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The Nature of Acid-Catalyzed Acetalization Reaction of 1,2-Propylene Glycol and Acetaldehyde
( Chen Cheng ),( Hui Chen ),( Xia Li ),( Jian Li Hu ),( Bao Chen Liang ) 한국화학공학회 2015 Korean Chemical Engineering Research(HWAHAK KONGHA Vol.53 No.4
We investigated catalytic activity of ion-exchange resins in acetalization of 1,2-propylene glycol with acetaldehyde. The impacts of reaction variables, such as temperature, reaction time, catalyst loading and feedstock composition, on the conversion of 1,2-propylene glycol were measured. The life of the catalyst was also studied. Furthermore, the reaction kinetics of 1,2-propylene glycol acetalization was studied. It was found that reaction rate followed the firstorder kinetics to acetaldehyde and 1,2-propylene glycol, respectively. Therefore, overall acetalization reaction should follow the second-order reaction kinetics, expressed as r=kC pile{nA#A} C pile{nB#B} =19.74 {-6650} over {T} C pile{1#A} C pile{1#B}.
Detection and Identification of Defects in Transparent Film
Bao-yuan Chen,Chao Zheng,Zhong-xiang Sun,Xiao-yang Yu 보안공학연구지원센터 2015 International Journal of Future Generation Communi Vol.8 No.4
Biaxially oriented polyester film (BOPET) defect is an important factor affecting the quality of the film. In view of identification of defects in the conventional film production process, this mathod resulted in the identification of defects inaccurate. and low labor efficiency and machine vision recognition on identification of specific defect. This paper presents a LVQ neural network-based BOPET film of defects detection and identification methods. In this algorithm, the film images were processed and the outlines of the membrane defects were obtained. Through extracting the aspect ration, circularity, complexity and elongation , projection histogram central moment and so on, the characteristic values of membrane defects, which from the image of film images after image processing, and then input to the defects recognition system based on LVQ neural network that had been trained, in order to achieve the film defects identification, classification and localization. Through the study of features of the defects in BOPET and extracted some quantities as character input of the LVQ neural network, then input some characteristic values as training value into the LVQ neural network to achieve the learning and prediction purpose, and the LVQ neural network was designed. The experiments show that, the proposed method can meet the requirements analysis of air defects in transparent film.
Dose-Dependent Associations between Wine Drinking and Breast Cancer Risk - Meta-Analysis Findings
Chen, Jia-Yan,Zhu, Hong-Cheng,Guo, Qing,Shu, Zheng,Bao, Xu-Hui,Sun, Feng,Qin, Qin,Yang, Xi,Zhang, Chi,Cheng, Hong-Yan,Sun, Xin-Chen Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.3
Purpose: To investigate any potential association between wine and breast cancer risk. Materials and Methods: We quantitatively assessed associations by conducting a meta-analysis based on evidence from observational studies. In May 2014, we performed electronic searches in PubMed, EmBase and the Cochrane Library to identify studies examining the effect of wine drinking on breast cancer incidence. The relative risk (RR) or odds ratio (OR) were used to measure any such association. Results: The analysis was further stratified by confounding factors that could influence the results. A total of twenty-six studies (eight case-control and eighteen cohort studies) involving 21,149 cases were included in our meta-analysis. Our study demonstrated that wine drinking was associated with breast cancer risk. A 36% increase in breast cancer risk was observed across overall studies based on the highest versus lowest model, with a combined RR of 1.0059 (95%CI 0.97-1.05) in dose-response analysis. However, 5 g/d ethanol from wine seemed to have protective value from our non-linear model. Conclusions: Our findings indicate that wine drinking is associated with breast cancer risk in a dose-dependent manner. High consumption of wine contributes to breast cancer risk with protection exerted by low doses. Further investigations are needed for clarification.
