胶州湾沉积物中石油降解菌的降解能力及多样性研究

2013年青岛输油管道爆炸,大量石油污染了附近海岸。课题组采集了污染的沉积物样品,以原油为唯一碳源和能源,富集了四个石油降解菌群。生物多样性和群落分析表明,Luteibacter、Parvibaculum 和属于食烷菌科的一个属是降解菌群的主要优势菌,都属于变形菌门。从石油降解菌群中分离筛选,获得了9株具有不同16S rRNA基因序列的降解菌,分别属于8个属。重量法测定降解菌的石油降解率,其中5株的石油降解率大于30%。GC-MS分析结果表明,石油降解菌多倾向于降解烷烃,对多环芳烃的降解能力较差,其中5株细菌的烷烃降解率较大,仅1株菌D2对多环芳烃的降解率较大,其降解率在34.9%到77.5%。通过对高通量数据的分析,表明食烷菌属是菌群A和菌群E的主要降解菌群,其中筛选获得的菌株E4可能是菌群E的一株优势降解菌。本研究所筛选菌株证明了其石油降解潜力,为油污染海滩生物修复提供了菌株资源。     

电解法处理船舶压载水的杀菌性能及机理研究

船舶压载水携带的微生物对目的海域的污染问题亟待解决。采用电解法,以渤海湾的海水为处理对象,以炭纤维材料为阴极,分别以碳棒、碳板和炭纤维为阳极,首先考察了施电2.00 V下3种阳极炭材料对应的杀菌效果,进而重点考查了碳板为阳极材料时施加不同槽压下的杀菌性能,并对其杀菌机理进行初步分析。结果表明,3种阳极材料对应的杀菌效果先后顺序为碳棒碳板炭纤维,各自的杀菌效果均较为明显,施电18 min时碳板对应的灭活率可达100%;以碳板为阳极时,施加槽压越高杀菌效果越显著,本研究范围内以1.81 V为佳,施电18 min时灭活率在99%以上;不同槽压下体系中氯离子浓度和p H都随时间整体呈减小趋势,一定程度上可用于解释杀菌作用过程。研究结果可为电解法处理船舶压载水提供参考和借鉴。     

巡天项目中的白矮星搜寻

首先,描述了白矮星的颜色特点和光谱型分类。白矮星是大多数恒星的终极状态,它会随着时间的推移而逐渐冷却。根据表面大气成分,它被划分成DA和DB等不同的光谱型。对某一颗白矮星来说,其光谱型分类可能会随着时间的推移而发生变化,这主要是由于其大气包层中的元素含量被对流过程改变引起的。为了对各类光谱型有更深入的研究,样本的完备性不可或缺。得益于近十几年来大型巡天项目的开展(如斯隆数字巡天、郭守敬望远镜的光谱巡天等),目前通过光谱证认的白矮星已超过4×10~4颗,其中绝大多数是H主导的DA型白矮星,另外还包含2 000多颗He主导的DB白矮星。此外,GALEX项目和GAIA卫星分别提供了有价值的白矮星紫外数据、空间位置和速度等信息。这些数据和信息对于白矮星的研究工作起到了非常大的促进作用。随后,对白矮星的大气参数、质量和运动学等内容作了简单的总结。人们利用模板匹配测量了绝大多数已知白矮星的大气参数,并获得了DB型白矮星的有效温度与紫外颜色间的线性关系。基于斯隆数字巡天的光谱数据,白矮星的质量分布和质量-半径关系也得到了较深入的研究。小质量白矮星具有较大的速度弥散,而大质量的则相反。最后,讨论了白矮星的形成和演化机制,这些机制都是基于现有的理论模型得到的。随着巡天项目中白矮星样本的增加,现有的模型会逐渐被修正和完善,新的模型也将随之建立。     

一种高光谱遥感图像快速谱聚类算法

为获得分类效果更优良的遥感图像分类方式并解决高光谱遥感图像分类运算速度缓慢的问题,集成Lanczos算法与谱聚类算法,探讨了高光谱遥感图像谱聚类算法应用于遥感图像分类的可行性,提出了一种面向高光谱遥感图像的快速谱聚类算法;通过对比美国圣地亚哥机场高光谱遥感图像K-均值算法与谱聚类算法的分类结果,发现面向高光谱遥感图像的谱聚类算法易于识别线性地物,且分类的速度能得到较大提升。     

