无量山大寨子黑长臂猿一夫二妻制的群体结构及其行为学原因

2003年8月—2005年8月，对无量山大寨子5个黑长臂猿群体的结构和组成进行了观察。当一个群体在早晨鸣叫或依次通过树冠时，记录群体的结构和组成。每个群体都由1个成年雄性、2个成年雌性及其后代组成。2003年8月平均群体大小为6.2只；到2005年8月,平均群体大小发展为6.4只，其中有2个亚成年雄性从出生群迁出，且有3只幼猿出生。 在3个群体(G1、G2和G3)中两个成年雌性都成功繁殖了后代。同一群体内两个成年雌性间无攻击或等级行为。2005年4月15日，当一只亚成年雌性进入G3的领域后，两只成年雌性对其进行追逐驱赶，并且干扰其与成年雄性配合进行二重唱， 成年雄性没有直接驱赶流浪的亚成年雌性，10天后这只亚成年雌性离开了G3的领域。亚成年雄性经常与群体其他成员保持一定距离，并且在出生地通过独唱练习鸣叫。黑长臂猿可能通过亚成年雄性和雌性的迁出，及成年雌性对外来流浪雌性的驱赶维持这种一夫二妻的群体结构。     

基于SSR标记的30份玉米种质遗传完整性分析

利用70对SSR引物,对30份玉米地方品种种质进行遗传完整性检测,每一份种质包含来自两个不同繁种年份的供试亚群体。取样方法为DNA混合取样。结果表明,30份种质的供试亚群体之间的遗传相似系数除红包谷(统一编号00230080)为0.77外,其他都大于0.80。聚类分析表明,除二黄(统一编号00210055)和红包谷两份种质的亚群体出现分支外,其他28份种质亚群体分支都按照同一种质群分别聚类。本文同时探讨了个别种质亚群体之间遗传分化的原因,以及SSR标记作为玉米种质遗传完整性检测方法的可行性。     

H广义线性模型中的参数估计的比较

本文研究H广义线性模型中未知参数的两种估计方法,一种是边际似然函数法,另一种是Lee和Nelder提出来的L-N法．对于一类具有两个随机效应的典型的Poisson-Gamma类模型,在一些正则性条件之下,我们已经证明了其中固定效应卢的L-N估计的强相合性及渐近正态性,并得到了其收敛于真值的速度．针对这类模型,本文进一步给出了其边际似然函数的解析表达式,并且通过Monte Carlo模拟,对模型中固定效应β的边际似然估计和L—N估计进行了比较,模拟表明L—N估计比边际似然估计在拟Poisson-Gamma模型中有着更加优良的表现,具有更高的精度。     

基于高密度SNP标记估计群体间遗传关联

联合育种的准确性受到群体间遗传关联程度的影响.本研究通过比较基于系谱数据和基因组数据计算的群体遗传关联,探究高密度SNP标记在遗传关联估计中的应用前景.本研究同时使用了模拟数据和真实数据,采用6种不同的遗传关联计算方法,包括PEVD(prediction error variance of differences)、P...     

无量山大寨子黑长臂猿一夫二妻制的群体结构及其行为学原因

2003年8月—2005年8月,对无量山大寨子5个黑长臂猿群体的结构和组成进行了观察。当一个群体在早晨鸣叫或依次通过树冠时,记录群体的结构和组成。每个群体都由1个成年雄性、2个成年雌性及其后代组成。2003年8月平均群体大小为6·2只;到2005年8月,平均群体大小发展为6·4只,其中有2个亚成年雄性从出生群迁出,且有3只幼猿出生。在3个群体(G1、G2和G3)中两个成年雌性都成功繁殖了后代。同一群体内两个成年雌性间无攻击或等级行为。2005年4月15日,当一只亚成年雌性进入G3的领域后,两只成年雌性对其进行追逐驱赶,并且干扰其与成年雄性配合进行二重唱,成年雄性没有直接驱赶流浪的亚成年雌性,10天后这只亚成年雌性离开了G3的领域。亚成年雄性经常与群体其他成员保持一定距离,并且在出生地通过独唱练习鸣叫。黑长臂猿可能通过亚成年雄性和雌性的迁出,及成年雌性对外来流浪雌性的驱赶维持这种一夫二妻的群体结构。     

