Sentence examples for experiment to adjust from inspiring English sources

The same preparations of DNA from HeLa, Daudi, and Jurkat cell lines were used as positive controls in every experiment to adjust for interassay variation.

In Figure 2, normalized transduction index (nTI) was computed by dividing TI by maximum TI in each experiment to adjust for differences due to cell culture variability; thus, error for maximal values for PAV 12 and PAV10 cannot be computed.

Among other data, we used in particular these experiments to adjust the parameter set for sub-model II.

Nevertheless, detailed experiments to adjust the optimum irradiation dose to obtain an efficient sterilisation of the water while minimizing the effect on the target compounds should be performed.

The animals were grouped and housed in stainless steel cages under good laboratory conditions (temperature 25°C ± 2°C) with a dark/light cycle (12/12 h) for minimum of 7 days before the beginning of the experiments, to adjust to the new environment and to overcome the stress possibly incurred during transit.

The problem is solved by means of an iterative strategy that – by sequentially designing a series of experiments – strives to adjust the settings of the experimental conditions by exploiting the results from previous experiments.

The relative trigger used for these experiments was to adjust the cantilever loading force to 1.5 nN to minimize the damage to the cells.

This is in line with the trade-off stability reported in Figure 6: subjects use the same sub-strategies throughout the course of the experiment without need to adjust to the experienced costs.

The inclusion of the identical reference samples from the same tissue in every batch in every experiment allows us to adjust for non-biological variation and hence be able to distinguish differences in gene expression due to the underlying disease biology from those due to confounding batch effects.

In that case Ab initio calculations, atomistic simulations and carefully designed experiments are necessary to adjust these parameters.

Design of experiments is used to adjust the parameters of the proposed MA and GA algorithms including the population size, crossover rate, and mutation rate.