Search

The era of self-media and the widespread popularity of online social software have led to short video platforms becoming “incubators” easily for the origin and fermentation of public opinion events. Analyzing the public opinion comments on these platforms is crucial for the early warning, handling, and guidance of such incidents. In view of this, this paper proposes a text classification model combining BERT and TextCNN, named BERT-MLFF-TextCNN, which integrates multi-level features from BERT for sentiment analysis of relevant comment data on the Douyin short video platform. Firstly, the BERT pre-trained model is used to encode the input text. Secondly, semantic feature vectors from each encoding layer are extracted and fused. Subsequently, a self-attention mechanism is integrated to highlight key features, thereby effectively utilizing them. Finally, the resulting feature sequence is input into the TextCNN model for classification. The results demonstrate that the BERT-MLFF-TextCNN model outperforms BERT-TextCNN, GloVe-TextCNN, and Word2vec-TextCNN models, achieving an [F1] score of 0.977. This model effectively identifies the emotional tendencies in public opinions on short video platforms. Based on this, using the TextRank algorithm for topic mining allows for the visualization of thematic words related to the sentiment polarity of public opinion comments, providing a decision-making reference for relevant departments in the public opinion management work.

Thermodynamic-driven biomanufacturing of fructose catalyzed by phosphorylation and dephosphorylation cascade reactions is considered as the future of industrial fructose production due to its high theoretical yield of 100 %. Co-immobilizing all four cascade enzymes involved on solid materials is crucial for its successful industrial application, as it significantly reduces costs through enzyme reusage. Graphene oxide served as a multi-enzyme carrier in the thermodynamic-driven biosystem of fructose and displayed high loading capacities for the four cascade enzymes. The resulting co-immobilized biosystem based on graphene oxide exhibited superior biocatalytic performance than the other support materials. Additionally, it yielded 54.7 % fructose from maltodextrin. Utilizing two additional enzymes to improve the substrate utilization, an 85.2 % fructose yield was achieved, surpassing the current industrial-scale fructose production process employing monosaccharide isomerization. This study sheds light on the potential industrial applications of thermodynamic-driven biomanufacturing systems for fructose production. [Display omitted] • Graphene oxide exhibited high loading capacities for cascade enzymes. • The co-immobilized enzymes showed good biocatalytic efficiency and reusability. • A fructose yield of 85.2 % was achieved from the co-immobilized biosystem. [ABSTRACT FROM AUTHOR]