Proteomic aspects of infection by lymphocystis disease virus in Japanese flounder (Paralichthys olivaceus)

To reveal the key factor in self-healing from LCDV (lymphocystis disease virus)-infec Japanese flounder (Paralichthys olivaceus), serum proteins from self-healing and sick Japanese floun were separated by two-dimensional electrophoresis to screen differentially expressed proteins. Prot spots demonstrating changes greater than two-fold in the expression level were digested and furt identified in capillary liquid chromatography tandem mass spectrometry (LC-MS/MS). Two immuni relevant proteins were thus identified as transferrin and the complement component C3 of Japan flounder. These findings suggest that the two proteins may play important roles in the self-healing lymphocystis in Japanese flounder. This is an important theoretical foundation to promote self-healing LCDV-infected Japanese flounder by improving their innate immunity.     

谱线形成深度的理论及其应用(Ⅰ):贡献函数和谱线形成深度

本系列文章中给出了谱线形成深度理论的发展特别是其最新进展，分别叙述了与此理论相联系的贡献函数和响应函数的演化过程，讨论了此理论的应用特别是用于太阳矢量磁场空间三维结构的推导．在这第一篇文章中，叙述了与贡献函数相夫的理论，指出了应用此理论的局限性，并讨论了唯一性问题．     

山东省构造体系的成生发展历史

本文用地质力学的观点,以构造体系的成生发展过程来反映山东地质发展历史,分别叙述了每个地质年代内,山东所处的构造应力场,各种构造体系的活动方式,以及它们活动所控制的沉积和岩浆活动。太古代至古生代山东主要受到了东西向构造体系的控制,形成了基底“地槽”和“地台”盖层。中生代以来主要受到了新华夏系的控制,此外尚有东西向构造和南北向构造体系的活动。在新华夏系活动的同时,还分别派生了一些大型的帚状构造、“S”型构造、入字型构造等。上述这些构造体系的成生发展过程,形成了许多拗陷、凹陷、断裂、褶皱等结构面;沿着断裂还侵入有岩浆,形成大小不等的各种岩体;同时控制形成了各种内生和外生矿产;在一些地方各种不同的构造体系还发生了联合和复合作用。新生代,尤其是新构造活动,各种构造体系的活动还控制了现代山川形势和地层及岩体的展布。     

Time Lags of Z Source GX 5-1

We investigated the time lags and the evolution of the cross spectra of Z source GX 5-1, observed by the Rossi X-ray Timing Explorer (RXTE), when it is in the horizontal branch oscillations. We showed that the time lags of three horizontal branch oscillations are related to the position on the hardness intensity diagram. All of the three QPOs were shown to have hard time lags. However on the cross spectra, one is in a ‘dip’, one in a ‘bump’, the other has not so obvious characteristic. The time lags of two of the QPOs decrease with QPO's frequency, while the other has a trend increasing with its frequency. Moreover, in the normal branch, we found no significant time lags in the present observational data. This revised version was published online in July 2006 with corrections to the Cover Date.     

A METHOD TO ESTIMATE DYNAMIC HEIGHT AND GEOSTROPHIC TRANSPORT RELATIVE TO DEEPER LEVELS FROM 400M EXPENDABLE BATHYTHERMOGRAPH IN THE INDONESIAN THROUGHFLOW

The Expendable Bathythermograph (XBT) Programme used a mix of T4 (450m) and T7(750 m) XBT's during the pre-TOGA periods. Studies are needed to determine how to use the T4/T7 datatogether, in particular with regard to a reference level for calculation of dynamic height and geostrophiccurrents. Temperature profiles to 750 m collected from 1986 through 1989 on the trackline across theIndonesian throughflow between NW Australia and Java are used to show the relations between dynamicbeight and geostriohic flow using reference levels at 400 db and 750 db. A very high temporalcorrelation between vertically averaged temperture in the upper 400 m and dynamic height at 50 m rela-tive to 750 db was found. The corresponding regression relationships are presented for all one degree lati-tude bins along the section and can be used for dynamical calculation of currents in the upper 400 m rel-ative to 750 db .An attempt is made to estimate volume transport relative to 750 db from 400 m pro-files. Problems which make est     

黑龙江省测绘控制成果管理信息系统的开发

黑龙江省测绘控制成果管理信息系统结合办公自动化的发展 ,利用计算机等现代化办公设备和GIS、WEB技术、图文数据库、计算机制图等技术 ,实现地理信息数据的输入输出、文档查询、空间检索查询和统计分析等功能 ,以便管理人员掌握控制成果的分布、标志的完好情况 ,促进测量标志的管理     

水体中芽孢杆菌和微囊藻的生长及其资源竞争

以C、N、P为主要限制性因子研究了芽孢杆菌和微囊藻在水中的生长率 ,并据Monod方程了解种群增长率与营养浓度之间的关系 ,以判断藻菌资源竞争的结果。研究结果显示 ,氮浓度的升高或磷浓度的降低 ,即N/P比值的升高 ,有利于芽孢杆菌的生长 ;而当氮浓度一定时 ,C/N比值越高 ,芽孢杆菌生长得越好。而微囊藻作为一种自养的光合植物 ,其生长与水中的C源无关 ,与氮磷浓度有关。氮磷浓度越高则生长越好。在此研究结果基础上进行藻菌生长动态的比较表明 ,在氮限制条件下 ,微囊藻的生长率稍高于芽孢杆菌 ;在磷限制条件下 ,芽孢杆菌的生长率总是大大高于微囊藻的生长率     

基于机器学习的大地电磁时域数据处理的研究现状

大地电磁测深法基于天然电磁场,其存在信号弱频带宽的特点,因此很难获得无噪声的数据,而传统的大地电磁数据处理方法面临着噪声环境日益复杂、对于海量数据的处理效率不高和难以剔除持续性噪声等诸多挑战.机器学习方法是一种基于统计分析的数据驱动方法,能够发现数据内部的结构和规律,从而对未来时刻和未知状态进行预测和判断.本文从大地电磁噪声分析入手,基于目前在大地电磁数据处理中研究和应用较为广泛的神经网络、字典学习等机器学习方法,分析了其方法原理、应用领域及优缺点,并与传统方法做了对比.发现机器学习方法在海量数据处理、大地电磁噪声模式识别和特征提取、数据预测等方面具有巨大的优势.同时,提高泛化能力和将机器学习方法与大地电磁理论相结合等仍是目前需要进一步探索的问题.随着计算机技术的发展和三维探测的实用化,机器学习方法在大地电磁数据处理中的应用将更加广泛.