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“这个真的不好说.” (It is Hard to Say): Positioning, Graphicons, and Culture: A Multimodal Discourse Analysis of a WeChat Discussion
No full textThis article examined the intersection and interaction among positioning, communication modes, and culture by taking positioning theory as a theoretical framework. Data were collected from a WeChat discussion group where three Chinese international students engaged in a community of English as a second language (L2) literacies. A multimodal discourse analysis reveals that three WeChat group members creatively, freely, and deliberately used verbal language and graphicons along with their cultural beliefs and situational contexts to construct, negotiate, and sometimes reject positions. Findings also show that three types of self-other positioning were frequently constructed and negotiated through their discussions, such as the “Self-Agreed-to-Other,” “Self-Opposed-to-Other,” and “Self-Complained-to-Other” positioning. The “Self-Agreed-with-Other” positioning was explicitly conveyed, but the “Self-Opposed-to-Other” positioning was implicitly expressed, which can be attributed to one of the Chinese cultural values: face (mianzi). In addition, graphicons, such as emojis and stickers, were used to challenge first-order positioning and negotiate second-order positioning. Also, the semiotic sign @ used to specify WeChat message recipients performed illocutionary acts as including someone or excluding them from the discussion based on a specific interactional discourse. Graphicons, collectively and sometimes independently, were utilized to contribute to positions that not only provided or limited opportunities for L2 literacies practice but also invited or sometimes rejected community memberships. Future research on the incongruent verbal and nonverbal expression for different types of positioning is needed, especially when verbal language and graphicons are used collaboratively to design meaning
Fuzzy style flat-based clustering
No full textThe recently developed fuzzy style k-plane clustering (S-KPC) algorithm displays promising clustering quality by leveraging both similarities and distinguishable styles between samples on stylistic data. However, S-KPC becomes vulnerable to similar styles that are not easily distinguishable. In this study, a novel fuzzy style flat-based clustering (FSFC) algorithm is proposed to overcome this vulnerability. In FSFC, a style flat matrix (SFM) is designed to project samples onto appropriate flats while maintaining the styles of different clusters in a reasonable manner. Based on SFM, the core of FSFC is to learn the potentially intersecting manifold structures of clusters in the projected flat space to make samples with the same style close to the cluster center and simultaneously far away from the other cluster centers. Furthermore, the objective function of FSFC can provide scale flexibility for each flat in the projected flat space. In particular, the optimization problem of FSFC can be decomposed into a series of sub-problems about the flat parameters, which can be locally optimized using the concave-convex procedure (CCCP). Extensive experiments on both synthetic and real-world datasets demonstrate the competitive clustering performance of FSFC. Moreover, FSFC outperforms some state-of-the-art manifold clustering algorithms on six case studies about stylistic data
Reference prices and withdrawn acquisitions
No full textUsing a sample of 1525 withdrawn deals from 1981 to 2015 in the United States, we find that target firms close to their 52-week high prices after merger announcements have lower withdrawal probabilities. The effect is different across merger waves. The out-wave deals are sensitive to the target reference prices while in-wave deals are not. Moreover, targets with post-announcement prices close to 52-week high tend to have higher withdrawn returns and receive higher adjustments of offering prices in renegotiation. Overall, our results suggest that target post-announcement stock prices significantly affect deal outcomes
Assessment of Fungal Succession in Decomposing Swine Carcasses (Sus scrofa L.) Using DNA Metabarcoding
