A Normative Study on English Translation of Metro Public Signs in China under the Cognitive Translatology: A Case Study of Chengdu the Host City for the Universiade

With the acceleration of its internationalization, China is faced with epochal task of optimizing its international-standard linguistic environment, which is especially impending for Chengdu, the host city for the Universiade. The neo-analysis, at first, sorts out and analyzes different versions of official translation norms for toponyms through document research, as well as from the first-hand resources on public signs of rail transit from TFL and MTA, and then, continues the empirical case study under the theoretical guidance of Cognitive Translatology. This paper has proposed several translation principles and a new method - Conceptual Motivation Mapping - for public signs, attempting to explore the way to build up its international discourse system consistent with the status of Chengdu as a global hub

Understanding Inclusive Education in the “Front of the Class” Movie in Chinese Perspective

To explore the beliefs of Inclusive Education in the film " Front of the class ", this study uses the method of content analysis to interpret and analyze this film from the perspective of the concept of inclusive education, inclusive family, inclusive school, and inclusive society. It found that the film contains rich beliefs and concepts of inclusive education, which helps to pursue the quality of education examine educational equity and social equity, provide intellectual support for the construction of inclusive society, responding the UN's sustainable development goal 4 (SDG 4) focuses on ensuring inclusive and equitable, quality education and lifelong learning opportunities for all

Consumers\u27 Repurchase Probability in Online Marketplace: A Belief Updating Perspective

It is commonly recognized that online transactions are “one-shot” transactions. However, a contemporary dataset from a dominant online marketplace in China reveals that averagely 24.3% transactions are repurchase transactions. Given that consumers already have purchase experience with a specific seller, their repurchase behavior may be influenced by both the seller’s reputation and their perceived seller performance. A consequent research question is: Whether and how do these two streams of information jointly affect consumers’ repurchase behavior? We adopt a belief update model, and also collect actual transaction data to examine this research question. Our findings include: (1) both seller reputation and consumers’ perceived seller performance have positive effects on consumers’ repurchase probability; (2) the effect of seller reputation is positively moderated by performance ambiguity; (3) consumers’ perceived seller performance has stronger effects on their repurchase probability when the seller has low reputation (vs. high reputation)

Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening

Vulvovaginal candidiasis (VVC) is the most prevalent human candidal infection, estimated to afflict approximately 75% of all women at least once in their lifetime. It will lead to several symptoms including pruritus, vaginal soreness, and so on. Automatic whole slide image (WSI) classification is highly demanded, for the huge burden of disease control and prevention. However, the WSI-based computer-aided VCC screening method is still vacant due to the scarce labeled data and unique properties of candida. Candida in WSI is challenging to be captured by conventional classification models due to its distinctive elongated shape, the small proportion of their spatial distribution, and the style gap from WSIs. To make the model focus on the candida easier, we propose an attention-guided method, which can obtain a robust diagnosis classification model. Specifically, we first use a pre-trained detection model as prior instruction to initialize the classification model. Then we design a Skip Self-Attention module to refine the attention onto the fined-grained features of candida. Finally, we use a contrastive learning method to alleviate the overfitting caused by the style gap of WSIs and suppress the attention to false positive regions. Our experimental results demonstrate that our framework achieves state-of-the-art performance. Code and example data are available at https://github.com/cjdbehumble/MICCAI2023-VVC-Screening.Comment: Accepted in the main conference MICCAI 202

Processing of Individual Items during Ensemble Coding of Facial Expressions

There is growing evidence that human observers are able to extract the mean emotion or other type of information from a set of faces. The most intriguing aspect of this phenomenon is that observers often fail to identify or form a representation for individual faces in a face set. However, most of these results were based on judgments under limited processing resource. We examined a wider range of exposure time and observed how the relationship between the extraction of a mean and representation of individual facial expressions would change. The results showed that with an exposure time of 50 ms for the faces, observers were more sensitive to mean representation over individual representation, replicating the typical findings in the literature. With longer exposure time, however, observers were able to extract both individual and mean representation more accurately. Furthermore, diffusion model analysis revealed that the mean representation is also more prone to suffer from the noise accumulated in redundant processing time and leads to a more conservative decision bias, whereas individual representations seem more resistant to this noise. Results suggest that the encoding of emotional information from multiple faces may take two forms: single face processing and crowd face processi