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In [1], many arguments were demonstrated to question the usefulness of the mean squared error (MSE) in image and audio processing due to our complex human perception and these arguments were nicely supported by many practical examples and observations.
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These predictions are consistent with both our examples and the observation that the complementary interaction was the predominant type of statistically detectable epistasis in rice QTL mapping studies [4] [8], [44], and that most downstream loci tended to be detected as AGs in large selection experiments (unpublished data).
Two canonical examples are announcements and observations.
Social scientists collect, reflect on and derive themes, meanings and theories from empirical data from, for example, interviews and observation.
Snow, humidity, and solar radiation measurements are too sparse, for example, and few observations of soil moisture or groundwater stocks exist.
Then comes a bit of Asian history, a nicely written précis of the Mongol advance or the opium wars, for example, and some observations on historical and cultural injustices of life, injustices that ultimately lead people to have unprotected sex or share needles.
The effectiveness of the proposed approach is demonstrated by numerical examples and some interesting observations and conclusions are summarized from the analyses and discussions.
A detailed description of the RESCO and examples of observations are given by Abdu et al. (2002) and Denardini et al. (2004, 2005, 2006, 2009, 2015).
For example, differing representation of samples and observations as either rows or columns, and the mechanism for incorporating sample or observation metadata (if possible at all), cause the formats used by different software packages to be incompatible.
For example, combining interviews and observation, MacIntosh et al 18 identified the extent to which interactions between clinicians and managers were two-way discussions, finding that each group presented themselves as less powerful than the other group and lacking agency.
The models and observations all agree, for example, that the last decade was the warmest on record.
Write better and faster with AI suggestions while staying true to your unique style.
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