Comparing neural sentence encoders for topic segmentation across domains: not your typical text similarity task

Neural sentence encoders (NSE) are effective in many NLP tasks, including topic segmentation.However, no systematic comparison of their performance in topic segmentation has been performed.Here, we present such a comparison, using supervised and unsupervised segmentation models based on NSEs.We first compare results with baselines, showing that the

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Anti-fibrotic activity of a rho-kinase inhibitor restores outflow function and intraocular pressure homeostasis

Glucocorticoids are widely used as an ophthalmic medication.A common, sight-threatening adverse event of glucocorticoid usage is ocular hypertension, caused by dysfunction of the conventional outflow pathway.We report that netarsudil, a rho-kinase inhibitor, decreased glucocorticoid-induced ocular Cholesterol Synthesis hypertension in patients whos

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Short-Term Hydrological Drought Forecasting Based on Different Nature-Inspired Optimization Algorithms Hybridized With Artificial Neural Networks

Hydrological drought forecasting plays a substantial role in water resources management.Hydrological drought highly affects the water allocation and hydropower generation.In this research, short term hydrological drought forecasted based Cholesterol Synthesis on the hybridized of novel nature-inspired optimization algorithms and Artificial Neural N

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