No abstract

No abstract

No abstract

This study explored whether the color of letters could influence letter discrimination task performances and whether this effect of color could be modulated by processing level (global vs. local) and attention level of color (color-attended vs. color-unattended). We used the Navon letters in red, green, or white as stimuli at a relatively small (Experiment 1) or large visual angle (Experiments 2, 3, and 4). Each experiment included two tasks: color-attended task in which participants were told to respond only to target letters in a designated color; color-unattended task in which color was task-irrelevant. Experiment 1 found that the responses to red stimuli were significantly faster than those to the other color stimuli in the color-attended task. In Experiment 2, the same pattern occurred only at the local level in the color-attended task. Experiments 3 and 4 further controlled the brightness and chroma of stimuli and the results replicated the enhancement effect of red at the local level in the color-attended task and demonstrated an interference effect of red and green in the color-unattended task. These results suggested that red facilitated letter discrimination at the local processing level, reflecting the effect of avoidance motivation evoked by red on cognition and behavior which was consistent with color-in-context model. Moreover, this study found that the effect of color was modulated by attention level of color, and the interference effect of color in the color-unattended task confirmed that the color effect might mainly arise from controlled processes but not automatic processes.

Criticality experiments are the foundation of the criticality safety validation, the reactor parameter prediction and the nuclear data validation. Criticality experiments have been used in the field of nuclear data adjustment in the last decades. In applications like criticality safety validations and nuclear data adjustments, many criticality experiments are used together in one application. In practice, experts found that some experiments have bad influence in nuclear data adjustments, and they excluded them in these applications. But the reason why these experiments should be excluded is not clear. To give these exclusion a clear physical explanation, we have developed the cross-evaluation method, which could evaluate the random biases of the experimental results by analyzing the C − E (Calculation result - Experiment result) values of similar experiments. In this paper, we use the cross-evaluation method to assess the random biases of some highly enriched metal uranium fast criticality experiments. By the cross-evaluation method, experts could choose criticality experiments which should be used in the applications of criticality safety validations or nuclear data adjustments, and might find the reason why some experiments should be excluded in applications of nuclear data adjustments.