玉米数量性状的遗传分析 Ⅰ.我国玉米自交系的遗传潜势及其利用

以NcI交配设计和p(p-1)/2双列杂交设计抽样估计了我国玉米自交系总体和优良自交系亚总体各数量性状的基本遗传参数。结果表明,大多数数量性状遗传方差的主要分量是加性方差,显性方差较小。优良自交系亚总体各性状的遗传方差则普遍减小,说明其遗传基础更为狭窄。所以,为了不断地育出更好的自交系间杂种,迫切需要补充新的基因源。而现有的一些自交系和杂交种,则可用以合成综合种或复合种,再进行群体改良。这类群体由于加性变异丰富,在选择下将能产生较快的育种进展。     

大豆花叶病毒种子传毒率测定方法的比较

用苗期症状观察和酶联免疫吸附试验(ELISA)两种方法检查了大豆种子内的大豆花叶病毒(sMV)的传毒率及带毒率,并对两种方法所得的结果进行了比较。带毒大豆种子产生的病苗,其症状主要有花叶、卷叶、叶脉束状、叶脉坏死、凸斑和单叶扭曲等类型。苗期症状观察得到的种子传毒率,与用ELISA法检查去种皮大豆种子的带毒率高度吻合,相关系数r=0.92(n=31),说明此两种方法检查种子传(带)毒率具有相同的生物学和病理学意义。 本文提出了种子“群体病毒浓度”的概念。“群体病毒浓度”=群体内病毒总量/群体内种子总数。38个处理组合和3,591粒种子逐粒用ELISA法检查表明,“群体病毒浓度”与该群体的种子传毒率呈正相关,r=0.93(n=38)。将种子群体作为一个整体用ELISA法检查的结果也证明,“群体病毒浓度”与种子传毒率呈直线相关。因此认为可以用ELISA法对种子群体直接进行测定来估计种子的传毒率。     

MAXIMUM LIKELIHOOD APPROACH TO CLUSTERING

在各种各样应用研究的模型中,经常会遇到所研究的总体是由两个或多个具不同性质的亚总体混合而成的。因此混合分布,特别是混合正态分布可以广泛应用于这些模型。混向总体的分解问题是相当重要和有用的。对于当观测资料不知属于两个可能的总体的哪一个时的分类问题,本文研究了通常使用的基于极大似然估计的两种聚类方法。文中给出了基于在混合抽样和分离抽样这两种不同的抽并方式下的模拟结果对比,并阐述了这两种方法的基本假设及其有关性质。文中使用了基于抗血友病因子(AHF)话性和似抗血友病(AHF-like)抗原为变量以判别妇女是正常还是血友病 A 基因携带者的实际资料,分帮了这两种方法的基本区别。     

在DH或RIL群体中两对重叠基因控制性状的定位

在DH或RIL群体中,若只找到与两对重叠基因控制性状连锁的1个分子标记,可采用极大似然法估计控制性状的一对基因与分子标记间的重组率,并推导出重组率估计值的标准误公式。Monte Carlo模拟显示,重组率估计值的无偏性较好,其变异随时样本容量或重组率的增加而减少。     

两个时期收集的云南水稻农家品种表型多样性比较

本研究以两个时期(1980年、2007年)收集的来自云南15个州、市有代表性的601份水稻农家品种为试验材料,在云南西双版纳和海南三亚种植鉴定,调查记载了播抽历期、株高、穗长、有效穗数、每穗粒数、结实率、千粒重、谷粒长、谷粒宽、长宽比、穗抽出度、剑叶长和剑叶宽等13个农艺性状,并分析了两个不同时期收集群体间的表型和多样性指数差异。研究表明,在云南西双版纳和海南三亚,播抽历期、株高、每穗粒数、谷粒宽、长宽比、穗抽出度等6个性状的表型平均值在两个时期间均表现为显著或极显著差异,而且播抽历期、每穗粒数、长宽比的均值表现为2007年收集的群体(简称G2群体)高于1980年收集的群体(简称G1群体),株高、谷粒宽、穗抽出度的均值表现为G1群体高于G2群体。在两种植地点两个群体的变异系数在两时期间差异均不显著,多样性指数在云南种植地点有显著差异。对两个时期间不同州、市的表型多样性分析发现,在两个种植地点,各州、市在两个时期间的表型多样性指数差异不显著。对不同时期收集的籼、粳两亚群间多样性比较表明,两个群体中粳稻亚群的平均多样性指数均高于籼稻亚群;籼稻亚群的平均多样性指数在两个种植地点均是G2群体(1.845/1.867)高于G1群体(1.791/1.830),而粳稻亚群的平均多样性指数则相反。综上所述,近30年来云南水稻农家品种的表型变异在两个时期间无显著差异,但总体表现为播抽历期变长,株高变矮,每穗粒数变多,谷粒长宽比变大,穗抽出度变短等趋势,表型性状的多样性指数也有增加的趋势。     

