Mining heuristic evidence sentences for more interpretable document-level relation extraction

Current research on evidence sentences is aimed at developing document-level relational extraction models with improved interpretability. Evidence sentences extracted using existing methods are often incomplete, leading to poor relationship prediction accuracy. To address this problem, we developed a novel efficient heuristic rule and entity representation method. First, a heuristic rule is constructed according to the interactions between different mentions of the head and tail entities of the target entity pair, and evidence sentences are subsequently extracted. Second, pseudo documents, constructed according to the original document order, are used as input text to remove noisy statements. Finally, different representations of the same entity in different entity pairs are learned to represent it more accurately through the interactive mention of head and tail entities. Experiments on the document-level general domain dataset DocRED indicated that our heuristic rules improved sentence extraction by 6.01% compared to that achieved by the baseline model Paths-BiLSTM. In terms of relation prediction, the accuracy of the proposed method was comparable to those of existing models that use the entire document as input text; however, the input text used by the proposed method was shorter and more interpretable

Improved Method for Measuring the Permeability of Nanoporous Material and Its Application to Shale Matrix with Ultra-Low Permeability

Nanoporous materials have a wide range of applications in clean energy and environmental research. The permeability of nanoporous materials is low, which affects the fluid transport behavior inside the nanopores and thus also affects the performance of technologies based on such materials. For example, during the development of shale gas resources, the permeability of the shale matrix is normally lower than 10−3 mD and has an important influence on rock parameters. It is challenging to measure small pressure changes accurately under high pressure. Although the pressure decay method provides an effective means for the measurement of low permeability, most apparatuses and experiments have difficulty measuring permeability in high pressure conditions over 1.38 MPa. Here, we propose an improved experimental method for the measurement of low permeability. To overcome the challenge of measuring small changes in pressure at high pressure, a pressure difference sensor is used. By improving the constant temperature accuracy and reducing the helium leakage rate, we measure shale matrix permeabilities ranging from 0.05 to 2 nD at pore pressures of up to 8 MPa, with good repeatability and sample mass irrelevance. The results show that porosity, pore pressure, and moisture conditions influence the matrix permeability. The permeability of moist shale is lower than that of dry shale, since water blocks some of the nanopores

Ultra-low threshold InAs/GaAs quantum dot microdisk lasers on planar on-axis Si (001) substrates

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