Genetic and environmental influences on cognition during childhood

The basic methodology of behavior genetics is described in the context of the twin and sibling/adoption design. Results of applying this model to cross-sectional data on cognitive development throughout the lifespan are presented. Results from a large longitudinal twin and adoption study of general intelligence are presented to illustrate the use of the basic behavior genetic model in studying the causes of continuity and change in development. A special model is presented for the study of abnormal behavior occurring at the extremes of the distribution and an adaptation of the model is discussed for the study of genetic linkage or the mapping of quantitative trait loci (QTL). Results of applying this model to a sample of twins and kindred siblings indicated the presence of a major QTL for dyslexia on chromosome 6. The purpose of the paper is to illustrate the scope of behavior genetic methodology in studying individual differences in behavior in a biosocial context.     

An efficient polynomial space and polynomial delay algorithm for enumeration of maximal motifs in a sequence

In this paper, we consider the problem of enumerating all maximal motifs in an input string for the class of repeated motifs with wild cards. A maximal motif is such a representative motif that is not properly contained in any larger motifs with the same location lists. Although the enumeration problem for maximal motifs with wild cards has been studied in Parida et al. (2001), Pisanti et al. (2003) and Pelfrêne et al. (2003), its output-polynomial time computability has been still open. The main result of this paper is a polynomial space polynomial delay algorithm for the maximal motif enumeration problem for the repeated motifs with wild cards. This algorithm enumerates all maximal motifs in an input string of length n in O(n ³) time per motif with O(n) space, in particular O(n ³) delay. The key of the algorithm is depth-first search on a tree-shaped search route over all maximal motifs based on a technique called prefix-preserving closure extension. We also show an exponential lower bound and a succinctness result on the number of maximal motifs, which indicate the limit of a straightforward approach. The results of the computational experiments show that our algorithm can be applicable to huge string data such as genome data in practice, and does not take large additional computational cost compared to usual frequent motif mining algorithms. This work is done during the Hiroki Arimura’s visit in LIRIS, University Claude-Bernard Lyon 1, France.     

An immune algorithm with stochastic aging and kullback entropy for the chromatic number problem

We present a new Immune Algorithm, IMMALG, that incorporates a Stochastic Aging operator and a simple local search procedure to improve the overall performances in tackling the chromatic number problem (CNP) instances. We characterize the algorithm and set its parameters in terms of Kullback Entropy. Experiments will show that the IA we propose is very competitive with the state-of-art evolutionary algorithms.     

The robust economic statistical design of the Hotelling's T2 chart

ABSTRACT

Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. But, in practice the process may be affected by more than one scenario which may lead to severe cost penalties if the wrong design is used. Here, we investigate the robust economic statistical design (RESD) of the T² chart in an attempt to reduce these cost penalties when there are multiple scenarios. Our method is to employ the genetic algorithm (GA) optimization method to minimize the total expected monitoring cost across all distinct scenarios. We illustrate the effectiveness of the method using two numerical examples. Simulation studies indicate that robust economic statistical designs should be encouraged in practice.     

皮亚杰“儿童自我中心主义”概念评析

在皮亚杰的发生认识论学说中,“儿童自我中心”概念具有非常重要的意义。“儿童自我中心主义”表现在两个方面,即理智的自我中心和社会的自我中心。同时也表现在儿童心理发展的两个不同阶段,即感知-运动阶段和前运算阶段。皮亚杰指出:话动缺乏协调、主客体没有分化是心理上的自我中心状态的根源。儿童理智上的和社会的自我中心都是随着动作的逐渐协调而消逝的。如果仅从个体心理的基础来看,皮亚杰对儿童自我中心状态的根源的分析,以及他所指出的去除自我中心的途径,是基本正确的。但从社会心理机制的角度看,则存在一些明显的局限:明显的认知中心论,混淆了主客体关系与主体间关系,忽略了符号功能与摆脱社会的自我中心状态的内在联系。     

供应链二级分销网络的优化研究

在综合考虑各种费用要素的基础上,提出了供应链二级分销网络优化模型,该模型属于一类选址-分配问题,文章采用遗传算法对其进行求解,从中选出预建立的分销中心,然后采用蚂蚁算法对建立起的二级网络优化运输路线,从而使得总成本更小,文章中用具体的例子进行了仿真,验证了优化模型的正确性和算法的有效性。     

Newsvendor Problems with Demand Shocks and Unknown Demand Distributions

In today's competitive market, demand volume and even the underlying demand distribution can change quickly for a newsvendor seller. We refer to sudden changes in demand distribution as demand shocks. When a newsvendor seller has limited demand distribution information and also experiences underlying demand shocks, the majority of existing methods for newsvendor problems may not work well since they either require demand distribution information or assume stationary demand distribution. We present a new, robust, and effective machine learning algorithm for newsvendor problems with demand shocks but without any demand distribution information. The algorithm needs only an approximate estimate of the lower and upper bounds of demand range; no other knowledge such as demand mean, variance, or distribution type is necessary. We establish the theoretical bounds that determine this machine learning algorithm's performance in handling demand shocks. Computational experiments show that this algorithm outperforms the traditional approaches in a variety of situations including large and frequent shocks of the demand mean. The method can also be used as a meta‐algorithm by incorporating other traditional approaches as experts. Working together, the original algorithm and the extended meta‐algorithm can help manufacturers and retailers better adapt their production and inventory control decisions in dynamic environments where demand information is limited and demand shocks are frequent      

安徽省市域经济增长质量动态模糊综合评价——基于改进的AHP-FCE集成模型

基于评价指标提供的信息和运用改进的AHP-FCE集成模型对2002—2011年间安徽省各市经济增长质量进行了动态模糊综合评价。从构建的描述经济增长质量5个维度的指标体系中选取了8个代表性指标,建立模糊关系矩阵并优化生成客观权重,由模糊合成运算得到动态综合评价结果。通过各市经济增长质量动态综合评价值、最大序差和影响因素分析,显示出安徽省市域经济增长质量在10年间的动态变化轨迹和区域性差异,只有个别城市处于经济增长质量的核心区域,更多的城市则处于经济增长质量的＂跳跃＂区域,经济增长质量的各维度发展程度不均衡。     

文化与基因有无联系?——现代达尔文主义进军社会领域的思想轨迹

文化与基因是否有关系?达尔文的进化论与社会人文科学的关系如何?解决这些问题,就需要从达尔文主义入手,进而研究达尔文主义与"社会达尔文主义"和种族主义的根本差别,显然,达尔文主义进入人性和道德等领域过程中出现的动物行为学、社会生物学和进化心理学等学科,扩展了人们关于人自身的认识,对人文社会科学的发展具有推动作用。但也留下一系列不能简单地用基因与文化的直接关系来解决的难题。为了解决这些问题,需要对人类的行为模式和心理机制作深入科学的、历史的研究。     

Experiences and issues in evaluating tool requirements using genetic algorithms

This paper is concerned with the optimization of tool requirements in flexible manufacturing systems (FMSs). The main aim is to determine the best tool spectrum (i.e. the number of duplicates for each tool type to be provided) considering different layouts of the tool management area (tool rooms). The optimization method is based on the reciprocal interaction between a genetic algorithm (GA) and the simulation model of the FMS considered. Thus, the results proposed refer to the efficacy of the technique adopted and its practical application to tool management.