地灾监测的大数据信息平台研究及应用

重点对地灾监测方面的方案研究进行了阐述,在构建大数据信息平台的设计方案时,以实现高度自动化的全方位监测功能为导向,依托导航卫星数据接收机和多源传感器,集成构建大数据信息平台的系统解决方案,主要包括扼流圈卫星天线、GNSS数据接收机、MEMS传感器、环境测量单元、防雷区域单元等功能元件的组成、多传感器的系统集成,以及全方位监测的功能实现。按照地灾监测大数据信息平台建设、构建大数据平台关键技术突破及检测数据解算软件功能实现的顺序,完成了GNSS实时监测预警应用网络系统HCmonitor的研发。综合应用多种手段实现地灾监测的功能升级,为解决重大灾害预警提供了新的思路和解决方案,该项成果在甘肃舟曲的灾后重建工程得到应用与推广。     

More than two hundred and fifty thousand spectroscopic binary or variable star candidates discovered by LAMOST

About 786.4 thousand stars were observed by LAMOST twice or more during the first stage of its spectroscopic survey. The radial velocity differences for about 256 thousand targets are larger than10 km s^-1 and they are possible spectroscopic binary or variable candidates(SBVCs). It is shown that most SBVCs are slightly metal poorer than the Sun. There are two peaks in the temperature distribution of SBVCs around 5760 K and 4870 K, while there are three peaks in the distribution of the gravitational acceleration at 2.461, 4.171 and 4.621 cm s^-2. The locations of SBVCs on the [Fe/H]-T, [Fe/H]-log g, log g-T and H-R diagrams are investigated. It is found that the detected SBVCs could be classified into four groups. The first group has higher log g～4.621 and lower T ～ 4870 K which are mainly cool red dwarf binaries. The second group of SBVCs has logg around 4.171 cm s^-2 that includes binaries and pulsating stars such as δSet and γ Dor variables. The gravitational accelerations of the third group of SBVCs are higher and some of them are below the zero-age main sequence. They may be contact binaries in which the primary components are losing energy to the secondaries in the common envelopes and are at a special stellar evolutionary stage.The last group is composed of giants or supergiants with log g around 2.461 cm s^-2 that may be evolved pulsating stars. One target(C134624.29+333921.2) is confirmed as an eclipsing binary with a period of 0.65 days. A preliminary analysis suggests that it is a detached binary with a mass ratio of 0.46. The primary fills its critical Roche lobe by about 89%, indicating that mass transfer will occur between the two components.     

SAR image despeckling with a multilayer perceptron neural network

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.     

Recent insights into physiological responses to nutrients by the cylindrospermopsin producing cyanobacterium,Cylindrospermopsis raciborskii

The harmful cyanobacterium Cylindrospermopsis raciborskii is a widespread species increasingly being recorded in freshwater systems around the world. Studies have demonstrated some key attributes of this species which may explain its global dominance. It has a high level of flexibility with respect to light and nutrients, being capable of growth under low and variable light conditions. However, it is the strategy with respect to nutrient utilization that has received more attention. Unlike many bloom forming species, the dominance of this species is not simply linked to higher nutrient loads. In fact it appears that it is more competitive when phosphorus and nitrogen availability is low and/or variable. An important component of this flexibility appears to be the result of within-population strain variability in responses to nutrients, as well as key physiological adaptations. Strain variability also appears to have an effect on the population-level cell quota of toxins, specifically cylindrospermopsins(CYNs). Field studies in Australia showed that populations had the highest proportion of toxic strains when dissolved inorganic phosphorus was added, resulting in stoichiometrically balanced nitrogen and phosphorus within the cells. These strategies are part of an arsenal of responses to environmental conditions, making it a challenging species to manage. However, our ability to improve bloom prediction will rely on a more detailed understanding of the complex physiology and ecology of this species.     

等效沙厚度研究进展

风、沉积物和地表覆盖是控制沙丘地貌的三大要素.沉积物尤其是沙源供应对沙丘地貌的影响仍有待深入研究.沙丘体积的研究促使了等效沙厚度(equivalent sand thickness,EST)概念的提出.EST研究经历了多个沙丘和亚沙丘尺度2个研究阶段.多个沙丘EST研究发现,EST与沙丘高度之间具有较好的一致性,其与方...