基于DBSCAN聚类的城市区域火灾风险计算方法——以深圳市盐田区为例*

为探究评估城市区域的火灾综合风险,提出空间聚类和层次分析法对深圳市盐田区2011年至2019年火灾数据进行建模分析。运用DBSCAN聚类模型对火灾地点进行分类,结合层次分析法构建火灾风险评估验证模型,探讨聚类结果、火灾场景、火灾原因构建系统层次结构模型,综合得出风险评估结果。通过将聚类区域还原至百度地图,结合场景信息及层次分析法指标值对模型的有效性进行验证。结果表明:由于各区区域功能及地理位置不同,区域火灾风险值有明显差异,模型计算出的4个区域结果与实际火灾情况具有一致性。     

富营养化评价的幂函数加和型普适指数公式

提出了一个用幂函数加和型表示湖泊富营养化评价的综合指数公式,并采用粒子群算法优化公式中的参数,得出优化后适用于多指标的富营养化综合评价的普适指数公式,该公式的特例也可作为单项指标的富营养化评价指数公式.将优化好的湖泊富营养化评价公式用于我国不同地域和不同类型的65个湖泊的实例评价.其评价结果与用修正卡森指数公式TSI.和我国营养状态指数公式TSI,及其它方法的评价结果基本一致,并与实况相符,从而为水体富营养化评价提供了一种新的有效途径.     

大气污染总量控制GA方法对气象因子的敏感性

通过数值模拟试验,研究了基于遗传算法(GA)的大气污染总量控制方法对风向、风速、稳定度三个最重要的气象因子的敏感性。结果表明,用基于遗传算法的大气污染总量控制方法所求得的区域允许排放总量以及允许排放总量在各污染源之间的分配方案,对风向、风速、稳定度三个气象因子都敏感,从而验证了该方法的稳定性和可靠性。     

小气候自记图图像数据采集的数字化处理方法

提出一种用数字图像处理技术(digital image processing,DIP)和算法获取小气候自记图图纸上数据的方法,解决了此类图纸中弧形时间轴变成直角坐标轴的问题,并且提高了数据的获取量,基本方法是利用图象软件Imagetool中的“Point”功能获取小气候自记图图象上的记录曲线上点的像素值,然后通过我们给出的算法转换成相应的数据资料,步骤包括：自记图纸扫描、自记图纸的图像纠偏、事件数字化、时间轴的标准化、温湿度的计算、现场时间的计算、时间和数字化图形一致性生成。同时通过实例比较和分析说明了手工与DIP方法在数据取样密度和表现性能差异上的来源。图4参4。     

利用RAPD标记分析卧龙自然保护区不同海拔沙棘种群的遗传变异

从1800m到3400m五个海拔连续取样,用RAPD分子标记研究了卧龙自然保护区中国沙棘种群的遗传结构和遗传变异.用11条寡核苷酸引物,扩增得到151个重复性好的位点,其中143个多态位点,多态率达94.7%.在5个沙棘种群中,总遗传多样性值(HT)为0.289,B种群内的遗传多样性值为0.315,这完全符合沙棘这种多年生、远交的木本植物高遗传变异的特性.5个种群内遗传多样性随海拔升高呈低—高—低变异趋势,在2200m海拔处的B种群遗传多样性达最大值0.315,3400m海拔处的E种群则表现最小,仅0.098.5个种群间的遗传分化值GST=0.406,也即是说有40.6%的遗传变异存在于种群间,59.4%存在种群内.1800m海拔处的A种群与其他种群的明显分离是造成种群间遗传分化大的原因.UPGMA聚类图和PCoA散点图分别进一步确证了5个种群间关系和所有个体间的关系.最后,经过Mantel检测,遗传距离与海拔表现了明显的相关性(r=0.646,P=0.011).     

