http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Zhilei Sun (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
Microbial Communities in Semi-consolidated Carbonate Sediments of the Southwest Indian Ridge
Jiwei Li,Xiaotong Peng,Huaiyang Zhou,Jiangtao Li,Zhilei Sun,Shun Chen 한국미생물학회 2014 The journal of microbiology Vol.52 No.2
White semi-consolidated carbonate sediments attached toblack ferromanganese oxide films were collected approximately50 km west of a newly discovered hydrothermal fieldnear the Southwest Indian Ridge (SWIR). The biodiversity ofthe prokaryotic communities within the field was examinedusing clone library-based culture-independent analysis ofthe exterior black oxides and the interior white carbonates. Subsequent 16S rRNA gene analysis suggested that Gammaproteobacteria,Acidobacteria, and Thaumarchaeota membersdominated the bacterial and archaeal clone libraries. To further characterize the metabolic processes within themicrobial community, analyses of the amoA (coding the alphasubunit of the ammonia monooxygenase for Archaea)and aprA (coding the alpha subunit of the dissimilatory adenosine-5 -phosphosulfate reductase for the sulfate-reducingand sulfur-oxidizing prokaryotes) functional genes wereconducted. The functional gene analysis results suggestedthat Thaumarchaeota and Alphaproteobacteria memberswere the potential players that participated in N and S cyclesin this marine carbonate sedimentary environment. Thispaper is the first to describe the microbial communities andtheir potential metabolic pathways within the semi-consolidatedcarbonate sediments of the SWIR.
-
( Yiming Kou ),( Mingming Wan ),( Wei Shi ),( Jie Liu ),( Zhilei Zhao ),( Yongqing Xu ),( Wei Wei ),( Bo Sun ),( Feng Gao ),( Linjun Cai ),( Chunlai Jiang ) 한국미생물생명공학회(구 한국산업미생물학회) 2018 Journal of microbiology and biotechnology Vol.28 No.6
Tuberculosis (TB) remains a serious health issue around the word. Adenovirus (Ad)-based vaccine and modified vaccinia virus Ankara (MVA)-based vaccine have emerged as two of the most promising immunization candidates over the past few years. However, the performance of the homologous and heterologous prime-boost immunization regimens of these two viral vector-based vaccines remains unclear. In the present study, we constructed recombinant Ad and MVA expressing an Ag85B-TB10.4 fusion protein (AdH4 and MVAH4) and evaluated the impact of their different immunization regimens on the humoral and cellular immune responses. We found that the viral vector-based vaccines could generate significantly higher levels of antigen-specific antibodies, IFN-γ-producing splenocytes, CD69<sup>+</sup>CD8<sup>+</sup> T cells, and IFN-γ secretion when compared with bacillus Calmette-Guerin (BCG) in a mouse model. AdH4-containing immunization regimens (AdH4-AdH4, AdH4-MVAH4, and MVAH4-AdH4) induced significantly stronger antibody responses, much more IFN-γ-producing splenocytes and CD69<sup>+</sup>CD8<sup>+</sup> T cells, and higher levels of IFN-γ secretion when compared with the MVAH4-MVAH4 immunization regimen. The number of IFN-γ-producing splenocytes sensitive to CD8<sup>+</sup> T-cell restricted peptides of Ag85B (9-1p and 9-2p) and Th1-related cytokines (IFN-γ and TNF-α) in the AdH4-MVAH4 heterologous prime-boost regimen immunization group was significantly higher than that in the other viral vector-based vaccine- and BCG-immunized groups, respectively. These results indicate that an immunization regimen involving AdH4 may have a higher capacity to induce humoral and cellular immune responses against TB in mice than that by regimens containing BCG or MVAH4 alone, and the AdH4-MVAH4 prime-boost regimen may generate an ideal protective effect.
-
Zhi Lei,Qinsong Zhu,Yuqing Zhou,Bintao Sun,Weifang Sun,Xiaoming Pan 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.8 No.3
Tools are the most vulnerable components in milling processes conducted using numerical control milling machines, and their wear condition directly influences work-product quality and operational safety. As such, tool wear estimation is an essential component of NC milling operations. This study addresses this issue by proposing an extreme learning machine (ELM) method enhanced by a hybrid genetic algorithm and particle swarm optimization (GAPSO) approach for conducting tool wear estimation based on workpiece vibration signals. Here, a few feature parameters in the time, frequency, and time–frequency (Ensemble empirical mode decomposition, EEMD) domains of the workpiece vibration signals are extracted as the input of the ELM model. Then, the initialized weights and thresholds of the ELM model are optimized based on the GAPSO approach with training dataset. Finally, tool wear is estimated using the optimized ELM model with testing dataset. The effectiveness of the proposed method is verified by its application to vibration signals collected from two milling tool wear experiments (an open-access benchmark dataset and a milling tool wear experiment) by comparison to the ELM, GA-ELM, and PSO-ELM methods. The results indicate that the estimation accuracy and optimization efficiency of the proposed method outperforms that of other three methods.
ScienceON
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
