Sentence examples for appreciable errors from inspiring English sources

This work shows that such an assumption may lead to appreciable errors under certain physiological conditions and proposes a new numerical approach to interpret voltage clamp experiment results.

Figures 4 and 5, with accompanying statistical analysis, confirm that full automation did not introduce appreciable errors.

However, this is not recommended in the case of coarse-textured soils such as that in the experimental plot because samples of this type of soil are easily overwetted and small amounts of free water can lead to appreciable errors in the measurements (Rhoades 1996).

The theoretical and experimental values of frequencies were in good agreement except in the case of thinner panels where there was appreciable error.

Thus, optical losses due to absorption in the low-iron glass can be ignored without introducing appreciable error that was made in the above calculations.

In this case, the used of steady model may bring appreciable error since the state probability of the power equipment is still in the transient period in most of the time.

This is only seen to cause appreciable error with low sphere-to-background contrast and small spheres, and hence, we expect that the impact on the test objects used in this study is likely to be minimal.

The analysis shows that the ability to accurately estimate past consumption based on survey or audit data, even in a relatively short time-horizon is prone to appreciable error — a mean absolute error of 426 Wh/day per customer on a mean consumption of 113 Wh/day per customer.

This might be marginally stable for sufficiently long for the ribosome to make an appreciable error rate.

Simulated results presented for a numerical example indicate that the motion-induced vibration can be considerable and that the vibration of the tail section can cause appreciable position errors.

Moreover, it has been shown that using only a single control gene can lead to appreciable normalization errors and that using several normalizers is preferable in order to compensate for the potential biases introduced by an inappropriate normalizer [19], [21] [22].