Multidimensional-unified topological relations computation: a hierarchical geometric algebra-based approach

This article presents a geometric algebra-based model for topological relation computation. This computational model is composed of three major components: the Grassmann structure preserving hierarchical multivector-tree representation (MVTree), multidimensional unified operators for intersection relation computation, and the judgement rules for assembling the intersections into topological relations. With this model, the intersection relations between the different dimensional objects (nodes at different levels) are computed using the Tree Meet operator. The meet operation between two arbitrary objects is accomplished by transforming the computation into the meet product between each pair of MVTree nodes, which produces a series of intersection relations in the form of MVTree. This intersection tree is then processed through a set of judgement rules to determine the topological relations between two objects in the hierarchy. Case studies of topological relations between two triangles in 3D space are employed to illustrate the model. The results show that with the new model, the topological relations can be computed in a simple way without referring to dimension. This dimensionless way of computing topological relations from geographic data is significant given the increased dimensionality of geographic information in the digital era.     

The atmospheric circulation patterns influencing the frequency of spring sand-dust storms in the Tarim Basin

Using NCEP/NCAR reanalysis data and the sand-storm frequency data fi＇om 37 weather stations in the Tarim Basin for the period 1961-2009, the relationship between the frequency of spring sandstorms in the Tafim Basin and the associated atmospheric circu- lation pattems is analyzed in this study. We found significantly negative correlations between sandstorm frequency and the 500-hPa geopotential height over the Paris Basin and midwestem Mongolia, while there were positive correlations over the Ural River region. The rising of the 500-hPa geopotential height in midwestem Mongolia and its falling over the Ural region corre- spond to a weakening of the large-scale wave patterns in the Eurasian region, which directly causes the frequency of the sand-dust storms in the Tarim Basin to decline. Also, the abrupt decline in the spring sandstorm frequency in the Tarim Basin observed in the last half-century is associated with profound changes in the atmospheric circulation in these key regions. At the interannual scale, the strengthened cyclonic atmospheric circulation patterns in the western part of Mongolia and the anticyclonic patterns over the East European plains at 500-hPa geopotential height, are responsible for frequent sandstorm occurrences in the Tarim Basin.     

CLM4.0模式对中国区域土壤湿度的数值模拟及评估研究

本文利用普林斯顿大学全球大气强迫场资料,驱动公用陆面过程模式（Community Land Model version 4.0,CLM4.0）模拟了中国区域1961～2010年土壤湿度的时空变化。将模拟结果与观测结果、美国国家环境预报中心再分析数据（National Centers for Environmental Prediction Reanalysis,NCEP）和高级微波扫描辐射计（Advanced Microwave Scanning Radiometer-EOS,AMSR-E）反演的土壤湿度进行了对比分析,结果表明CLM4.0模拟结果可以反映出中国区域观测土壤湿度的空间分布和时空变化特征,但东北、江淮和河套三个地区模拟值相对于观测值在各层次均系统性偏大。模拟与NCEP再分析土壤湿度的空间分布基本一致,与AMSR-E的反演值在35°N以北的分布也基本一致;从1961～2010年土壤湿度模拟结果分析得出,各层土壤湿度空间分布从西北向东南增加。低值区主要分布在新疆、青海、甘肃和内蒙古西部地区。东北平原、江淮地区和长江流域为高值区。土壤湿度数值总体上从浅层向深层增加。不同深度土壤湿度变化趋势基本相同。除新疆西部和东北部分地区外,土壤湿度在35°N以北以减少趋势为主,30°N以南的长江流域、华南及西南地区以增加为主。在全球气候变暖的背景下,CLM4.0模拟的夏季土壤湿度在不同程度上响应了降水的变化。中国典型干旱区和半干旱区土壤湿度减小,湿润区增加。其中湿润区土壤湿度对降水的响应最为显著,其次是半干旱区和干旱区。     

基于EEMD的黄河中上游夏季降水预报方法的研究

传统的统计方法难以很好的对气候系统这一集非线性、非平稳性为一身的多层次系统进行处理。因此集层次化处理和平稳化处理的集合正交经验模态分解技术(EEMD)的提出,为解决上述问题提供了有效的途径。本文选取黄河中上游24个气象观测站的逐月降水资料,结合组合预报和集合预报思路,基于EEMD建立了统计预报模型。其中对降水序列中的高频部分进行了二次平稳化处理,实现对2008—2013年6—8月的降水预报,并用预报评分检测预报效果。结果表明:EEMD模型对黄河中上游夏季降水有着较强的预报能力,在该区域与气候模式和传统的统计方法相比具有更高的精度和更好的应用前景。     

Evaluation of the biological toxicity of fluorine in Antarctic krill

Antarctic krill is a potentially nutritious food source for humans, but fluorine(F) toxicity is a matter of concern. To evaluate the toxicity of F in Antarctic krill, 30 Wistar rats were divided into three groups with different dietary regimens: a control group, a krill treatment group(150 mg·kg-1 F), and a sodium fluoride(NaF) treatment group(150 mg·kg-1 F). After three months, F concentrations in feces, plasma, and bone were determined, and the degree of dental and skeletal fluorosis was assessed. The F concentrations in plasma and bone from the krill treatment group were 0.167 0±0.020 4 mg.L-1 and 2 709.8±301.9 mg·kg-1, respectively, compared with 0.043 8±0.005 5 mg·L-1 and 442.4±60.7 mg·kg-1, respectively, in samples from the control group. Concentrations of F in plasma and bone in the krill treatment group were higher than in the control group, but lower than in the NaF treatment group. The degree of dental fluorosis in the krill treatment group was moderate, compared with severe in the NaF treatment group and normal in the control group. The degree of skeletal fluorosis did not change significantly in any group. These results showed that the toxicity of F in Antarctic krill was lower than for an equivalent concentration of F in NaF, but it was toxic for rats consuming krill in large quantities. To conclude, we discuss possible reasons for the reduced toxicity of F in Antarctic krill. The present study provides a direct toxicological reference for the consideration of Antarctic krill for human consumption.     

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Numerical Simulations of Laminar Air–Water Flow of a Non-linear Progressive Wave at Low Wind Speed

A numerical simulation for two-dimensional laminar air–water flow of a non-linear progressive water wave with large steepness is performed when the background wind speed varies from zero to the wave phase speed. It is revealed that in the water the difference between the analytical solution of potential flow and numerical solution of viscous flow is very small, indicating that both solutions of the potential flow and viscous flow describe the water wave very accurately. In the air the solutions of potential and viscous flows are very different due to the effects of viscosity. The velocity distribution in the airflow is strongly influenced by the background wind speed and it is found that three wind speeds, $U=0$ , $U=u_m$ (the maximum orbital velocity of a water wave), and $U=c$ (the wave phase speed), are important in distinguishing different features of the flow patterns.