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The rapid development of image processing technology and the improvement of computing power in recent years have made deep learning one of the main methods for plant disease identification. Currently, many neural network models have shown better performance in plant disease identification. Typically, the performance improvement of the model needs to be achieved by increasing the depth of the network. However, this also increases the computational complexity, memory requirements, and training time, which will be detrimental to the deployment of the model on mobile devices. To address this problem, a novel lightweight convolutional neural network has been proposed for plant disease detection. Skip connections are introduced into the conventional MobileNetV3 network to enrich the input features of the deep network, and the feature fusion weight parameters in the skip connections are optimized using an improved whale optimization algorithm to achieve higher classification accuracy. In addition, the bias loss substitutes the conventional cross-entropy loss to reduce the interference caused by redundant data during the learning process. The proposed model is pre-trained on the plant classification task dataset instead of using the classical ImageNet for pre-training, which further enhances the performance and robustness of the model. The constructed network achieved high performance with fewer parameters, reaching an accuracy of 99.8% on the PlantVillage dataset. Encouragingly, it also achieved a prediction accuracy of 97.8% on an apple leaf disease dataset with a complex outdoor background. The experimental results show that compared with existing advanced plant disease diagnosis models, the proposed model has fewer parameters, higher recognition accuracy, and lower complexity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Quan, Wang, Jia, Yang and Xu.)

When many people say the same thing, the individual is more likely to endorse this information than when just a single person says the same. Yet, the influence of consensus information may be modulated by many personal, contextual and cultural variables. Here, we study the sensitivity of Chinese ( N = 68) and Spanish ( N = 82) preschoolers to consensus in social decision making contexts. Children faced two different types of peer-interaction events, which involved (1) uncertain or ambiguous scenarios open to interpretation (social interpretation context), and (2) explicit scenarios depicting the exclusion of a peer (moral judgment context). Children first observed a video in which a group of teachers offered their opinion about the events, and then they were asked to evaluate the information provided. Participants were assigned to two conditions that differed in the type of consensus: Unanimous majority ( non-dissenter condition) and non-unanimous majority ( dissenter condition). In the dissenter condition, we presented the conflicting opinions of three teachers vs. one teacher. In the non-dissenter condition, we presented the unanimous opinion of three teachers. The general results indicated that children's sensitivity to consensus varies depending both on the degree of ambiguity of the social events and the presence or not of a dissenter: (1) Children were much more likely to endorse the majority view when they were uncertain (social interpretation context), than when they already had a clear interpretation of the situation (moral judgment context); (2) The presence of a dissenter resulted in a significant decrease in children's confidence in majority. Interestingly, in the moral judgment context, Chinese and Spanish children differed in their willingness to defy a majority whose opinion run against their own. While Spanish children maintained their own criteria regardless of the type of condition, Chinese children did so when an "allied" dissenter was present (dissenter condition) but not when confronting a unanimous majority (non-dissenter condition). Tentatively, we suggest that this difference might be related to culture-specific patterns regarding children's deference toward adults.