业务流程个性化和可视化的实现

引入面向对象设计的思想，提出了业务流程组件的概念，通过通用的业务流程组件的建模，并将其参数化而使得业务流程平台成为根据用户权限而可以自由进行可视化组装的工作平台。设计了新的会商流程，实现了天气预报会商的多媒体化，同时输出多媒体的天气预报幻灯片，作为台站之间交流的信息产品。     

Research Status and Future Trends of Natural Resources and Sustainable Development in China: Visual Analysis based on CiteSpace

As an important foundation for promoting social progress and economic development, natural resources play an important role in the sustainable development of cities. However, the increasing demand of human beings for natural resources has led to various ecological environmental problems, such as excessive population density, serious environmental pollution, the continuous decline of total natural resources and per capita resources, all of which have hindered sustainable development. Therefore, the study of natural resources and sustainable development has become the focus of many current scholars. In this paper, CiteSpace is used as an analysis tool to analyze the literature on natural resources and sustainable development over the past 20 years. First of all, this paper deeply analyzes the research status of this field in terms of academic research trends, authors and research institutions, co-occurrence of keywords, etc., and on this basis, it then deeply analyzes its evolutionary path and research hot spots in the past 20 years through keyword emergence. Finally, according to the visualization of the analysis results, the future development trends of this research field are speculated: (1) Grasp the current research focus; (2) Improve the research accuracy; (3) Enrich the theoretical system of research; and (4) Establish an interdisciplinary research system.     

Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery

The rational function model (RFM) is widely used as an alternative to physical sensor models for 3D ground point determination with high-resolution satellite imagery (HRSI). However, owing to the sensor orientation bias inherent in the vendor-provided rational polynomial coefficients (RPCs), the geo-positioning accuracy obtained from these RPCs is limited. In this paper, the performances of two schemes for orientation bias correction (i.e., RPCs modification and RPCs regeneration) is presented based on one separate-orbit QuickBird stereo image pair in Shanghai, and four cases for bias correction, including shift bias correction, shift and drift bias correction, affine model bias correction and second-order polynomial bias correction, are examined. A 2-step least squares adjustment method is adopted for correction parameter estimation with a comparison with the RPC bundle adjustment method. The experiment results demonstrate that in general the accuracy of the 2-step least squares adjustment method is almost identical to that of the RPC bundle adjustment method. With the shift bias correction method and minimal 1 ground control point (GCP), the modified RPCs improve the accuracy from the original 23 m to 3 m in planimetry and 17 m to 4 m in height. With the shift and drift bias correction method, the regenerated RPCs achieve a further improved positioning accuracy of 0.6 m in planimetry and 1 m in height with minimal 2 well-distributed GCPs. The affine model bias correction yields a geo-positioning accuracy of better than 0.5 m in planimetry and 1 m in height with 3 well-positioned GCPs. Further tests with the second-order polynomial bias correction model indicate the existence of potential high-order error signals in the vendor-provided RPCs, and on condition that an adequate redundancy in GCP number is available, an accuracy of 0.4 m in planimetry and 0.8 m in height is attainable.     

基于数字高程模型的水系自动生成

为从数字高程模型(DEM)中自动提取区域水流特征,分析了DEM中地形的形态特征,并进行洼地填充和平地抬升的预处理,应用坡面流模拟方法进行了水流方向的确定及水流方向数字阵列的生成,最后根据水流方向阵列和河流栅格网络图生成需要的水系,其结果与手工数字化的水系基本一致,证明该方法是有效的。     

不同无机氮浓度下三角褐指藻藻际细菌群落变化研究

藻际环境细菌和微藻间存在着独特的生态关系,它们可以通过转化和交换浮游植物分泌的有机质来影响其生理和代谢。尽管一些功能微生物在藻际环境的营养循环中具有重要作用,例如氮代谢,但是关于细菌群落与共生藻类如何响应环境中氮营养条件的改变目前并不十分清楚,其对于我们了解全球营养物质循环、藻华的形成以及生态系统功能至关重要。本文基于16S rRNA基因的高通量测序技术,分析了不同形态、不同浓度无机氮培养条件下三角褐指藻藻际环境中相关细菌群落的多样性和群落结构。系统发育分析结果表明,变形菌（Proteobacteria）和拟杆菌（Bacteroidetes）是所有样品中的优势菌,占序列总数的99.5%。同时发现,不同氮浓度培养条件下,细菌群落结构随微藻丰度的变化而改变。氮浓度及形态的变化对菌群结构的影响不显著。此外,γ-变形菌纲中三种细菌（Marinobacter;Algiphilus;Methylophaga）的相对丰度在氮限制培养条件下明显增加,它们可能在共生体系的氮转化过程中具有重要作用。     

Identification of bacteria-derived urease in the coral gastric cavity

Nitrogen cycle is critical to maintain a healthy coral reef ecosystem. Urea can provide a source of nitrogen for coral holobiont and is important for coral calcification through degradation by urease. Despite the involvement of coral-associated bacteria in nitrogen fixation, nitrification and denitrification are well recognized, to what extend urea degradation by bacteria contributing to the urea utilization by coral holobiont remains to be investigated. In this study, we demonstrate that the urea utilization is a common feature of Halomonas spp. that is a dominant genus in cultivable coral-associated bacteria. A urease operon was characterized by genome sequencing and gene knock-out technique in Halomonas meridiana SCSIO 43005, isolated from the gastric cavity of healthy scleractinian coral Galaxea fascicularis. H. meridiana showed high urease activity which was induced by urea and deletion of the urease operon reduced the capability to use urea as solo nitrogen source. Furthermore,approximately 1/3 coral-associated bacteria in the IMG/M database possess complete urease operons indicating the involvement of bacteria-derived ureases in coral holobiont. These results suggest that urease from coral-associated bacteria might be important player in the nitrogen cycling of coral reefs.     

