海产动物选择育种的研究进展

随着养殖业的不断发展,优良品种的选育已日趋重要.本文对国外海产动物选择育种的进展情况作初步介绍和评价,以便大家对当前国际上在这方面的研究进展有所了解,同时也希望对国内这方面工作的开展起到一定的促进作用.     

除草剂San9785在高EPA后棘藻品系筛选中的应用

后棘藻(Ellipsoidion sp.)是一种高脂海洋微藻,采用微生物筛选平板的方法,利用多不饱和脂肪酸EPA合成的阻断剂——除草剂San9785对紫外线诱变的后棘藻细胞进行了高EPA个体的筛选,气相分析结果显示,在检测的8株筛选品系中,5株EPA含量高于出发藻种,平均提高了121.6%,另3株EPA含量低于出发藻种,平均降低的量为12.6%,EPA含量最高的品系达到总脂肪酸的26.22%,比出发藻种提高了212%.提示除草剂San9785可以作为一种高效筛选压力,选育多不饱和脂肪酸含量丰富的微藻品系.     

Information System for Ocean Wave Resources and Its Application to Wave Power Utilization

An information system for ocean wave resources and its application to wave power utilizationare indtroduced.It can manage,analyze and process the data in the monthly report of ocean wave observa-tion records of the State Ocean Administration,and can provide various kinds of curves and numericalcharacters of statistics.This system has been put into utility in Guangzhou Institute of Energy Conversion(GIEC),the Chinese Academy of Sciences since 1996.An application example is given of theinverstigation and analysis on ocean wave resource of the Nan Ao Island,Guangdong Province,where a100 kW onshore OWC(oscillating water column)wave power station will be built.The wave power distri-bution is obtained in different wave directions for different wave periods.It is found that 70 percent of thewave power comes from the direction of ENE,and more than 95 percent of the wave power is related withdirection E.The average wave power density is about 3 kW/m,and more than 80 percent of the wavepower is distributed in the     

Phenolics and Proteins Affecting Palatability of Spartina Leaves to the Gastropod Littoraria irrorata

Along the southeastern coast of the United States, the saltmarsh periwinkle Littoraria irrorata is a major consumer of Spartina alterniflora . It prefers to feed on dead rather than living plants. During senescence and early decay, S. alterniflora leaves become colonized by fungi, their phenolic content declines, and their lipid content increases. In this study, the food preferences of L. irrorata were assessed by offering intact leaves or leaf powder suspended in agar. Relative palatabilities were determined by measuring the weight loss of intact leaves, or by estimating the area of feeding marks left on the surface of leaf powder suspensions. Both techniques demonstrated a clear preference for standing dead rather than yellow-green (senescent) leaves. Yellow-green leaves contained methanol-soluble feeding deterrents. A comparable deterrent effect could be achieved by adding ferulic acid, a phenolic compound common in yellow-green S. alterniflora , to leaf powder. The deterrent effects of methanol extracts or ferulic acid could be neutralized by simultaneously adding fungal mycelium or BSA. Littoraria irrorata preferred leaves colonized by fungi or bacteria over sterile leaves. When offered a choice of sterile leaves colonized by different fungi, the results were variable. In one experiment, L. irrorata clearly preferred one of three leaffungus combinations. The same preference was shown after the food items were treated with methanol/chloroform to remove lipids. In a second experiment with four other fungal strains, there was only a clear preference for one leaf-fungus combination after removal of lipids. The results suggest that the saltmarsh periwinkle prefers S. alterniflora leaves with low concentrations of phenolic deterrents, most likely ferulic acid, and with sufficient fungal biomass. The food choice may be influenced to a smaller degree by fungal components, which, depending on the species or strain, may be lipids or other compounds.     

GENTOOLS在国家1：50000数据库更新工程中的应用研究

1：50000地形数据库更新是一项复杂的地形数据库制作工程。传统的缩编技术工艺与相应的工具难以适应新的生产需要,适应于数字环境下的缩编生产工具的需求则变得非常迫切。GENTOOLS很好地解决了1：50000数据库更新工程中的诸多难题,采用半自动和手动相结合的方法,大大提高了缩编效率,同时也为地形图缩编提供了一种新的选择。     

基于GANBPSO-SVM的高光谱影像特征选择方法

为了在保持对目标检测和分类分析所需信息的同时,降低高光谱影像的维度,提出了一种混合优化策略的特征选择方法。该方法将遗传算法和二进制粒子群优化算法融合成一种新的混合优化策略（GANBPSO）,自动选择最优波段组合,同时优化分类器支持向量机（RBF-SVM）的参数,以提高分类器的分类性能。为了说明所提出方法的有效性,采用了在高光谱分类中广泛使用的Indian Pines（AVIRIS 92AV3C）数据集进行测试。结果表明所提出方法（GANBPSO-SVM）能够自动选择包含最多信息的特征子集以保证分类精度,而不需要预先设置所需要的特征子集数量,本方法与传统方法相比具有更好的分类效果。     

Data field for mining big data

Abstract

Big data is a highlighted challenge for many fields with the rapid expansion of large-volume, complex, and fast-growing sources of data. Mining from big data is required for exploring the essence of data and providing meaningful information. To this end, we have previously introduced the theory of physical field to explore relations between objects in data space and proposed a framework of data field to discover the underlying distribution of big data. This paper concerns an overview of big data mining by the use of data field. It mainly discusses the theory of data field and different aspects of applications including feature selection for high-dimensional data, clustering, and the recognition of facial expression in human–computer interaction. In these applications, data field is employed to capture the intrinsic distribution of data objects for selecting meaningful features, fast clustering, and describing variation of facial expression. It is expected that our contributions would help overcome the problems in accordance with big data.     

数字海图水深注记的自动选取

水深注记作为表示海底地形地貌特征的主要制图要素,它的正确选取对于保证航海安全、反映海底地貌起伏具有重要意义。针对传统的水深注记方法,该文提出一种顾及多重约束条件的水深注记选取方法。在总结水深注记综合约束条件基础上,以Vononoi图为支撑几何构造,对水深注记综合涉及的地形特征、空间分布特征、邻近特征3个方面的综合约束进行了形式化定义;借鉴人工选取的思想,在水深综合约束条件重要性排序的基础上,通过反映地形、空间分布、邻近关系等主体特征的重要水深的依次选取,以及背景水深的抽稀实现水深注记选取;最后以实测数据进行实验,验证该方法的有效性。