ABSTRACTComputers are now able to automatically generate metaphors, but some automatically generated metaphors are more well received than others. In this article, we showed participants a series of “A is B” type metaphors that were either generated by humans or taken from the Twitter account “MetaphorIsMyBusiness”, which is linked to a fully automated metaphor generator. We used these metaphors to assess linguistic factors that drive metaphor appreciation and understanding, including the role of novelty, word frequency, concreteness, and emotional valence of (...) the topic and vehicle terms. We additionally assessed how these metaphors were understood in three languages, including English, Spanish, and Mandarin Chinese, and whether participants thought they had been generated by a human or a computer. We found that meaningfulness, appreciation, speed in finding meaning, and humanness ratings were reliably correlated with each other in all three languages, which we interpret to indicate a mor... (shrink)

We investigate how a broker firm’s initial public offering affects its analysts’ fiduciary duty of providing independent and objective recommendations. We find that the analysts of newly listed broker firms issue more positively biased recommendations in the first 2 to 3 years after their employers’ IPO than before the IPO. The increase in the recommendation bias is greater among analysts of affiliated brokers and brokers that raise additional capital after their IPO than among other analysts. Newly listed broker firms experience (...) significant increases in revenue and trading commission, and the increases are positively related to recommendation bias, after controlling for many other factors. More importantly, recommendation bias decreases as newly listed broker firms season and as the importance of trading commission declines. This suggests that public exposure through a broker firm’s IPO does not enhance the integrity and professional conduct of its financial analysts. Rather, economic incentives make financial analysts more accepting of unethical behavior. The overall results imply that the public trading of financial gatekeepers compromises the ethical relationship between financial service professionals and society in general. (shrink)

Legal Judgment Prediction (LJP) is a typical application of Artificial Intelligence in the intelligent judiciary. Current research primarily focuses on automatically predicting law articles, charges, and terms of penalty based on the fact description of cases. However, existing methods for LJP have limitations, such as neglecting document structure and ignoring case similarities. We propose a novel framework called Graph Contrastive Learning with Augmentation (GCLA) for legal judgment prediction to address these issues. GCLA constructs trainable document-level graphs for fact description, capturing (...) local and global context through sentence-level subgraphs. Graph augmentation enhances robustness. We introduce a comparison case relation perspective, using graph contrastive learning to model case-text label relationships effectively. Experimental results on real-world datasets demonstrate the competitive performance of GCLA. (shrink)

PurposeThis study aims to examine the mediating role recovery plays in the relationship between resilience and posttraumatic growth among breast cancer patients.MethodsA cross-sectional study design was implemented between January 02, 2021 and April 29, 2021. A total of 789 breast cancer patients from eight hospitals in Liaoning province were selected for participation in this study. These participants completed questionnaires, which included the Post-Traumatic Growth Inventory, EGO Resilience Scale and the Questionnaire about the Process of Recovery. The associated factors of PTG (...) were analyzed using hierarchical multiple regression. The proposed relationships among resilience, recovery, and PTG were checked by structural equation modeling analyses.ResultsThe average PTG score of breast cancer patients was 53.00 ± 28.30. PTG was positively correlated with both recovery and PTG.ConclusionBreast cancer patients were found to exhibit a moderate degree of PTG. Resilience was positively associated with PTG and recovery mediated the positive effect of resilience on PTG. Resilience might serve as a crucial protective factor that could explain positive growth in life-threatening illnesses through the mediating path of recovery. (shrink)

In this article, we use the two-sided market theory as a support and take the operating data of eight Chinese third-party payment platform companies as samples, based on pricing models and multiple regression analysis, to build a price feature model for a third-party payment platform. The results show that under the two-sided market environment, the scale of consumer and the same-side network externality of the merchant have a negative significant effect on the pricing of the third-party payment platform to the (...) seller; The market share of the platform and the bank fee cost of the platform have a positive significant effect on the pricing of a third-party payment platform to the merchant. At the same time, the same-side network externality of the seller, the scale of a merchant, and the selection of the business model of the platform have no significant effect on the pricing of the third-party payment platform to the merchant. These conclusions provide a scientific basis for a third-party payment platform enterprise to develop an appropriate pricing strategy and operating model. (shrink)

Neurite orientation dispersion and density imaging is a diffusion model specifically designed for brain magnetic resonance imaging. Despite recent studies suggesting that NODDI modeling might be more sensitive to brain development than diffusion tensor imaging, these studies were limited to a relatively small age range and mainly based on the manually operated region of interest analysis. Therefore, this study applied NODDI to investigate brain development in a large sample size of 214 subjects ranging in ages from 0 to 14. The (...) whole brain was automatically segmented into 122 regions. The maturation trajectory of each region was characterized by the time course of diffusion metrics and further quantified using nonlinear regression. The NODDI-derived metrics, neurite density index and orientation dispersion index, increased with age. And these two metrics were superior to the DTI-derived metrics in SVM regression models of age. The NDI in white matter exhibited a more rapid growth than that in gray matter. These diffusion indicators experienced conspicuous increases during early childhood and the growth speed slowed down in adolescence. Region-specific maturation patterns were described throughout the brain, including white matter, cortical and deep gray matter. These development patterns were evaluated and discussed on the basis of NODDI’s model assumptions. To summarize, this study verified the high sensitivity of NODDI to age over a crucial developmental period from newborn to adolescence. Moreover, the existing knowledge of brain development has been complemented, suggesting that NODDI has a potential capability in the investigation of brain development. (shrink)

Conditional automated driving [level 3, Society of Automotive Engineers ] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal (...) time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism. Each driver experienced takeover under the two-stage warning systems with four time intervals. The takeover performance and subjective opinions for time intervals and situation awareness were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation. Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers. (shrink)