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...     

论海相页岩气富集机理——以四川盆地五峰组—龙马溪组为例

深入探究页岩气富集机理是保障勘探开发高效推进的基础。本研究通过对四川盆地五峰组—龙马溪组页岩气勘探开发实践的系统分析,梳理总结前人研究成果,从生成机理、运移机理、赋存机理和保存机理四个方面对海相页岩气富集机理进行了深入分析,并讨论了深层和常压页岩气的勘探开发潜力。结果表明：在生成机理方面,埋藏史和热演化史控制了页岩生排烃史、生排烃量和现今含气量;页岩气运移机理涉及运移动力、运移相态、运移方式和运移通道四方面内容,页岩气运移主要是烃源岩内的初次运移,同时讨论了初次运移的影响因素;在赋存机理方面,甲烷—页岩间表现出单/多分子层吸附和微孔充填等多种赋存机制,组分润湿性和孔隙有效性是决定甲烷吸附赋存和解吸运移的关键;在保存机理方面,盖层和物性自封闭是主要的保存机理,构造运动引起的裂缝—流体活动是页岩气保存条件遭到破坏的主要原因,流体活动时间和期次研究是页岩气保存条件和含气量定量评价的重要内容。页岩气富集机理的系统分析和创新认识为页岩气勘探开发评价提供了重要依据,建议加强页岩气演化历史全过程的动态评价。结合深层和常压页岩气勘探实践,分析了深层和常压页岩气的成因机制及主要特征,指出了下一步攻关内容及勘探方向。     

遥感影像植被信息提取方法研究及思考

从植被光谱特征出发,对植被信息提取的方法和现状进行了综述,其中主要介绍了几种具有代表性的植被提取方法,如:植被指数提取法、NDVI与波段合成法、HIS融合法、分级分类提取法、基于知识库提取法等,对各种方法的原理、特点、优势与限制进行了分析、对比、思考,并展望了下一步研究方向。     

全国重要矿产总量预测方法

全国重要矿产资源评价涉及25种重要矿产的近百种矿床类型,需要在1∶20万尺度水平圈定成矿预测远景区,并科学估算各远景区资源量,为国家矿产资源战略勘查和战略部署提供技术支撑。为了保证预测成果在同一层面上进行全国汇总,制定了全国一致的、标准的技术要求和方法。通过对中国以往一轮、二轮区划预测方法、全国矿产资源总量预测方法及国外最新预测方法的分析和总结,结合近年来预测理论的新发展,确定了全国重要矿产总量预测的理论基础是成矿系列理论、现代成矿动力学理论和综合信息矿产预测理论,采用的预测思路是矿床模型综合地质信息预测方法。文章陈述了总量预测的方法流程和预测技术要求,有关方法思路可供资源评价人员参考。     

青藏高原北缘昆仑-羊湖地区构造演化特征

昆仑—羊湖地区位于青藏高原北缘昆仑山脉中段之南侧,区內发育古生代以来地层和几克里阔勒蛇绿岩、阿克苏库勒蛇绿岩、奥依亚依拉克花岗岩带、昆仑花岗岩带,经历了祁秦昆(原特提斯)洋的形成和发展阶段;南昆仑洋的形成和发展阶段;金沙江(古特提斯)洋的形成和发展阶段、陆內造山及隆升阶段。     

深圳西涌滨海旅游区海滩裂流风险评估及特征分析

基于海滩地形动力学、遥感影像的风险预识别以及现场排查等方法,对西涌滨海旅游区海滩裂流风险进行了初步评估.评估结果表明:地形动力分析结果显示,西涌滨海旅游区泳场逐月平均沙滩类型大部分是沿岸沙坝和裂流沟槽交替的沙坝型(B),风险等级高;影像特征判断该沙滩属于沿岸沙坝和裂流沟槽交替的沙坝型(B)或者低潮位附近伴有冲流沙坝及裂...     

基于R语言的NetCDF文件分析和可视化应用

气象领域目前有多种广泛应用的气象数据分析和可视化工具集,包括GrADS、NCL、CDO和IDL等。R语言是一种由统计学家开发的统计计算和绘图的语言和环境,具有大数据处理的能力。R语言数量众多的扩展包为R语言用于海量气象数据分析和可视化提供了强有力的支持。基于R语言对NCEP发布的数据集进行了统计分析和可视化,展示了R语言在气象数据处理和可视化方面的应用。结合R语言提供的贝叶斯统计扩展包和高性能并行计算扩展包探讨了R语言在气象数据处理和可视化应用方面的广泛前景。