Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

In this paper, we propose a very deep fully convolutional encoding-decoding framework for image restoration such as denoising and super-resolution. The network is composed of multiple layers of convolution and de-convolution operators, learning end-to-end mappings from corrupted images to the original ones. The convolutional layers act as the feature extractor, which capture the abstraction of image contents while eliminating noises/corruptions. De-convolutional layers are then used to recover the image details. We propose to symmetrically link convolutional and de-convolutional layers with skip-layer connections, with which the training converges much faster and attains a higher-quality local optimum. First, The skip connections allow the signal to be back-propagated to bottom layers directly, and thus tackles the problem of gradient vanishing, making training deep networks easier and achieving restoration performance gains consequently. Second, these skip connections pass image details from convolutional layers to de-convolutional layers, which is beneficial in recovering the original image. Significantly, with the large capacity, we can handle different levels of noises using a single model. Experimental results show that our network achieves better performance than all previously reported state-of-the-art methods.Comment: Accepted to Proc. Advances in Neural Information Processing Systems (NIPS'16). Content of the final version may be slightly different. Extended version is available at http://arxiv.org/abs/1606.0892

Neutron Density Distributions of Neutron-Rich Nuclei Studied with the Isobaric Yield Ratio Difference

The isobaric yield ratio difference (IBD) between two reactions of similar experimental setups is found to be sensitive to nuclear density differences between projectiles. In this article, the IBD probe is used to study the density variation in neutron-rich $^{48}$Ca. By adjusting diffuseness in the neutron density distribution, three different neutron density distributions of $^{48}$Ca are obtained. The yields of fragments in the 80$A$ MeV $^{40, 48}$Ca + $^{12}$C reactions are calculated by using a modified statistical abrasion-ablation model. It is found that the IBD results obtained from the prefragments are sensitive to the density distribution of the projectile, while the IBD results from the final fragments are less sensitive to the density distribution of the projectile.Comment: 3 figure

Description of a Sulfitobacter Strain and Its Extracellular Cyclodipeptides

A marine bacterium M44 was separated from 30 m deep seawater in the East China Sea (26° 28.3′ N 122° 29.0′ E) in 2006. 16S rDNA gene sequence comparison showed that the strain M44 was a member of the genus Sulfitobacter and highly similar to KMM 3554T. A series of experiments demonstrated that this strain M44 had many distinctive characteristics: its cells were gram-negative and mesophilic; its colonies were slightly yellowish, round, convex, and smooth; and it could grow at 10–28°C, pH 6.0–10.0, and in the presence of 0–12.5% (w/v) NaCl; the optimum growth conditions were 25°C and pH 7.0, and the optimum Na+ concentration was 2.5%. In addition, strain M44 contained 18 : 1 ω7c, 11 methyl 18 : 1 ω7c and 16 : 0 fatty acids as major fatty acids, and the genomic DNA G+C content was 58.04 mol%. According to our results of the secondary metabolites, six cyclodipeptides were isolated from the strain M44, which were Cyclo (Val-Leu), Cyclo (Phe-Val), Cyclo (Phe-Leu), Cyclo (Leu-Ile), Cyclo (Phe-Ile), and Cyclo (Trp-Pro). It is the first study of secondary metabolites isolated from this genus

Disruption of the Gene Encoding Endo-β-1, 4-Xylanase Affects the Growth and Virulence of Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Lib.) de Bary is a devastating fungal pathogen with worldwide distribution. S. sclerotiorum is a necrotrophic fungus that secretes many cell wall-degrading enzymes (CWDEs) that destroy plant’s cell-wall components. Functional analyses of the genes that encode CWEDs will help explain the mechanisms of growth and pathogenicity of S. sclerotiorum. Here, we isolated and characterized a gene SsXyl1 that encoded an endo-β-1, 4-xylanase in S. sclerotiorum. The SsXyl1 expression showed a slight increase during the development and germination stages of sclerotia and a dramatic increase during infection. The expression of SsXyl1 was induced by xylan. The SsXyl1 deletion strains produce aberrant sclerotia that could not germinate to form apothecia. The SsXyl1 deletion strains also lost virulence to the hosts. This study demonstrates the important roles of endo-β-1, 4-xylanase in the growth and virulence of S. sclerotiorum

Using inductive Energy Participation Ratio for Superconducting Quantum Chip Characterization

We have developed an inductive energy participation ratio (iEPR) method and a concise procedure for superconducting quantum chip layout simulation and verification that is increasingly indispensable in large-scale, fault-tolerant quantum computing. It can be utilized to extract the characteristic parameters and the bare Hamiltonian of the layout in an efficient way. In theory, iEPR sheds light on the deep-seated relationship between energy distribution and representation transformation. As a stirring application, we apply it to a typical quantum chip layout, obtaining all the crucial characteristic parameters in one step that would be extremely challenging through the existing methods. Our work is expected to significantly improve the simulation and verification techniques and takes an essential step toward quantum electronic design automation