Genetic estimations for body size characters, development period and development rate in a coccinelid beetle,Harmonia axyridis

Heritabilities and genetic correlations for body size characters and development period in a coccinellid beetle,Harmonia axyridis were estimated by a sib-analysis experiment. Positive genetic correlations were detected between size characters and development rate. If this is upheld in the field, genetic variation would be eliminated, as the loci affecting the characters are supposed to be fixed. However, the results indicated moderate heritabilities for all characters. Possible explanations for the results are discussed.     

Stories in Decisions: How At-Risk Individuals Decide to Request Predictive Testing for Huntington Disease

Huntington Disease (HD) is a hereditary neurological disease that typically occurs in mid-life. There is no prevention or cure, but persons at risk may request predictive genetic testing to learn whether or not they will develop the disease later in life. Many studies describe why such persons request this knowledge. Few consider how people actually make this novel decision. Drawing on in-depth interviews with sixteen test candidates, this article differentiates three types of stories about—as well as embedded in—the experience of deciding. Each type of story sheds a different light on the meaning and experience of making this decision. Stories of having to know reveal that decision-making may be experienced as a self-evident act while stories of evolving toward it feature an incremental process of weighing up the implications. Stories of taking the decision feature a pivotal point which involves the narrator in seeing anew the opportunity to make a choice. Emphasizing previously neglected temporal, biographical and phenomenological dimensions of decision-making, this typology underscores the relevance of narrative in complex processes of decision-making. It also illustrates the inadequacy of understanding decision-making purely through the lens of rational choice.     

幻方的遗传算法构造初探

首先介绍遗传算法,并针对一个古老的数学问题——幻方提出了一种基于遗传算法的幻方构造新方法.     

Deme formation in gall-making aphidsAdelges japonicus (Homoptera: Adelgidae)

The deme formation hypothesis in herbivorous insects states that herbivores differentiate genetically into small demes, each specialized in the idiosyncratic traits of individual plants. We examined this hypothesis in gall-forming aphids,Adelges japonicus, by reciprocal transfers of aphids among three susceptible clones ofPicea jezoensis standing in proximity. Performance of aphids transferred to their natal clone was compared with that of aphids transferred to other novel clones. ANCOVA showed no significant donor (source of aphids) by receptor (recipient of aphids) interactions for both total aphid performance on the host tree over a life cycle and its three subdivisions(q ₁,q ₂ andq ₃). In addition, the total performance on the natal clone was lowest among those in the three clones, which was explicitly against the prediction from the local adaptation. In contrast, there were significant receptor effects onq ₁ (fecundity of gallicolae multiplied by survivorship of fundatrices while feeding on needles) andq ₃ (fecundity of fundatrices multiplied by survivorship of gallicolae before emergence from the galls), suggesting genetic differences in resistance among clones. The two-fold difference inq ₃ among clones was due to different gall size, which was highly correlated with the number of gallicolae that emerged from the gall. The two-fold difference inq ₁ seemed to be caused by different survivorship of larval fundatrices while feeding on needles.     

基因工程技术及其在林木培育中的应用

概述了基因工程在国内外林木培育中的应用现状及发展趋势 ,综述了我国十多年来林木在抗虫、抗病、抗逆境、品质改良、育性等基因工程的研究与应用研究取得的一些进展及今后的发展方向。     

Bayesian incorporation of repeated measurements in logistic discrimination

A common problem in medical statistics is the discrimination between two groups on the basis of diagnostic information. Information on patient characteristics is used to classify individuals into one of two groups: diseased or disease-free. This classification is often with respect to a particular disease. This discrimination has two probabilistic components: (1) the discrimination is not without error, and (2) in many cases the a priori chance of disease can be estimated. Logistic models (Cox 1970; Anderson 1972) provide methods for incorporating both of these components. The a posteriori probability of disease may be estimated for a patient on the basis of both current measurement of patient characteristics and prior information. The parameters of the logistic model may be estimated on the basis of a calibration trial. In practice, not one but several sets of measurements of one characteristic of the patient may be made on a questionable case. These measurements typically are correlated; they are far from independent. How should these correlated measurements be used? This paper presents a method for incorporating several sets of measurements in the classification of a case.     

Families and donor insemination: the views of semen donors

One of the consequences of donor insemination for the semen donor is that he becomes a member of two families: his own family in which he has a genetic and social connection with his offspring; and the family of the recipient couple, in which he has a genetic connection to the offspring, but usually no social connection with either the offspring or the recipient couple. This article challenges the dominant view that donor insemination as a practice of mainly medical or legal importance by looking at the attitudes of donors to both their own family and the family to which they have contributed their genetic material. Results are presented concerning who donors have told about their donation, who they think should be told, whether they think recipient couples should tell their donor insemination offspring about their conception, and concerning their opinions about factors that are considered in matching donors with recipient fathers.     

A lower bound for the transition density function of a stochastic differential equation

Let W_t be a one-dimensional Brownian motion on the probability space (Ω,F,P), and let dx_t = a(x_t)dt + b(x_t)dw_t, b²(x) > 0, be a one-dimensional Ito stochastic differential equation. For a(x) = a₀ + a₁x + … + a_nxⁿ on a bounded interval we obtain a lower bound for p(t,x,y), the transition density function of the homogeneous Markov process x_t, depending directly on the coefficients a₀,a₁, …, a_n, and b(x).     

为了寻根与告别的还乡——试论“游子还乡”主题对中国现代漂泊母题叙事文学的丰富

"游子还乡"是中国现代漂泊母题叙事文学创作的重要主题之一。与传统文学不同的是,"还乡"的内涵已完全改变,主人公有关家乡的幻梦已经破灭,还乡之旅充斥着哀怜、讽刺、厌恶、仇恨等负面情绪。游子们的"还乡"是源于"寻根"的需要,但"还乡"又坚定了游子离家漂泊的路。"游子还乡"主题也因此丰富了中国现代漂泊母题叙事文学的创作内容和形式,为中国现代文学展示了另一道风景。     

Genetic programming as a means for programming computers by natural selection

Many seemingly different problems in machine learning, artificial intelligence, and symbolic processing can be viewed as requiring the discovery of a computer program that produces some desired output for particular inputs. When viewed in this way, the process of solving these problems becomes equivalent to searching a space of possible computer programs for a highly fit individual computer program. The recently developed genetic programming paradigm described herein provides a way to search the space of possible computer programs for a highly fit individual computer program to solve (or approximately solve) a surprising variety of different problems from different fields. In genetic programming, populations of computer programs are genetically bred using the Darwinian principle of survival of the fittest and using a genetic crossover (sexual recombination) operator appropriate for genetically mating computer programs. Genetic programming is illustrated via an example of machine learning of the Boolean 11-multiplexer function and symbolic regression of the econometric exchange equation from noisy empirical data.Hierarchical automatic function definition enables genetic programming to define potentially useful functions automatically and dynamically during a run, much as a human programmer writing a complex computer program creates subroutines (procedures, functions) to perform groups of steps which must be performed with different instantiations of the dummy variables (formal parameters) in more than one place in the main program. Hierarchical automatic function definition is illustrated via the machine learning of the Boolean 11-parity function.