Nondiffractive feature of γN→ρ±N\gamma N\to \rho^\pm N with ρ\rho-meson electromagnetic multipole moments

We investigate photoproduction of charged $\rho$ off the nucleon using $\rho(770)+\pi(140)$ Regge pole exchanges by considering the $\rho$-meson electromagnetic multipole moments. The significance of the Ward identity at the $\gamma\rho\rho$ vertex is emphasized for current conservation in the process. Given $\pi$ exchange with the well-known coupling constants for $\gamma\pi\rho$ and $\pi NN$, we analyze the role of the $\rho$ exchange in the $\gamma p\to \rho^+n$ and $\gamma n\to\rho^-p$ processes without model-dependences except for the magnetic moment $\mu_{\rho^\pm}=\pm2.01$ and electric quadrupole moment ${\cal Q}_{\rho^\pm}=\pm0.027$ fm$^2$ taken from theoretical estimates. The nondiffractive feature of both cross sections is reproduced with a rapid decrease beyond the resonance region by the dominance of $\pi$ exchange over the $\rho$\,. % Cross sections for differential and density matrix elements are presented to compare with existing data. The parity and photon polarization asymmetries are predicted to demonstrate the apparent roles of the $\rho$-meson electromagnetic multipole moments.Comment: 5 pages, 8 figure

An Alternative Approach to Functional Linear Partial Quantile Regression

We have previously proposed the partial quantile regression (PQR) prediction procedure for functional linear model by using partial quantile covariance techniques and developed the simple partial quantile regression (SIMPQR) algorithm to efficiently extract PQR basis for estimating functional coefficients. However, although the PQR approach is considered as an attractive alternative to projections onto the principal component basis, there are certain limitations to uncovering the corresponding asymptotic properties mainly because of its iterative nature and the non-differentiability of the quantile loss function. In this article, we propose and implement an alternative formulation of partial quantile regression (APQR) for functional linear model by using block relaxation method and finite smoothing techniques. The proposed reformulation leads to insightful results and motivates new theory, demonstrating consistency and establishing convergence rates by applying advanced techniques from empirical process theory. Two simulations and two real data from ADHD-200 sample and ADNI are investigated to show the superiority of our proposed methods

Predicting Social Links for New Users across Aligned Heterogeneous Social Networks

Online social networks have gained great success in recent years and many of them involve multiple kinds of nodes and complex relationships. Among these relationships, social links among users are of great importance. Many existing link prediction methods focus on predicting social links that will appear in the future among all users based upon a snapshot of the social network. In real-world social networks, many new users are joining in the service every day. Predicting links for new users are more important. Different from conventional link prediction problems, link prediction for new users are more challenging due to the following reasons: (1) differences in information distributions between new users and the existing active users (i.e., old users); (2) lack of information from the new users in the network. We propose a link prediction method called SCAN-PS (Supervised Cross Aligned Networks link prediction with Personalized Sampling), to solve the link prediction problem for new users with information transferred from both the existing active users in the target network and other source networks through aligned accounts. We proposed a within-target-network personalized sampling method to process the existing active users' information in order to accommodate the differences in information distributions before the intra-network knowledge transfer. SCAN-PS can also exploit information in other source networks, where the user accounts are aligned with the target network. In this way, SCAN-PS could solve the cold start problem when information of these new users is total absent in the target network.Comment: 11 pages, 10 figures, 4 table