Estimating Population Size with Noninvasive Capture-Mark-Recapture Data

Abstract:  Estimating population size of elusive and rare species is challenging. The difficulties in catching such species has triggered the use of samples collected noninvasively, such as feces or hair, from which genetic analysis yields data similar to capture-mark-recapture (CMR) data. There are, however, two differences between classical CMR and noninvasive CMR. First, capture and recapture data are gathered over multiple sampling sessions in classical CMR, whereas in noninvasive CMR they can be obtained from a single sampling session. Second, because of genotyping errors and unlike classical CMR, there is no simple relationship between (genetic) marks and individuals in noninvasive CMR. We evaluated, through simulations, the reliability of population size estimates based on noninvasive CMR. For equal sampling efforts, we compared estimates of population size N obtained from accumulation curves, a maximum likelihood, and a Bayesian estimator. For a closed population and without sampling heterogeneity, estimates obtained from noninvasive CMR were as reliable as estimates from classical CMR. The sampling structure (single or multiple session) did not alter the results, the Bayesian estimator in the case of a single sampling session presented the best compromise between low mean squared error and a 95% confidence interval encompassing the parametric value of N in most simulations. Finally, when suitable field and lab protocols were used, genotyping errors did not substantially bias population size estimates (bias < 3.5% in all simulations). The ability to reliably estimate population size from noninvasive samples taken during a single session offers a new and useful technique for the management and conservation of elusive and rare species.     

A spatial zero-inflated poisson regression model for oak regeneration

Ecological counts data are often characterized by an excess of zeros and spatial dependence. Excess zeros can occur in regions outside the range of the distribution of a given species. A zero-inflated Poisson regression model is developed, under which the species range is determined by a spatial probit model, including physical variables as covariates. Within that range, species counts are independently drawn from a Poisson distribution whose mean depends on biotic variables. Bayesian inference for this model is illustrated using data on oak seedling counts. Received: May 2004 / Revised: December 2004     

Design of a water quality monitoring network in a large river system using the genetic algorithm

Despite several decades of operations and the increasing importance of water quality monitoring networks, the authorities still rely on experiential insights and subjective judgments in siting water quality monitoring stations. This study proposes an integrated technique which uses a genetic algorithm (GA) and a geographic information system (GIS) for the design of an effective water quality monitoring network in a large river system. In order to develop a design scheme, planning objectives were identified for water quality monitoring networks and corresponding fitness functions were defined using linear combinations of five selection criteria that are critical for developing a monitoring system. The criteria include the representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness levels were obtained through a series of calculations of the fitness functions using GIS data. A sensitivity analysis was performed for major parameters such as the numbers of generations, population sizes and probability of crossover and mutation, in order to determine a good fitness level and convergence for optimum solutions. The proposed methodology was applied to the design of water quality monitoring networks in the Nakdong River system, in Korea. The results showed that only 35 out of 110 stations currently in operation coincide with those in the new network design, therefore indicating that the effectiveness of the current monitoring network should be carefully re-examined. From this study, it was concluded that the proposed methodology could be a useful decision support tool for the optimized design of water quality monitoring networks.     

根癌农杆菌介导工业化产甘油假丝酵母的遗传转化

通过构建质粒pCAM3300-zeocin,将其电击转化到根癌农杆菌LBA4404中.将含有目的质粒pCAM3300-zeocin的根癌农杆菌和工业化产甘油假丝酵母(Candida glycerinogenes)WL2002-5共培养,利用zeocin抗性基因为筛选标记,实现了pCAM3300-zeocin对产甘油假丝酵母的转化.并根据产甘油假丝酵母的生长特性,对转化条件进行了优化,在共培养时间为24h,产甘油假丝酵母和根癌农杆菌的细胞比例为1∶(500～1000)时最高转化率达到2个转化子/104个酵母细胞.初步建立了根癌农杆菌介导转化产甘油假丝酵母的转化方法.     

根瘤菌的遗传多样性与系统发育研究进展

根瘤菌 (ｒｈｉｚｏｂｉａ)是一类广泛分布于土壤中的革兰氏阴性细菌。它可以侵染豆科植物根部或茎部形成根瘤和少数茎瘤 ,固定空气中的分子态氮形成氨 ,为植物提供氮素营养 .据估计 ,全球每年生物固氮量达 1.75× 10 8ｔ,为世界工业氮肥产量的4 .37倍[1] .根瘤菌与豆科植物的共生固氮作用是生物固氮中固氮效率最高的体系 .因此 ,根瘤菌与豆科植物的共生固氮作用是实现农业可持续发展的重大研究课题之一 .研究根瘤菌的遗传多样性 ,对于发掘新的根瘤菌种质资源 ,保藏并合理利用根瘤菌基因资源库 ,选育高效菌株直接应用于农业生产有重要意义 .…