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Using the image_data command again displays the filtered data, as shown in Figure 3.
This MSA seems to be the most diverse based on the demographic data as shown above.
Conventionally, constructing an effective ML model requires first developing a suitable representation for the input data as shown in Fig. 1.
To extract the saturation magnetization (M s ) of Ni80Fe20 film samples after annealing, the Kittel equation was fitted to the data as shown in Fig. 3(a).
The same data as shown in Figure 13 has been plotted, but this time limits are indicated for the third and last-but-one points.
Video-oculography of the right and left eyes (left) and kinetic traces of the recorded eye movements (right) for the same segment of data as shown in Fig. 1e.
By default, the fit is plotted as a red line over the data, as shown in Figure 2. Clearly a first-order polynomial does not give a good fit to the data set.
Engineering stress and strain are calculated from force and displacement data as shown in Fig. 16.
This assumption is supported by EDX data as shown in Fig. 10b.
The new developed correlation shows the highest agreement with experimental data, as shown in Table 9.
The experimental values complied exactly with the theoretical calculation data as shown in Figure 9.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com