The effect of aquifer heterogeneity on natural attenuation rate of BTEX

Monitored natural attenuation can be a viable option for remediation of groundwater contamination by BTEX compounds. Under the field conditions, the rate of contaminant mass attenuation through natural processes, such as biodegradation, to a large extent affected by the groundwater flow regime, which is primarily controlled by the aquifer heterogeneity. Numerical simulation techniques were used to describe quantitatively the relationship between biodegradation rate of BTEX and aquifer heterogeneity. Different levels of aquifer heterogeneity were described by random hydraulic conductivity fields (K) having different statistical parameters, the coefficient of variation (CV) and the correlation length (h). The Turning Bands Algorithm was used to generate such K fields. Visual MODFLOW/RT3D was used to simulate the fate and transport of dissolved BTEX plume within heterogeneous aquifers. The multispecies reactive transport approach described BTEX degradation using multiple terminal electron-accepting processes. First-order biodegradation rate constants were calculated from simulated BTEX plumes in heterogeneous flow fields. The results showed that aquifer heterogeneity significantly affected biodegradation rate; it decreased with increasing CV when h was in the range of up to 12 m, whereas it increased with increasing CV when h was greater than about 12 m. For well characterized aquifers, this finding could be of great value in assessing the effectiveness of natural attenuation during feasibility studies at BTEX contaminated sites.     

顾及目标异质性的极化SAR图像非局部均值滤波

相干斑抑制是极化合成孔径雷达(Pol SAR)图像分析的重要预处理步骤。为了更好地抑制极化SAR图像中的相干斑,本文综合目标的异质性和结构信息,提出基于目标异质性的非局部均值滤波方法。首先利用K分布距离度量目标的异质性,并以异质性为基础,保留图像中的点、线等高异质性目标;然后计算图像块之间的异质性差异,最后将其作为度量非局部均值加权滤波像元相似性的权重系数,实现对Pol SAR图像的相干斑抑制。实验对比结果表明:本文方法能够有效地抑制相干斑,同时对细节信息和极化信息也具有良好的保持性,能够为后续的图像应用提供支持。     

主题学习和稀疏表示的MODIS图像超分辨率重建

针对MODIS图像分辨率受传感器限制和噪声干扰,且分辨率局限在一定水平等问题,提出一种采用主题学习和稀疏表示的MODIS图像超分辨率重建方法,该方法通过双边滤波将MODIS图像的平滑及纹理部分分离,并将纹理部分看成是由若干"文档"组成的训练样本;运用概率潜在语义分析提取"文档"的潜在语义特征,从而确定"文档"所属的"主题"。在此基础上,针对每个主题所对应的图像块,采用改进的K-SVD方法训练若干适用于不同主题的高低分辨率字典对,从而可以运用这些字典对,通过稀疏编码实现测试图像相应主题块的超分辨率重建。实验结果表明,重建图像在视觉效果和PSNR等指标上均优于传统方法。     

财产保险公司的地理扩张与利润

中国财产保险业（简称产险业）的经营状况存在明显的空间分异性,且近些年中国产险公司进行了较快速的地理扩张,那么,地理扩张如何影响了公司的盈利能力?本文基于2006-2015年中国64家产险公司的面板数据,采用地理加权方法估计了每家公司的利润效率,并基于多个地理扩张指标进行了回归分析。研究发现：① 地理扩张与盈利能力呈显著正相关,六成以上的正相关来自于有更强盈利能力的产险公司更会去实施地理扩张。② 地理扩张对产险公司的盈利能力仍然产生了一定程度的正向影响,其他条件不变时,如果产险公司经营的省区市数目增加10家、产险公司来自于非总部所在的省区市的保费收入份额增加10个百分点、产险公司在各省区市的保费收入的集中度降低单位标准差、产险公司总部与分部的平均距离增加1%,那么,产险公司的盈利能力将分别提高样本中单位标准差的2%、1%、2%、1%。③ 采用基于普通方法估计的利润效率时,难以得到地理扩张影响产险公司的盈利能力的结论。     

GWR模型在土壤重金属高光谱预测中的应用

目前土壤重金属高光谱反演模型大多忽视了重金属与光谱变量间相关关系的空间异质性,这与实际情况不相吻合,而地理权重回归（GWR）模型能有效地揭示变量间关系的空间异质性。本文以福州市土壤重金属Cd、Cu、Pb、Cr、Zn、Ni为对象,构建土壤重金属预测的GWR高光谱模型,并将预测结果与普通最小二乘法回归（OLS）结果进行比较分析,探讨GWR模型在土壤重金属高光谱预测中的适用性及局限性。结果表明：① GWR模型在土壤重金属高光谱预测中适用与否取决于重金属对光谱变量影响的空间异质性程度：对于Cr、Cu、Zn、Pb等对光谱变量影响空间异质性大的元素,其GWR预测精度较OLS提高明显,表现为GWR模型的调节R²较OLS模型有了明显提高,分别为OLS模型的2.69倍、2.01倍、1.87倍和1.53倍;而AIC值以及残差平方和较OLS模型却明显降低,AIC值减少量均大于3个单位,残差平方和则仅分别为OLS模型的25.33%、30.09%、47.22%和86.84%;对于Cd和Ni等对光谱变量影响空间异质性小的元素,相较于OLS模型,GWR模型的调节R²分别提高了0.015和0.007,残差平方和分别减少了5.97%和4.18%,但AIC值却分别增加了2.737和2.762,GWR预测效果改善不明显;② 光谱变换可以有效增强土壤重金属的光谱特征,其中以光谱的倒数变换效果最好,而且该变换及其微分形式可以很好地提高模型的预测效果;③ GWR模型的应用前提是变量间关系的空间非平稳性,适合在与土壤光谱变量间关系具有显著空间异质性的重金属高光谱预测中推广。     

Extracting and analyzing semantic relatedness between cities using news articles

News articles capture a variety of topics about our society. They reflect not only the socioeconomic activities that happened in our physical world, but also some of the cultures, human interests, and public concerns that exist only in the perceptions of people. Cities are frequently mentioned in news articles, and two or more cities may co-occur in the same article. Such co-occurrence often suggests certain relatedness between the mentioned cities, and the relatedness may be under different topics depending on the contents of the news articles. We consider the relatedness under different topics as semantic relatedness. By reading news articles, one can grasp the general semantic relatedness between cities; yet, given hundreds of thousands of news articles, it is very difficult, if not impossible, for anyone to manually read them. This paper proposes a computational framework which can ‘read’ a large number of news articles and extract the semantic relatedness between cities. This framework is based on a natural language processing model and employs a machine learning process to identify the main topics of news articles. We describe the overall structure of this framework and its individual modules, and then apply it to an experimental dataset with more than 500,000 news articles covering the top 100 US cities spanning a 10-year period. We perform exploratory visualizations of the extracted semantic relatedness under different topics and over multiple years. We also analyze the impact of geographic distance on semantic relatedness and find varied distance decay effects. The proposed framework can be used to support large-scale content analysis in city network research.     

华北地台东部金伯利岩源区反演及其不均一性探讨

华北地台东部有６个金伯利岩岩区，它们分布于古陆核的中心（如富矿的复县一蒙阴）、北缘（如贫矿的铁岭）及西缘元古代裂陷带（如无矿的涉县一鹤壁）。本文在不相容元素、同位素源区约束讨论的基础上，选择代表性的金伯利岩进行源区地球化学定量反演，进而讨论了源区的不均一性。金伯利岩产出的构造部位及由此所反映的岩石圈厚度、地慢流体活动强度的差异，不仅影响金伯利岩含金刚石性，而且也是地幔源区不均一性的影响因素