Global Structure-Acute Toxicity Relationships for Mice Using Structural Parameter Ratios: New Approach to Molecular Design and Screening

Abstract

A method for a preliminary survey of the relationship between molecular structure and performance was described using 1506 random data of structure-acute toxicity for mice (intravenously dosed). The structural patterns of the weakest toxic structures (111) were extracted from the data and the patterns discriminated for 64.2% of the other structures (1395). As for the 826 structures of strongest toxicity, 78.3% were discriminated by these structural patterns. These results were obtained by using structural parameter ratios to describe the structural patterns and the exhaustive elimination process to select the best parameter ratio from many candidates. The results were summarized in the form of a chart which can be used for practical screening for the weakest toxic structures.     

Graph Coloring with Adaptive Evolutionary Algorithms

This paper presents the results of an experimental investigation on solving graph coloring problems with Evolutionary Algorithms (EAs). After testing different algorithm variants we conclude that the best option is an asexual EA using order-based representation and an adaptation mechanism that periodically changes the fitness function during the evolution. This adaptive EA is general, using no domain specific knowledge, except, of course, from the decoder (fitness function). We compare this adaptive EA to a powerful traditional graph coloring technique DSatur and the Grouping Genetic Algorithm (GGA) on a wide range of problem instances with different size, topology and edge density. The results show that the adaptive EA is superior to the Grouping (GA) and outperforms DSatur on the hardest problem instances. Furthermore, it scales up better with the problem size than the other two algorithms and indicates a linear computational complexity.     

A quantile domain perspective on the relationships between optimal grouping, spacing and stratification problems

The relationships between two distributions having the same solutions for problems of optimal spacing selection for the asymptotically best linear unbiased estimator of a location or scale parameter or for problems of optimal stratification for estimation of a population mean are investigated. Easily checked necessary and sufficient conditions under which two distributions have identical solutions to these problems are given in terms of their quantile and density-quantile functions. As an application of these results a quantile domain analoque of a theorem due to Adatia and Chan (1981) on the equivalence of optimal grouping, spacing and stratification problems is obtained.     

Academic achievement with cooperative learning using homogeneous and heterogeneous groups

Cooperative learning is a proven teaching strategy that teachers have been using for over 40 years. Teachers often group students heterogeneously so that students who are lower achieving are learning with and from higher achieving students. The purpose of this study was to test homogeneous and heterogeneous grouping while using cooperative learning teaching structure. This study aimed to answer the question of whether students be grouped homogeneously or heterogeneously while participating in cooperative learning. The primary research design for this study was a quasi-experimental nonequivalent control-group design. A convenience sample of fifth-grade students was drawn from a Georgia elementary school in the 2017–2018 school year. The data were analyzed using analysis of covariance (ANCOVA) and paired samples t tests. The ANCOVA was run to compare the scores from the FOSS Survey/Posttest, and the analysis showed no significant difference between the homogeneous and heterogeneous group posttest scores. Both groups made significant gains (as shown by the results of the paired samples t-tests).     

有时间窗装卸问题的多策略分组编码遗传算法

根据有时间窗装卸问题(PDPTW)的数学模型,设计了多策略分组编码遗传算法,将禁忌思想用于产生可行解的启发式插入算法之中,对计算实例进行了求解,结果表明,此算法可以有效求得有时间窗装卸问题的近似最优解.     

A Markov Chain Monte Carlo comparison of variance estimators for the sampling of particulate mixtures

During the sampling of particulate mixtures, samples taken are analyzed for their mass concentration, which generally has non‐zero sample‐to‐sample variance. Bias, variance, and mean squared error (MSE) of a number of variance estimators, derived by Geelhoed, were studied in this article. The Monte Carlo simulation was applied using an observable first‐order Markov Chain with transition probabilities that served as a model for the sample drawing process. Because the bias and variance of a variance estimator could depend on the specific circumstances under which it is applied, Monte Carlo simulation was performed for a wide range of practically relevant scenarios. Using the ‘smallest mean squared error’ as a criterion, an adaptation of an estimator based on a first‐order Taylor linearization of the sample concentration is the best. An estimator based on the Horvitz–Thompson estimator is not practically applicable because of the potentially high MSE for the cases studied. The results indicate that the Poisson estimator leads to a biased estimator for the variance of fundamental sampling error (up to 428% absolute value of relative bias) in case of low levels of grouping and segregation. The uncertainty of the results obtained by the simulations was also addressed and it was found that the results were not significantly affected. The potentials of a recently described other approach are discussed for extending the first‐order Markov Chain described here to account also for higher levels of grouping and segregation. Copyright © 2013 John Wiley & Sons, Ltd.     

A Novel Bit-level Image Encryption Method Based on Chaotic Map and Dynamic Grouping

In this paper,a novel bit-level image encryption method based on dynamic grouping is proposed.In the proposed method,the plain-image is divided into several groups randomly,then permutation-diffusion process on bit level is carried out.The keystream generated by logistic map is related to the plain-image,which confuses the relationship between the plain-image and the cipher-image.The computer simulation results of statistical analysis,information entropy analysis and sensitivity analysis show that the proposed encryption method is secure and reliable enough to be used for communication application.     

基于脉冲分组的光剂量监控新算法

精确控制脉冲激光加工光剂量是保证加工产品工艺和质量的关键。在对现有的光剂量控制算法进行分析后,提出了基于脉冲分组的光剂量监控新算法,有效提高了光剂量监测精度和反馈控制速度。设计了光剂量监控系统,实现了脉冲激光加工光剂量实时监测及反馈控制。与Ophir公司的StarLab激光能量测量系统相比,500个激光脉冲以内的总能量测量,本系统测量误差不超过±0.1 5%。对一套脉冲最大重复频率为10 kHz、单脉冲最大能量为5 mJ、恒压工作下最大能量波动为±10%的脉冲激光加工系统光剂量进行了监控实验。在本系统的监控下,可将日标光剂量为150 mJ/mm~2以内的加工光剂量控制精度和重复精度分别控制在0.90%和0.100mJ/mm~2以内,同时将光剂量反馈控制速度提高了4倍。     

突发事件应急救援人员的分组方法研究

针对突发事件应急救援人员分组问题,给出了一种基于优化模型的分组方法。在本文中,首先描述了突发事件的应急救援人员分组问题;然后依据救援人员特征表现评价信息,计算救援人员完成不同任务的综合表现评价值;进一步地,以完成各救援任务的"效果"最好为目标,考虑每个救援人员只能被分到一个组里且每组中的人员数量要满足救援任务的需要,构建了救援人员分组的多目标优化模型,并通过求解优化模型来得到应急救援人员的分组方案。最后,通过一个算例分析说明了本文提出方法的可行性和有效性。