中华乌塘鳢的群体生物学研究 Ⅱ.生化遗传变异

用同工酶谱法发现中华乌塘鳢Bostrichthy sinensis四个群体的遗传变异水平很低,在所检测的30个基因座位中,多态座位比例只有0—10％,平均杂合度仅为0.2—0.5％,物种的平均杂合度为0.33±0.10％。四个群体共享常见的等位基因。虽然其中三个群体拥有特有的等位基因,但其基因频率都未超过5％。四个群体的Nei氏遗传距只有1.68—12.13×10~(-5)。据分析,近交可能是遗传变异水平低和形态特征分化差的主要原因。种苗生产上应注意广泛采集不同地理群体的鱼作亲鱼,以丰富养殖群体的基因库。     

A synthesis of iron deposits in the eastern Tianshan,NW China

The northern Xinjiang region is one of the most significant iron metallogenic provinces in China.Iron deposits are found mainly within three regions:the Altay,western Tianshan,and eastern Tianshan orogenic belts.Previous studies have elaborated on the genesis of Fe deposits in the Altay orogenic belt and western Tianshan.However,the geological characteristics and mineralization history of iron deposits in the eastern Tianshan are still poorly understood.In this paper I describe the geological characteristics of iron deposits in the eastern Tianshan,and discuss their genetic types as well as metallogenic-tectonic settings,Iron deposits are preferentially distributed in central and southern parts of the eastern Tianshan.The known iron deposits in the eastern Tianshan show characteristics of magmatic Fe-Ti-V(e.g.,Weiya and Niumaoquan),sedimentary-metamorphic type(e.g.,Tianhu),and iron skarn(e.g.,Hongyuntan).In addition to the abovementioned iron deposits,many iron deposits in the eastern Tianshan are hosted in submarine volcanic rocks with well-developed skarn mineral assemblages.Their geological characteristics and magnetite compositions suggest that they may belong to distal skarns.SIMS zircon U-Pb analyses suggest that the Fe-Ti oxide ores from Niumaoquan and Weiya deposits were formed at 307.7±1.3 Ma and 242.7±1.9 Ma,respectively.Combined with available isotopic age data,the timing of Fe mineralization in the eastern Tianshan can be divided into four broad intervals:Early Ordovician-Early Silurian(476-438 Ma),Carboniferous(335-303 Ma),Early Permian(295-282 Ma),and Triassic(ca.243 Ma).Each of these episodes corresponds to a period of subduction,post-collision,and intraplate tectonics during the Paleozoic and Mesozoic time.     

基于投影寻踪模型和加速遗传算法的石羊河流域水资源承载力综合评价

针对区域水资源承载力状况,采用高维降维技术——投影寻踪分类模型（PPC）,利用基于实数编码的加速遗传算法（RAGA）优化其投影方向,将多维数据指标（样本评价指标）转换到低维子空间,根据投影函数值的大小评价出样本的优劣,从而做出评价,最大限度避免了灰色关联法评判中权重矩阵取值的人为干扰,为区域水资源承载力状况评价及其它评判问题提供一条新的方法与思路。     

基于混合遗传算法的斜测电离图参数反演

斜向探测是获取电离层状态信息的重要手段之一,对斜测电离图的反演可以得到电离层的相关结构参数.遗传算法是一种有效的并得到普遍应用的反演方法,该算法的求解不依赖于初值的选择,可以有效地减少反演问题解的非唯一性,但也存在“过早收敛”和局部搜索能力差等缺陷,从而导致反演精度下降,影响反演结果的可靠性.本文提出将基于模拟退火的混合遗传算法应用到斜测电离图的参数反演中,该算法不仅把握总体能力强,且具有较强的局部搜索能力,是遗传算法和模拟退火算法的优势互补.为了验证该算法反演结果的可靠性和稳定性,首先分别采用遗传算法、模拟退火算法和混合遗传算法对合成的电离图进行反演,反演参数包括临界频率,最大电子浓度和半厚度.通过对三种算法反演结果的对比,得出混合遗传算法的反演结果最接近真实值,需要的迭代次数也远远小于其他两种算法;通过改变种群大小和总迭代次数来判断参数值的改变对三种算法反演结果的影响,得出混合遗传算法有效地降低了参数的选取对反演结果的影响.然后用这三种反演算法对实测电离图进行反演,并将它们的反演结果与斜测链路中点的实际垂测数据进行比较,结果显示混合遗传算法84.62%的反演结果可以控制在误差范围之内,高于遗传算法（76.93%）和模拟退火算法（65.38%）.这些都表明了混合遗传算法的反演结果具有较强的可靠性,在反演的寻优能力和稳定性上要明显优于遗传算法和模拟退火算法,对实测电离层图的反演具有很强的借鉴意义和应用价值.     

