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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.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.
An ORNL team has developed a method for screening for an immunoregulatory protein, which includes assessing the sequence of a candidate protein to determine if it is an immunoregulatory protein when at least one plasminogen-apple-nematode (PAN) domain with a consensus sequence