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Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.
Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.
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.