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High scale values on the scale represent high resilience in contrast to low scale values.
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Indirect drivers tend to show low scale sensitivity, whereas direct drivers show high scale sensitivity, as they operate in a non-linear way across the administrative scale.
In this regard, it was shown that c-AFM gives the extra possibility to electrically investigate buried interfaces to a very low scale being superior in this regard to the standard I V measurements which exhibit a strong average character.
According to the characteristics of the S/D binary representation, genetic and evolutionary algorithms (GEAs) can be applied from the high scaled to the low scaled BBs sequentially to avoid a noise from the competing BBs and improve GEAs' performance.
Complementary information confined down to extremely low scales is accessible.
The approximate coefficients can be iterated to the lowest scale, quantized, and reconstructed prior to the predictions.
Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima.
All spectra shown in Figure 5b are vertically shifted and plotted using a low scale to clearly display the Fermi edge [7]. Figure 5 UPS spectra in the low kinetic and low binding energy regions.
In this article, we propose a specific approach of such multi-scale strategy, the outline of which is to transform the constrained dictionary learning problem into the augmented Lagrangian (AL) framework first and then refine the dictionary from low scale to high.
Suppose that each iterative step is regarded as a scale, then the dictionary updating, via summing the multiplication of primal and dual variables (i.e., Equation 10), can be seemed as a refinement process from the low scale to the high one.
In contrast to previous observation using low scale sequencing, our results show a prevalence of vd-sRNAs.
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