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In line with our prediction, subjects were better at detecting manipulations that included physically implausible changes (geometrical inconsistencies, shadow inconsistencies, and super-additive manipulations) than images that included physically plausible changes (airbrushing alterations and addition or subtraction of objects).
To test this last prediction, subjects also underwent a low-level Vigilance Task scan before performing the Fact Encoding Task scans.
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Figure 1 Example of a calibrated femtocell coverage prediction subject to diffraction errors due to lower-frequency FDTD simulation.
Also consistent with our predictions, subjects viewed newcomers especially negatively, more negatively than one might expect by extrapolating from other tenure lengths.
Therefore, it is important to test the robustness of the estimates of model parameters and model predictions subject to such physiological variation.
The present study provides a quantitative reevaluation of the previous uniporter model [11] to test the robustness of the estimates of model parameters and model predictions subject to physiologically reasonable variation in matrix [Ca2+] ranging from 100 nM to 500 nM.
The second line shows predictions subject to the current sample { θS} for a different experiment.
In addition to the prediction of subjects' recall performance, we evaluated a relationship between subjects' and computational recall orders that may further clarify the dynamic of theta phase precession.
The sequential choice model provided the most comprehensive and accurate prediction of subjects' preferences.
Ingrid, in her studies, found that spell-check programs combined with word prediction allow subjects to write longer sentences and make fewer mistakes.
To evaluate our prediction Caucasian subjects were trained on African American faces.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com