Estimation of Population Regression Coefficient in Successive Sampling

An attempt has been made to derive the theory of successive sampling for estimation of regression coefficient. The situations considered are estimation of regression coefficient for current occasion, estimation of change of regression coefficients over two occasions and estimation of average of regression coefficients over two occasions. The expressions of optimum estimators along with their variances have been worked out. On comparing their efficiencies empirically, it has been observed that similar to the estimation of mean, successive sampling can also be used with advantage for estimation of regression coefficient.     

Evaluation of airway resistance determined by whole-body plethysmography

Methods of estimation of the airway resistance by flow-pressure curve obtained in whole-body plethysmography are investigated. The analysis of the physical processes controlling the flow-limitation during expiration shows that these methods are useful only for healthy subjects for the estimation of the airway resistance. The way for estimation of the airway resistance by flow-pressure curve is proposed.     

Estimation of variance components of quantitative traits in inbred populations

Use of variance-component estimation for mapping of quantitative-trait loci in humans is a subject of great current interest. When only trait values, not genotypic information, are considered, variance-component estimation can also be used to estimate heritability of a quantitative trait. Inbred pedigrees present special challenges for variance-component estimation. First, there are more variance components to be estimated in the inbred case, even for a relatively simple model including additive, dominance, and environmental effects. Second, more identity coefficients need to be calculated from an inbred pedigree in order to perform the estimation, and these are computationally more difficult to obtain in the inbred than in the outbred case. As a result, inbreeding effects have generally been ignored in practice. We describe here the calculation of identity coefficients and estimation of variance components of quantitative traits in large inbred pedigrees, using the example of HDL in the Hutterites. We use a multivariate normal model for the genetic effects, extending the central-limit theorem of Lange to allow for both inbreeding and dominance under the assumptions of our variance-component model. We use simulated examples to give an indication of under what conditions one has the power to detect the additional variance components and to examine their impact on variance-component estimation. We discuss the implications for mapping and heritability estimation by use of variance components in inbred populations.     

Application of Artificial Bee Colony Algorithm to Maximum Likelihood DOA Estimation

Maximum Likelihood (ML) method has an excellent performance for Direction-Of-Arrival (DOA) estimation, but a multidimensional nonlinear solution search is required which complicates the computation and prevents the method from practical use. To reduce the high computational burden of ML method and make it more suitable to engineering applications, we apply the Artificial Bee Colony (ABC) algorithm to maximize the likelihood function for DOA estimation. As a recently proposed bio-inspired computing algorithm, ABC algorithm is originally used to optimize multivariable functions by imitating the behavior of bee colony finding excellent nectar sources in the nature environment. It offers an excellent alternative to the conventional methods in ML-DOA estimation. The performance of ABC-based ML and other popular meta-heuristic-based ML methods for DOA estimation are compared for various scenarios of convergence, Signal-to-Noise Ratio (SNR), and number of iterations. The computation loads of ABC-based ML and the conventional ML methods for DOA estimation are also investigated. Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.     

