黄鳝野生群体和养殖群体遗传结构的RAPD分析

采用RAPD标记技术对黄鳝野生群体和养殖群体遗传结构进行初步研究.用24个随机引物在野生群体和养殖群体中分别扩增出259和251条DNA片段,其中多态性片段数分别为116和92条,多态性片段的比例分别为44.79%和36.65%,平均杂合度分别为0.2155和0.1908,遗传相似率分别为0.9053和0.9583,群体间遗传相似率为0.8863.而Shannon遗传多样性指数表明,两群体中的遗传变异有81.51%来自群体内,只有18.49%来自群体间.野生群体的多态性位点比例和杂合度明显高于养殖群体,说明黄鳝野生种质资源状况较好,应加以合理保护.与野生群体相比,养殖群体的杂合度和遗传多样性有所下降,提示在黄鳝的人工繁殖过程中应引进标记辅助选择等技术手段.图1表3参24     

Quantifying the efficiency of soil sampling designs: A multivariate approach

The objective of this paper is to quantify and compare the loss functions of the standard two-stage design and its composite sample alternative in the context of multivariate soil sampling. The loss function is defined (conceptually) as the ratio of cost over information and measures design inefficiency. The efficiency of the design is the reciprocal of the loss function. The focus of this paper is twofold: (a) we define a measure of multivariate information using the Kullback–Leibler distance, and (b) we derive the variance-covariance structure for two soil sampling designs: a standard two-stage design and its composite sample counterpart. Randomness in the mass of soil samples is taken into account in both designs. A pilot study in Slovenia is used to demonstrate the calculations of the loss function and to compare the efficiency of the two designs. The results show that the composite sample design is more efficient than the two-stage design. The efficiency ratio is 1.3 for pH, 2.0 for C, 2.1 for N, and 2.5 for CEC. The multivariate efficiency ratio is 2.3. These ratios primarily reflect cost ratios; influence of the information is small.     

Efficiency of composite sampling for estimating a lognormal distribution

In many environmental studies measuring the amount of a contaminant in a sampling unit is expensive. In such cases, composite sampling is often used to reduce data collection cost. However, composite sampling is known to be beneficial for estimating the mean of a population, but not necessarily for estimating the variance or other parameters. As some applications, for example, Monte Carlo risk assessment, require an estimate of the entire distribution, and as the lognormal model is commonly used in environmental risk assessment, in this paper we investigate efficiency of composite sampling for estimating a lognormal distribution. In particular, we examine the magnitude of savings in the number of measurements over simple random sampling, and the nature of its dependence on composite size and the parameters of the distribution utilizing simulation and asymptotic calculations.     

Random binary matrices in biogeographical ecology—Instituting a good neighbor policy

Binary matrices originating from presence/absence data on species (rows) distributed over sites (columns) have been a subject of much controversy in ecological biogeography. Under the null hypothesis that every matrix is equally likely, the distributions of some test statistics measuring co-occurrences between species are sought, conditional on the row and column totals being fixed at the values observed for some particular matrix. Many ad hoc methods have been proposed in the literature, but at least some of them do not provide uniform random samples of matrices. In particular, some swap algorithms have not accounted for the number of neighbors each matrix has in the universe of matrices with a set of fixed row and column sums. We provide a Monte-Carlo method using random walks on graphs that gives correct estimates for the distributions of statistics. We exemplify its use with one statistic.     

On the random placement hypothesis

A traditional method of summarizing spatial distribution of species is the observed species-area curve. Often the observed species-area curve is surprisingly close to the expected species-area curve under the hypothesis of random placement of individuals. This has been used as evidence supporting the hypothesis. In this paper, we argue that using the observed species-area curve to test the general random placement hypothesis is highly inefficient. We present a testing method based on the classical ² test for over-dispersion which is not only more efficient but also applicable to situations where complete abundance information are unavailable. We also discuss three alternatives of the hypothesis. The focus of this paper is on these and other general issues relevant to communities of different types. No applications are included in this paper.     

Comparison of Spatial Methods for the Assessment of Planktonic Patches

Planktonic patches are defined as areas where the abundance of plankters is above a threshold value τ. The estimation of patch size and shape can be approached using spatial statistical tools, using truncated random fields or indicator random fields as classifiers. In all cases there is the risk of false positive and false negative errors. In this paper we present the results of a comparative study on the performance of four commonly used methods: conditional simulation and kriging, both in the original measurement units of the data and under an indicator transform. We used a misclassification cost function to compare the four methods. Our results show that conditional simulation in the original measurement units attains the lowest misclassification cost. We also illustrate how the point at which this minimum is attained can be used to chose an optimal cut-off value for binary classification. Received: December 2003 / Revised: June 2005     

水质自动监测中的质量保证与质量控制

质量保证与质量控制是水质自动监测中十分重要的技术工作和管理工作,包括人员素质、运行与管理机制、试剂与标准溶液的配制及文件记录等.在实际工作中,监测人员可根据仪器的运行状况,定期时仪器进行校准、标准溶液的核查、比对实验验证及试剂有效性检查,用以检查仪器的基线飘移情况.如果分析中出现一个异常值,它的前后均为正常值,这种数值大多是由仪器的进样、仪器内部试剂传输等原因所致,如果发生原因不明的数据异常,就要及时检查系统的各个环节并采集实际水样进行人工分析,直至查清原因,剔除异常值,并在周报中加以说明,以确保上报数据的准确性、精密性和可比性.     

疲劳损伤等效在随机振动试验中的应用

以疲劳损伤等价为基础的随机振动试验是评价结构振动环境适应性能力的重要手段.将基于位移模态和应变模态的模态叠加方法分别应用于结构振动位移响应和应力响应的分析中,建立了随机振动试验不同激励条件下,结构振动响应的关系;将结构随机振动应力响应的峰值概率分布通用关系应用于疲劳损伤评估,导出了振动疲劳损伤等效关系.以一个试验为例介绍了疲劳损伤等效原则在随机振动试验中的应用.     

摩擦压力机打击力的测量误差分析

对摩擦压力机打击力测量不准确的现象进行了试验验证 ,并从理论上分析了摩擦压力机打击力测量误差产生的原因 ,探讨了摩擦压力机滑块初速度、工件质量和刚度以及测力传感器质量和刚度对摩擦压力机打击力测量误差的影响。     

基于MAIB事故报告的人为失误灰色关联分析

人为失误作为海上交通事故的主要原因,受到多种因素的影响。为了识别这些影响因素,避免或减少因人为失误导致的海上交通事故,基于96件英国海事调查委员会(MAIB)事故报告,应用熵加权灰色关联分析,分别按船旗国、船舶类型、事故类型计算人为失误与影响因素之间的关联度。结果表明,能力/技能/知识、团队协作、程序和现行规程、设备、交流(内部和外部)和管理/检验/检查是影响人为失误的主要因素。