Possibly New Charmed Baryon States from Bˉ0→ppˉD0\bar B^0\to p\bar p D^{0} Decay

We examine the invariant mass spectrum of $D^{0}p$ in $\bar B^0\to p\bar p D^{0}$ decay measured by BABAR and find that through the 2-step processes of $\bar B^0\to {\bf B_c^+}(\to D^{0} p)\bar p$, where ${\bf B_c}$ denotes a charmed baryon state, some of the peaks can be identified with the established $\Sigma_c(2800)^+$, $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$. Moreover, in order to account for the measured spectrum, it is necessary to introduce a new charmed baryon resonance with $(m,\,\Gamma)=(3212\pm 20,\,167\pm 34)$ MeV.Comment: 8 pages, 1 figure, title changed and discussions updated, version accepted for publication in Phys. Rev.

Caching and Auditing in the RPPM Model

Crampton and Sellwood recently introduced a variant of relationship-based access control based on the concepts of relationships, paths and principal matching, to which we will refer as the RPPM model. In this paper, we show that the RPPM model can be extended to provide support for caching of authorization decisions and enforcement of separation of duty policies. We show that these extensions are natural and powerful. Indeed, caching provides far greater advantages in RPPM than it does in most other access control models and we are able to support a wide range of separation of duty policies.Comment: Accepted for publication at STM 2014 (without proofs, which are included in this longer version

Learning Points and Routes to Recommend Trajectories

The problem of recommending tours to travellers is an important and broadly studied area. Suggested solutions include various approaches of points-of-interest (POI) recommendation and route planning. We consider the task of recommending a sequence of POIs, that simultaneously uses information about POIs and routes. Our approach unifies the treatment of various sources of information by representing them as features in machine learning algorithms, enabling us to learn from past behaviour. Information about POIs are used to learn a POI ranking model that accounts for the start and end points of tours. Data about previous trajectories are used for learning transition patterns between POIs that enable us to recommend probable routes. In addition, a probabilistic model is proposed to combine the results of POI ranking and the POI to POI transitions. We propose a new F$_1$ score on pairs of POIs that capture the order of visits. Empirical results show that our approach improves on recent methods, and demonstrate that combining points and routes enables better trajectory recommendations

Seeing Is Believing: Analysts' Corporate Site Visits

This study examines the impact of corporate site visits on analysts’ forecast accuracy based on a sample of such visits to Chinese listed firms during 2009–2012. We find that analysts who conduct visits (“visiting analysts”) have a greater increase in forecast accuracy than other analysts. Consistent with the notion that site visits facilitate analysts’ information acquisition through observing firms’ operations, we find that the results are stronger for manufacturing firms, firms with more tangible assets, and firms with more concentrated business lines. Moreover, we find that the effect of a site visit is greater when the site visit is an analyst-only visit, when the current visit is preceded by fewer visits, and when visiting analysts are based far from the visited firms. Furthermore, we find that site visits partially mitigate nonlocal analysts’ information disadvantage. Collectively, these results indicate that site visits are an important information acquisition activity for analysts.postprin

Torque ripple minimization of doubly salient permanent-magnet motors

Due to the nature of salient poles in both the stator and rotor, the doubly salient permanent-magnet (DSPM) motor suffers from severe torque ripples. In this paper, the torque ripple of DSPM motors is analyzed, and the torque ripple factor is newly derived. A new approach, namely the conduction angle control, is proposed to minimize the torque ripple. Moreover, the genetic algorithm is employed to optimize the corresponding control angles. Computer simulation and experimental results are given to verify the proposed approach. © 2005 IEEE.published_or_final_versio