Molecular organization of the B mating type locus of a Lentinula edodes monokaryon strain SUP2
Bao Da-Peng Chen Ming-Jie,Song Wen-Hua,Song Chun-yan,Zhang Mei-Yan,Chen Xiang,Lin Nan 한국버섯학회 2010 한국버섯학회지 Vol.8 No.4
Lentinula edodes is an important cultivated mushroom in China. The development of Lentinula edodes production promotes more studies on it. In our previous work, degenerate PCR and chromosome walking technologies were used to obtain one pheromone receptor gene and one pheromone precursor gene from Lentinula edodes. In this study, four pairs of specific primers were designed according to the whole genome sequencing of the protoplast monokaryon of Lentinula edodes strain 135, to amplify STE3-like pheromone receptor gene and its flanking conserved genes in the protoplast monokaryon strain SUP2 derived from Lentinula edodes strain Suxiang and 33655bp DNA sequence was obtained. By BlastX search, seven putative genes were identified, and three of them are pheromone receptor encoded genes. Furthermore, near to two pheromone receptor genes, four genes encoding proteins with conserved motifs of pheromone precursors were found. This study firstly reveals the molecular organization of the B mating type locus of Lentinula edodes.
Removal of the Glycosylation of Prion Protein Provokes Apoptosis in SF126
Chen, Lan,Yang, Yang,Han, Jun,Zhang, Bao-Yun,Zhao, Lin,Nie, Kai,Wang, Xiao-Fan,Li, Feng,Gao, Chen,Dong, Xiao-Ping,Xu, Cai-Min Korean Society for Biochemistry and Molecular Biol 2007 Journal of biochemistry and molecular biology Vol.40 No.5
Although the function of cellular prion protein (PrP$^C$) and the pathogenesis of prion diseases have been widely described, the mechanisms are not fully clarified. In this study, increases of the portion of non-glycosylated prion protein deposited in the hamster brains infected with scrapie strain 263K were described. To elucidate the pathological role of glycosylation profile of PrP, wild type human PrP (HuPrP) and two genetic engineering generated non-glycosylated PrP mutants (N181Q/N197Q and T183A/T199A) were transiently expressed in human astrocytoma cell line SF126. The results revealed that expressions of non-glycosylated PrP induced significantly more apoptosis cells than that of wild type PrP. It illustrated that Bcl-2 proteins might be involved in the apoptosis pathway of non-glycosylated PrPs. Our data highlights that removal of glycosylation of prion protein provokes cells apoptosis.
Bao, Chen,Sun, Yongduo,Wu, Yuanjun,Wang, Kaiqing,Wang, Li,He, Guangwei Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.6
By using miniature SENB specimens, the fracture properties of the materials in the region of welded metal, 321 stainless steel heat affected zone, 690 alloy heat affected zone of 321/690 dissimilar metal girth welded joints were tested. Both the J-resistance curves and critical fracture toughness of the three different materials are affected by the crack size because of the effect of crack tip constraint. Groups of constraint corrected J-resistance curves of the three materials are obtained according to J-Q-M approach. The welded metals exhibit the best fracture resistance but the worst fracture resistance is observed in the material of 690 alloy heat affected zone.
Voice Activity Detection Algorithm based on Improved Radial Basis Function Neural Network
Bao-yuan Chen,Ya-qiong Lan,Jing-yang Liu,Zi-he Li,Xiao-yang Yu 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5
Voice activity detection (VAD) is the key of voice recognition, voice synthesis and speech-sound enhancement.For the sake of improve the accuracy and robustness of speech endpoint detection system. Combining the advantages of adaptive genetic algorithm (AGA) and improved radial basis function network (RBF) defects in existing learning methods. This paper presents a comprehensive detection method-- Adaptive genetic algorithm radial basis function network. This method uses adaptive genetic algorithm to simultaneously optimize the center, the width and the structure of RBF network. The method using wavelet analysis to extract the characteristics of the speech signal, use them as an input amount to the radial basis function networks. Establish voice detection system model, this method enhance the accuracy of the detection system and has better robustness.