Landslide Investigation at Phata Village on Rudraprayag-Kedarnath Road, Uttaranchal — A Case Study

Phata village on the Guptakashi-Gaurikund road in the Mandakini valley of Garhwal Himalaya was affected by a major landslide on 16th July 2001 due to heavy rainfall. The debris flow not only swept away several houses but it also claimed 15 lives. A detailed landslide investigation was carried out to assess the present stability condition. Geotechnical investigation was carried out to determine the soil properties. Seismic refraction survey to determine the overburden thickness was also carried out using Engineering Seismograph. Slope stability analysis was carried out to ascertain the existing stability of the slope. It was found that with rise in pore pressure the slope is marginally stable. The seismic stability analysis showed that seismicity of the order of 0.15g may trigger slips on the slope. The human settlement on the downhill slope may get effected in the eventuality of slide due to seismicity or rain. The paper presents the results of the geological and geotechnical studies which helped to assess the present stability condition

Social Interactions vs Revisions, What is important for Promotion in Wikipedia?

In epistemic community, people are said to be selected on their knowledge contribution to the project (articles, codes, etc.) However, the socialization process is an important factor for inclusion, sustainability as a contributor, and promotion. Finally, what does matter to be promoted? being a good contributor? being a good animator? knowing the boss? We explore this question looking at the process of election for administrator in the English Wikipedia community. We modeled the candidates according to their revisions and/or social attributes. These attributes are used to construct a predictive model of promotion success, based on the candidates's past behavior, computed thanks to a random forest algorithm. Our model combining knowledge contribution variables and social networking variables successfully explain 78% of the results which is better than the former models. It also helps to refine the criterion for election. If the number of knowledge contributions is the most important element, social interactions come close second to explain the election. But being connected with the future peers (the admins) can make the difference between success and failure, making this epistemic community a very social community too