Masses of Scalar and Axial-Vector B Mesons Revisited

The SU(3) quark model encounters a great challenge in describing even-parity mesons. Specifically, the $q\bar q$ quark model has difficulties in understanding the light scalar mesons below 1 GeV, scalar and axial-vector charmed mesons and $1^+$ charmonium-like state $X(3872)$. A common wisdom for the resolution of these difficulties lies on the coupled channel effects which will distort the quark model calculations. In this work, we focus on the near mass degeneracy of scalar charmed mesons, $D_{s0}^*$ and $D_0^{*0}$, and its implications. Within the framework of heavy meson chiral perturbation theory, we show that near degeneracy can be qualitatively understood as a consequence of self-energy effects due to strong coupled channels. Quantitatively, the closeness of $D_{s0}^*$ and $D_0^{*0}$ masses can be implemented by adjusting two relevant strong couplings and the renormalization scale appearing in the loop diagram. Then this in turn implies the mass similarity of $B_{s0}^*$ and $B_0^{*0}$ mesons. The $P_0^* P'_1$ interaction with the Goldstone boson is crucial for understanding the phenomenon of near degeneracy. Based on heavy quark symmetry in conjunction with corrections from QCD and $1/m_Q$ effects, we obtain the masses of $B^*_{(s)0}$ and $B'_{(s)1}$ mesons, for example, $M_{B_{s0}^*}= (5715\pm1)\,{\rm MeV}+\delta\Delta_S$, $M_{B'_{s1}}=(5763\pm1)\,{\rm MeV}+\delta\Delta_S$ with $\delta\Delta_S$ being $1/m_Q$ corrections. We find that the predicted mass difference of 48 MeV between $B'_{s1}$ and $B_{s0}^*$ is larger than that of $20\sim 30$ MeV inferred from the relativistic quark models, whereas the difference of 15 MeV between the central values of $M_{B'_{s1}}$ and $M_{B'_1}$ is much smaller than the quark model expectation of $60-100$ MeV.Comment: 21 pages, 1 figure, to appear in Eur. Phys. J. (2017). arXiv admin note: text overlap with arXiv:1404.377

Video Highlight Prediction Using Audience Chat Reactions

Sports channel video portals offer an exciting domain for research on multimodal, multilingual analysis. We present methods addressing the problem of automatic video highlight prediction based on joint visual features and textual analysis of the real-world audience discourse with complex slang, in both English and traditional Chinese. We present a novel dataset based on League of Legends championships recorded from North American and Taiwanese Twitch.tv channels (will be released for further research), and demonstrate strong results on these using multimodal, character-level CNN-RNN model architectures.Comment: EMNLP 201

Rapid (<5 min) identification of pathogen in human blood by electrokinetic concentration and surface-enhanced Raman spectroscopy.

This study reports a novel microfluidic platform for rapid and long-ranged concentration of rare-pathogen from human blood for subsequent on-chip surface-enhanced Raman spectroscopy (SERS) identification/discrimination of bacteria based on their detected fingerprints. Using a hybrid electrokinetic mechanism, bacteria can be concentrated at the stagnation area on the SERS-active roughened electrode, while blood cells were excluded away from this region at the center of concentric circular electrodes. This electrokinetic approach performs isolation and concentration of bacteria in about three minutes; the density factor is increased approximately a thousand fold in a local area of ~5000 μm(2) from a low bacteria concentration of 5 × 10(3) CFU/ml. Besides, three genera of bacteria, S. aureus, E. coli, and P. aeruginosa that are found in most of the isolated infections in bacteremia were successfully identified in less than one minute on-chip without the use of any antibody/chemical immobilization and reaction processes