A Novel Model of Working Set Selection for SMO Decomposition Methods

In the process of training Support Vector Machines (SVMs) by decomposition methods, working set selection is an important technique, and some exciting schemes were employed into this field. To improve working set selection, we propose a new model for working set selection in sequential minimal optimization (SMO) decomposition methods. In this model, it selects B as working set without reselection. Some properties are given by simple proof, and experiments demonstrate that the proposed method is in general faster than existing methods.Comment: 8 pages, 12 figures, it was submitted to IEEE International conference of Tools on Artificial Intelligenc

Physical properties of noncentrosymmetric superconductor Ru7_7B3_3

Transition metal boride Ru$_7$B$_3$ was found to be a noncentrosymmetric superconductor with $T_{C}$ equal to 3.3 K. Superconducting and normal state properties of Ru$_7$B$_3$ were determined by a self-consistent analysis through resistivity($\rho_{xx}$ and $\rho_{xy}$), specific heat, lower critical field measurement and electronic band structure calculation. It is found that Ru$_7$B$_3$ belongs to an s-wave dominated single band superconductor with energy gap 0.5 meV and could be categorized into type II superconductor with weak electron-phonon coupling. Unusual 'kink' feature is clearly observed in field-broadening resistivity curves, suggesting the possible mixture of spin triplet induced by the lattice without inversion symmetry.Comment: 11 pages, 16 figures. submitted to Phys. Rev.

Evidence for Two Gaps and Breakdown of the Uemura Plot in Ba0.6_{0.6}K0.4_{0.4}Fe2_2As2_2 Single Crystals

We report a detailed investigation on the lower critical field $H_{c1}$ of the superconducting Ba$_{0.6}$K$_{0.4}$Fe$_2$As$_2$ (FeAs-122) single crystals. A pronounced kink is observed on the $H_{c1}(T)$ curve, which is attributed to the existence of two superconducting gaps. By fitting the data $H_{c1}(T)$ to the two-gap BCS model in full temperature region, a small gap of $\Delta_a(0)=2.0\pm 0.3$ meV and a large gap of $\Delta_b(0)=8.9\pm 0.4$ meV are obtained. The in-plane penetration depth $\lambda_{ab}(0)$ is estimated to be 105 nm corresponding to a rather large superfluid density, which points to the breakdown of the Uemura plot in FeAs-122 superconductors.Comment: 5 pages, 4 figure

Polychromatic drivers for inertial fusion energy

Although tremendous achievements have been made toward inertial confinement fusion, laser plasma instabilities (LPIs) remain to be an inevitable problem for current drive schemes. To mitigate these instabilities, significant efforts have been paid to produce high-power broadband ultraviolet lasers. However, no practical scheme has been demonstrated up to now for efficient triple-frequency conversion of broadband laser. Here we propose the design of polychromatic drivers for the generation of multicolor beams mainly based upon the optical parametric amplification, which can significantly enhance the third-harmonic conversion efficiency. Each polychromatic light has four colors of monochromatic beamlets with a full spectrum width of 3\%, and the beamlet colors of any two adjacent flanges are different. The suppression effects of such polychromatic lights have been investigated via large scale particle-in-cell simulations, which indicate that more than 35\% of the incident energy can be saved from the LPIs compared with monochromatic lasers for the direct-drive scheme, or high-density filled target for the indirect-drive scheme. The proposed polychromatic drivers are based on the matured technologies, and thus may pave the way towards realization of robust and high-efficiency fusion ignition

Xanthogranulomatous Inflammation of the Female Genital Tract: Report of Three Cases

Purpose and Methods: This is a series of three cases diagnosed with xanthogranulomatous inflammation of the female genital with emphasis on the etiology, clinical-pathologic features and biological behavior. Clinical, pathologic, radiologic and follow up data are reported

Quaternion-Based Graph Convolution Network for Recommendation

Graph Convolution Network (GCN) has been widely applied in recommender systems for its representation learning capability on user and item embeddings. However, GCN is vulnerable to noisy and incomplete graphs, which are common in real world, due to its recursive message propagation mechanism. In the literature, some work propose to remove the feature transformation during message propagation, but making it unable to effectively capture the graph structural features. Moreover, they model users and items in the Euclidean space, which has been demonstrated to have high distortion when modeling complex graphs, further degrading the capability to capture the graph structural features and leading to sub-optimal performance. To this end, in this paper, we propose a simple yet effective Quaternion-based Graph Convolution Network (QGCN) recommendation model. In the proposed model, we utilize the hyper-complex Quaternion space to learn user and item representations and feature transformation to improve both performance and robustness. Specifically, we first embed all users and items into the Quaternion space. Then, we introduce the quaternion embedding propagation layers with quaternion feature transformation to perform message propagation. Finally, we combine the embeddings generated at each layer with the mean pooling strategy to obtain the final embeddings for recommendation. Extensive experiments on three public benchmark datasets demonstrate that our proposed QGCN model outperforms baseline methods by a large margin.Comment: 13 pages, 7 figures, 6 tables. Submitted to ICDE 202