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It is my hope that these photographs will show this problem to those who are unaware or have done their best to ignore this issue.
A main result is that, under the assumption that the identified parameters are sufficiently close to their true values, we show this problem to be convex in the input spectrum with linear matrix inequality constraints.
Tree-ring width data don't obviously show this problem, though there are indeed other issues (for example, my colleagues and I published a paper in Nature Geosciences just a few weeks ago showing that tree-ring widths from treeline locations may underestimate the large cooling events following particularly large volcanic eruptions).
We pick a subset of PEs to show this problem.
Though the resultant secrecy rate maximization (SRM) problem is nonconvex by nature, we show this problem actually falls into the context of difference-of-concave (DC) programming [29].
Sorted neonatal SVZ cells do not show this problem.
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But the study shows this problem is far more profound than previously realised.
Figure 12 shows this problem.
Of course, even a cursory glimpse at the last 20 years shows this problem clearly isn't limited to one community.
However, recent studies conducted in USA [ 12] and Canada [ 13] have shown this problem is not confined to the UK.
The above new study has shown this problem can also be overcome by use of thinner samples.
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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