Supervising the environmental protection behavior of enterprises is a key strategy to achieve “carbon peaking and carbon neutrality”. This research innovatively proposes the concept of precise supervision, aiming to implement differentiated supervision measures for different types of enterprises, and realize the precise supervision method of enterprise environmental protection, which is different from the traditional supervision mode. Firstly, this paper proposes a novel MEBF+ method based on the benchmark algorithm MEBF, and obtains MEBF++ after incorporating the model bias. Secondly, based on the dataset of environmental supervision and certification of listed Chinese companies, the accuracy and robustness of the proposed method are verified by using multiple evaluation indicators. Finally, based on the analysis of the experimental results, two precise supervision concepts, narrow and broad, are proposed under the low-carbon background. The results show that compared with the benchmark method, the accuracy of the proposed method has been improved to a large extent. In addition, the precise supervision proposed in this paper can help reduce the consumption of manpower and resources as well as unite the public to monitor the environmental protection behavior of enterprises.

Aiming at the problem of data sparsity, cold start, and privacy concerns in complex information recommendation systems, such as personalized marketing on Alibaba or TikTok, this paper proposes a mobile social recommendation model integrating users’ personality traits and social relationship strength under privacy concerns (PC-MSPR). Firstly, PC-MSPR focuses on specific personality traits, including openness, extraversion, and agreeableness, and their impacts on mobile users’ online behaviors. A personality traits calculation method that incorporates privacy preferences (PP-PTM) is then introduced. Secondly, a novel method for calculating the users’ relationship strength, based on their social network interactive activities and domain ontologies (AI-URS) is proposed. AI-URS divides the interactive activities into activity domains and calculates the strength of relationships between users belonging to the same activity domain; at the same time, the comprehensive relationship strength of users in the same domain, including direct relationships and indirect relationships, is calculated based on interactive activity documents. Finally, social recommendations are derived by integrating personality traits and social relationships to calculate user similarity. The proposed model is validated using empirical data. The results show the model’s superiority in alleviating data sparsity and cold-start problems, obtaining higher recommendation precision, and reducing the impact of privacy concerns regarding the users’ adoption of personalized recommendation services.

The ductile-to-brittle-transition (DBT) of Sn occurring when the temperature decreases to a critical temperature poses a restriction on the Sn-based solders in the cryogenic electronics interconnection. Previous investigations about the DBT mainly adopt the Charpy impact test, however, the transient property of Charpy impact test makes it difficult to capture the deformation features accompanying DBT and clearly elucidate the DBT mechanism. In this paper, we studied the plastic deformation of Sn before cryogenic brittle fracture through in-situ cryogenic uniaxial tensile experiments under optical microscopy. It is found that {301} deformation twins were activated and thickened before the brittle fracture. Due to the occurrence of deformation twins, multiple twin-grain boundary intersections and twin-twin intersections formed within Sn grains, which could strongly prevent dislocation slip and thus lead to stress concentration. As a result, the brittle cracks initiate and propagate along these intersections. According to the suggested specific mechanism, we designed a green pre-treatment method of pre-twining-RT tempering to increase the cryogenic ductility of Sn-based solder alloys without any energy consumption. Eventually, the fracture elongation of Sn at LNT was significantly improved from ~6% to ~14%.