Context-Based Feature Technique for Sarcasm Identification in Benchmark Datasets Using Deep Learning and BERT Model

Sarcasm is a complicated linguistic term commonly found in e-commerce and social media sites.Failure to identify sarcastic utterances in Natural Language Processing applications such as sentiment analysis and opinion mining will confuse classification algorithms and generate false results.Several studies on sarcasm detection have utilised different

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The Endophytic Strain ZS-3 Enhances Salt Tolerance in Arabidopsis thaliana by Regulating Photosynthesis, Osmotic Stress, and Ion Homeostasis and Inducing Systemic Tolerance

Soil salinity is one of the main factors limiting agricultural development worldwide and has an adverse effect on plant growth and yield.To date, plant growth-promoting rhizobacteria (PGPR) are considered to be one of the most promising eco-friendly strategies for improving saline soils.The bacterium Bacillus megaterium ZS-3 is an excellent PGPR st

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Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates

Abstract Osteoporosis is becoming a global health issue due to increased life expectancy.However, it is difficult to detect in its early stages owing to a lack of discernible symptoms.Hence, screening for osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful.In this study, we investigate the use of deep

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