A Content-Based Recommendation Framework for Judicial Cases

Under the background of the Judicial Reform of China, big data of judicial cases are widely used to solve the problem of judicial research. Similarity analysis of judicial cases is the basis of wisdom judicature. In view of the necessity of getting rid of the ineffective information and extracting useful rules and conditions from the descriptive document, the analysis of Chinese judicial cases with a certain format is a big challenge. Hence, we propose a method that focuses on producing recommendations that are based on the content of judicial cases. Considering the particularity of Chinese language, we use “jieba” text segmentation to preprocess the cases. In view of the lack of labels of user interest and behavior, the proposed method considers the content information via adopting TF-IDF combined with LDA topic model, as opposed to the traditional methods such as CF (Collaborative Filtering Recommendations). Users are recommended to compute cosine similarity of cases in the same topic. In the experiments, we evaluate the performance of the proposed model on a given dataset of nearly 200,000 judicial cases. The experimental result reveals when the number of topics is around 80, the proposed method gets the best performance.

Microbial-driven ectopic uranium extraction with net electrical energy production

The extraction of uranium (U) from U-bearing wastewater is of paramount importance for mitigating negative environmental impacts and recovering U resources. Microbial reduction of soluble hexavalent uranium (U(VI)) to insoluble tetravalent uranium (U(IV)) holds immense potential for this purpose, but its practical application has been impeded by the challenges associated with managing U-bacterial mixtures and the biotoxicity of U. To address these challenges, we present a novel spontaneous microbial electrochemical (SMEC) method that spatially decoupled the microbial oxidation reaction and the U(VI) reduction reaction. Our results demonstrated stable and efficient U extraction with net electrical energy production, which was achieved with both synthetic and real wastewater. U(VI) removal occurred via diffusion-controlled U(VI)-to-U(IV) reduction-precipitation at the cathode, and the UIVO_(2) deposited on the surface of the cathode contributed to the stability and durability of the abiotic U(VI) reduction. Metagenomic sequencing revealed the formation of efficient electroactive communities on the anodic biofilm and enrichment of the key functional genes and metabolic pathways involved in electron transfer, energy metabolism, the TCA cycle, and acetate metabolism, which indicated the ectopic reduction of U(VI) at the cathode. Our study represents a significant advancement in the cost-effective recovery of U from U(VI)-bearing wastewater and may open a new avenue for sustainable uranium extraction.