BET氮气吸附等手段进行了表征.所制备的α-Zr（HPO4）2·H2O的BET表面积为12.29 m^2/g.研究了α-Zr（HPO4）2·H2O的插入行为,与四甲基溴化铵和十六烷基三甲基溴化铵的插入反应表明插入是完全的,层间距分别增加了0.46 nm和1.68 nm,且插入化合物的荧光性质在室温被检测.     

一种基于变精度粗糙集的图像分类方法

基于变精度粗糙集,引入近似区分矩阵的概念,提出一种基于颜色特征的图像分类模型及其分类算法.变精度粗糙集理论在数据分类应用中主要是将集合间精确的包含关系改为多数包含关系,既允许一定程度的错误分辨率存在.用该方法进行图像资源的分类,克服了经典粗糙集不宜处理带有噪声的数据和决策表不协调的分类问题的缺陷,同时又大大简化分类规则,且形成的规则集便于用户理解.完善近似空间的概念.实验结果表明：在处理决策表不协调的图像分类问题,变精度粗糙集方法性能良好,分类准确、高效.