Diquarks and the Semi-Leptonic Decay of Λb\Lambda_{b} in the Hybrid Scheme

In this work we use the heavy-quark-light-diquark picture to study the semileptonic decay $\Lambda_b \to \Lambda_c+l+\bar{\nu}_l$ in the so-called hybrid scheme. Namely, we apply the heavy quark effective theory (HQET) for larger $q^2$ (corresponding to small recoil), which is the invariant mass square of $l+\bar\nu$, whereas the perturbative QCD approach for smaller $q^2$ to calculate the form factors. The turning point where we require the form factors derived in the two approaches to be connected, is chosen near $\rho_{cut}=1.1$. It is noted that the kinematic parameter $\rho$ which is usually adopted in the perturbative QCD approach, is in fact exactly the same as the recoil factor $\omega=v\cdot v'$ used in HQET where $v$, $v'$ are the four velocities of $\Lambda_b$ and $\Lambda_c$ respectively. We find that the final result is not much sensitive to the choice, so that it is relatively reliable. Moreover, we apply a proper numerical program within a small range around $\rho_{cut}$ to make the connection sufficiently smooth and we parameterize the form factor by fitting the curve gained in the hybrid scheme. The expression and involved parameters can be compared with the ones gained by fitting the experimental data. In this scheme the end-point singularities do not appear at all. The calculated value is satisfactorily consistent with the data which is recently measured by the DELPHI collaboration within two standard deviations.Comment: 16 pages, including 4 figures, revtex

Forsythia suspensa extract has inhibitory effect on proliferation and apoptosis of A549 lung cancer cells

Purpose: To investigate the effect of Forsythia suspensa extract (FSE) on apoptosis and proliferation in A549 human lung cancer cells. Methods: Inverted microscope was employed to observe morphological changes in A549 cells after exposure to FSE. Trypan blue staining of living cells was used to construct the cell growth curve after treatment with varying concentrations of FSE. The influence of FSE on cell proliferation, apoptosis and cell cycle was determined by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay, while protein expressions of key apoptosis-related enzymes were evaluated by immunocytochemical method. Results: FSE inhibited the growth of A549 lung cancer cells at a concentration range of 10 - 150 μg/mL. Flow cytometry results showed that FSE induced apoptosis in A549 cells. The proportion of cells in G0/G1-phase increased significantly (p < 0.01), while the proportion of cells in S- and G2/M-phase decreased correspondingly, indicating that the cells were in G0/G1-phase arrest. Cell cycle arrest and apoptosis-inducing effect gradually rose with increase in FSE concentration. With increasing concentrations of FSE, there was also significant increase in the expressions of caspase-3 (p < 0.05), caspase-8 (p < 0.01) and caspase-9 (p < 0.05), but significant decrease in Ki-67 (p < 0.01) and p21 ras protein (p < 0.01). Conclusion: FSE exerts significant inhibitory effect on the proliferation of A549 lung cancer cells. Therefore, the plant can potentially be developed for the treatment of lung cancer

Query weighting for ranking model adaptation

We propose to directly measure the importance of queries in the source domain to the target domain where no rank labels of documents are available, which is referred to as query weighting. Query weighting is a key step in ranking model adaptation. As the learning object of ranking algorithms is divided by query instances, we argue that it’s more reasonable to conduct importance weighting at query level than document level. We present two query weighting schemes. The first compresses the query into a query feature vector, which aggregates all document instances in the same query, and then conducts query weighting based on the query feature vector. This method can efficiently estimate query importance by compressing query data, but the potential risk is information loss resulted from the compression. The second measures the similarity between the source query and each target query, and then combines these fine-grained similarity values for its importance estimation. Adaptation experiments on LETOR3.0 data set demonstrate that query weighting significantly outperforms document instance weighting methods.