Weak acid leaching of uranium ore from a high carbonate uranium deposit

Journal of Radioanalytical and Nuclear Chemistry - Mineralogical study showed that the Yuejin uranium ore is from a low grade, high carbonate and high pyrite sandstone type uranium deposit. Uranium...     

Determination of Triterpenoids and Phenolic Acids from Sanguisorba officinalis L. by HPLC-ELSD and Its Application

A novel analytical method involving high-performance liquid chromatography with evaporative light scattering detection (HPLC-ELSD) was developed for simultaneous determination of 11 phenolic acids and 12 triterpenes in Sanguisorba officinalis L. Chromatographic separation was conducted with gradient elution mode by using a Diamonsil^TM C₁₈ column (250 mm × 4.6 mm, 5 μm) with the mobile phase of 0.1% acetic acid water (A) and methanol (B). The drift tube temperature of ELSD was set at 70 °C and the nitrogen cumulative flow rate was 1.6 L/min. The method was fully validated to be linear over a wide concentration range (R² ≥ 0.9991). The precisions (RSD) were less than 3.0% and the recoveries were between 97.7% and 101.4% for all compounds. The results indicated that this method is accurate and effective for the determination of 23 functional components in Sanguisorba officinalis L. and could also be successfully applied to study the influence of processing method on those functional components in Sanguisorba officinalis L.     

A last updating evolution model for online social networks

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.