B\"{a}cklund transformations for the constrained dispersionless hierarchies and dispersionless hierarchies with self-consistent sources

The B\"{a}cklund transformations between the constrained dispersionless KP hierarchy (cdKPH) and the constrained dispersionless mKP hieararchy (cdmKPH) and between the dispersionless KP hieararchy with self-consistent sources (dKPHSCS) and the dispersionless mKP hieararchy with self-consistent sources (dmKPHSCS) are constructed. The auto-B\"{a}cklund transformations for the cdmKPH and for the dmKPHSCS are also formulated.Comment: 11 page

Exact Algorithms for Maximum Independent Set

We show that the maximum independent set problem (MIS) on an $n$-vertex graph can be solved in $1.1996^nn^{O(1)}$ time and polynomial space, which even is faster than Robson's $1.2109^{n}n^{O(1)}$-time exponential-space algorithm published in 1986. We also obtain improved algorithms for MIS in graphs with maximum degree 6 and 7, which run in time of $1.1893^nn^{O(1)}$ and $1.1970^nn^{O(1)}$, respectively. Our algorithms are obtained by using fast algorithms for MIS in low-degree graphs in a hierarchical way and making a careful analyses on the structure of bounded-degree graphs

Stray field and superconducting surface spin valve effect in La0.7_{0.7}Ca0.3_{0.3}MnO3_3/YBa2_2Cu3_3O7−δ_{7-\delta} bilayers

Electronic transport and magnetization measurements were performed on La$_{0.7}$Ca$_{0.3}$MnO$_3$/YBa$_2$Cu$_3$O$_{7-\delta}$ (LCMO/YBCO) bilayers below the superconducting transition temperature in order to study the interaction between magnetism and superconductivity. This study shows that a substantial number of weakly pinned vortices are induced in the YBCO layer by the large out-of-plane stray field in the domain walls. Their motion gives rise to large dissipation peaks at the coercive field. The angular dependent magnetoresistance (MR) data reveal the interaction between the stripe domain structure present in the LCMO layer and the vortices and anti-vortices induced in the YBCO layer by the out-of-plane stray field. In addition, this study shows that a superconducting surface spin valve effect is present in these bilayers as a result of the relative orientation between the magnetization at the LCMO/YBCO interface and the magnetization in the interior of the LCMO layer that can be tuned by the rotation of a small $H$. This latter finding will facilitate the development of superconductive magnetoresistive memory devices. These low-magnetic field MR data, furthermore, suggest that triplet superconductivity is induced in the LCMO layer, which is consistent with recent reports of triplet superconductivity in LCMO/YBCO/LCMO trilayers and LCMO/YBCO bilayers.Comment: 14 pages, 3 figure

Real-time motion data annotation via action string

Even though there is an explosive growth of motion capture data, there is still a lack of efficient and reliable methods to automatically annotate all the motions in a database. Moreover, because of the popularity of mocap devices in home entertainment systems, real-time human motion annotation or recognition becomes more and more imperative. This paper presents a new motion annotation method that achieves both the aforementioned two targets at the same time. It uses a probabilistic pose feature based on the Gaussian Mixture Model to represent each pose. After training a clustered pose feature model, a motion clip could be represented as an action string. Then, a dynamic programming-based string matching method is introduced to compare the differences between action strings. Finally, in order to achieve the real-time target, we construct a hierarchical action string structure to quickly label each given action string. The experimental results demonstrate the efficacy and efficiency of our method

Charmless B→PV,VVB \to PV, VV decays and new physics effects in the mSUGRA model

By employing the QCD factorization approach, we calculate the new physics contributions to the branching radios of the two-body charmless $B \to PV$ and $B \to VV$ decays in the framework of the minimal supergravity (mSUGRA) model. we choose three typical sets of the mSUGRA input parameters in which the Wilson coefficient $C_{7\gamma}(m_b)$ can be either SM-like (the case A and C) or has a flipped-sign (the case B). We found numerically that (a) the SUSY contributions are always very small for both case A and C; (b) for those tree-dominated decays, the SUSY contributions in case B are also very small; (c) for those QCD penguin-dominated decay modes, the SUSY contributions in case B can be significant, and can provide an enhancement about $30$ to the branching ratios of $B \to K^*(\pi,\phi,\rho)$ and $K \phi$ decays, but a reduction about $30$ to $B\to K(\rho, \omega)$ decays; and (d) the large SUSY contributions in the case B may be masked by the large theoretical errors dominated by the uncertainty from our ignorance of calculating the annihilation contributions in the QCD factorization approach.Comment: 34 pages, 8 PS figures, this is the correct version

Competition between Hidden Spin and Charge Orderings in Stripe Phase

The correlation between charge and spin orderings in hole-doped antiferromagnets is studied within an effective model of quantum strings fluctuating in an antiferromagnetic background. In particular, we perform the direct estimation of the charge and spin long-range-order parameters by means of the quantum Monte Carlo simulation. A hidden spin long-range order is found to be governed by a competition between the two trends caused by increasing hole mobility: the enhancement of the two-dimensional spin-spin correlation mediated by hole motions and the reformation of a strong stripe order.Comment: 4 pages, 8 figures. Accepted for publication as a Rapid Communication in Physical Review

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction