First Abundance Measurement of Organic Molecules in the Atmosphere of HH 212 Protostellar Disk

HH 212 is one of the well-studied protostellar systems, showing the first vertically resolved disk with a warm atmosphere around the central protostar. Here we report a detection of 9 organic molecules (including newly detected ketene, formic acid, deuterated acetonitrile, methyl formate, and ethanol) in the disk atmosphere, confirming that the disk atmosphere is, for HH 212, the chemically rich component, identified before at a lower resolution as a "hot-corino". More importantly, we report the first systematic survey and abundance measurement of organic molecules in the disk atmosphere within $\sim$ 40 au of the central protostar. The relative abundances of these molecules are similar to those in the hot corinos around other protostars and in Comet Lovejoy. These molecules can be either (i) originally formed on icy grains and then desorbed into gas phase or (ii) quickly formed in the gas phase using simpler species ejected from the dust mantles. The abundances and spatial distributions of the molecules provide strong constraints on models of their formation and transport in star formation. These molecules are expected to form even more complex organic molecules needed for life and deeper observations are needed to find them.Comment: 12 pages, 4 figure

An Effective Friend Recommendation Method Using Learning to Rank and Social Influence

Social network sites have become an important medium for people to receive information anytime anywhere. Users of social network sites share information by posting updates. The updates shared by friends form social update streams that provide people with up-to-date information. To receive novel information, users of social network sites are encouraged to establish social relations. However, having too many friends can lead to an information overload problem causing users to be overwhelmed by the huge number of updates shared continuously by numerous friends. The information overload problem can result in bad user experiences. It may also affect user intentions to join social network sites and thereby possibly reduce the sites’ advertising earnings which are based on the number of users. To resolve this problem, there is an urgent need of effective friend recommendation methods. A user is considered as a valuable friend if people like the updates the user posts. In this paper, we propose a model-based recommendation method which suggests valuable friends to users. Techniques of matrix factorization and learning to rank are designed to model the latent preferences of users and updates. At the same time, social influence is incorporated into the proposed method to enhance the learned preferences. Valuable friends are recommended if the preferences of the updates that they share are highly associated with the preferences of a target user. Our experiment findings that are based on a huge real-world dataset demonstrate the effectiveness of the social influence and learning to rank on a friend recommendation task. The results show that the proposed method is effective and it outperforms many well-known friend recommendation methods in terms of the coverage rate and ranking performance

Mechanism of action and resistant profile of anti-HIV-1 coumarin derivatives

Dicamphanoyl khellactone (DCK) is a coumarin derivative that can potently inhibit HIV-1 replication. DCK does not inhibit RNA-dependent DNA synthesis. However, an HIV reverse transcriptase (RT) inhibitor-resistant strain, HIV-1/RTMDR1, is resistant to DCK. Thus, it is possible that HIV-1 RT is the target of DCK. To test this possibility, DCK-resistant viruses were selected in the presence of DCK. Our results indicate that a single amino acid mutation, E138K in HIV-1 RT, is sufficient to confer DCK resistance. Interestingly, a DCK derivative, 3'R,4'R-Di-O-(-)-camphanoyl-2-ethyl-2',2'-dimethyldihydropyrano[2,3-f]chromo ne (DCP8), is effective against HIV-1/RTMDR1. However, the DCK-escape virus carrying the E138K mutation remains resistant to DCP8. Since DCK did not inhibit the RNA-dependent DNA polymerase activity of HIV-1 RT when using poly-rA or poly-rC as template, we evaluated the effect of DCK on the DNA-dependent DNA polymerase activity of HIV-1 RT. Our results indicate that DCK can inhibit the DNA-dependent DNA polymerase activity of HIV-1 RT. In conclusion, DCK is a unique HIV-1 RT inhibitor that inhibits the DNA-dependent DNA polymerase activity. In contrast, DCK did not significantly affect the RNA-dependent DNA polymerase activity when poly-rA or poly-rC was used as templates. An E138K mutation in the non-nucleoside RT inhibitors (NNRTIs) binding pocket of HIV-1 RT confers resistance to DCK and its chromone derivative, DCP8