Identifying vital edges in Chinese air route network via memetic algorithm

Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems

Bosonization of quantum sine-Gordon field with a boundary

Boundary operators and boundary ground states in sine-Gordon model with a fixed boundary condition are studied using bosonization and q-deformed oscillators.We also obtain the form-factors of this model.Comment: Latex 25page

A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks

In most networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a Mutual Attraction Model to characterize weighted evolving networks. By introducing the initial attractiveness $A$ and the general mechanism of mutual attraction (controlled by parameter $m$), the model can naturally reproduce scale-free distributions of degree, weight and strength, as found in many real systems. Simulation results are in consistent with theoretical predictions. Interestingly, we also obtain nontrivial clustering coefficient C and tunable degree assortativity r, depending on $m$ and A. Our weighted model appears as the first one that unifies the characterization of both assortative and disassortative weighted networks.Comment: 4 pages, 3 figure

Observation on intravitreal injection of ranibizumab combined with laser photocoagulation for the treatment of macular edema in BRVO

AIM: To observe the safety and efficacy of intravitreal injection of ranibizumab combined with laser photocoagulation for the treatment of macular edema in branch retinal vein occlusion(BRVO).<p>METHODS: According to fundus fluorescein angiography(FFA), 30 eyes of 30 patients with BRVO were randomized into three groups: group 1(10 eyes)received grid laser treatment alone, group 2 received a single dose of intravitreal injection of ranibizumab(0.05mL/0.5mg)followed by grid laser treatment on 7d following injection, while group 3(10 eyes)received three loading doses of intravitreal ranibizumab with 0.05mL/0.5mg for three times. At 1mo interval, grid laser treatment was performed after 7d of the 1st injection. After 6mo follow-up, the best-corrected visual acuity and optical coherence tomography(OCT)and central macular thickness were observed. <p>RESULTS:After 6mo, the visual acuity of patients were improved significantly. There was an average increase of 11 letters, 17 letters and 18 letters in group 1, 2, and 3, respectively, with the average decrease in OCT being 208.7μm, 312.9μm and 326.8μm, respectively, in these groups. Gain in visual acuity more than 3 lines was 1 case(10%)in group 1. There were 3 cases(30%)in group 2 and 4 cases(40%)in group 3.<p>CONCLUSION:Combined therapy is better than laser therapy alone. Single dose of intravitreal ranibizumab with grid laser for macular edema in BRVO seems to be effective

General Dynamics of Topology and Traffic on Weighted Technological Networks

For most technical networks, the interplay of dynamics, traffic and topology is assumed crucial to their evolution. In this paper, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general strength-coupling mechanism under which the traffic and topology mutually interact, the model gives power-law distributions of degree, weight and strength, as confirmed in many real networks. Particularly, depending on a parameter W that controls the total weight growth of the system, the nontrivial clustering coefficient C, degree assortativity coefficient r and degree-strength correlation are all in consistence with empirical evidences.Comment: 4 pages, 4 figure