基于双谱滤波的综合脉冲星时算法研究

毫秒脉冲星的自转频率非常稳定,提供了一种独立的基于遥远自然天体并能持续数百万乃至数十亿年的时间基准,具有稳定性强、运行时间长、服务范围广等特点.为了减弱毫秒脉冲星计时观测中各种高斯噪声对脉冲星时的影响,研究了一种基于双谱滤波的综合脉冲星时构建算法,处理分析了国际脉冲星计时阵(International Pul-sar Timing Array,IPTA)最新发布的4颗毫秒脉冲星(PSR J0437-4715、J0613-0200、J1713+0747和J1909-3744)的观测数据,分析了不同时间尺度综合脉冲星时的稳定性,并与构成国际原子时(International Atomic Time,TAI)的4家授时单位原子钟稳定性进行了比较.结果表明:双谱滤波算法能够较好地抑制观测噪声,提高综合脉冲星时的稳定性.相比于经典加权算法,综合脉冲星时1 yr、10 yr稳定度从7.77×10^-14、8.56×10^-16分别提高到1.50×10^-14、3.50×10^-16,单脉冲星时稳定性的提升也类似.同时发现,综合脉冲星时稳定性在5 yr及以上时间尺度上优于原子钟稳定性,可用于改善当前原子时的长期稳定性.     

Temporal-Spatial Variation of Surface Suspended Matter and Controlling Factors in the Inner Shelf of the East China Sea in Winter

Based on the observed surface suspended matter in the East China Sea in February 2007 and June 2015, an empirical model was established using L1 b's band 4 data to retrieve surface suspended matter from the Moderate Resolution Imagine Spectroradiometer Terra imagery. The squared correlation coefficient is 0.8358, and the root mean square error is 0.4285 mg L-1. The model reflects the distribution characteristics of surface suspended matter in the inner shelf of the East China Sea. In this paper, the satellite images of the study area were retrieved in January from 2001 to 2015, and the monthly distribution of surface suspended matter were obtained. The inter-annual distribution of the study area is similar, and the concentration of surface suspended matter is higher near the shore than offshore. A large amount of surface suspended matter is transported southeast under the influence of Zhejiang and Fujian coastal current and Taiwan warm current. Only a small amount of surface suspension can reach the Kuroshio area. The surface suspended matter concentration changes obviously near the estuary because of the effect of differences in the flux of the Yangtze River. Meanwhile, winter monsoon, temperature front, El Ni?o events, and other factors affect the distribution of surface suspended matter in 100 m isobath to coastal water but minimally influence the distribution in 100 m isobath to deep sea.     

A-FPN算法及其在遥感图像船舶检测中的应用

光学遥感图像船舶检测主要面临两个挑战:光学遥感图像背景复杂,船舶检测易受海浪、云雾及陆地建筑等多方面干扰;遥感图像分辨率低,船舶目标小,对于其分类与定位带来很大困难;针对上述问题,在FPN的基础上,提出一种融入显著性特征的卷积神经网络模型A-FPN (Attention-Based Feature Pyramid Networks)。首先,利用卷积提取图像特征金字塔;然后,利用顶层金字塔逐级构建显著特征层,抑制背景信息,通过金字塔顶层的细粒度特征提高浅层特征的表达能力,构建自上而下的多级显著特征映射结构;最后利用Softmax分类器进行多层级船舶检测。A-FPN模型利用显著性机制引导不同感受下的特征进行融合,提高了模型的分辨能力,对遥感图像处理领域具有重要应用价值。实验阶段,利用公开的遥感目标检测数据集NWPU VHR-10中的船舶样本进行测试,准确率为92.8%,表明A-FPN模型适用于遥感图像船舶检测。     

Benthic foraminiferal fauna and sediment provenance of Eocene syn-rift sequences in Taiwan: implication for onset of Asian epi-continental marginal seas off China coast

Marine Geophysical Research - Early Cenozoic rift basins developed commonly on the Mesozoic basement along the SE Asia Continent. However, Eocene–Oligocene sequences were only exposed widely...     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

