http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Haitao Guo,Zhenyu Wang,Han Pan,Xin Li,Li Chen,Weili Rao,Yuan Gao,Dequan Zhang 한국식품과학회 2014 Food Science and Biotechnology Vol.23 No.3
Different amounts of the potent mutagenic and/or carcinogenic heterocyclic aromatic amines (HAAs) areformed in muscle-based foods under different cookingmethods. HAAs (9 varieties) in lamb patties cooked usingtraditional Chinese cooking methods (roasting, frying, panfrying,and stewing in seasonings) were investigated. Thetotal HAAs contents in roasted, fried, pan-fried, and stewedpatties were 4.39-123.15 ng/g, 3.59-43.24 ng/g, 0.71-10.05ng/g, and 51.07-120.32 ng/g, respectively. Amounts of HAAsincreased as cooking time increased. 2-amino-1-methyl-6-phenylimidazo [4,5-b] pyridine (PhIP) was the dominantHAAs in deep roasted and fried samples, while 1-methyl-9H-pyrido [3,4-b] indole (Harman) and 9H-pyrido [3,4-b]indole (Norharman) were the main HAAs in pan-fried andstewed samples. Types and contents of HAAs formed atdifferent cooking times using different methods are unique. Stewing in seasoning generated a higher HAAs contentthan the high-temperature cooking methods roasting,frying, and pan-frying.
Chen Mingna,Zhang Jiancheng,Liu Hu,Wang Mian,Pan LiJuan,Chen Na,Wang Tong,Jing Yu,Chi Xiaoyuan,Du Binghai 한국미생물학회 2020 The journal of microbiology Vol.58 No.7
Balancing soil microbial diversity and abundance is critical to sustaining soil health, and understanding the dynamics of soil microbes in a monocropping system can help determine how continuous monocropping practices induce soil sickness mediated by microorganisms. This study used previously constructed gradient continuous monocropping plots and four varieties with different monocropping responses were investigated. The feedback responses of their soil fungal communities to short-term and long-term continuous monocropping were tracked using high-throughput sequencing techniques. The analyses indicated that soil samples from 1 and 2 year monocropped plots were grouped into one class, and samples from the 11 and 12 year plots were grouped into another, regardless of variety. At the species level, the F. solani, Fusarium oxysporum, Neocosmospora striata, Acrophialophora levis, Aspergillus niger, Aspergillus corrugatus, Thielavia hyrcaniae, Emericellopsis minima, and Scedosporium aurantiacum taxa showed significantly increased abundances in the long-term monocropping libraries compared to the short-term cropping libraries. In contrast, Talaromyces flavus, Talaromyces purpureogenus, Mortierella alpina, Paranamyces uniporus, and Volutella citrinella decreased in the long-term monocropping libraries compared to the shortterm libraries. This study, combined with our previous study, showed that fungal community structure was significantly affected by the length of the monocropping period, but peanut variety and growth stages were less important. The increase in pathogen abundances and the decrease in beneficial fungi abundances seem to be the main cause for the yield decline and poor growth of long-term monocultured peanut. Simplification of fungal community diversity could also contribute to peanut soil sickness under long-term monocropping. Additionally, the different responses of peanut varieties to monocropping may be related to variations in their microbial community structure.
Robust Segmentation for Low Quality Cell Images from Blood and Bone Marrow
Chen Pan,Yi Fang,Xiang-guo Yan,Chong-xun Zheng 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.5
Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.
Chen, Jian,Chen, Jie,Ding, Hong-Yan,Pan, Qin-Shi,Hong, Wan-Dong,Xu, Gang,Yu, Fang-You,Wang, Yu-Min Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.12
Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.
Chen, Jie,Pan, Qin-Shi,Hong, Wan-Dong,Pan, Jingye,Zhang, Wen-Hui,Xu, Gang,Wang, Yu-Min Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.13
Statistical methods to analyze and predict the related risk factors of nosocomial infection in lung cancer patients are various, but the results are inconsistent. A total of 609 patients with lung cancer were enrolled to allow factor comparison using Student's t-test or the Mann-Whitney test or the Chi-square test. Variables that were significantly related to the presence of nosocomial infection were selected as candidates for input into the final ANN model. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of nosocomial infection from lung cancer in this entire study population was 20.1% (165/609), nosocomial infections occurring in sputum specimens (85.5%), followed by blood (6.73%), urine (6.0%) and pleural effusions (1.82%). It was shown that long term hospitalization (${\geq}22days$, P= 0.000), poor clinical stage (IIIb and IV stage, P=0.002), older age (${\geq}61days$ old, P=0.023), and use the hormones were linked to nosocomial infection and the ANN model consisted of these four factors. The artificial neural network model with variables consisting of age, clinical stage, time of hospitalization, and use of hormones should be useful for predicting nosocomial infection in lung cancer cases.
Kinetics of Nitrogen Absorption in Molten AISI 316 Stainless Steel During Immersion Nitrogen Blowing
Chen Jian-Bin,Chen Qi-Zhong,Chen Zhao-Ping,Jiang Zhou-Hua,Huang Zong-Ze,Pan Jia-Qi 대한금속·재료학회 2012 METALS AND MATERIALS International Vol.18 No.1
Nitrogen absorption in molten metal for stainless steel AISI316 has been investigated by immersion nitrogen blowing through an immersed alumina nozzle with an internal diameter of 3 mm. Based on these experimental data, some kinetic parameters of nitrogen absorption, such as reaction order, rate constant and apparent activation energy of nitrogen absorption reaction, have been obtained. Effect of stirring by immersion nitrogen blowing through an immersed alumina nozzle on nitrogen absorption reaction has been observed. Results show the following: (1) Nitrogen absorption reaction is the −1.5th order reaction. The rate constant N is of the order of 10−5wt%2.5·min −1. Nitrogen absorption reaction for AISI 316 has negative apparent activation energy of −92.40 kJ·mol −1. This indicates that the nitrogen absorption reaction has a complex and multistep reaction mechanism. (2) The rate of nitrogen absorption reaction in molten stainless steel is mixture control by the adsorption of monatomic nitrogen on the surface of molten stainless steel and mass transfer in molten metal. (3) A rate equation of nitrogen absorption reaction has been derived based on a mixed control mechanism by both the -1st order nitrogen absorption reaction and mass transfer in molten metal.
Pan Chen,Jihua Zhai,Wei Sun,Yue-hua Hu,Zhigang Yin,Xiangsheng Lai 한국공업화학회 2017 Journal of Industrial and Engineering Chemistry Vol.53 No.-
In order to get further understanding of lead ions adsorption onto ilmenite surface, zeta potential analysis, adsorption density calculation, FT-IR and XPS analysis were employed. The results showed that the adsorption of lead ions onto ilmenite surface was a chemically dominating process. Lead species could interact with iron-hydroxyl complex compounds to form a Fe–O–Pb complex. The hydrophobic complex of Pb(OL)2 was also observed. Iron and adsorbed lead ions on ilmenite surface served as the main active-sites via chemisorption with oleate species. Introducing lead ions, as a surface modification means, can efficiently improve ilmenite flotability.