Southwest University

About: Southwest University is a education organization based out in Chongqing, China. It is known for research contribution in the topics: Gene & Population. The organization has 29772 authors who have published 27755 publications receiving 409441 citations. The organization is also known as: Southwest University in Chongqing & SWU.

Facile Synthesis of Novel Networked Ultralong Cobalt Sulfide Nanotubes and Its Application in Supercapacitors

Abstract: Ultralong cobalt sulfide (CoS1.097) nanotube networks are synthesized by a simple one-step solvothermal method without any surfactant or template. A possible formation mechanism for the growth processes is proposed. Owing to the hollow structure and large specific area, the novel CoS1.097 materials present outstanding electrochemical properties. Electrochemical measurements for supercapacitors show that the as-prepared ultralong CoS1.097 nanotube networks exhibit high specific capacity, good capacity retention, and excellent Coulombic efficiency.

The complete mitochondrial genome of Chinese rare minnow, Gobiocypris rarus (Teleostei: Cypriniformes)

Abstract: The Chinese rare minnow, Gobiocypris rarus, which is endemic to China, is an attractive aquatic laboratory animal in China In the present study, the complete mitogenome sequence of G rarus has been determined using long polymerase chain reaction (PCR) method It was 16,601 bp in length and contained 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and a control region, the gene composition and order of which are similar to most other vertebrates Except for eight tRNA and ND6 genes, all other mitochondrial genes are encoded on the heavy strand The overall base composition of the heavy strand is 295% A, 276% T, 257% C, and 172% G, with a slight AT bias of 571% There are 10 regions of gene overlap totaling 27 bp and 13 intergenic spacer regions totaling 63 bp The mitogenome sequence of G rarus could contribute to a better solution of its phylogenetic position within cyprinid fishes based on the whole mitogenomic data

Identifying influential nodes in complex networks based on the inverse-square law

Abstract: How to identify influential nodes in complex networks continues to be an open issue. A number of centrality measures have been presented to address this problem. However, these studies focus only on a centrality measure and each centrality measure has its own shortcomings and limitations. To solve problems above, in this paper, a novel method is proposed to identify influential nodes based on the inverse-square law. The mutual attraction between different nodes has been defined in complex network, which is inversely proportional to the square of the distance between two nodes. Then, the definition of intensity of node in a complex network is proposed and described as the sum of attraction between a pair of nodes in the network. The ranking method is presented based on the intensity of node, which can be considered as the influence of the node. In order to illustrate the effectiveness of the proposed method, several experiments are conducted to identify vital nodes simulations on four real networks, and the superiority of the proposed method can be demonstrated by the results of comparison experiments.