Information Filtering on Coupled Social Networks

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm based on the coupled social networks, which considers the effects of both social influence and personalized preference. Experimental results on two real datasets, \emph{Epinions} and \emph{Friendfeed}, show that hybrid pattern can not only provide more accurate recommendations, but also can enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding structure and function of coupled social networks

Research on object placement method based on trajectory recognition in Metaverse

Many studies focus on only one aspect while placing objects in virtual reality environment, such as efficiency, accuracy or interactivity. However, striking a balance between these aspects and taking into account multiple indicators is important as it is the key to improving user experience. Therefore, this paper proposes an efficient and interactive object placement method for recognizing controller trajectory in virtual reality environment. For creating user-friendly feedback, we visualize the intersection of the ray and the scene by linking the controller motion information and the ray. The trajectory is abstracted as point-clouds for matching, and the corresponding object is instantiated at the center of the trajectory. To verify the interactive performance and user satisfaction with this method, we carry out a study on user experience. The results show that both the efficiency and interaction interest are improved by applying our new method, which provides a good idea for the interactive design of virtual reality layout applications

Electronic Structures of Graphene Layers on Metal Foil: Effect of Point Defects

Here we report a facile method to generate a high density of point defects in graphene on metal foil and show how the point defects affect the electronic structures of graphene layers. Our scanning tunneling microscopy (STM) measurements, complemented by first principle calculations, reveal that the point defects result in both the intervalley and intravalley scattering of graphene. The Fermi velocity is reduced in the vicinity area of the defect due to the enhanced scattering. Additionally, our analysis further points out that periodic point defects can tailor the electronic properties of graphene by introducing a significant bandgap, which opens an avenue towards all-graphene electronics.Comment: 4 figure

Macrophage migration inhibitory factor (MIF) family in arthropods : Cloning and expression analysis of two MIF and one D-dopachrome tautomerase (DDT) homologues in Mud crabs, Scylla paramamosain

Acknowledgements This research was supported by grants from the National Natural Science Foundation of China (Nos. 31172438 and U1205123), the Natural Science Foundation of Fujian Province (No. 2012J06008 and 201311180002) and the projects-sponsored by SRF. TW received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Peer reviewedPostprin

Antirheumatoid Arthritis Activities and Chemical Compositions of Phenolic Compounds-Rich Fraction from Urtica atrichocaulis, an Endemic Plant to China

Urtica atrichocaulis, an endemic plant to China, is commonly used to treat rheumatoid arthritis even though its pharmaceutical activities and chemical constituents were not studied. Herein, we reported our investigations on the chemical compositions of the phenolic compounds-rich fraction from U. atrichocaulis (TFUA) and their antirheumatoid arthritis activities. We found that the TFUA significantly inhibited the adjuvant-induced rats arthritis, carrageenin-induced rats paw edema, cotton pellet-induced mice granuloma, and the acetic acid-induced mice writhing response. Our phytochemical investigations on the TFUA resulted in the first-time isolation and identification of 17 phenolic constituents and a bis (5-formylfurfuryl) ether. The extensive HPLC analysis also revealed the chemical compositions of TFUA. Our further biological evaluation of the main phenolic components, individually and collectively, indicated that the antirheumatoid arthritis activities of TFUA were the combined effect of multiple phenolic constituents