苏北浅滩沉积物中的大型绿藻微观繁殖体的垂直分布和物种多样性

本研究通过在2017年秋冬季组织实施的2个绿潮种源调查航次,研究苏北浅滩紫菜养殖区沉积物中的大型绿藻微观繁殖体的垂直分布和物种多样性。对沉积物中的微观繁殖体的定量实验结果表明:表层泥样中绿藻微观繁殖体的丰度最高,随着深度的增加迅速降低。在9月份表层沉积物中丰度为9±2ind./g,而在11月份表层丰度达到98±25ind./g;与9月份相比, 11月份浅滩沉积物中绿藻繁殖体数量呈现出显著升高的趋势。通过对51个绿藻样品的分子鉴定发现:沉积物中存在石莼属(Ulva)、尾孢藻属(Urospora)、盘苔属(Blidingia)等大型绿藻的微观繁殖体;数量占优是石莼属繁殖体,主要包括曲浒苔(Ulva flexuosa)、浒苔(Ulva prolifera)、扁浒苔(Ulva compressa)、缘管浒苔(Ulva linza);其中曲浒苔占据的比例最高,在9和11月份分别达到80.94%和73.33%。在2个调查航次中,都从沉积物中发现了绿潮浒苔的微观繁殖体,这些微观繁殖体是绿潮浒苔在苏北浅滩种源维持的重要方式和关键阶段,也构成了黄海浒苔绿潮连年暴发的"种子库"。     

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995–2016

Global research progress on coastal flooding was studied using a bibliometric evaluation of publications listed in the Web of Science extended scientific citation index. There was substantial growth in coastal flooding research output, with increasing publications, a higher collaboration index, and more references during the 1995–2016 period. The USA has taken a dominant position in coastal flooding research, with the US Geological Survey leading the publications ranking. Research collaborations at institutional scales have become more important than those at global scales. International collaborative publications consistently drew more citations than those from a single country. Furthermore, coastal flooding research included combinations of multi-disciplinary categories, including ‘Geology' and ‘Environmental Sciences Ecology'. The most important coastal flooding research sites were wetlands and estuaries. While numerical modeling and 3 S(Remote sensing, RS; Geography information systems, GIS; Global positioning systems, GPS) technology were the most commonly used methods for studying coastal flooding, Lidar gained in popularity. The vulnerability and adaptation of coastal environments, their resilience after flooding, and ecosystem services function showed increases in interest.     

Permeability Characteristics of Broken Coal and Rock Under Cyclic Loading and Unloading

Natural Resources Research - During longwall mining, the permeability evaluation in a caving zone is one of the most challenging risks for mine operators because it controls the behavior of gas...     

Assessment of alternative adsorption models and global sensitivity analysis to characterize hexavalent chromium loss from soil to surface runoff

We investigate our ability to assess transfer of hexavalent chromium, Cr(VI), from the soil to surface runoff by considering the effect of coupling diverse adsorption models with a two‐layer solute transfer model. Our analyses are grounded on a set of two experiments associated with soils characterized by diverse particle size distributions. Our study is motivated by the observation that Cr(VI) is receiving much attention for the assessment of environmental risks due to its high solubility, mobility, and toxicological significance. Adsorption of Cr(VI) is considered to be at equilibrium in the mixing layer under our experimental conditions. Four adsorption models, that is, the Langmuir, Freundlich, Temkin, and linear models, constitute our set of alternative (competing) mathematical formulations. Experimental results reveal that the soil samples characterized by the finest grain sizes are associated with the highest release of Cr(VI) to runoff. We compare the relative abilities of the four models to interpret experimental results through maximum likelihood model calibration and four model identification criteria (i.e., the Akaike information criteria [AIC and AIC_C] and the Bayesian and Kashyap information criteria). Our study results enable us to rank the tested models on the basis of a set of posterior weights assigned to each of them. A classical variance‐based global sensitivity analysis is then performed to assess the relative importance of the uncertain parameters associated with each of the models considered, within subregions of the parameter space. In this context, the modelling strategy resulting from coupling the Langmuir isotherm with a two‐layer solute transfer model is then evaluated as the most skilful for the overall interpretation of both sets of experiments. Our results document that (a) the depth of the mixing layer is the most influential factor for all models tested, with the exception of the Freundlich isotherm, and (b) the total sensitivity of the adsorption parameters varies in time, with a trend to increase as time progresses for all of the models. These results suggest that adsorption has a significant effect on the uncertainty associated with the release of Cr(VI) from the soil to the surface runoff component.