基于网络搜索行为的公众环境关心指标体系构建研究

利用环境相关的网络搜索数据构建指标体系,对中国公众环境关心程度进行评价.构建的环境关心指标体系包括环境污染关心、环境知识关心、环境法规关心和环境行为关心4分类指数和42具体指标.分析结果表明,环境关心指数主要受节能、减排、绿色出行等环境行为关心类指标影响;2011年以来,中国公众环境关心指数取值集中在100~200之间,且呈稳步上升趋势,并具有明显的季节性变动特征.     

城市生活垃圾收运路线优化的数学模型与算法

给出了城市生活垃圾收运路线优化问题的一般描述,考虑时间窗、车容量等约束,以收运路线总行程最短为目标。建立了该优化问题的数学模型。设计了求解谊问题的单一组合邻域搜索算法。随机邻域搜索算法和变邻域搜索算法三种类型的邻域搜索算法。通过对多组算例的求解实验,结果表明变邻域搜索算法的优化效果明显优于其余类型的邻域搜索算法。     

Homology and phylogeny and their automated inference

The analysis of the ever-increasing amount of biological and biomedical data can be pushed forward by comparing the data within and among species. For example, an integrative analysis of data from the genome sequencing projects for various species traces the evolution of the genomes and identifies conserved and innovative parts. Here, I review the foundations and advantages of this "historical" approach and evaluate recent attempts at automating such analyses. Biological data is comparable if a common origin exists (homology), as is the case for members of a gene family originating via duplication of an ancestral gene. If the family has relatives in other species, we can assume that the ancestral gene was present in the ancestral species from which all the other species evolved. In particular, describing the relationships among the duplicated biological sequences found in the various species is often possible by a phylogeny, which is more informative than homology statements. Detecting and elaborating on common origins may answer how certain biological sequences developed, and predict what sequences are in a particular species and what their function is. Such knowledge transfer from sequences in one species to the homologous sequences of the other is based on the principle of 'my closest relative looks and behaves like I do', often referred to as 'guilt by association'. To enable knowledge transfer on a large scale, several automated 'phylogenomics pipelines' have been developed in recent years, and seven of these will be described and compared. Overall, the examples in this review demonstrate that homology and phylogeny analyses, done on a large (and automated) scale, can give insights into function in biology and biomedicine.     

基于免疫禁忌优化算法的生态环境评价指数公式及其应用

通过模拟流域生态环境自然发展的演化过程,结合巢湖流域的具体情况,提出了适用于多个指标的巢湖流域生态环境评价指数公式。通过设定公式中生态环境指标“参照”值,采用免疫禁忌搜索算法对公式中的待定参数进行优化,使生态环境评价指数公式形式简单、方便实用,并具有一定的普适性。生态环境质量评价结果表明,合肥市和巢湖流域整体生态环境质量为Ⅲ级(及格),而巢湖市和六安市生态环境质量较差。     

基于AVMD与DPC-FCM的旋转机械无监督故障诊断方法

目的 针对旋转机械故障诊断过程中存在故障信号特征提取困难、故障诊断过程有标签数据较少、故障诊断准确率低等问题,提出自适应变分模态分解算法(Adaptive Variational Mode Decomposition, AVMD)与密度峰值算法优化的模糊C均值算法(Clustering by Fast Search and Find of Density Peaks Optimizing Fuzzy C-Means,DPC-FCM)结合的无监督诊断方法。方法 首先,将多尺度排列熵与峭度相结合的综合系数作为适应度函数,对VMD算法的惩罚因子alpha和模态个数K进行参数寻优,提取分解后本征模态函数(Intrinsic Mode Function,IMF)的平均样本熵与平均模糊熵,并输入至聚类算法中。其次,提出利用密度峰值聚类算法确定FCM的初始聚类中心,降低聚类结果的随机性。结果 将提出的无监督故障诊断模型应用到滚动轴承试验信号中,实现了准确的故障诊断。结论 AVMD在故障提取方面具有优越性,同时DPC算法可以有效提高FCM算法无监督聚类的准确性,二者结合可以有效实现旋转机械故障的智能分类。     

环境中抗生素抗性基因丰度与抗生素和重金属含量的相关性分析:基于Web of Science数据库检索

抗生素和重金属是两种重要的环境污染物和耐药性选择压力源,但低含量水平下其对环境微生物种群耐药性水平的影响尚不明确.本文全面检索了截至2020年1月1日发表在Web of Science数据库中同时监测了抗生素抗性基因（ARGs）丰度、抗生素含量或重金属含量的研究文献,提取相关数据,利用统计回归方法调查环境介质中3个参数的相关关系.结果表明,除废水外,地表水、沉积物和土壤等环境介质中,即使在非常低的抗生素含量水平下,抗生素选择压力也会对ARGs丰度的增加产生显著的统计效应（P<0.05）.不同类别抗生素对耐药基因表现出不同程度的选择和富集作用.重金属含量以及抗生素含量和重金属含量的交互作用对ARGs的传播也具有显著影响（P<0.05）.水相和固相环境样本的多变量统计回归模型的最终R²分别为0.482和0.707,比单变量回归的R²更高,能更好地解释ARGs丰度的差异,但环境中还存在其他可能影响ARGs丰度的因素.本文的研究结果可为环境中抗生素耐药性风险评估及传播控制提供支撑.