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Here, we consider again the 2D localization error for an easier, although more challenging, comparison with results presented in Section 4.2.
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In the WINNER channel models, parameter estimation is much more challenging in comparison to the two-path channel models since a much larger number of propagation paths I>2 is considered.
However, this is a non-trivial task for algorithms because there could be missing tissues as well as distortions during sectioning, making stitching neuronal segments across multiple sections much more challenging in comparison with stitching overlapping tiles within single sections [6, 7] (Fig. 1c).
Conducting research and particularly randomised controlled trials in frail elderly populations is often more challenging and complex in comparison to younger healthy adults [ 16].
The SLIC (N = 367) and Raine (N = 667) cohorts are larger than the York cohort but less well-characterized with mathematical measures making direct comparisons more challenging because of inconsistency across available phenotypes.
Serving sizes per 100 g, while useful for product comparison, are more challenging for consumers to extract nutrition information, as found in Lesotho (40).
Wurmser and colleagues [ 8] reported that infants who had received a diagnosis of excessive crying were also judged to be temperamentally "more challenging" at 30 months in comparison to other children.
A Visual Sensor Network environment is a more challenging setup for feature-based image comparison algorithms.
It is worth keeping in mind, the analyst told clients, that as September results come in, comparisons will become more challenging, given a strong September last year.
The second, more challenging, data set describes a microarray platform comparison study using hippocampal δC-doublecortin-like kinase transgenic mice that were compared to wild-type mice, which was combined with results from Solexa/Illumina deep sequencing runs.
For these reasons, distinguishing signal from noise in a manner that allows comparison between datasets is more challenging with DNaseI-seq than with other high-throughput sequencing approaches, such as ChIP-seq.
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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