An aerobic, Gram-stain-negative, rod-shaped bacterium with agellum, designated L22 T , was isolated from freshwater of Hulun Lake, Inner Mongolia, China. The organism was found to grow optimally at 30 ℃ in medium containing 0-0.75%(w/v) NaCl at pH 7.5. The major fatty acid identi ed was summed feature 8 (C 16:1 ω7c). The dominant polar lipids were phosphomonoester, phosphatidylethanolamine, phosphatidylglycerol and phosphatidylcholine. The main ubiquinone was Q-10. The G + C content of genomic DNA was 69.8 mol%. The 16S rRNA gene sequences indicated that strain L22 T was a liated with the genus Methylobrevis within the family Pleomorphomonadaceae, being most closely related to M. pamukkalensis JCM 30229 T with 95.9% sequences similarity. Based on taxonomic results in this study, we proposed that strain L22 T was placed into a novel species in the genus Methylobrevis of the family Pleomorphomonadaceae, for which the name Methylobrevis albus sp. nov. is proposed. The type strain is L22 T (= KCTC 72858 T = MCCC 1H00432 T ).
An aerobic, Gram-stain-negative, rod-shaped bacterium with flagellum, designated L22T, was isolated from freshwater of Hulun Lake, Inner Mongolia, China. The organism was found to grow optimally at 30 ℃ in medium containing 0-0.75%(w/v) NaCl at pH 7.5. The major fatty acid identified was summed feature 8 (C16:1ω7c). The dominant polar lipids were phosphomonoester, phosphatidylethanolamine, phosphatidylglycerol and phosphatidylcholine. The main ubiquinone was Q-10. The G + C content of genomic DNA was 69.8 mol%. The 16S rRNA gene sequences indicated that strain L22T was affiliated with the genus Methylobrevis within the family Pleomorphomonadaceae, being most closely related to M. pamukkalensis JCM 30229T with 95.9% sequences similarity. Based on taxonomic results in this study, we proposed that strain L22T was placed into a novel species in the genus Methylobrevis of the family Pleomorphomonadaceae, for which the name Methylobrevis albus sp. nov. is proposed. The type strain is L22T (= KCTC 72858T = MCCC 1H00432T).
With the continuous development and advancement of computer technology, big data guarantees the establishment of an urban intelligent transportation system, a solid environmental basis to reform its application, and the construction of a deeply integrated data mechanism for big data-driven traffic management. This review paper briefly elaborates on the basic characteristics and sources of traffic big data as well as expound on the problems and application mechanisms of big data in intelligent transportation systems.
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