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is a well-known traditional Chinese medicine originating in Xinjiang. It is widely distributed in northern Africa, India, etc. The major bioactive component of is phenylethanoid glycosides (PhGs). Echinacoside and acteoside are the indicative components for the determination of PhGs and are mainly used for liver protection, immune protection, etc. Therefore, it is very important to extract the PhGs from In this study, the ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and high-speed shearing homogenization extraction (HSHE) methods were compared. Furthermore, the extraction conditions of the HSHE method were optimized. The results showed that the HSHE method was better than both the UAE and MAE methods, and the optimal extraction parameters of HSHE were an ethanol concentration of 50%, an extraction temperature of 70°C, a rotation speed of 16 000 rpm, an extraction time of 2 min, a solid-to-liquid ratio of 1:9, and one extraction cycle. The yields of echinacoside and acteoside were 1.366 and 0.519%, respectively, and the transfer rates of echinacoside and acteoside reached 87 and 94%, respectively. It can be concluded that the HSHE method is a simple, rapid, and efficient technique for extracting PhGs from An efficient and ecofriendly HSHE method has been investigated for the extraction of PhGs from . The optimum conditions of the HSHE method for the extraction of PhGs from were obtained. This research provides a new method for the industrial extraction of PhGs from .

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With the rapid development of digital platforms, users can now interact in endless ways from writing business reviews and comments to sharing information with their friends and followers. As a result, organizations have numerous digital social networks available for graph learning problems with little guidance on how to select the right graph or how to combine multiple edge types. In this paper, we first describe the types of user-to-user networks available across the Facebook (FB) and Instagram (IG) platforms. We observe minimal edge overlap between these networks, indicating users are exhibiting different behaviors and interaction patterns between platforms. We then compare predictive performance metrics across various node attribute prediction tasks for an ads click prediction task on Facebook and for a publicly available dataset from the Open Graph Benchmark. We adapt an existing node attribute prediction method for binary prediction, LINK-Naive Bayes, to account for both edge direction and weights on single-layer networks. We observe meaningful predictive performance gains when incorporating edge direction and weight. We then introduce an approach called MultiLayerLINK-NaiveBayes that can combine multiple network layers during training and observe superior performance over the single-layer results. Ultimately, whether edge direction, edge weights, and multi-layers are practically useful will depend on the particular setting. Our approach enables practitioners to quickly combine multiple layers and additional edge information such as direction or weight.

Leasing has been increasingly seen as a viable alternative to traditional business models. In this paper, we consider a manufacturer making decisions on green product design by accounting for the trade-off between traditional and environmental qualities under three business models, including a pure selling, a pure leasing, and a hybrid model with both selling and leasing. Under leasing, there exists the pooling effect that allows a manufacturer to meet consumer needs with fewer products. Since the pooling effect decreases the marginal cost of production, leasing produces positive incentives to increase product quality. However, the cannibalization effect within the product line distorts the incentives so that the pooling effect only increases the traditional quality rather than the environmental quality. As a result, leasing may have a negative impact on the average environmental quality of products. The manufacturer should make business model choices depending on some factors, including the types of markets, the usage cost, and the pooling effect. In general, when the pooling effect is strong, the manufacturer prefers a leasing or hybrid model to selling but designs products with lower environmental quality than selling. When the pooling effect is weak, the optimal decision should be made depending on the types of markets and the usage cost: in the high-end (low-end) market, the manufacturer should adopt a leasing or hybrid model only when the usage cost is high (low); the adoption of leasing or hybrid model can improve the average environmental quality.

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