Spatial heterogeneity of a microbial community in Kongsfjorden, Svalbard during late summer 2006 and its relationship to biotic and abiotic factors

The 16S and 18S ribosomal ribonucleic acid genes of microbial organisms collected from the contrasting environments (temperature, salinity, silicate, phosphate and nitrate, p <0.05) of the inner and outer basins of Kongsfjorden (Spitsbergen, Arctic) were studied using polymerase chain reaction-denaturing gradient gel electrophoresis(DGGE) fingerprinting. Comparison of the microbial fingerprints and the physicochemical parameters revealed that molecular methodology exhibited a greater sensitivity. Sequences obtained from bacterial DGGE were affiliated with four main phylogenetic groups of bacteria:Proteobacteria(Alpha, Beta and Gamma), Bacteroidetes, Verrucomicrobia and Cyanobacteria. The relationships between the genotype distribution of these microbes and associated biotic/abiotic factors, revealed by canonical correspondence analysis, showed that Station 1 at 30 m (outer fjord) was grouped separately from the other sites. This difference could be a consequence of the thermocline and base of the euphotic layer at this depth where the Atlantic and Arctic-type waters overlapped.     

基于遗传算法的神经网络短期气候预测模型

用遗传算法优化神经网络的连接权和网络结构,并在遗传进化过程中采取保留最佳个体的方法,进行短期气候预测建模研究。该方法克服了由于神经网络初始权值的随机性和网络结构确定过程中所带来的网络振荡,以及网络极易陷入局部解问题。作为应用实例,以广西全区4月份平均降水作为预报量及前期500hPa月平均高度场,海温场高相关区作为预报因子,建立基于遗传算法的神经网络短期气候预测模型。将这种方法与传统的逐步回归方法作对比分析,结果表明,该方法具有预报精度高,稳定性好的特点。     

CAPPS多箱模式中光化学模式的嵌套与城市大气臭氧数值预报

为解决城市边界层中大气O3浓度的预报问题,选用一种简明有效的光化学反应方案建立光化学模式, 并与大气平流扩散的箱格预报模型进行了嵌套,从而将大气化学过程引入到城市空气污染数值预报系统 (CAPPS) 中。同时,根据实际需要研究了VOC (Volatile Organic Compounds) 浓度及NOx源排放量等参数缺测时,根据前期监测浓度采用遗传算法反演未知参数的具体方法。利用2001年9月8~17日在北京舞蹈学院监测的O3、NOx资料及相应的气象数据,用改进后的CAPPS模式进行了单箱预报试验。预报试验结果表明,嵌套后的模式对O3浓度的变化具备一定的预报能力。     

地下结构孕险环境危险性预警的改进SVM模型

针对地震作用下孕险环境样本数据有限、复杂非线性等特点,提出了一种基于最小二乘支持向量机的地下结构孕险环境危险性预警方法。围绕地震后效应的地下工程区域孕险环境危险性预警目标和特征参数,设计孕险环境危险性问题的向量机表示形式,提出孕险环境危险性支持向量机训练工作机制,利用支持向量机结构风险最小化原则和非线性映射特性,建立基于最小二乘支持向量机的地下结构孕险环境危险性预警模型及其算法组件,并利用遗传算法优化其惩罚函数和核函数参数,隐式表达孕险环境危险性与其影响因素之间的非线性关系。结果表明,模型具有有效的小样本学习能力,具有较高的拟合和预测精度,明显优于神经网络等预测模型。     

南海海域红斑后海螯虾(Metanephrops thomsoni)的分子识别与群体遗传分化

利用16S rRNA基因序列分子识别红斑后海螯虾,然后对海南附近海域(18°30′-19°00′N,111 °30′-112°30′ E)、北部湾口海域(15°41′ N,110°40′ E)和南沙群岛海域(5°20′-5°29′N,110°09′-111°26′E)三个地理群体进行ITS1的扩增测序.16S rRNA基因序列的结果表明所取样本准确;三个地理群体分别得到616-623bp、619bp和614bp的ITS1全长序列,A、G、T、C含量平均分别为22.3％、29.4％、17.8％和30.6％;其中562个保守位点,39个多态位点.ML和NJ聚类分析显示三个地理群体共聚为三个大支,其中海南群体有群体分化.表明红斑后海螯虾三个地理群体分化极其显著,且海南群体具有相对高的遗传多样性.     

Local gravity field modeling using spherical radial basis functions and a genetic algorithm

Spherical Radial Basis Functions (SRBFs) can express the local gravity field model of the Earth if they are parameterized optimally on or below the Bjerhammar sphere. This parameterization is generally defined as the shape of the base functions, their number, center locations, bandwidths, and scale coefficients. The number/location and bandwidths of the base functions are the most important parameters for accurately representing the gravity field; once they are determined, the scale coefficients can then be computed accordingly. In this study, the point-mass kernel, as the simplest shape of SRBFs, is chosen to evaluate the synthesized free-air gravity anomalies over the rough area in Auvergne and GNSS/Leveling points (synthetic height anomalies) are used to validate the results. A two-step automatic approach is proposed to determine the optimum distribution of the base functions. First, the location of the base functions and their bandwidths are found using the genetic algorithm; second, the conjugate gradient least squares method is employed to estimate the scale coefficients. The proposed methodology shows promising results. On the one hand, when using the genetic algorithm, the base functions do not need to be set to a regular grid and they can move according to the roughness of topography. In this way, the models meet the desired accuracy with a low number of base functions. On the other hand, the conjugate gradient method removes the bias between derived quasigeoid heights from the model and from the GNSS/leveling points; this means there is no need for a corrector surface. The numerical test on the area of interest revealed an RMS of 0.48 mGal for the differences between predicted and observed gravity anomalies, and a corresponding 9 cm for the differences in GNSS/leveling points.