地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

Intellectual Property in Computing: (How) Should Software Be Protected? An Industry Perspective

The future of the software industry is today being shaped in the courtroom. Most discussions of intellectual property to date, however, have been frames as debates about how the existing law --- promulgated long before the computer revolution --- should be applied to software. This memo is a transcript of a panel discussion on what forms of legal protection should apply to software to best serve both the industry and society in general. After addressing that question we can consider what laws would bring this about.

Colorimetric and ratiometric fluorescence sensing of fluoride: Tuning selectivity in proton transfer

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Characterization of interaction property of multicomponents in Chinese Herb with protein by microdialysis combined with HPLC

Interaction of traditional Chinese Herb Rhizoma Chuanxiong and protein was studied by microdialysis coupled with high performance liquid chromatography. Compounds in Rhizoma Chuanxiong, such as ferulic acid, senkyunolide A and 3-butylphthalide, were identified by HPLC, HPLC-MS and UV-vis. Microdialysis recoveries and binding degrees of compounds in Rhizoma Chuanxiong with human serum albumin (HSA) and other human plasma protein were determined: recoveries of microdialysis sampling ranged from 36.7 to 98.4% with R.S.D. below 3.1%; while binding to HSA ranged from 0 to 91.5% (0.3 mM HSA) and from 0 to 93.5% (0.6 mM HSA), respectively. Compared with HSA, most of compounds bound to human blood serum more extensively and the results showed that binding of these compounds in Rhizoma Chuanxiong was influenced by pH. Two compounds were found to bind to HSA and human blood serum. their binding degrees were consistent with ferulic acid and 3-butylphthalide, the active compounds in Rhizoma Chuanoxiong. (c) 2005 Elsevier B.V. All rights reserved.

Tactile Sensing: new directions, new challenges

Lee M.H., ?Tactile Sensing: new directions, new challenges?, Int J. Robotics Research 19: 7, 636-643. July 2000.

Opportunities for X-ray remote sensing at Mercury

Grande, Manuel; Dunkin, S. K.; Kellett, B., 'Opportunities for X-ray remote sensing at Mercury', Planetary And Space Science (2001) 49(14-15) pp.1553-1559 RAE2008