Aiming at the problems such as low reconstruction efficiency,fuzzy texture details,and difficult convergence of reconstruction network face image super-resolution reconstruction algorithms,a new super-resolution recon...Aiming at the problems such as low reconstruction efficiency,fuzzy texture details,and difficult convergence of reconstruction network face image super-resolution reconstruction algorithms,a new super-resolution reconstruction algorithm with residual concern was proposed.Firstly,to solve the influence of redundant and invalid information about the face image super-resolution reconstruction network,an attention mechanism was introduced into the feature extraction module of the network,which improved the feature utilization rate of the overall network.Secondly,to alleviate the problem of gradient disappearance,the adaptive residual was introduced into the network to make the network model easier to converge during training,and features were supplemented according to the needs during training.The experimental results showed that the proposed algorithm had better reconstruction performance,more facial details,and clearer texture in the reconstructed face image than the comparison algorithm.In objective evaluation,the proposed algorithm's peak signalto-noise ratio and structural similarity were also better than other algorithms.展开更多
We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against targe...We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against target attack relatively. Furthermore, duplication-divergence network is broken down more quickly than its counterpart BA network under target attack. Such result is consistent with the fact of WWW and Internet networks under target attack. So duplication-divergence model is a more realistic one for us to investigate the characteristics of the world wide web in future. We also observe that the exponent γ of degree distribution and average degree are important parameters of networks, reflecting the performance of networks under target attack. Our results are helpful to the research on the security of network.展开更多
Myasthenia gravis （MG） is an autoimmune neuromuscular junction disease mediated by antibodies against the acetylcholine receptor （AChR）. The etiology and immunopathogenesis of MG remain unclear. Recent research ha...Myasthenia gravis （MG） is an autoimmune neuromuscular junction disease mediated by antibodies against the acetylcholine receptor （AChR）. The etiology and immunopathogenesis of MG remain unclear. Recent research has shown the involvement of autoantibodies, lymphocytes, cytokines and chemokines, in the pathogenesis of MG. Systematic factors are also demonstrated, such as inheritance and endocrine. This review indicates the research development in immunopathogenesis of MG.展开更多
基金supported by National Natural Science Foundation of China(No.62063014)。
文摘Aiming at the problems such as low reconstruction efficiency,fuzzy texture details,and difficult convergence of reconstruction network face image super-resolution reconstruction algorithms,a new super-resolution reconstruction algorithm with residual concern was proposed.Firstly,to solve the influence of redundant and invalid information about the face image super-resolution reconstruction network,an attention mechanism was introduced into the feature extraction module of the network,which improved the feature utilization rate of the overall network.Secondly,to alleviate the problem of gradient disappearance,the adaptive residual was introduced into the network to make the network model easier to converge during training,and features were supplemented according to the needs during training.The experimental results showed that the proposed algorithm had better reconstruction performance,more facial details,and clearer texture in the reconstructed face image than the comparison algorithm.In objective evaluation,the proposed algorithm's peak signalto-noise ratio and structural similarity were also better than other algorithms.
基金The project supported by National Natural Science Foundation of China under Grant No. 10375022Acknowledgment We thank Prof. Tang Yi for helpful discussions.
文摘We study the attack vulnerability of network with duplication-divergence mechanism. Numerical results have shown that the duplication-divergence network with larger retention probability a is more robust against target attack relatively. Furthermore, duplication-divergence network is broken down more quickly than its counterpart BA network under target attack. Such result is consistent with the fact of WWW and Internet networks under target attack. So duplication-divergence model is a more realistic one for us to investigate the characteristics of the world wide web in future. We also observe that the exponent γ of degree distribution and average degree are important parameters of networks, reflecting the performance of networks under target attack. Our results are helpful to the research on the security of network.
文摘Myasthenia gravis （MG） is an autoimmune neuromuscular junction disease mediated by antibodies against the acetylcholine receptor （AChR）. The etiology and immunopathogenesis of MG remain unclear. Recent research has shown the involvement of autoantibodies, lymphocytes, cytokines and chemokines, in the pathogenesis of MG. Systematic factors are also demonstrated, such as inheritance and endocrine. This review indicates the research development in immunopathogenesis of MG.
