水质模型参数优化的遗传算法实现及控制参数分析

参数识别是数学模型应用的前提.遗传算法是一种通用的全局优化算法,结构简单.一个实际应用问题能否利用遗传算法解决,关键在于遗传算法的设计和控制参数的选取.本文结合水质模型参数优化的特点,提出采用正交试验设计的方法来考察遗传算法不同控制参数对参数优化性能的影响,结果显示,正交法较好地识别了关键影响因素,并提出可能的最优方案.表明遗传算法能较好地应用于复杂多参数水质模型的参数识别研究.     

基因工程菌强化芳香化合物的处理工艺

分别固定克隆有甲苯加双氧酶基因的工程菌和筛选出的野生菌株,串联两种固定化细胞反应器,研究以基因工程菌突破关键步骤的限制,筛选菌株辅助完成彻底降解芳香类污染物复合工艺可行性和强化效果.克隆有苯降解过程中的关键基因——甲苯加双氧酶的基因工程菌E. coli. JM109(pKST11)对苯具有较高的降解效率和降解速度,应用于固定化细胞反应器中效果突出.在较短的水力停留时间内,可以将1500mg/L苯降解70%,降解速度为1.11mg/(Ls),延长水力停留时间,可以使去除率达到95%以上.该反应器对高浓度的苯具有突出的处理效果.同时所得到的产物为环己二烯双醇,可以被野生非高效菌W3快速利用.     

Current molecular biologic techniques for characterizing environmental microbial community

Microbes are vital to the earth because of their enormous numbers and instinct function maintaining the natural balance. Since the microbiology was applied in environmental science and engineering more than a century ago, researchers desire for more and more information concerning the microbial spatio-temporal variations in almost every fields from contaminated soil to wastewater treatment plant (WWTP). For the past 30 years, molecular biologic techniques explored for environmental microbial community (EMC) have spanned a broad range of approaches to facilitate the researches with the assistance of computer science: faster, more accurate and more sensitive. In this feature article, we outlined several current and emerging molecular biologic techniques applied in detection of EMC, and presented and assessed in detail the application of three promising tools.     

改进型量子遗传算法应用于区域水资源可持续利用评价

提出了一种对多项指标都能普遍适用的区域水资源可持续利用评价模型,将实数编码混沌量子遗传算法应用于区域水资源可持续利用评价模型中参数的优化,并用优化好的模型对区域水资源可持续利用做出评价。通过对中国12个区域实测数据的评价实例研究及与其它评价方法得到的结果进行对比,表明该模型具有实用性和可行性。     

应用遗传算法建立云杉针叶表面PCDD/Fs光解半衰期的预测模型

采用量子化学PM3算法计算PCDD/Fs的量子化学参数,应用遗传算法(Genetic Algorithm, GA)对所建模型中的变量进行筛选,建立了能预测吸附到云杉[Picea abies (L.) Karst.]针叶表面的PCDD/Fs光解半衰期(t_1/2)的定量结构-性质关系(QSPR)模型,认为影响PCDD/Fs光解速率的主要因素是分子最高占据轨道能(E_HOMO)、前线分子轨道能量差(E_LUMO-E_HOMO)和平均极化率(α).随着EHOMO和α的增大;其lg t_1/2值增大,PCDD/Fs的lg t_1/2值与其(E_LUMO-E_HOMO)值呈抛物线关系,当E_LUMO-E_HOMO＝7.847时,lg t_1/2有最小值;当E_LUMO-E_HOMO≤7.847时,lg t_1/2值随着E_LUMO-E_HOMO的增大而减小;当E_LUMO-E_HOMO≥7.847时,lg t_1/2值随着E_LUMO-E_HOMO的增大而增大.     

基于遗传算法的大气颗粒物的源解析

遗传算法是一种全局优化的随机搜索方法,适用于模型参数寻优。将遗传算法用于大气颗粒物源解析的CMB方程组中参数的优化,得到各污染源对大气颗粒物的优化贡献率。该方法应用于成都市大气颗粒物的源解析结果与用其他多种源解析法得出的结果基本一致。理论分析和应用实践表明了遗传算法用于大气颗粒物源解析研究具有简便、准确和实用性强等特点。      

垃圾填埋场渗滤液对小鼠遗传毒性和肝肾功能的影响

对垃圾填埋过程中产生的渗滤液的遗传毒性及其对肝肾功能的影响进行了初步研究. 选用经口急性毒性试验和微核试验,以某垃圾卫生填埋场2005年11月渗滤液为受试物,ICR纯种小鼠为受试对象,设置高、中、低3个浓度(即渗滤液原液,10倍稀释液和100倍稀释液)渗滤液染毒组和对照组,取小鼠眼静脉血测定总胆红素(TBIL)、谷丙转氨酶(ALT)、谷草转氨酶(AST) 、血清肌酐(Cr)和血尿酸氮(BUN)5项生化指标,探讨渗滤液诱发小鼠肝肾及遗传损伤. 结果表明,高、中浓度组小鼠骨髓嗜多染红细胞的微核率分别为18.8‰和3.8‰,与阴性对照组相比,2组的微核率显著增加(n10,P<0.05). 血清生化分析表明,中、高浓度组谷丙转氨酶(ALT)分别为70.4和70.0 U/L,与对照组差异显著(P<0.05);渗滤液低、中、高浓度组谷草转氨酶(AST)分别为247.1,255.1和281.6 U/L,与对照组相比,3个浓度组的差别均具有统计学意义(P<0.01).整体动物试验水平表明,渗滤液可能对哺乳动物具有遗传损伤效应,对肝功能也可能会产生一定的影响.      

Predicting the Deleterious Effects of Mutation Load in Fragmented Populations

Abstract:  Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure ( F_ST ) and within-deme heterozygosity ( H_S ). A similar part of variance in median time to extinction was explained by a combination of local population size ( N ) and heterozygosity ( H_S ). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.