The influence of ultra-low moisture content on the seed viability of rice in store

This paper deals with the influence of ultra-lowmoisture content and the rate of desiccation on rice seed viability and physiological property bydesiccating using four kinds of desiccants(phos-

UGC-Driven Social Influence Study in Online Micro- Blogging Sites

In Web 2.0 era,the content on a web page is increasingly generated by end users,rather than limited number of administrators.Hence,large number of User Generated Content(UGC) has driven the explosion of content in the web.Thanks to UGC,the pattern of web usage has evolved from download dominated way to a hybrid one with both information download and upload.Large number of UGC has unveiled great capacity of information that is unavailable for researchers before,such as individual preferences,social connections,and etc.In this paper,we propose a novel model which studies the UGC in micro-blogging web sites,the largest and fastest information diffusion media online,and evaluate the social influence for an arbitrary individual.Experimental results show that our model outperforms state-of-the-art techniques in social influence evaluation in both the running time and accuracy.

Geological controls of shale gas accumulation and enrichment mechanism in Lower Cambrian Niutitang Formation of western Hubei, Middle Yangtze, China

The lower Cambrian Niutitang Formation is of crucial importance for shale gas target reservoirs in western Hubei,China;however,little work has been done in this field,and its shale gas accumulation and enrichment mechanism are still unclear.Based on survey wells,outcrop data,and large numbers of tests,the geological conditions of shale gas accumulation were studied;moreover,the factors that influence the gas content were thoroughly discussed.The results show that the Niutitang Formation(Є1n)can be divided into three sections:the first section(Є_(1)n^(1)),the second section(Є_(1)n^(2)),and the third section(Є1n3).TheЄ_(1)n^(2) is the main shale gas reservoir.The deep shelf facies is the main sedimentary facies and can be divided into three main lithofacies:argillaceous siltstone,carbonaceous shale and carbonaceous siliceous rock.The total organic carbon(TOC)content shows gentle growth trends until bottom of theЄ_(1)n^(2) and then decreases rapidly within theЄ_(1)n^(1),and the TOC content mainly ranges from 2%to 4%horizontally.The calcite and dolomite dissolution pores,clay intergranular pores and organic pores are the main pore types and the micropore types are clearly related to the mineral compositions and the TOC content.Vertically,the gas content is mainly affected by the TOC content.Horizontally,wells with high gas contents are distributed only southeast of the Huangling anticline,and the combination of structural styles,fault and fracture development,and the distribution of the regional unconformity boundary between the upper Sinian Dengying Formation(Z2d)and theЄ_(1)n^(2) are the three most important factors affecting the gas content.The favorable areas must meet the following conditions:a deep shelf environment,the presence of theЄ_(1)n^(1),wide and gentle folds,far from large normal faults that are more than 5 km,moderate thermal evolution,and greater than 500 m burial depth;this includes the block with the YD2–ZD2 wells,and the block with the Y1 and YD4 wells,which are distributed in the southern portion of the Huangling anticline and northern portion of the Xiannvshan fault.

Joint model of user check-in activities for point-of-interest recommendation

With the rapid development of location-based networks, point-of-interest（POI） recommendation has become an important means to help people discover interesting and attractive locations, especially when users travel out of town. However, because users only check-in interaction is highly sparse, which creates a big challenge for POI recommendation. To tackle this challenge, we propose a joint probabilistic generative model called geographical temporal social content popularity（GTSCP） to imitate user check-in activities in a process of decision making, which effectively integrates the geographical influence, temporal effect, social correlation, content information and popularity impact factors to overcome the data sparsity, especially for out-of-town users. Our proposed the GTSCP supports two recommendation scenarios in a joint model, i.e., home-town recommendation and out-of-town recommendation. Experimental results show that GTSCP achieves significantly superior recommendation quality compared to other state-of-the-art POI recommendation techniques.