No full textThe decomposition of animal bodies is a process defined by specific stages, described by the state of the body and participation of certain guilds of invertebrates and microorganisms. While the participation of invertebrates in decomposing is well-studied and actively used in crime scene investigations, information on bacteria and fungi from the scene is rarely collected or used in the identification of important factors such as estimated time of death. Modern molecular techniques such as DNA metabarcoding allow the identification and quantification of the composition of microbial communities. In this study, we used DNA metabarcoding to monitor fungal succession during the decomposition of juvenile pigs in grasslands of New Jersey, USA. Our findings show that decomposition stages differ in a diversity of fungal communities. In particular, we noted increased fungal species richness in the more advanced stages of decomposition (e.g., bloat and decay stages), with unique fungal taxa becoming active with the progression of decay. Overall, our findings improve knowledge of how fungi contribute to forensically relevant decomposition and could help with the assessment of crime scenes
Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China
No full textThe current research aims to launch effective accounting fraud detection models using imbalanced ensemble learning algorithms for China A-Share listed firms. Based on a sample of 33,544 Chinese firm-year instances from 1998 to 2017, this research respectively established one logistic regression and four ensemble learning classifiers (AdaBoost, XGBoost, CUSBoost, and RUSBoost) by 12 financial ratios and 28 raw financial data. Additionally, we divided the sample into the train and test observations to evaluate the classifiers\u27 out-of-sample performance. In detail, we applied two metrics, namely, Area under the ROC (receiver operating characteristic) curve (AUC) and Area under the Precision-Recall curve (AUPR), to evaluate classifiers\u27 discriminability. In the supplement test, this study put forward an algebraic fused model on the basis of the four ensemble learning classifiers and introduced the sliding window technique. The empirical results showed that the ensemble learning classifiers can detect accounting fraud for the imbalanced China A-listed firms far more effectively than the logistic regression model. Moreover, imbalanced ensemble learning classifiers (CUSBoost and RUSBoost) effectively performed better than the common ensemble learning models (AdaBoost and XGBoost) in average. The algebraic fused model in the supplement test also obtained the highest average AUC and AUPR among all the employed algorithms. Our results offer firm support for the potential role of Machine Learning (ML)-based Artificial Intelligence (AI) approaches in reliably predicting accounting fraud with high accuracy. Similarly, for the Chinese settings, our ML-based AI offers utmost advantage in forecasting accounting fraud. Finally, this paper fills the research gap on the applications of imbalanced ensemble learning in accounting fraud detection for Chinese listed firms
Impact of Lipid Metabolism on Macrophage Polarization: Implications for Inflammation and Tumor Immunity
No full textMacrophage polarization is influenced by lipids, which also exert significant control over macrophage functions. Lipids and their metabolites are players in intricate signaling pathways that modulate macrophages’ responses to pathogens, phagocytosis, ferroptosis, and inflammation. This review focuses on lipid metabolism and macrophage functions and addresses potential molecular targets for the treatment of macrophage-related diseases. While lipogenesis is crucial for lipid accumulation and phagocytosis in M1 macrophages, M2 macrophages likely rely on fatty acid β-oxidation to utilize fatty acids as their primary energy source. Cholesterol metabolism, regulated by factors such as SREBPs, PPARs, and LXRs, is associated with the cholesterol efflux capacity and the formation of foam cells (M2-like macrophages). Foam cells, which are targets for atherosclerosis, are associated with an increase in inflammatory cytokines. Lipolysis and fatty acid uptake markers, such as CD36, also contribute to the production of cytokines. Enhancing the immune system through the inhibition of lipid-metabolism-related factors can potentially serve as a targeted approach against tumor cells. Cyclooxygenase inhibitors, which block the conversion of arachidonic acid into various inflammatory mediators, influence macrophage polarization and have generated attention in cancer research
Development and Validation of the Parental Anxiety over a Child’s Education Scale: Evidence from China
No full textThis study was conducted to develop a self-report Parental Anxiety over Children’s Education Scale (PACES) and examine its psychometric properties in China. The study began with a qualitative phase to develop the scale’s items pool, then exploratory factor analyses with a sample of 1042 adults and confirmatory factor analyses with a sample of 1052 adults were conducted to identify the underlying structure of the scale. A PACES consists of 14 items and three dimensions: physiological, behavioral, and cognitive. Supplementary analysis with a number of demographic variables provided rich information about parental anxiety over their children’s education. Our results show that PACES is a valid and reliable instrument to assess parental anxiety over their children’s education in China
