Topological Spin Texture in a Quantum Anomalous Hall Insulator

The quantum anomalous Hall (QAH) effect has been recently discovered in experiment using thin-film topological insulator with ferromagnetic ordering and strong spin-orbit coupling. Here we investigate the spin degree of freedom of a QAH insulator and uncover a fundamental phenomenon that the edge states exhibit topologically stable spin texture in the boundary when a chiral-like symmetry is present. This result shows that edge states are chiral in both the orbital and spin degrees of freedom, and the chiral edge spin texture corresponds to the bulk topological states of the QAH insulator. We also study the potential applications of the edge spin texture in designing topological-state-based spin devices which might be applicable to future spintronic technologies.Comment: 5 pages manuscript, 8+ pages supplementary information, 8 figures; published versio

The Predicament of Specialized Villages and Its Solutions: A Case Study of Zhe-Village

Due to high competition in the same trade, residents in a specialized village become “homogeneous without shared interest”. Based on a case study of Zhe-Village, this paper describes the competition and conflicts inside specialized villages, as well as attempts at reconciliation. We find traditional measures of reconciliation, e.g. through personal relationship, community elites or their local government, to be fundamentally divergent from the economic aim of specialized villages, hence the limited effectiveness. Establishing a trade association is a possible solution to the predicament of Zhe-Village, but the lack of shared interests and inaction of the local government, combined with the attitude and distorted knowledge of villagers, hamper the founding of a trade association. To overcome these obstacles, specialized villages need rules of market competition, government support and updated knowledge. In this process, social integration may reappear in specialized village

Association between platelet count and the risk and progression of hand, foot, and mouth disease among children

OBJECTIVE: We aimed to evaluate the association between platelet (PLT) count and the risk and progression of hand, foot, and mouth disease (HFMD). METHODS: In total, 122 HFMD patients and 40 healthy controls were enrolled in the study. The differences between variables among the different subgroups were compared. Logistic regression analyses were performed to assess the relationship between various parameters and HFMD risk/progression. Sensitivity analysis was conducted by detecting the trend of the association between PLT count quartiles and HFMD risk/progression. A generalized additive model was used to identify the nonlinear relationship between PLT count and HFMD risk/ progression. The relationship between gender and PLT count as well as the risk/progression of HFMD was detected using a stratified logistic regression model. RESULTS: Significant differences were observed in terms of age, male/female ratio, white blood cell (WBC) count, and PLT count between patients with stage I-II, III-IV HFMD and healthy controls. Moreover, the alanine aminotransferase and magnesium levels between patients with stage I-II and III-IV HFMD significantly differed. Moreover, a significant difference was noted in the male/female ratio among the different PLT groups. The group with a low PLT count had a lower risk of HFMD progression than the group with a high PLT count (Q4) (p=0.039). Lower age, male gender, and WBC count were found to be associated with HFMD risk. Meanwhile, PLT count was correlated to HFMD progression. The sensitivity analysis yielded a similar result using the minimally adjusted model (p for trend=0.037), and minimal changes were observed using the crude and fully adjusted model (p for trend=0.054; 0.090). A significant nonlinear relationship was observed between PLT count and HFMD progression after adjusting for age, gender, and WBC (p=0.039). CONCLUSIONS: PLT was independently associated with HFMD progression in a nonlinear manner

Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian Inference

Latent Factor Model (LFM) is one of the most successful methods for Collaborative filtering (CF) in the recommendation system, in which both users and items are projected into a joint latent factor space. Base on matrix factorization applied usually in pattern recognition, LFM models user-item interactions as inner products of factor vectors of user and item in that space and can be efficiently solved by least square methods with optimal estimation. However, such optimal estimation methods are prone to overfitting due to the extreme sparsity of user-item interactions. In this paper, we propose a Bayesian treatment for LFM, named Bayesian Latent Factor Model (BLFM). Based on observed user-item interactions, we build a probabilistic factor model in which the regularization is introduced via placing prior constraint on latent factors, and the likelihood function is established over observations and parameters. Then we draw samples of latent factors from the posterior distribution with Variational Inference (VI) to predict expected value. We further make an extension to BLFM, called BLFMBias, incorporating user-dependent and item-dependent biases into the model for enhancing performance. Extensive experiments on the movie rating dataset show the effectiveness of our proposed models by compared with several strong baselines.Comment: 8 pages, 5 figures, ICPR2020 conferenc