anon_123g987

In the International System of Units (SI):

  k: kilo-   = *1000, prefix
  K: kelvin  = the unit of thermodynamic temperature

  b: bit     = the basic unit of information
  B: byte    = a set of adjacent bits (usually, but not necessarily, eight)

https://en.wikipedia.org/wiki/International_System_of_Units

https://en.wikipedia.org/wiki/IEEE_1541-2002

Don't use the term "open access" like this. A paper published on arXiv is free to read, and was freely published. "Open access" is a scam by the big publishers, where they don't take money from the readers, but make the authors pay. Or, putting it another way, anyone can pay their way in those journals and publish (sometimes sub par) papers.

Just a sidenote: it is at most our second serious model. Aristotle's Physics has a bad rap, but it's "a correct and non-intuitive approximation of Newtonian physics in the suitable domain (motion in fluids), in the same technical sense in which Newton theory is an approximation of Einstein's theory". See "Aristotle's Physics: a Physicist's Look" by Carlo Rovelli (https://arxiv.org/abs/1312.4057).

  > '%mult%' <- function(a,b) a*b
  > 3 %mult% 5
  [1] 15

  > '*'(3,5)
  [1] 15

https://phys.org/news/2008-07-james-webb-space-telescope-ful...

It looks the same to me.

FFmpeg 5.0 (https://github.com/FFmpeg/FFmpeg/blob/release/5.0/Changelog)

113 points|_Gyan_|3 days ago|27 comments

The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936. It is a multi-dimensional generalization of the idea of measuring how many standard deviations away P is from the mean of D. This distance is zero for P at the mean of D and grows as P moves away from the mean along each principal component axis. If each of these axes is re-scaled to have unit variance, then the Mahalanobis distance corresponds to standard Euclidean distance in the transformed space. The Mahalanobis distance is thus unitless, scale-invariant, and takes into account the correlations of the data set.

https://en.wikipedia.org/wiki/Mahalanobis_distance

https://invidious.io/

https://yewtu.be/

  sudo apt install mate-system-monitor

This is my experience, too, and in my opinion this is exactly what has to change for really reproducible research, not ready to run software supplied by the author.

There are many good arguments in support of publishing code, but reproducibility is not one of them, that's all I'm saying.

Everybody here talks about how publishing code helps (or even makes possible) reproducibility, but this is not true, on the contrary, it hinders it. Reproducing the results does not mean running the same code as the author and plotting the same figures as in the paper. This is trivial and good for nothing. Reproduction is other researchers independently reimplementing the code using only the published theory, and getting the same results. If the author publishes the code, no one will bother with this, and this is bad for science.