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Copyright of Chinese Journal of Contemporary Pediatrics is the property of Xiangya Medical Periodical Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Agricultural Outlook (1673-3908) is the property of Institute of Agricultural Information, Chinese Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai University of Engineering Science / Shanghai Gongcheng Jishu Daxue Xuebao is the property of Journal of Shanghai University of Engineering Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to predict the total amount of city tap water supply accurately, a predicting method of the extreme learning machine (ELM) optimized by teachinglearning-based optimization was proposed. An improved TLBO algorithm (ITLBO) was proposed to solve the problem of low convergence accuracy and easy to fall into local optimization. In ITLBO, an extra tutoring stage was added for the worst student, and the teacher could help the student individually or adopt the opposition-based learning strategy to quickly improve the student's performance. On this basis, a disturbance operator was used to perturb the teacher position, which increased the kinetic energy of the population to jump out of the local optimum. Finally, the improved ITLBO algorithm was used to optimize and adjust the input weight and hidden threshold parameters of ELM model, and the ITLBO-ELM water supply prediction model was built. ITLBO-ELM model was used to predict the tap water supply in Shanghai. The simulation results show that the model can accurately predict the tap water supply total amount. [ABSTRACT FROM AUTHOR]

Copyright of Southwest China Journal of Agricultural Sciences is the property of Editorial Department of Southwest China Journal of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Preventive Veterinary Medicine / Zhongguo Yufang Shouyi Xuebao is the property of Chinese Journal of Preventive Veterinary Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Southwest China Journal of Agricultural Sciences is the property of Editorial Department of Southwest China Journal of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Guihaia is the property of Guihaia Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

HPLC fingerprints of different preliminary processing Gentiana rigescens were established, and 4 index contents as loganic acid, swertimarin, gentiopicroside and swerosidefour were determined. Principal component analysis (PCA) was employed to evaluate nine preliminary processing methods. The results showed relatively high similarity among samples. The contents of swertimarin, gentiopicroside and sweroside were the highest in Gentiana rigescens samples which were cleaned by rinsing and indoor seasoning, and reached(5.89 ±0.23), (15.62±0.84),(3.79 ±0.16)mg/g, respectively. While the sample which was treated by microwave had the highest content of loganic acid, was( 8. 58 ± 1 .48) mg/g. The total content of the 4 effective components was(27. 67 ± 6. 09) mg/g. The results of principal component analysis revealed that cumulativerate of contribution of PC A1 and PC A2 reached 86. 822 %, and formed linearrelation with four effective constituents: F(PC1) =-0.003X1 + 0.409X2 + 0.31X3 + 0.398X4, F(PC2) = 0.875X1 - 0.168X2 + 0. 329X3 - 0.078X4; The results showed that the samples with the skin dried indoor after washing got the highest score in PCA. Analysis results revealed cleaning by rinsing and indoor seasoning was more optimizing processing method than others. [ABSTRACT FROM AUTHOR]