CunGui Cheng

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Name: 程存归; CunGui Cheng
Organization: Zhejiang Normal University
Department: Zhejiang Key Laboratory for Reactive Chemistry on Solid Surfaces, Department of Chemistry
Title:
Co-reporter:Jian Zhang, Mingchang Wu, Wei Lu, Shuaifeng Wang, Yan Zhang, Cungui Cheng, and Gangguo Zhu
The Journal of Organic Chemistry October 20, 2017 Volume 82(Issue 20) pp:11134-11134
Publication Date(Web):September 26, 2017
DOI:10.1021/acs.joc.7b02131
The direct access to 2-amino-5-homoallylfurans has been realized by a palladium-catalyzed tandem cycloisomerization/Heck-type coupling between homoallenyl amides and allyltrialkylsilanes, using a novel DDQ/MnO2 combination as the efficient oxidant. The reaction exclusively affords γ-allylation products in good to excellent yields with broad substrate scope under exceptionally mild reaction conditions. It represents one of the rare examples of the Pd-catalyzed intermolecular Heck-type coupling of allytrialkylsilanes terminated by β-silyl elimination, thus complementing traditional allylation methods because of the excellent γ-selectivity.
Co-reporter:Cungui Cheng, Jia Liu, Wenqing Cao, Renwei Zheng, Hong Wang, Changjiang Zhang
Vibrational Spectroscopy 2010 Volume 54(Issue 1) pp:50-55
Publication Date(Web):18 September 2010
DOI:10.1016/j.vibspec.2010.06.004
Horizontal attenuated total reflectance Fourier transform infrared spectroscopy (HATR-FTIR) technique is used to measure the FTIR spectra of Bidens frondosa L. seed and Bidens bipinnata L. seed. Because they belong to the same genus plants, their chemical components are very similar. In order to extract the difference between B. frondosa L. seed and B. bipinnata L. seed, discrete stationary wavelet transform (DSWT) is used to decompose the FTIR spectra of B. frondosa L. seed and B. bipinnata L. seed. Three main scales are selected as the feature extracting space in the DSWT domain. According to the distribution of FTIR spectra of B. frondosa L. seed and B. bipinnata L. seed, three feature regions are determined by the information content of substance construction in their FTIR spectra in the DSWT domain. Thus nine feature parameters form the feature vector. The feature vector is input to the probability neural network (PNN) to train so as to accurately classify the B. frondosa L. seed and B. bipinnata L. seed. Experimental results show that the accurate recognition rate between B. frondosa L. seed and B. bipinnata L. seed is in the range of 98–100% by using the proposed method.
Co-reporter:Cungui CHENG;Wei XIONG ;Yumei TIAN
Chinese Journal of Chemistry 2009 Volume 27( Issue 5) pp:911-914
Publication Date(Web):
DOI:10.1002/cjoc.200990154

Abstract

A feature extracting method based on wavelets for horizontal attenuated total reflectance Fourier transform infrared spectroscopy (HATR-FTIR) and the cancer classification using artificial neural network trained with back-propagation algorithm is presented. The FTIR data collected from 36 normal Sprague-dawley (SD) rats, 60 1,2-DMH-induced SD rats, and 44 second generation rats of those induced rats were first preprocessed. Then, 12 feature variants were extracted using continuous wavelet analysis. Based on BPNN classification, all spectra were classified into two categories: normal and abnormal ones. The accuracy values of identifying normal, dysplastic, early carcinoma, and advanced carcinoma were 100%, 94%, 97.5%, and 100%, respectively. This result indicated that FTIR with continuous wavelet transform (CWT) and the back-propagation neural network (BPNN) could effectively and easily diagnose colon cancer in its early stages.

Piperidine, 2,2,6,6-tetramethyl-1-(trifluoromethoxy)-
3-BUTENOIC ACID, 2,2-DIFLUORO-4,4-DIPHENYL-, ETHYL ESTER
METHANESULFONAMIDE, N-(PHENYLETHYNYL)-N-(PHENYLMETHYL)-
2-(Bromodifluoromethyl)-1,3-benzoxazole
Morpholine, 4-(bromodifluoroacetyl)-
Cyclohexanecarboxaldehyde, 2-(2-propenyl)-, (1R,2S)-rel-
1-Allyl-1H-pyrrole-2-carbaldehyde