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This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk’s lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.

α-l-arabinofuranosidase is a subfamily of glycosidases involved in the hydrolysis of l-arabinofuranosidic bonds, especially in those of the terminal non-reducing arabinofuranosyl residues of glycosides, from which efficient glycoside hydrolases can be screened for the transformation of ginsenosides. In this study, the ginsenoside Rc-hydrolyzing α-l-arabinofuranosidase gene, BsAbfA, was cloned from Bacilus subtilis, and its codons were optimized for efficient expression in E. coli BL21 (DE3). The recombinant protein BsAbfA fused with an N-terminal His-tag was overexpressed and purified, and then subjected to enzymatic characterization. Site-directed mutagenesis of BsAbfA was performed to verify the catalytic site, and the molecular mechanism of BsAbfA catalyzing ginsenoside Rc was analyzed by molecular docking, using the homology model of sequence alignment with other β-glycosidases. The results show that the purified BsAbfA had a specific activity of 32.6 U/mg. Under optimal conditions (pH 5, 40 °C), the kinetic parameters Km of BsAbfA for pNP-α-Araf and ginsenoside Rc were 0.6 mM and 0.4 mM, while the Kcat/Km were 181.5 s−1 mM−1 and 197.8 s−1 mM−1, respectively. More than 90% of ginsenoside Rc could be transformed by 12 U/mL purified BsAbfA at 40 °C and pH 5 in 24 h. The results of molecular docking and site-directed mutagenesis suggested that the E173 and E292 variants for BsAbfA are important in recognizing ginsenoside Rc effectively, and to make it enter the active pocket to hydrolyze the outer arabinofuranosyl moieties at C20 position. These remarkable properties and the catalytic mechanism of BsAbfA provide a good alternative for the effective biotransformation of the major ginsenoside Rc into Rd.

To contribute to the debate on the importance of state vis-à-vis inter-firm competition in regional development, this paper examines a representative dataset of the relocation of manufacturing firms in Guangdong province of China with multinomial logistic regression models. To improve the competitiveness of manufacturing in the Pearl River Delta, the Guangdong government implemented pro-active policies to encourage the relocation of existing manufacturing firms to their designated industrial parks during the 2000s. Although the initial results appear to support the usefulness of relocation policy, further examination reveals its effectiveness depends on the industrial sector and profiles of the relocated firms. In fact, the relocation of large-scale labor-intensive firms is not driven by local government initiatives. The physical proximity of high-technology parks to airports/ports has a bigger impact on the relocation of small-scale locally-funded high-technology firms into designated parks. In the case of locally-funded firms in polluting sectors, they are expanding rather than relocating to designated industrial parks. The empirical evidence indicates the non-binary nature of the industrial relocation policy. The nuances of relocation policy and its multi-scalar effects on relocated firms rejects any simplistic generalization. [ABSTRACT FROM AUTHOR]