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Chaihu-shugan-san, as a traditional Chinese herbal formula, is composed of seven different herbs. This medicine can treat cancer due to its antioxidant compounds. In this study, the effect of Chaihu-shugan-san was considered on cytotoxicity induction and PDGF gene expression in cervical cancer cell line HeLa at different concentrations and at different times, by the MTT method. Paclitaxel + cisplatin were used as a control in this study. The expression of the PDGF gene was quantitatively evaluated in treated cells by real-time PCR, and a generalized linear model was used to evaluate the effect of the medicine, and Duncan's multiple range tests were used to evaluate the data. The results of the MTT test showed that Chaihu-shugan-san had antitumor properties in different concentrations, but there was a significant difference between this medicine and paclitaxel +cisplatin. Also, examination of gene expression showed that this medicine reduced the expression of the PDGF gene in the HeLa cancer cell line (P ? 0.04). Therefore, Chaihu-shugan-san could be suggested as an effective factor in preventing the growth of cervical cancer cells and controlling angiogenic factors that play an important role in the metastasis of cancerous tumors.

The effective feature mining method is one of the key problems in the field of pattern recognition. Moreover, the lack of efficient feature extraction and selection methods has limited the application and development of electronic nose (e-nose) technology. In this study, a synergetic strategy for e-nose sensors data feature mining was proposed in combination with Support Vector Machine (SVM) to determine the beer olfactory information. First, twenty time-domain features and twenty frequency-domain features of e-nose sensors data were extracted to represent the olfactory characteristics of beer. Second, forty features were sorted with variable importance in projection (VIP) scores and forty subsets of multi-features with the best VIP score were generated. Finally, the classification models were established based on SVM, and the best parameter c and g of SVM models was calculated by Genetic Algorithm (GA). Furthermore, the classification performance of each class was evaluated by efficiency value (EFF) in different feature sets. The result indicates that GA-SVM model achieves good classification performance based on the #27 feature set with 81.67% and 96.67% in calibration set and testing set, respectively, and the EFF value is also the highest compared with other feature sets. In conclusion, it indicated that the analytical method can be used as a reliable tool for accurate identification of beer olfactory information.

In this paper, we aim to use odor fingerprint analysis to identify and detect various odors. We obtained the olfactory sensory evaluation of eight different brands of Chinese liquor by a lab-developed intelligent nose. From the respective combination of the time domain and frequency domain, we extract features to reflect the samples comprehensively. However, the extracted feature combined time domain and frequency domain will bring redundant information that affects performance. Therefore, we proposed data by Principal Component Analysis (PCA) and Variable Importance Projection (VIP) to delete redundant information to construct a more precise odor fingerprint. Then, Random Forest (RF) and Probabilistic Neural Network (PNN) were built based on the above. Results showed that the VIP-based models achieved better classification performance than PCA-based models. In addition, the peak performance (92.5%) of the VIP-RF model had a higher classification rate than the VIP-PNN model (90%). In conclusion, odor fingerprint analysis using a feature mining method based on the olfactory sensory evaluation can be applied to monitor product quality in the actual process of industrialization.

Following the agreement on WTO, more and more foreign commercial banks have debuted into China bank industry since 2007. Currently, the domestic commercial banks in China will face especially more challenge and competition in their running. Efficiency of commercial banks is the main factor on reflecting the competition capability of banks. The comprehensive evaluation method, denoted as Data Envelopment Analysis, was applied to efficiency measurement of China commercial banks in this paper. By using the comprehensive evaluation results, the measurements for enhancing the efficiency of China commercial banks were drawn.