基于NPP-VIIRS数据的夜间灯光指数变化分析——以夏河MS5.7地震为例

夜间灯光数据具有反映人类活动的特点,其数据变化与电力设施运行情况、建筑物和其他发光物体息息相关,因此近年来被广泛应用于各类科学研究中。本文从夜间灯光数据特点出发,以夏河M_S5.7地震灾区为研究区,利用多时相NPP-VIIRS夜间灯光数据,经过数据预处理后获得三种灯光指数,从而分析灾区的夜间灯光变化,为地震应急救援工作提供一种震后灾情信息获取的途径和方法,为甘肃县级尺度的地震应急工作提供另一种思路。     

Antagonism between coral pathogen Vibrio coralliilyticus and other bacteria in the gastric cavity of scleractinian coral Galaxea fascicularis

Scleractinian corals host numerous microbial symbionts with different types of interactions. The gastric cavity of scleractinian coral, as a semiclosed subenvironment with distinct chemical characteristics(e.g., dissolved O2, pH, alkalinity, and nutrients), harbors a distinct microbial community and a diverse array of bacteria that can be pathogenic or beneficial. Galaxea fascicularis is one of the dominant massive scleractinian coral species on inshore fringing reefs in the northern South China Sea.Although the abundance of coral-associated bacteria has been investigated in G. fascicularis, less is known about the microorganisms in the gastric cavity. In this study, we specially isolated cultivable bacterial strains from the gastric cavity of G.fascicularis collected from Hainan Island using a noninvasive sampling approach. Among the 101 representative bacterial strains, one Vibrio coralliilyticus strain, SCSIO 43001, was found to be a temperature-dependent opportunistic pathogen of G.fascicularis. The antagonistic activity between the 100 strains and V. coralliilyticus SCSIO 43001 was tested using a modified Burkholder diffusion assay. Our results showed that V. coralliilyticus SCSIO 43001 inhibits the growth of Erythrobacter flavus and Sphingomonas yabuuchiae. Additionally, we found that three Pseudoalteromonas strains showed moderate to high antibacterial activity against V. coralliilyticus SCSIO 43001 and several other coral-associated Gram-negative bacterial strains.These results suggest that competition between the coral pathogen and other bacteria also occurs in the gastric cavity of coral, and Pseudoalteromonas strains in the gastric cavity of G. fascicularis may provide a protective role in the defense against coinhabiting coral pathogens at elevated temperature.     

Deep origin of Cenozoic volcanoes in Northeast China revealed by 3-D electrical structure

The three-dimensional(3-D)electrical structure of the upper-mantle was used to examine the deep origins of and relationship among the Cenozoic volcanoes located in Northeast China(NEC).High-quality,long-period magnetotelluric(LMT)full-impedance tensor data were collected in NEC and subjected to 3-D Gauss-Newton inversion in order to construct a resistivity model.The resulting model reveals the presence of multiple localized low-resistivity anomalies(LRAs)within the high resistivity lithosphere beneath NEC.These LRAs partially coincide with Cenozoic volcanoes on the surface.Three LRAs that form a larger,annular LRA were observed in the deep upper mantle beneath the Songliao Basin,whereas vein-like LRAs were found in the asthenosphere that connect the lithosphere and deep upper mantle.Petrophysical analyses suggest that the LRAs may have been caused by fluid-induced melting.Based on our electrical model,we propose that,following dehydration of the subducted Western Pacific slab into the mantle transition zone(MTZ)beneath NEC,the released water migrated upward and caused partial melting at the top of the MTZ beneath the Songliao Basin.Under the effect of buoyancy,the melted mantle formed a thermal upwelling that caused melting of asthenosphere before diapiring at the base of the dry lithosphere.The magma then penetrated structural boundaries(such as thinner,weaker,or activated suture zones)and finally reached the Earth's surface.This melting and upwelling of hot mantle materials may have resulted in large-scale volcanism in the region throughout the Cenozoic,including the eruption of Changbai Mountain and Halaha Volcanoes.Our results suggest that the Cenozoic NEC volcanoes may all share a similar mode of genesis,and probably originated from the annular LRA in the deep upper mantle.     

A new fluid factor and its application using a deep learning approach

Amplitude interpretation for hydrocarbon prediction is an important task in the oil and gas industry. Seismic amplitude is dominated by porosity, the volume of clay, pore-filled fluid type and lithology. A few seismic attributes are proposed to predict the existence of hydrocarbon. This paper proposes a new fluid factor by adding a correct item based on the J attribute. The algorithm is verified through stochastic Monte Carlo modelling that contains various rock physical properties of sand and shale. Both gas and oil responses are separated by the new fluid factor. Furthermore, an approach based on the neural network model is trained using the deep learning method to predict the new fluid factor. The confusion matrix shows that this model performs well. This model allows the application of the new fluid factor in the seismic data. In this study, the Marmousi II data set is used to examine the performance of the new fluid factor, and the result is good. Most hydrocarbon reservoirs are identified in the shale–sandstone sequences. The combination of deep learning and the new fluid factor provides a more accurate way for hydrocarbon prediction.