Degree correlation effect of bipartite network on personalized recommendation

In this paper, by introducing a new user similarity index base on the diffusion process, we propose a modified collaborative filtering (MCF) algorithm, which has remarkably higher accuracy than the standard collaborative filtering. In the proposed algorithm, the degree correlation between users and objects is taken into account and embedded into the similarity index by a tunable parameter. The numerical simulation on a benchmark data set shows that the algorithmic accuracy of the MCF, measured by the average ranking score, is further improved by 18.19% in the optimal case. In addition, two significant criteria of algorithmic performance, diversity and popularity, are also taken into account. Numerical results show that the presented algorithm can provide more diverse and less popular recommendations, for example, when the recommendation list contains 10 objects, the diversity, measured by the hamming distance, is improved by 21.90%.Comment: 9 pages, 3 figure

Students' Family Support, Peer Relationships, and Learning Motivation and Teachers Fairness Have an Influence on the Victims of Bullying in Middle School of Hong Kong

This study aims to explore the effect of students’ family socio-economic status, gender, family support, learning motivation and peer relationships and teachers’ equity on the victims of school bullying in Hong Kong. Additionally, the model was analyzed by SEM. The participants in this study were 15 year-old middle school students living in Hong Kong. The data were collected from the PISA 2015 database and the valid number was 4856. The results indicating that family support, peer relationships, and teacher fairness have a negative influence on school bullying. Family support affects one’s risk of being bullied by influencing learning motivation. Peer relationship affects one’s risk of being bullied by influencing learning motivation. Teacher fairness affects one’s risk of being bullied by influencing learning motivation. &nbsp

Differential regulation of the activity of deleted in liver cancer 1 (DLC1) by tensins controls cell migration and transformation

The epithelial growth factor receptor plays an important role in cell migration and cancer metastasis, but the underlying molecular mechanism is not fully understood. We show here that differential regulation of the rhodopsin-GTPase-activating (Rho-GAP) activity of deleted in liver cancer 1 (DLC1) by tensin3 and COOH-terminal tensin-like protein (cten) controls EGF-driven cell migration and transformation. Tensin3 binds DLC1 through its actin-binding domain, a region that is missing in cten, and thereby releases an autoinhibitory interaction between the sterile alpha motif and Rho-GAP domains of DLC1. Consequently, tensin3, but not cten, promotes the activation of DLC1, which, in turn, leads to inactivation of RhoA and decreased cell migration. Depletion of endogenous tensin3, but not cten, augmented the formation of actin stress fibers and focal adhesions and enhanced cell motility. These effects were, however, ablated by an inhibitor of the Rho-associated protein kinase. Importantly, activation of DLC1 by tensin3 or its actin-binding domain drastically reduced the anchorage-independent growth of transformed cells. Our study therefore links dynamic regulation of tensin family members by EGF to Rho-GAP through DLC1 and suggests that the tensin-DLC1-RhoA signaling axis plays an important role in tumorigenesis and cancer metastasis, and may be explored for cancer intervention

CDA: A clustering degree based influential spreader identification algorithm in weighted complex network

Identifying the most influential spreaders in a weighted complex network is vital for optimizing utilization of the network structure and promoting the information propagation. Most existing algorithms focus on node centrality, which consider more connectivity than clustering. In this paper, a novel algorithm based on clustering degree algorithm (CDA) is proposed to identify the most influential spreaders in a weighted network. First, the weighted degree of a node is defined according to the node degree and strength. Then, based on the node weighted degree, the clustering degree of a node is calculated in respect to the network topological structure. Finally, the propagation capability of a node is achieved by accounting the clustering degree of the node and the contribution from its neighbors. In order to evaluate the performance of the proposed CDA algorithm, the susceptible-infected-recovered model is adopted to simulate the propagation process in real-world networks. The experiment results have showed that CDA is the most effective algorithm in terms of Kendall's tau coefficient and with the highest accuracy in influential spreader identification compared with other algorithms such as weighted degree centrality, weighted closeness centrality, evidential centrality, and evidential semilocal centrality

Transcriptional up-regulation of relaxin-3 by Nur77 attenuates β-adrenergic agonist-induced apoptosis in cardiomyocytes.

The relaxin family peptides have been shown to exert several beneficial effects on the heart, including anti-apoptosis, anti-fibrosis, and anti-hypertrophy activity. Understanding their regulation might provide new opportunities for therapeutic interventions, but the molecular mechanism(s) coordinating relaxin expression in the heart remain largely obscured. Previous work demonstrated a role for the orphan nuclear receptor Nur77 in regulating cardiomyocyte apoptosis. We therefore investigated Nur77 in the hopes of identifying novel relaxin regulators. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) data indicated that ectopic expression of orphan nuclear receptor Nur77 markedly increased the expression of latexin-3 (RLN3), but not relaxin-1 (RLN1), in neonatal rat ventricular cardiomyocytes (NRVMs). Furthermore, we found that the -adrenergic agonist isoproterenol (ISO) markedly stimulated RLN3 expression, and this stimulation was significantly attenuated in Nur77 knockdown cardiomyocytes and Nur77 knockout hearts. We showed that Nur77 significantly increased RLN3 promoter activity via specific binding to the RLN3 promoter, as demonstrated by electrophoretic mobility shift assay (EMSA) and chromatin immuno-precipitation (ChIP) assays. Furthermore, we found that Nur77 overexpression potently inhibited ISO-induced cardiomyocyte apoptosis, whereas this protective effect was significantly attenuated in RLN3 knockdown cardiomyocytes, suggesting that Nur77-induced RLN3 expression is an important mediator for the suppression of cardiomyocyte apoptosis. These findings show that Nur77 regulates RLN3 expression, therefore suppressing apoptosis in the heart, and suggest that activation of Nur77 may represent a useful therapeutic strategy for inhibition of cardiac fibrosis and heart failure. © 2018 You et al

Structure and superconductivity of Mg(B1-xCx)2 compounds

In this paper, we reported the structural properties and superconductivity of Mg(B1-xCx)2 compounds. Powder x-ray diffraction results indicate that the samples crystallize in a hexagonal AlB2-type structure. Due to the chemical activity of Mg powders, a small amount of MgO impurity phase was detected by x-ray diffraction. The lattice parameters decrease slightly with increasing carbon content. Magnetization measurements indicate the non-stoichiometry of MgB2 has no influence on the superconducting transition temperature and the transition temperature width. The addition of carbon results in a decrease of Tc and an increase in the superconducting transition width, implying the loss of superconductivity.Comment: PDF files, 5 pages,3 figures, Accepted by Chinese Physics on Feb. 26, 2001(in press