Sentence examples for faces generated by from inspiring English sources

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Scrambled faces (generated by a self-programmed software) served as the baseline condition, and motor control reflected a simple motor response task (reacting towards an unrelated target word out of two words) in order to subtract motor and reading related activity.

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(a) the PCA projections of 9 subjects' face images generated by varying viewpoints under one lighting condition.

(c) the PCA projections of 9 subjects' face images generated by varying lighting conditions under one viewpoint.

In this paper the second part of the subjective evaluation was assessed by 25 users, without any image processing background, with ages varying between 18 and 28 years, who evaluated 10 face images generated by the four compared methods, with one image per method (totaling 40 images per person).

Figures 7(a)– 7(h) illustrate the inverted intensity, SICR, SIV, SACR, SAV, LOGIV, DLOGIV, and DPV en face views generated by integrating their values between the region 30 μm posterior to the vitreoretinal interface and the region 130 μm anterior to IS/OS. Figure 7(a) shows that the meshwork of capillaries is barely visible in the intensity en face view.

In addition, after the first 10 ns of the simulation, Tyr from monomer A rotated away from Thr and utilized a different rotamer such that the side chain faced the cavity generated by the mutation of Tyr to cysteine (Supplementary Figure S12B), increasing the distance from Thr to ~14 Å (Supplementary Figure S11C).

They might, for example, face bad publicity generated by an upheld complaint to the ASA.

Biological systems are continuously faced with variability generated by both internal and external sources.

To show the capillary meshwork of the inner retina through depth using logarithmic intensity-based motion contrast methods, the LOGIV and DLOGIV en face views are generated by integrating their values through different depths.

Several depth integrated motion contrast en face images were generated by integrating the SICR, SACR, SIV, SAV, LOGIV, DLOGIV, and DPV between three different regions in the inner retina relative to IS/OS and vitreoretinal interface.

The ICER for full development and implementation of U@Uni (£22,844) falls towards the upper end of this range and the ICER for roll-out of U@Uni falls towards the lower end of the range, suggesting that an online multiple behaviour intervention can generate a similar ratio of costs to benefits as that generated by face-to-face interventions.

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