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Half of these bins are chosen at random, and solution atoms, within the projection of these bins along the interface normal, are moved into the surface by a random distance (per bin) between 0 and 10 Å along that normal.
To explore the extent of this problem, every plot was shifted by a random distance in both north-south and east-west directions (i.e. N 0,σ=5) in both directions) from the recorded location, the LiDAR TCH calculated from canopy-height-model pixels that lay within the boundary of the new plot, and a regression line fitted to these data.
To show the effect of projection misalignment, we use an ImageJ macro to shift each projection by a random distance with flat probability distribution between −1 and + 1 pixels along its length, using bicubic interpolation in the case of non-integer shifts.
Each geocode was then displaced at a random angle by a random distance drawn from the distribution of observed geocode location errors.
The first 'column cycle shuffle' controls for the linear alignment of consecutive position estimates by circularly shifting the estimated probability distribution over position (PDF) in each candidate event time bin by a random distance.
Each geocode was then displaced at a random angle from a uniform (0, 2π) distribution by a random distance drawn from an empirical distribution of geocode location errors (as reported in the Results).
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Random sampling was ensured by advancing the cutting stage a random distance (between 1 and 50 μm), before sections were collected (Coggeshall and Lekan 1996; Howard and Reed 1998) (Fig. 1a).
Therefore, in order to simulate the distribution of synapses in the neuropil, the empty space around the centroids of synaptic junctions had to be accounted for by a random minimum-spacing distance that would depend, at least partially, on the sizes of synaptic junctions themselves.
To evaluate errors arising from geolocation inaccuracies, every plot was shifted by random distances from its recorded location, a ACD-prediction model was calculated using TCH values estimated for these shifted plot locations, and ACD values predicted for the plots using that model.
CMP were generated by random permutations of different numbers of taxa and branch lengths from a random additive distance matrix.
In these models, the distance between crossovers is modeled by a random variable with some distribution.
More suggestions(16)
by a random process
by a random agglomeration
by a random computer
by a random sequence
by a random telephone
by a random link
by a random utility
by a random stranger
by a good distance
by a random sampling
by a minimum distance
by a random man
by a random distribution
by a vast distance
by a big distance
by a considerable distance
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com