The single-cell approach is useful for obtaining organism-specific sequence datasets from heterogeneous samples, and furthermore provides an insight into micro-heterogeneity at the population level.
The heterogeneous samples were cut from 2-ft long samples characterized with structured heterogeneities in the form of zero dip microscale lamination parallel to the flow direction.
Simulations on several heterogeneous samples show that the effective diffusivity strongly depends on the degree of heterogeneity.
The heterogeneous samples were specially ordered from an outcrop rock samples provider.
This kind of approach becomes indispensable to solve the challenge of micro heterogeneous samples.
Advanced 3D printing techniques were employed to construct heterogeneous samples that represented accurate distribution of gravel.
SXRFM encounters the same problem as XRF analysis; this typically limits SXRFM accuracy to ± 30% in thick heterogeneous samples.
However, traditional transparent materials (PMMA, glass, resin) are homogeneous and are of limited use for understanding heterogeneous samples.
In combination with a microscope, these techniques can also be used to study molecular distributions in heterogeneous samples.
In the first stage, uncertainty originates from data that are sparse, noisy, ambiguous, or derived from heterogeneous samples.
Highly heterogeneous samples (containing high pore and/or crystal fractions) will therefore have high values of ϕp′, and vice-versa.
