While link prediction methods in knowledge graphs have been increasingly utilized to locate potential associations between compounds and diseases, they suffer from lack of sufficient evidence to explain why a drug and a disease may be indicated. This is especially true for knowledge graph embedding (KGE) based methods where a drug-disease indication is linked only by information gleaned from a vector representation. Complementary pathwalking algorithms can increase the confidence of drug repurposing candidates by traversing a knowledge graph. However, these methods heavily weigh the relatedness of drugs, through their targets, pharmacology or shared diseases. Furthermore, these methods can rely on arbitrarily extracted paths as evidence of a compound to disease indication and lack the ability to make predictions on rare diseases. In this paper, we evaluate seven link prediction methods on a vast biomedical knowledge graph for drug repurposing. We follow the principle of consilience, and combine the reasoning paths and predictions provided by path-based reasoning approaches with those of KGE methods to identify putative drug repurposing indications. Finally, we highlight the utility of our approach through a potential repurposing indication.
Current mainstream research on on-demand labor platforms primarily focuses on the discussion of algorithmic technologies while overlooking the issue of how platforms achieve stable operations in a de-employment context. Addressing this research gap, this study investigates the approaches employed by Chinese food-delivery platforms to ensure stable labor supply. Utilizing qualitative data, the research reveals that Chinese food-delivery platforms have established stability in labor supply by implementing the outsourced model, partnering with third-party staffing agencies to establish service stations, and managing couriers offline. This approach helps to balance platform and courier needs, addressing the tension between work flexibility and income stability. This research provides a case study illuminating the interplay between technology and the labor market in labor relations. Additionally, it highlights the structural forces that workers form within the internal labor market, deepening our understanding of platform management and the complexities of labor relations.
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