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The number of hidden neurons is determined using the rule that the ratio of the number of training data to the number of connection weights should be 10 to 1 (Weigend et al. 1990).
In another words, while an application is running, it would build up a dynamic ratio which is of these metric data to the number of VMs needed for it (for a certain preferable environment resource provision).
We compared these data to the number of TSSs per gene reported in the literature and, as shown in Figure 7, the results were very similar, showing that we detected the majority of the TSSs per gene.
For this purpose, we examined global morbidity (prevalence) and mortality data for a representative list of pathogen/diseases, and then compared these data to the number of references in each category.
We compared these data to the number of oestrus events potentially observed by other nulliparous females in the same families whose first observed oestrus event did not coincide with a false oestrus event of a family member (mean 17.3 events, sd ±8.5) (see figure 2).
To handle this situation, we have normalized the data to the number of gene copies expected to be found in general bacterial genomes.
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I then compared the adjusted building permit data to the remaining number of dwellings in 2011.
After normalizing the input data to match the number of tags in the ChIP data, the number of input tags is subtracted from the number of ChIP tags in the target window before calculating its z-score.
Following data collection, a threshold of 3 or more red-alone puncta per cell was applied to the data to determine the number of cells undergoing mitophagy.
A limiting dilution analysis was applied to the data to estimate the number of viable Leishmania expressed as Limiting Dilution Assay Unit.
The figure suggests that while the posterior variability is relatively wide, there is information in the data to estimate the number of edges to remove.
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