Identifying chemical-induced disease (CID) semantic relations in the biomedical literature, including both intra- and inter-sentence interactions, has significant implications for various downstream applications. Although various advanced methods have been proposed, they often overlook the cross-sentence dependency information, which is crucial for accurately predicting inter-sentence relations. In this study, we propose DEGREx, a novel graph-based neural model that presents a biomedical document as a dependency graph. DEGREx improves the long-distance relation extraction by allowing direct information exchange among document graph nodes through dependency connections. The information transition process is based on the idea of controller gates in long short-term memory networks. Our model, DEGREx, exerts a multi-task learning framework to jointly train relation extraction with named entity recognition, improving the performance of the CID extraction task. Experimental results on the benchmark dataset demonstrate that our model DEGREx outperforms all nine compared recent state-of-the-art models.
For decades, the sulfido molybdenum complexes like [MoS 4 ] 2À , [Mo 2 S 12 ] 2À , [Mo 3 S 13 ] 2À have gained great attention because of their chemical versatility as well as their structural similarity to the edge-plan of the molybdenum disulfide (MoS 2 ) which shows promising catalytic ability for the H 2 generation. In this work, we report on the investigation of the dinuclear complex [Mo 2 S 12 ] 2À in both organic and aqueous solution. We demonstrate that [Mo 2 S 12 ] 2À is not intact during the H 2 evolution catalysis when it is assayed as a homogeneous catalyst in an electrolyte solution (e. g. in DMF or water solvent) nor when it is immobilized on an electrode surface (e. g. mesoporous carbon black). It transforms into the polymeric amorphous molybdenum sulfide [MoS] which subsequently acts as an actual catalyst. We discuss on the possible [Mo 2 S 12 ] 2À to [MoS] transformation mechanism by employing an arsenal of electrochemical analysis, spectroscopic analyses and microscopic analyses. Effects of the electrochemical operating conditions to the [Mo 2 S 12 ] 2À to [MoS] transformation as well as to the chemical nature and the catalytic performance of the [MoS] product are also emphasized.
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