Microbial diversity and biogenic methane potential of a thermogenic-gas coal mine

The microbial communities and biogenic methane potential of a gas coal mine were investigated by cultivation-independent and cultivation-dependent approaches. Stable carbon isotopic analysis indicated that in situ methane in the coal mine was dominantly of a thermogenic origin. However, a high level of diversity of bacteria and methanogens that were present in the coal mine was revealed by 454 pyrosequencing, and included various fermentative bacteria in the phyla of Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria, and acetotrophic, hydrogenotrophic, and methylotrophic methanogens. Methane was produced in enrichments of mine water samples supplemented with acetate under laboratory conditions. The microbial flora obtained from the enrichments could stimulate methane formation from coal samples. 16S rRNA gene clone library analysis indicated that the microbial community from coal cultivation samples supplemented with the enriched microbial consortium was dominated by the anaerobic fermentative Clostridiales and facultative acetoclastic Methanosarcina. This study suggests that the biogenic methane potential in the thermogenic-gas coal mine could be stimulated by the indigenous microorganisms

Superfluidity and Stabilities of a Bose-Einstein condensate with periodically modulated interatomic interaction

We study theoretically the superfluidity and stability of a Bose-Einstein condensate (BEC) whose interatomic scattering length is periodically modulated with optical Feshbach resonance. Our numerical study finds that the properties of this periodic BEC are strongly influenced by the modulation strength. When the modulation strength is small, only the Bloch waves close to the Brillouin zone edge suffer both Landau and dynamical instabilities. When the modulation strength is strong enough, all Bloch waves become dynamically unstable. In other words, the periodic BEC loses its superfluidity completely.Comment: 5 pages, 5 figure

Segmentation of ultrasound images of thyroid nodule for assisting fine needle aspiration cytology

The incidence of thyroid nodule is very high and generally increases with the age. Thyroid nodule may presage the emergence of thyroid cancer. The thyroid nodule can be completely cured if detected early. Fine needle aspiration cytology is a recognized early diagnosis method of thyroid nodule. There are still some limitations in the fine needle aspiration cytology, and the ultrasound diagnosis of thyroid nodule has become the first choice for auxiliary examination of thyroid nodular disease. If we could combine medical imaging technology and fine needle aspiration cytology, the diagnostic rate of thyroid nodule would be improved significantly. The properties of ultrasound will degrade the image quality, which makes it difficult to recognize the edges for physicians. Image segmentation technique based on graph theory has become a research hotspot at present. Normalized cut (Ncut) is a representative one, which is suitable for segmentation of feature parts of medical image. However, how to solve the normalized cut has become a problem, which needs large memory capacity and heavy calculation of weight matrix. It always generates over segmentation or less segmentation which leads to inaccurate in the segmentation. The speckle noise in B ultrasound image of thyroid tumor makes the quality of the image deteriorate. In the light of this characteristic, we combine the anisotropic diffusion model with the normalized cut in this paper. After the enhancement of anisotropic diffusion model, it removes the noise in the B ultrasound image while preserves the important edges and local details. This reduces the amount of computation in constructing the weight matrix of the improved normalized cut and improves the accuracy of the final segmentation results. The feasibility of the method is proved by the experimental results.Comment: 15pages,13figure