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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.
ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.
The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.
QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.