Cultural traits or social norms? Both responsibilism and norms linked to accepting COVID-19 vaccine
No full textWe studied the factors that influence attitudes toward the COVID-19 vaccine by testing 1872 people across 29 provinces in China. We investigated an individual trait (responsibilism) and two situational factors (a descriptive norm and an injunctive norm). Responsibilism is a version of collectivism that emphasizes tight social ties and responsibilities in close relationships. Responsibilism and perceptions of strong social norms predicted acceptance of the COVID-19 vaccine. The data also revealed an interplay between responsibilism and social norms. People high in responsibilism accepted the vaccine regardless of social norms. But people low in responsibilism were wary of the vaccine, unless they perceived strong injunctive norms. These findings contribute to the research on psychological factors behind vaccine hesitancy. The findings could help provide a roadmap for public health efforts to encourage vaccines
Distinct climatic regions drive antibiotic resistance genes dynamics across public parks and pristine soil ecosystems
No full textTo address the global concern of antibiotic resistance, a one-health concept is considered necessary that recognizes the interdependency between humans, animals and the environment, and acknowledges that each of these factors contributes to the evolution and rapid bloom of antibiotic resistance genes (ARGs). We implemented a GeoChip 5.0 strategy to examine the wide-spectrum profile of ARGs in the soil of urban parks and reference forests across three distinct climatic regions: Boreal (Lathi, Finland), Temperate (Baltimore, USA), and Tropical (Singapore). ARGs encoding multidrug resistance (MRGs) were among the most abundant, accounting for 90% of all ARGs detected. MRGs include MFS, MATE, Mex, SMR and ABC, which are involved in the transportation/efflux of multiple antibiotics. Multivariate analysis revealed that the ARG profile tends to be partitioned separately in urban parks and climatic regions. In addition, we opted to examine the impact of plant functional type (recalcitrant and labile tree litter, lawn) on ARGs. There was no significant influence of vegetation type on ARGs except in the tropical region, where its impact was evident as compared with boreal and temperate regions. More interestingly, the majority of ARGs were detected to have a higher relative abundance in the tropical region as compared to the boreal and temperate regions. Regional characteristics of the tropical area likely affects ARGs and the ARG-host profile, thereby boosting soil microbial abundances. Additionally, MFS, Mex, B_lactamase_A, vgb, ABC, Van, fosb, ABC_ multi, Tet and Mate_antibiotic were considerably more abundant in old parks as compared with young parks across the three climatic regions. Nevertheless, urban parks harboured a significantly higher abundance of ARGs than forests. Our study presents evidence of ARGs in varied climatic regions and provides valuable new insights in our understanding of ARGs in human-dominated environments as well as their prevalence in pristine ecosystems
Dark personality traits and sensation-seeking tourist behaviors. Is there a link? A preliminary investigation of Chinese tourists
No full textThe present study is the first attempt to understand sensation-seeking tourist behavior (SSTB) from the perspective of dark personality taxonomy of dark tetrad traits (DTT) (narcissism, Machiavellianism, psychopathy, and sadism) and how SSTB affects tourists\u27 destination revisit intention (DRI). The research setting is the world\u27s largest tidal bore viewing site, Qiantang River, Zhejiang Province, China. We use the theoretical inferences of the Push-Pull theory to understand the destination\u27s pull for sensation seeking and DTT as tourists\u27 push for sensation seeking. The results evidenced a clear distinction among the DTT concerning adaptive and maladaptive SSTB. Specifically, the tourists high on narcissism and Machiavellianism traits had high adaptive sensation seeking, and tourists high on psychopathy and sadism had high maladaptive sensation seeking. Both sensation-seeking forms were positively linked with revisit intentions. This study bridges the gap between personality and tourism scholarship and offers novel insights for practitioners