Entropy Optimization of Scale-Free Networks Robustness to Random Failures

Many networks are characterized by highly heterogeneous distributions of links, which are called scale-free networks and the degree distributions follow $p(k)\sim ck^{-\alpha}$. We study the robustness of scale-free networks to random failures from the character of their heterogeneity. Entropy of the degree distribution can be an average measure of a network's heterogeneity. Optimization of scale-free network robustness to random failures with average connectivity constant is equivalent to maximize the entropy of the degree distribution. By examining the relationship of entropy of the degree distribution, scaling exponent and the minimal connectivity, we get the optimal design of scale-free network to random failures. We conclude that entropy of the degree distribution is an effective measure of network's resilience to random failures.Comment: 9 pages, 5 figures, accepted by Physica

Optimization of network structure to random failures

Network's resilience to the malfunction of its components has been of great concern. The goal of this work is to determine the network design guidelines, which maximizes the network efficiency while keeping the cost of the network (that is the average connectivity) constant. With a global optimization method, memory tabu search (MTS), we get the optimal network structure with the approximately best efficiency. We analyze the statistical characters of the network and find that a network with a small quantity of hub nodes, high degree of clustering may be much more resilient to perturbations than a random network and the optimal network is one kind of highly heterogeneous networks. The results strongly suggest that networks with higher efficiency are more robust to random failures. In addition, we propose a simple model to describe the statistical properties of the optimal network and investigate the synchronizability of this model.Comment: 11 pages, 6 figures, accepted by Physica

Relationship between occupational stress and job burnout among rural-to-urban migrant workers in Dongguan, China: a cross-sectional study

Objectives: In China, there have been an increasing number of migrant workers from rural to urban areas, and migrant workers have the highest incidence of occupational diseases. However, few studies have examined the impact of occupational stress on job burnout in these migrant workers. This study aimed to investigate the relationship between occupational stress and job burnout among migrant workers. Design: This study used a cross-sectional survey. Setting: This investigation was conducted in Dongguan city, Guangdong Province, China. Participants: 3806 migrant workers, aged 18–60 years, were randomly selected using multistage sampling procedures. Primary and secondary outcome measures: Multistage sampling procedures were used to examine demographic characteristics, behaviour customs and jobrelated data. Hierarchical linear regression and logistic regression models were constructed to explore the relationship between occupational stress and burnout. Results: Demographics, behaviour customs and jobrelated characteristics significantly affected on burnout. After adjusting for the control variable, a high level of emotional exhaustion was associated with high role overload, high role insufficiency, high role boundary, high physical environment, high psychological strain, high physical strain, low role ambiguity, low responsibility and low vocational strain. A high level of depersonalisation was associated with high role overload, high role ambiguity, high role boundary, high interpersonal strain, high recreation, low physical environment and low social support. A low level of personal accomplishment was associated with high role boundary, high role insufficiency, low responsibility, low social support, low physical environment, low self-care and low interpersonal strain. Compared to the personal resources, the job strain and personal strain were more likely to explain the burnout of rural-to-urban migrant workers in our study. Conclusions: The migrant workers have increased job burnouts in relation to occupational stress. Relieving occupational stress and maintaining an appropriate quantity and quality of work could be important measures for preventing job burnout among these workers

Entropy Optimization of Scale-Free Networks Robustness to Random Failures, Physica A 363

Many networks are characterized by highly heterogeneous distributions of links, which are called scale-free networks and the degree distributions follow p(k) ∼ ck −α. We study the robustness of scale-free networks to random failures from the character of their heterogeneity. Entropy of the degree distribution can be an average measure of a network’s heterogeneity. Optimization of scale-free network robustness to random failures with average connectivity constant is equivalent to maximize the entropy of the degree distribution. By examining the relationship of the entropy of the degree distribution, scaling exponent and the minimal connectivity, we get the optimal design of scale-free network to random failures. We conclude that the entropy of the degree distribution is an effective measure of network’s resilience to random failures. Key words: scale-free networks; information theory; entropy; random failures PACS: 89.75.-k; 89.75.Fb