Investigating possible decay modes of Y(4260)Y(4260) under the D1(2420)Dˉ+c.cD_1(2420)\bar D +c.c molecular state ansatz

By assuming that $Y(4260)$ is a $D_1\bar D$ molecular state, we investigate some hidden-charm and charmed pair decay channels of $Y(4260)$ via intermediate $D_1\bar D$ meson loops with an effective Lagrangian approach. Through investigating the $\alpha$-dependence of branching ratios and ratios between different decay channels, we show that the intermediate $D_1 \bar D$ meson loops are crucial for driving these transitions of $Y(4260)$ studied here. The coupled channel effects turn out to be more important in $Y(4260) \to D^{*}\bar{D}^{*}$, which can be tested in the future experiments.Comment: 8 pages, 6 figures; The width effects of Y(4260) considered; Revised version accepted by Phys. Rev.

Imagination Based Sample Construction for Zero-Shot Learning

Zero-shot learning (ZSL) which aims to recognize unseen classes with no labeled training sample, efficiently tackles the problem of missing labeled data in image retrieval. Nowadays there are mainly two types of popular methods for ZSL to recognize images of unseen classes: probabilistic reasoning and feature projection. Different from these existing types of methods, we propose a new method: sample construction to deal with the problem of ZSL. Our proposed method, called Imagination Based Sample Construction (IBSC), innovatively constructs image samples of target classes in feature space by mimicking human associative cognition process. Based on an association between attribute and feature, target samples are constructed from different parts of various samples. Furthermore, dissimilarity representation is employed to select high-quality constructed samples which are used as labeled data to train a specific classifier for those unseen classes. In this way, zero-shot learning is turned into a supervised learning problem. As far as we know, it is the first work to construct samples for ZSL thus, our work is viewed as a baseline for future sample construction methods. Experiments on four benchmark datasets show the superiority of our proposed method.Comment: Accepted as a short paper in ACM SIGIR 201

Risk-return Efficiency, Financial Distress Risk, and Bank Financial Strength Ratings

This paper investigates whether there is any consistency between banks' financial strength ratings (bank rating) and their risk-return profiles. It is expected that banks with high ratings tend to earn high expected returns for the risks they assume and thereby have a low probability of experiencing financial distress. Bank ratings, a measure of a bank's intrinsic safety and soundness, should therefore be able to capture the bank's ability to manage financial distress while achieving risk-return efficiency. We first estimate the expected returns, risks, and financial distress risk proxy (the inverse z-score), then apply the stochastic frontier analysis (SFA) to obtain the risk-return efficiency score for each bank, and finally conduct ordered logit regressions of bank ratings on estimated risks, risk-return efficiency, and the inverse z-score by controlling for other variables related to each bank's operating environment. We find that banks with a higher efficiency score on average tend to obtain favorable ratings. It appears that rating agencies generally encourage banks to trade expected returns for reduced risks, suggesting that these ratings are generally consistent with banks' risk-return profiles.bank ratings; risk-return efficiency; stochastic frontier analysis

Do Global Credit Rating Agencies Think Globally? The Information Content of Firm Ratings around the World

What is the information content of firm ratings? We disentangle the relative contribution to firms? ratings of sovereign risks and individual firms? performance indicators, reportedly employed by rating agencies. We reach three conclusions. First, sovereign risks? contribution is disproportionately greater in developing countries vis-ý-vis developed countries. Second, even controlling for the ?country ceiling effect??private ratings being constrained by their sovereign?s rating?firm ratings? information content is much smaller in developing countries. Third, cross-country indicators of information quality help explain but do not solve the puzzle entirely. Thus, global rating agencies do not (yet) think globally.