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A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.
Through the use of splicing methods, joining two different fiber types in the tow stage of the process enables great benefits to the strength of the material change.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.