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The overview of ICN-based content retrieval is shown in Fig. 2.
An example of automatic term-like phrases retrieval is shown in Fig. 8 with some term-like and filtered-off n-grams highlighted.
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Characteristics of donation and differences in organ retrieval are shown in Figure 3.
Details of antibodies, dilutions and requirement for antigen retrieval are shown in Table I.
The effect of mass accuracy windows during the database retrieval are shown in Figure 2c and d.
Antibodies, dilutions and requirement for antigen retrieval are shown in Table I.
The antibodies, dilutions and requirement for antigen retrieval are shown in Table I.
With optimal specification of τ550 and aerosol optical properties and correction for adjacency effects, the relative Mean Absolute Deviation (MAD) for all bands combined was 5.4% for RapidEye and 6.8% for Landsat 8. However uncertainties associated with satellite-based τ550 retrievals were shown to introduce significant error into the reflectance estimates.
The total number of successful satellite retrievals are shown in Figure 7A and are summarized regionally as population-weighted mean in Table 2. Lower sampling was fortuitously collocated with lower population.
Neural network retrieval performance is shown in Figure 3.
An overview of the geometry-aware retrieval pipeline is shown in Fig. 7.
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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