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Assessing the olfactory preferences of consumers is an important aspect of fragrance product development and marketing. With the advancement of wearable device technologies, physiological signals hold great potential for evaluating olfactory preferences. However, there is currently a lack of relevant studies and specific explanatory procedures for preference assessment methods that are based on physiological signals. In response to this gap, a synchronous data acquisition system was established using the ErgoLAB multi-channel physiology instrument and olfactory experience tester. Thirty-three participants were recruited for the olfactory preference experiments, and three types of autonomic response data (skin conductance, respiration, and heart rate) were collected. The results of both individual and overall analyses indicated that olfactory preferences can lead to changes in skin conductance (SC), respiration (RESP), and heart rate (HR). The trends of change in both RESP and HR showed significant differences (with the HR being more easily distinguishable), while the SC did not exhibit significant differences across different olfactory perception preferences. Additionally, gender differences did not result in significant variations. Therefore, HR is more suitable for evaluating olfactory perception preferences, followed by RESP, while SC shows the least effect. Moreover, a logistic regression model with a high accuracy (84.1%) in predicting olfactory perception preferences was developed using the changes in the RESP and HR features. This study has significant implications for advancing the assessment of consumer olfactory preferences. [ABSTRACT FROM AUTHOR]

Affective human–vehicle interaction of intelligent cockpits is a key factor affecting the acceptance, trust, and experience for intelligent connected vehicles. Driver emotion detection is the premise of realizing affective human–machine interaction. To achieve accurate and robust driver emotion detection, we propose a novel brain-inspired framework for on-road driver emotion detection using facial expressions. Then, we conduct driver emotion data collection in an on-road context. We develop a data annotation tool, annotate the collected data, and obtain the RoadEmo dataset, a dataset of facial expressions and road scenarios under the driver’s emotional driving. Finally, we validate the detection accuracy of the proposed framework. The experiment results show that our proposed framework achieves excellent detection performance in the on-road driver emotion detection task and outperforms existing frameworks. [ABSTRACT FROM AUTHOR]

Objective: This study aims to quantify the impact of olfactory stimulation and takeover modality on the performance of takeovers in conditionally automated driving.Background: Takeover requests are important for the safety of automated vehicles. The reaction time and subsequent performance of drivers in the takeover process are crucial for safety. In this study, peppermint was adopted as an auxiliary modality to the tactile and auditory design of takeover requests.Methods: Sixty participants took part in the experiment, which required participants to avoid a stalled vehicle after they were awoken from a state of light sleep by a takeover request. Takeover modality (tactile, auditory, and combined) was the within-subjects factor. In the between-subjects design, half of the participants received a peppermint odor stimulation when the takeover request occurred, and the other half received a placebo (air).Results: The presence of peppermint odor did not influence the reaction time, but participants did show signs of being more alert afterwards. For the moment of takeover, use of the auditory modality had a significant positive effect on reaction time compared to the tactile conditions.Conclusion: Peppermint odor had a positive impact on drivers' takeover quality when engaged in nondriving-related activities such as light sleep, and the takeover request modalities were shown to be crucial for a safe and successful takeover.Application: The results will be useful as a reference for developers of automated driving systems to design human-machine interfaces, shorten the driver's reaction time, and improve takeover quality. [ABSTRACT FROM AUTHOR]

Tooth development is accomplished by a series of epithelial-mesenchyme interactions. Epithelial Wnt/β-catenin signaling is sufficient to initiate tooth development by activating Shh, Bmps, Fgfs and Wnts in dental epithelium, which in turn, triggered the expression of odontogenic genes in the underlying mesenchyme. Although constitutive activation of Wnt/β-catenin signaling in oral ectoderm resulted in the continuous tooth formation throughout the life span, if the epithelial Wnt/β-catenin signaling could induce the mesenchyme other than oral mesenchyme still required to be elucidated. In this study, we found that in the K14-cre; Ctnnb1ex3f mice, the markers of dental epithelium, such as Pitx2, Shh, Bmp2, Fgf4, and Fgf8, were not only activated in the oral ectoderm, but also in the cheek epithelium. Surprisingly, the underlying cheek mesenchymal cells were elongated and expressed Dspp. Further investigations detected that the expression of Msx1 and Runx2 extended from oral to cheek mesenchyme. These findings suggested that epithelial Wnt/β-catenin signaling was capable of inducing Dspp expression in non-dental mesenchyme. Moreover, Dspp expression in the K14-cre; Ctnnb1ex3f oral mesenchyme was activated earlier than that in the wild type littermates. In contrast, although the elongated oral epithelial cells were detected in the K14-cre; Ctnnb1ex3f mice, the Amelogenin expression was suppressed. The differential effects of the persistent epithelial Wnt/β-catenin signaling on ameloblast and odontoblast differentiation might result from the altered BMP signaling. In summary, our findings suggested that the epithelial Wnt/β-catenin signaling could induce craniofacial mesenchyme into odontogenic program and promote odontoblast differentiation. [ABSTRACT FROM AUTHOR]