Amylose, a primarily linear polysaccharide of (1 ! 4)-a-D-glucose units, displays a folding in a helical conformation and has an ability to form an inclusion complex with a variety of ligands. In this study, debranched starch-ferulic acid complexes were produced by adding ferulic acid to the debranched cassava starch paste and their physicochemical properties and antioxidant capacity were investigated. The mixing ratios of ferulic acid to starch were 0.02 (DS-FA0.02), 0.05 (DS-FA0.05), and 0.10 g ferulic acid/g starch (DS-FA0.10). The amounts of bound ferulic acid in the DS-FA0.02, DS-FA0.05, and DS-FA0.10 were 6.8, 16.2, and 31.5 mg/g starch, respectively. The ferulic acid was observed to be entrapped in the hydrophobic core of double helices, which did not affect the crystalline structure, gelatinization temperatures, viscosity, and RS content of the crystallites formed by the linear-chain molecules of the debranched starch. The solubility and antioxidant capacity of the debranched starch-ferulic acid complexes increased with increasing in amount of bound ferulic acid in the complexes. The higher RS content and antioxidant capacity of the complexes are considered to have significant benefits for human health. Therefore, the debranched starch-ferulic acid complexes might be used as a new functional food as well as pharmaceutical products.
Chatbot research has advanced significantly over the years. Enterprises have been investigating how to improve these tools’ performance, adoption, and implementation to communicate with customers or internal teams through social media. Besides, businesses also want to pay attention to quality reviews from customers via social networks about products available in the market. From there, please select a new method to improve the service quality of their products and then send it to publishing agencies to publish based on the needs and evaluation of society. Although there have been numerous recent studies, not all of them address the issue of opinion evaluation on the chatbot system. The primary goal of this paper’s research is to evaluate human comments in English via the chatbot system. The system’s documents are preprocessed and opinion-matched to provide opinion judgments based on English comments. Based on practical needs and social conditions, this methodology aims to evolve chatbot content based on user inter-actions, allowing for a cyclic and human-supervised process with the following steps to evaluate comments in English. First, we preprocess the input data by collecting social media comments, and then our system parses those comments according to the rating views for each topic covered. Finally, our system will give a rating and comment result for each comment entered into the system. Experiments show that our method can improve accuracy better than the referenced methods by 78.53%.
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