Hydroacoustic study of spatial and temporal distribution of Gymnocypris przewalskii (Kessler, 1876) in Qinghai Lake, China

Gymnocypris przewalskii (Kessler 1876) is an endangered and state-protected rare fish species in Qinghai Lake, China. To further understand the life history and distribution of this fish, five surveys were carried out in Qinghai Lake between 2002-2006. Results of these surveys indicate that fishes were predominantly distributed about 2 m under the surface. In July, significant differences in fish density were found between surface and bottom layers (P = 0.001), and/or between middle and bottom layers (P = 0.025). Fish density was the greatest in the surface layer. In August and October, no significant differences were found between the different layers, but the bottom layer had a greater fish density. Furthermore, there were very large differences among different zones in fish distribution density. Differences in horizontal distribution were not significantly correlated to factors such as water depth and inshore distance, possibly because of very low and uniform fish density. Feeding, changes in water temperature, over-wintering and spawning appeared to influence fish distribution. Hydroacoustic estimates of G. przewalskii biomass in Qinghai Lake increased significantly between 2002 and 2006. We attribute this increase to the management measures put in place to protect this species.

Amplified fragment length polymorphism analysis to identify the genetic structure of the Gymnocypris przewalskii (Kessler, 1876) population from the Qinghai Basin, China

Amplified fragment length polymorphism (AFLP) was used to analyse the genetic structure of 45 individuals of Gymnocypris przewalskii (Kessler, 1876), an endangered and state-protected rare fish species, from three areas [the Heima (HM), Buha (BH) and Shaliu rivers (SL), all draining into Qinghai Lake]. A total of 563 polymorphic loci were detected. The HM, BH and SL populations have 435, 433 and 391 loci, respectively (Zhu and Wu, 1975), which account for 77.26%, 76.91% and 69.45% of the total number of polymorphic loci of each population, respectively. The Nei indices of genetic diversities (H) of the three populations were calculated to be 0.2869 (HM), 0.2884 (BH) and 0.2663 (SL), respectively. Their Shannon informative indices are 0.4244, 0.4251 and 0.3915, respectively. Research results show that the mean genetic distance between HM and BH is the smallest (0.0511), between BH and SL is the second shortest (0.0608), and between HM and SL is the largest (0.0713), with the mean genetic distance among the three populations being over 0.05. Data mentioned above indicate that the three populations have a certain genetic differentiation. The total genetic diversity (H-t = 0.3045) and the mean value of genetic diversity within the population (H-s = 0.2786) indicate that the variations have mainly come from within the population.

1876-1878 severe drought in North China: Facts, impacts and climatic background

Chinese Academy of Sciences [KZCX2-YW-315-2]; National Natural Science Foundation of China [40701021, 40625002]; National Key Technology R&D Program of China [2007BAC03A01]

一种Stewart结构六维力/力矩传感器参数辨识研究

介绍了一种大量程Stewart结构六维力/力矩传感器系统.建立了传感器力/力矩测量数学模型,构建了基于运动学逆解的优化目标函数.提出了一种新的参数标定法,称作分支轮换标定法.基于所研发的六维力/力矩传感器系统进行了实验研究,实验结果表明分支轮换法可以有效地辨识出传感器的结构参数,提高了测量精度.该方法可用于类似结构的六维力/力矩传感器参数标定.

大射电望远镜精调Stewart平台工作空间分析

针对大射电望远镜精调Stewart平台的五自由度运动特性,采用快速极坐标搜索法确定了五自由度大射电望远镜精调Stewart平台的工作空间.通过实例分析验证了所提出的工作空间分析方法的有效性.为大射电望远镜馈源轨迹跟踪实现和精调Stewart平台的设计奠定了坚实的基础.

基于Stewart平台六维力传感器的分区静态标定方法

基于Stewart平台的六维力传感器具有结构紧凑、刚度大、量程宽等特点,它在工业机器人、空间站对接等领域具有广泛的应用前景。好的标定方法是正确使用传感器的基础。由于基于Stewart平台的六维力传感器是一个复杂的非线性系统,所以采用常规的线性标定方法必将带来较大的标定误差从而影响其使用性能。标定的实质是,由测量值空间到理论值空间的映射函数的确定过程。由函数逼近理论可知,当只在已知点集上给出函数值时,可用多项式或分段多项式等较简单函数逼近待定函数。基于上述思想,本文将整个测量空间划分为若干连续的子测量空间,再对每个子空间进行线性标定,从而提高了整个测量系统的标定精度。实验分析结果表明了该标定方法有效。

并联Stewart机构位姿误差分析

从并联机构与串联机构的运动学等效 ,并联机构本身特征与并联机构实际工作空间出发 ,考虑各分支末端误差对最终运动平台末端误差的影响 ,提出了并联机构位姿误差放大因子分析法·依据位姿误差放大因子具有对误差定量分析的特点 ,该分析方法既可用于机构参数优化 ,又可用于结构精度设计· 最后 ,给出了一个实例说明本方法的有效性·