人工育珠对三角帆蚌(Hyriopsis cumingii)遗传基因影响的初步研究

采用酚-氯仿和试剂盒两种提取法对三角帆蚌怀珠群与非怀珠群各6个个体进行基因组DNA的提取,然后在优化RAPD(随机扩增多态性DNA)检测条件基础上,从80个随机引物中筛选出12个扩增较好且多态性强的引物进行RAPD扩增,产物通过水平板琼脂糖凝胶电泳和垂直板聚丙烯酰胺凝胶电泳两种方法进行检验并对DNA的多态性进行分析。结果显示在怀珠群和非怀珠群检测到的位点数、多态位点比例、平均Shannon多态性信息指数、平均Nei's基因多样性指数、群体内个体间平均遗传相似率和平均遗传距离分别为100、33%、0.1927、0.1324、0.904、0.096,95、47.37%、0.2711、0.1879、0.861、0.139,群体间的平均遗传距离为0.821,非怀珠群的变异性大于怀珠群;本研究还获得了两群体各自的特异扩增谱带及两群体间表达差异较大谱带,这些位点很可能是由人工育珠所引起。根据MEGA4.0软件的UPGMA和NJ程序构建的分子系统树可直观地将两群体分开。     

Classifier ensembles for land cover mapping using multitemporal SAR imagery

SAR data are almost independent from weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e., boosted decision tree and random forests) are applied to multi-temporal C-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forests are computationally highly efficient and are hence considered very well suited for land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.     

植被电磁散射的半空间模型研究

本文给出了地面植被电磁散射的半空间模型研究方法.在以往的相关文献中,均采用自由空间格林函数求解单个叶片散射体的散射场,本文利用半空间并矢格林函数求出了单个散射体的散射场,然后运用Monte Carlo方法模拟生成地面植被层,得到了在半空间下植被层的电磁散射特性,计算出了单、双站雷达散射截面,并与自由空间下的散射场做了相互对比.结果表明,在半空间格林函数下得到的散射场更为适用于描述地面植被的电磁散射特性.     

On-line estimation of nonlinear physical systems

Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared.     

光石沟花岗伟晶岩型铀矿小型重选试验及技术经济初步评价

光石沟花岗伟晶岩型铀矿小型重选试验为工业利用花岗伟晶岩铀矿床的矿石，特别是低品位矿石方面开拓了新的途径。试验证明重选法在回收花岗伟晶岩型铀矿床矿石的铀以及回收副产品和防止环境污染等方面均优于湿法冶炼，并有好的经济效益。     

随机地震模型及反应谱分析

本文以实际地震加速度的频谱特性和相位谱特性为依据，仿概率统计理论中的高斯概率密度函数，建立了随机地震加速度频数学模型。     

场地土的随机地震反应分析

研究了剪切模量随深度呈线性变化时场地土的随机地震反应分析方法, 分别建立了基岩输入地震动加速度功率谱函数为白噪声和过滤白噪声时场地土的随机地震反应分析理论。     

随机-模糊处理方法在岩石力学指标统计及岩组划分中的应用

探讨了随机 模糊处理方法在岩石力学指标统计和岩组定量划分中的应用。文中对计算中的隶属函数取值及迭代方式进行了深入讨论。通过计算结果的比较分析, 认为随机 模糊处理方法更符合实际, 并优于其他方法。最后作者提出了岩组定性划分 岩石样本参数的随机 模糊统计分析 岩组定量划分及参数重新统计的分析程序。     

锂同位素质谱法测定及其样品制备研究进展

近几十年来，锂同位素比值的测量得到了快速的发展。影响锂同位素比值测定因素很多，特别是在测定过程中分馏现象和记忆效应等都会引起锂同位素测定比值很大的误差。简要总结了锂同位素组成的质谱测定以及从天然样品（主要是固体样品）中提取纯化锂的方法。着重介绍了锂同位素测定中样品带使用的进展，从单带涂样发展到三带涂样，大大降低了测定中的锂同位素分馏。本文还对各种涂样形式的使用进行了比较。     

River flow mass exponents with fractal channel networks and rainfall

An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable.