民族传统文化对农作物遗传多样性的影响——以贵州黎平县香禾糯资源为例

贵州黎平县内丰富的香禾糯资源是侗族人民赖以生活的物质基础,孕育了侗族特有的生产生活方式和文化习俗,而侗族的传统文化习俗也促进了香禾糯的持续种植和保护.通过研究黎平县香禾糯的历史发展情况,结合2013 年对黎平县香禾糯品种资源的实地调查,发现黎平县至今仍保留了45 个不同品质特征和用途的香禾糯品种,说明香禾糯丰富的遗传多样性.从侗族的饮食文化、节日庆典、宗教信仰、传统农作方式等方面,探讨传统文化习俗与香禾糯品种资源保护的关系,发现香禾糯是侗族油茶、扁米、腌制品等日常食品的必备原料,也是婚丧嫁娶、传统节日、礼尚往来、祭祀仪式的必需品,同时,侗族和谐共生的“稻-鱼-鸭”生产模式更提高了香禾糯的社会经济效益,文章揭示了侗族的传统知识和文化习俗是保持香禾糯高度遗传多样性的根本原因.最后,针对香禾糯资源消失的现状,提出相应的保护措施与建议,供相关部门参考.     

地铁施工工人不安全行为关联规则研究

当前工人不安全行为研究多侧重从理论和方法的角度出发,而通过数据挖掘探究规律性方面的研究存在不足,因此,提出了地铁施工工人不安全行为关联规则研究。首先,构建关联规则挖掘数据库,以大量反映现场不安全行为的照片为数据来源。然后,利用Apriori算法,通过SPSS Modeler软件建模,以地铁车站施工机械操作人员为例介绍关联规则挖掘过程和结果。结果表明:机械操作人员存在有效强关联项为“开挖降水→挖土机作业时周围区域内有其余工人作业活动”。说明针对不同工种岗位的工人,在不同施工阶段存在易出现的不安全行为,可以有针对性地进行控制与管理,从而降低事故率。     

GCC盒和JERE盒介导的信号途径在水稻应答逆境中的作用

植物应答逆境的防御反应在很大程度是在基因转录水平调节的,其中转录因子与目标基因启动子上顺式作用元件的识别和结合起着关键的调节作用.本研究将从双子叶植物中发现的GCC盒(应答乙烯)和JERE盒(应答JA和激发子)与CaMV35S核心启动子融合构建成诱导型启动子,利用GUS报告基因构建其表达载体并进行农杆菌介导的水稻遗传转化.利用T1代株系分析了GCC盒和JERE盒水稻植株对不同逆境胁迫和激素处理的应答.结果表明在转基因植株中它们都具有很低的本底表达.稻瘟病侵染、稻纵卷叶螟取食和机械损伤处理可不同程度提高GUS基因的表达.另外,脱落酸(ABA)、水杨酸(SA)和茉莉酸(JA)也能提高GUS的表达.实验结果暗示JERE和GCC盒介导的信号途径在单子叶和双子叶之间有一定的保守性.图5参15     

地震灾害风险因素和风险评估指标的模糊算法

提出了影响地震灾害风险的主要因素 ,分析了地震震级、烈度、人口密度等因素与某些震害现象之间的相关性 ,以及建筑物的地震破坏程度与其它风险因素的关系。筛选出了地震灾害模糊风险分析指标———震损度DA(其用于风险评估的指标值为 (da) 0 )。给出了一种多变量信息分配算法的公式。在建立因果律模糊关系矩阵时 ,以归并、排序的方法解决了自变量在其样本空间组合后的重叠与错序问题 ,并简化了矩阵运算。在此基础上 ,建立了震损度指标值 (da) 0 的计算方法。     

氯代脂肪烃构效关系的遗传神经网络模式

通过检索美国国立职业与卫生研究所化学物质毒性效应登录（RTECS）1998年版光盘系统,搜集了65种氯代脂肪烃化合物对大鼠急性毒性口服LD₅₀数据,并利用遗传神经网络建立了氯代脂肪烃分子结构与对大鼠急性毒性关系的BP神经网络模式对预报集8种氯代脂肪烃测试结果表明,所建立的网络具有较好的实用性遗传神经网络是由遗传算法和神经网络耦合而成讨论了遗传神经网络的构造以及怎样利用遗传神经网络建立构效关系（QSAR）模式     

零价锌降解四氯乙烯的反应动力学模型研究

对零价锌(Zn(0))降解四氯乙烯(PCE)进行批实验,在假设各化学反应符合准一级反应的前提下,建立了多级链式平行反应数学模型,并使用混合函数遗传算法进行了动力学参数的反演.结果表明,在106h后残留物基本上为C2H4和C2H2.计算显示,氯代烃的反应活性大小为C2Cl2＞C2HCl＞t-DCE(反二氯乙烯)＞1,1-DCE(1,1-二氯乙烯)＞TCE(三氯乙烯)＞c-DCE(顺二氯乙烯)＞PCE;在4条重要的反应路径中,最重要的是PCE→TCE→t-DCE→C2H2→C2H4和PCE→C2Cl2→t-DCE→C2H2→C2H4;最终94.77%的PCE转化为C2H4,5.23%的PCE转换成了氯乙烯(VC).     

Phylogeography and Limited Genetic Connectivity in the Endangered Boring Giant Clam across the Coral Triangle

Abstract: The Coral Triangle is the global center of marine biodiversity; however, its coral reefs are critically threatened. Because of the bipartite life history of many marine species with sedentary adults and dispersive pelagic larvae, designing effective marine protected areas requires an understanding of patterns of larval dispersal and connectivity among geographically discrete populations. We used mtDNA sequence data to examine patterns of genetic connectivity in the boring giant clam (Tridacna crocea) in an effort to guide conservation efforts within the Coral Triangle. We collected an approximately 485 base pair fragment of mtDNA cytochrome c oxidase 1 (CO1) from 414 individuals at 26 sites across Indonesia. Genetic structure was strong between regions (φ_ST=0.549, p < 0.00001) with 3 strongly supported clades: one restricted to western Sumatra, another distributed across central Indonesia, and a third limited to eastern Indonesia and Papua. Even within the single largest clade, small but significant genetic structure was documented (φ_ST=0.069, p < 0.00001), which indicates limited gene flow within and among phylogeographic regions. Significant patterns of isolation by distance indicated an average dispersal distance of only 25–50 km, which is far below dispersal predictions of 406–708 km derived from estimates of passive dispersal over 10 days via surface currents. The strong regional genetic structure we found indicates potent limits to genetic and demographic connectivity for this species throughout the Coral Triangle and provides a regional context for conservation planning. The recovery of 3 distinct evolutionarily significant units within a well‐studied taxonomic group suggests that biodiversity in this region may be significantly underestimated and that Tridacna taxa may be more endangered than currently recognized.     

遗传算法改进措施

标准遗传算法是一种导向随机搜索算法,具有较强的全局搜索能力.但遗传算法存在早熟收敛及收敛速度慢等问题,许多改进的遗传算法被提出,有效地克服或减轻了上述问题.参17.     

Dynamic reserve design with the union-find algorithm

When reserve networks are established over time, there is a risk that sites will be developed in areas planned for future reservation, reducing the effectiveness of reserves. We developed a dynamic reserve design model that maximizes the expected number of species conserved, taking account of the risk of future habitat loss and fragmentation. The model makes use of the union-find algorithm, which is an efficient method for maintaining a list of connected regions in a graph as nodes and edges are inserted. A simple extension of the algorithm allows us to efficiently determine, for each species, when a sequence of site selections results in a reserve in which the species can persist. The extension also allows us to determine when a sequence of deforestation events results in the species becoming non-viable. The dynamic reserve design model is much more effective than commonly used heuristics, particularly when multiple connected sites are required for species persistence. The model also is able to solve much larger problems with greater effectiveness than the only previous dynamic reserve design model that considered site connectivity relationships. The union-find algorithm has much scope for addressing ecological management problems in which dynamic connectivity needs to be considered.