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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.
This technology provides a device, platform and method of fabrication of new atomically tailored materials. This “synthescope” is a scanning transmission electron microscope (STEM) transformed into an atomic-scale material manipulation platform.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.