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When people make decisions about sequentially presented items in psychophysical experiments, their decisions are always biased by their preceding decisions and the preceding items, either by assimilation (shift towards the decision or item) or contrast (shift away from the decision or item). Such sequential biases also occur in naturalistic and real-world judgments such as facial attractiveness judgments. In this article, we aimed to cast light on the causes of these sequential biases. We first found significant assimilative and contrastive effects in a visual face attractiveness judgment task and an auditory ringtone agreeableness judgment task, indicating that sequential effects are not limited to the visual modality. We then found that the provision of trial-by-trial feedback of the preceding stimulus value eliminated the contrastive effect, but only weakened the assimilative effect. When participants orally reported their judgments rather than indicated them via a keyboard button press, we found a significant diminished assimilative effect, suggesting that motor response repetition strengthened the assimilation bias. Finally, we found that when visual and auditory stimuli were alternated, there was no longer a contrastive effect from the immediately previous trial, but there was an assimilative effect both from the previous trial (cross-modal) and the 2-back trial (same stimulus modality). These findings suggested that the contrastive effect results from perceptual processing, while the assimilative effect results from anchoring of the previous judgment and is strengthened by response repetition and numerical priming.

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.

Sound environment plays an important role in urban open spaces, yet studies on the effects of perception of the sound environment on crowd behaviors have been limited. The aim of this study, therefore, is to explore how music, which is considered an important soundscape element, affects crowd behaviors in urban open spaces. On-site observations were performed at a 100 m × 70 m urban leisure square in Harbin, China. Typical music was used to study the effects of perception of the sound environment on crowd behaviors; then, these behaviors were classified into movement (passing by and walking around) and non-movement behaviors (sitting). The results show that the path of passing by in an urban leisure square with music was more centralized than without music. Without music, 8.3% of people passing by walked near the edge of the square, whereas with music, this percentage was zero. In terms of the speed of passing by behavior, no significant difference was observed with the presence or absence of background music. Regarding the effect of music on walking around behavior in the square, the mean area and perimeter when background music was played were smaller than without background music. The mean speed of those exhibiting walking around behavior with background music in the square was 0.296 m/s slower than when no background music was played. For those exhibiting sitting behavior, when background music was not present, crowd density showed no variation based on the distance from the sound source. When music was present, it was observed that as the distance from the sound source increased, crowd density of those sitting behavior decreased accordingly.