Estimation of Respiratory Nasal Pressure and Flow Rate Signals Using Different Respiratory Sound Features

BackgroundRespiratory sounds are associated with the flow rate, nasal flow pressure, and physical characteristics of airways. In this study, we aimed to develop the flow rate and nasal flow pressure estimation models for the clinical application, and find out the optimal feature set for estimation to achieve the optimal model performance.MethodsRespiratory sounds and flow rate were acquired from nine healthy volunteers. Respiratory sounds and nasal flow pressure were acquired from twenty-three healthy volunteers. Four types of respiratory sound features were extracted for flow rate and nasal flow pressure estimation using different estimation models. Effects of estimations using these features were evaluated using Bland-Altman analysis, estimation error, and respiratory sound feature calculation time. Besides, expiratory and inspiratory phases divided estimation errors were compared with united estimation errors.ResultsThe personalized logarithm model was selected as the optimal flow rate estimation model. Respiratory nasal flow pressure estimation based on this model was also performed. For the four different respiratory sound features, there is no statistically significant difference in flow rate and pressure estimation errors. LogEnvelope was, therefore, chosen as the optimal feature because of the lowest computational cost. In addition, for any type of respiratory sound feature, no statistically significant difference was observed between divided and united estimation errors (flow rate and pressure).ConclusionRespiratory flow rate and nasal flow pressure can be estimated accurately using respiratory sound features. Expiratory and inspiratory phases united estimation using respiratory sounds is a more reasonable estimation method than divided estimation. LogEnvelope can be used for this united respiratory flow rate and nasal flow pressure estimation with minimum computational cost and acceptable estimation error.     

Exponential decontamination models for count data

Several models are developed for the estimation of the rate of exponential die-off from decontamination data. Calculations with illustrative data are reported which indicate that the estimation of this rate and its variance are sensitive to changes in modelling assumptions. Since extrapolation using this estimated rate is used in the specification of planetary quarantine standards, special care should be taken in the selection of an appropriate model and corresponding estimation procedure for the analysis of each set of decontamination data to be used for this purpose.     

Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model

Population variability and uncertainty are important features of biological systems that must be considered when developing mathematical models for these systems. In this paper we present probability-based parameter estimation methods that account for such variability and uncertainty. Theoretical results that establish well-posedness and stability for these methods are discussed. A probabilistic parameter estimation technique is then applied to a toxicokinetic model for trichloroethylene using several types of simulated data. Comparison with results obtained using a standard, deterministic parameter estimation method suggests that the probabilistic methods are better able to capture population variability and uncertainty in model parameters.     

Plot size and estimation efficiency in plant community studies

We examine the effects of changing plot size on parameter estimation efficiency in multivariate (community-level) ecological studies, where estimation efficiency is defined in terms relating to the statistical precision of estimates of all variables (e.g. species) in a data set. Three ‘efficiency criteria’ for multivariate estimation are developed, and the relationship between estimation efficiency and plot size examined using three field data sets (deciduous understory, coniferous understory, and mire vegetation) from central Canada. For all three communities, estimation efficiency was found to increase monotonically with increasing plot size. However, relative gains in efficiency at larger plot sizes were offset by substantial increases in sampling effort (enumeration time per plot). Our results indicate that the largest plot size possible, given the constraints of time, should be used for parameter estimation in plant communities. Also, plots that are larger than the mean patch size should be utilized when sampling heterogeneous vegetation.     

REML estimation of variance parameters in nonlinear mixed effects models using the SAEM algorithm

Nonlinear mixed effects models are now widely used in biometrical studies, especially in pharmacokinetic research or for the analysis of growth traits for agricultural and laboratory species. Most of these studies, however, are often based on ML estimation procedures, which are known to be biased downwards. A few REML extensions have been proposed, but only for approximated methods. The aim of this paper is to present a REML implementation for nonlinear mixed effects models within an exact estimation scheme, based on an integration of the fixed effects and a stochastic estimation procedure. This method was implemented via a stochastic EM, namely the SAEM algorithm. The simulation study showed that the proposed REML estimation procedure considerably reduced the bias observed with the ML estimation, as well as the residual mean squared error of the variance parameter estimations, especially in the unbalanced cases. ML and REML based estimators of fixed effects were also compared via simulation. Although the two kinds of estimates were very close in terms of bias and mean square error, predictions of individual profiles were clearly improved when using REML vs. ML. An application of this estimation procedure is presented for the modelling of growth in lines of chicken.     

A semiparametric odds ratio model for measuring association

We propose a semiparametric odds ratio model to measure the association between two variables taking discrete values, continuous values, or a mixture of both. Methods for estimation and inference with varying degrees of robustness to model assumptions are studied. Semiparametric efficient estimation and inference procedures are also considered. The estimation methods are compared in a simulation study and applied to the study of associations among genital tract bacterial counts in HIV infected women.