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Scanning probe microscopy (SPM) images are often degraded due to the effects of two (or more) protrusions on the probe tip (i.e. effective mini-tips on a blunt tip), as well as containing sample tilt errors, image bow and drift, and stepping errors that occur while scanning the tip in two dimensions (2D) over the sample surface.
Reduced occurrence of stepping errors in the rapid step test was related to small molecules within glycerophospholipid, carbonyl and carboxylic acid metabolite classes (Supplemental Table 5).
Stepping errors would be an example of a variable with a negative relationship; the less the errors the better the performance.
In each of the three tests, reaction time measured from stimulus occurrence to movement initiation (lift off); movement time measured from movement initiation to step finalisation (step down) and stepping errors are measured.
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Using Convolution Quadrature we can then prove time stepping error estimates.
The two models produce similar stochastic errors, but Nanbu's model gives smaller time step errors.
Of these, 15 responded consistently for TMT-B, RTD and step errors, though one of the 5 non-responders showed a 9% improvement and was just below the 10% responder criteria.
Effectiveness of the optimization model approach to reduce the step errors was evaluated by comparing the DSM before and after adjustment.
To eliminate the gauge step errors of the random bouncing motions, we designed a reliable algorithm for step detection.
All but one of the misspecified models under cut-off p = 0.0001 were one-step errors.
Step errors were videotaped with a camera placed underneath the grid.
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