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over time. Stem cell populations can be highly heterogeneous and can exhibit complex responses. Using quantitative imaging data on large numbers of live cells over time, we can construct potential
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property data are available for only a few dozen fluids. A better understanding of fundamental fluid behavior would allow the accurate prediction of properties for those fluids lacking good data and thus
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–structure–property relationship by data fusion: Bayesian co-regionalization N-dimensional piecewise function learning. Digital Discovery, 3(11), pp.2211-2225. Materials Genome Initiative; Machine learning
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to effectively convert interactions occurring at gas-solid or liquid-solid interfaces, or between molecules, into measurable signals that provide information on the nature and concentration of chemical and
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considerable amount of data of the standard biological fluids on different LC-MS platforms and in-house software has been developed for chromatography alignment, spectral similarity, peak deconvolution, and
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pushed the limits of mass detection to spectral resolutions over 100,000, allowing for specific mass determination and unknown compound identification. Analytical methods and novel data-processing tools
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This research aims to study the formalization of information processes and systems, using modern approaches and techniques from mathematics. Distinct entities, each having its own database, ontology, or other
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techniques to study hydrogen locations and dynamics in materials necessary for advancing the Hydrogen Economy. Detailed information on hydrogen locations and binding potentials in a lattice is extracted as a
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states that can preserve quantum information. key words Enriched silicon; Quantum information; Quantum devices; Single electron devices; Coulomb blockade; qubit; hybrid quantum devices; materials
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of the uncertainties encountered in the physical experiments. These computational methods have been applied to nanorheology in photopolymerization 3D printing [1], human breath research for forensic and clinical data