Distribution of the indigenous microorganisms and mechanisms of their orientational activation in Daqing Oilfield

The distribution of indigenous microorganisms was surveyed in Block 1 of Daqing Oilfield. Based on this survey, the indigenous microorganisms in the formation water were activated with different activator systems at the simulated stratum ecological environment. The changes of the number of bacteria of various physiological groups were determined during the process of activation. Also changes of pH value and composition of gas productions were analyzed at the end of culturing. The results showed that the selected block formation water contained a great number of saprophytic bacteria, hydrocarbon-oxidizing bacteria, fermentative bacteria, methane-producing bacteria and sulfate-reducing bacteria. Under the conditions that the growth of sulfate-reducing bacteria was controlled the block had the potential to enhance oil recovery by activating beneficial bacteria. The growth of sulfate-reducing bacteria can be inhibited through the activation of nitrate-reducing bacteria. The number of nitrate-reducing bacteria reached 10⁶–10⁷ cells/mL, but sulfate-reducing bacteria reached only 0–45 cells/mL in A system. Methane-producing bacteria can be activated by C, D activators. The relative content of biological methane in the light hydrocarbon gas reached 80% in C, D systems. B activator was conducive to the propagation of acid-producing bacteria, so that the pH value of the culture medium decreased from 7.5 to around 5.0. Hydrocarbon-oxidizing bacteria can be activated by various activator systems. There was low molecular light hydrocarbon in gas production according to the analysis of gas chromatograph. According to the content of methane and the number of methane-producing bacteria, methane only can be generated through activating methane-producing bacteria. By choosing different activator systems, various populations of indigenous microorganisms can be activated accordingly.     

西藏羌塘南部地区的冰海杂砾岩及其成因

青藏高原及邻区广泛分布的漂砾层、杂砾岩、含砾板岩是一种特殊的冰海相沉积岩，称为冰海杂砾岩（Ｉｃｅ－ｓｅａＭｉｘ－ｃｏｎｇｌｏｍｅｒａｔｅｓ）。它们和一起产出的冷水型动物群、耐冷植物群视为这一地区冈瓦纳相最典型的标志，代表着冈瓦纳大陆上塔尔切尔（Ｔａｌｃｈｉｒ）冰期所影响的时间和空间。除“标准型”冰海杂砾岩外，羌塘腹地发现了蛇绿质和钙质冰海杂砾岩。这两种冰海杂砾岩的发现，不但丰富了冰海杂砾岩的家族成员，同时也为冰海沉积、物质来源问题、冈瓦纳大陆北界及特提斯演化研究提供了新的信息。经研究，冰海杂砾岩中的砾石来自印度半岛──冈瓦纳大陆本体，以冰筏为载体融冰落石成因。     

河西走廊最近一次强沙尘暴的调查分析

1996年5月29~31日在甘肃河西走廊又出现了一次强沙尘暴天气。从这次强沙尘暴和1993年"5·5"强沙尘暴的比较分析可知,春季在河西走廊周围易形成以沙漠为中心的高温低压区,与西西伯利亚向东南方向移动的高压冷气流形成明显的气压梯度,这就是大风的动力源。大风前期,在气温、压温比等方面有明显的预兆,由此可进行强沙尘暴的预测预报。     

基于多源数据融合的山地型旅游区游客时空行为研究

随着旅游者对休闲娱乐类旅游需求的不断增加,山地型旅游区已成为最受欢迎的旅游目的地之一,利用新兴且高效的轨迹记录方式挖掘山地型旅游区游客在小尺度范围内动态的时空行为特征和制约因素,对旅游区线路设计和旅游产品优化尤为重要,也将为山地型旅游区的深化发展和科学管理提供建议。本文以湖北省恩施州恩施大峡谷为案例地,基于“六只脚”平台的GNSS轨迹及位置照片数据,结合GIS在线地图绘制的景区路网和从BigMap平台获取的POI数据,选择GNSS轨迹栅格化的概念模式解析出恩施大峡谷游客轨迹的时空行为特征,尝试探讨与其他类别旅游区时空行为特征的差异,从而总结出山地型旅游区的行为特征,并通过网络点评数据和游记文本等网络文本挖掘行为特征形成的影响因素。研究表明：(1)月份和季相层面,游客行为5月游客量处于峰值,节日效应明显,短假期效应较强;淡旺季游客行为轨迹呈非集聚性,旺季游客量主要受气候条件影响呈不稳定态势;(2)游客行为轨迹于11:00—14:00游客量达到顶峰,日内结束时间相对较早,且兴趣点选择偏向知名度高的七星寨景区;(3)空间分布特征层面,受时空因素控制,单一路径景区轨迹集中度较强;(4)不同性别...     

腾冲火山区地表垂直形变分析

对腾冲火山区1998～2000年的3期垂直形变资料进行了分析，进而利用相关资料得出与计算有关的参数，再用多元Mogi模型反演了岩浆房的位置和大小，所得出的结果与地震层析反演结果基本相似。分析反演结果，认为火山区可能存在多个岩浆房，并有岩脉相通。     

Potential promoted productivity and spatial patterns of medium- and low-yield cropland land in China

With a continuously increasing population and better food consumption levels, improving the efficiency of arable land use and increasing its productivity have become fundamental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement. In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productivity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was located in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Heilongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.     

The surface photometry of NGC 3379

Surface photometry is carried out for the photometric standard galaxy NGC 3379 on the basis of two plates in the blue band taken with the Bejing Schmidt telescope. The results, including luminosity profiles, photometric parameters, integrated luminosity distribution, ellipticity and position angle variation, are presented in various forms of figures and tables. Especially our geometric profiles, i.e., ellipticity and position angle variations reach up to 5, much fainter region than that any previous study did. The accuracy of the present data is checked by comparing them with the surface photometry in the literature. We find the zero-point 0.12 mag brighter than the calibration of de Vaucouleurs and Capaccioli (1979), which agrees with the values 0.10–0.15 mag difference claimed by recent observations. The systematic differences is found to be less than 0.1 mag.     

The Impact of Irrigation on Bacterial Community Composition and Diversity in Liaohe Estuary Wetland

In this study, the sequencing of 16S ribosomal DNA was used to characterize the soil bacterial community composition and diversity in Liaohe estuarine wetland. Soil samples were taken from different locations in the wetland dominated by reed. Moreover, the soil quality parameters were evaluated (pH, moisture, organic matter, total nitrogen, available nitrogen, total phosphorus, available phosphorus). The results showed that the organic matter and nutrient contents were significantly higher in irrigated wetland than those in natural wetland. Major phylogenic groups of bacteria in soil samples including Proteobacteria, Acidobacteria, Gemmatimonadetes, Actinobacteria and Cyanobacteria were analyzed and we found that Proteobacteria was the most abundant in the community, and the phylum Acidobacteria was more abundant in irrigated wetland. Beta diversity analyses indicated that the soil bacterial community was mainly affected by sampling sites rather than seasons. In general, the bacterial community in natural wetland was not significantly different with that in artificial irrigated wetland. Artificial hydraulic engineering irrigated according to the water requirement rule of reed, increased the production of reeds, changed the way of wetland soil material input, but the diversity of bacterial community kept stable relatively.     

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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.