Large amount of data are exchanged and the internet is turning into twenty-first century Silk Road for data. Machine learning (ML) is the new area for the applications. The artificial intelligence (AI) is the field providing machines with intelligence. In the last decades, more developments have been made in the field of ML and deep learning. The technology and other advanced algorithms are implemented into more computational constrained devices. The online English test system based on ML breaks the shackles of (...) the traditional paper English test and improves the efficiency of the English test. At the same time, it also maintains the fairness of English test and improves the marking speed. In order to realize an online English test system based on ML and facilitate the assessment of students’ college English courses, this paper mainly adopts relevant research and design on the main functional modules, key technologies, and functional realization of the online English test. The brand-new powerful teaching software and the online examination system can help schools to conduct more systematic and scientific management. The conclusion shows that as brand-new and powerful teaching software, the online examination system can help schools to conduct more systematic and scientific management. (shrink)

Previous studies have shown the operational potential in political discourse analysis from the proximization perspective. This study adopts a cross-disciplinary approach to analyze political communication across transcultural contexts, especially in the cyber discourse space. Based on the spatial–temporal–axiological model, we compare the journalistic discourses on two social media platforms by China Xinhua News Agency, an official speaker for China worldwide. The corpuses are constructed with microblogs on Weibo in Chinese and Twitter in English containing key words of Sino–US trade war. (...) It is found that the speaker has shaped different realities of discourse in accordance with the cultural contexts and proximized from corresponding dimensions to increase political legitimacy. (shrink)

The purpose of this study was to evaluate the international scientific output on postpartum depression research during 2000–2020 through a bibliometric analysis and to explore research hotspots, frontiers, and trends in the field of postpartum depression. We searched the Web of Science Core Collection for publications on postpartum depression published between 2000 and 2020. CiteSpace, gCluto, and other software applications were used to analyze the data by year, journal, and country. A total of 2,963 publications were retrieved and 96 countries (...) or regions published related papers. The United States had the largest number of published papers and the highest betweenness centrality, which is the dominant position in the field of postpartum depression. A total of 717 journals published papers, with the Archives of Womens Mental Health ranked first in terms of volume and betweenness centrality. In this study, 31 high-frequency main MeSH terms/subheadings were selected. The high-frequency MeSH terms were clustered into six categories: an overview of depression-related research, diagnostic and screening scales for postpartum depression, epidemiological investigation into postpartum depression, treatment and drug selection for postpartum depression, psychological research on postpartum depression, and etiology, physiopathology, complications, genetics of postpartum depression. Finally, we used strategic diagram to analyze research trends in postpartum depression. This study has identified a continuous significant increase in the publication of PPD articles. Currently, the etiology, physiological pathology, intervention and treatment of complications on PPD are immature, which provides reference for the trend of obstetric psychology. (shrink)

The ventrolateral prefrontal cortex plays a pivotal role in cognitive reappraisal. Previous studies suggested a functional asymmetry of the bilateral VLPFC, but the evidence is still insufficient during cognitive reappraisal. In this study, we conducted an online single-pulse transcranial magnetic stimulation to investigate the causal and distinct roles of the left and right VLPFC in reappraisal. Participants were instructed to reappraise or attend to pictures depicting social exclusion scenarios while the spTMS was applied over the left or right VLPFC of (...) the participants’ brains. The results showed that spTMS of either the left or the right VLPFC would increase reappraisal difficulty. Meanwhile, the outcome of reappraisal significantly deteriorated when the right VLPFC was temporally interrupted by spTMS, while the verbal fluency during oral reporting of the reappraisal strategy was significantly reduced when the left VLPFC was interrupted by spTMS. Taken together, these findings provide causal evidence for the involvement of left and right VLPFC with distinct roles: while the left VLPFC is responsible for the linguistic especially semantic process of generating and selecting appraisals according to the goal of emotion regulation, the right VLPFC plays a critical role in inhibiting inappropriate negative emotions and thoughts generated by the effective scenarios. These findings deepen our understanding of the neurocognitive mechanism of emotion regulation. (shrink)

Despite the fact that human daily emotions are co-occurring by nature, most neuroscience studies have primarily adopted a univariate approach to identify the neural representation of emotion (emotion experience within a single emotion category) without adequate consideration of the co-occurrence of different emotions (emotion experience across different emotion categories simultaneously). To investigate the neural representations of multivariate emotion experience, this study employed the inter-situation representational similarity analysis (RSA) method. Researchers used an EEG dataset of 78 participants who watched 28 video (...) clips and rated their experience on eight emotion categories. The EEG-based electrophysiological representation was extracted as the power spectral density (PSD) feature per channel in the five frequency bands. The inter-situation RSA method revealed significant correlations between the multivariate emotion experience ratings and PSD features in the Alpha and Beta bands, primarily over the frontal and parietal-occipital brain regions. The study found the identified EEG representations to be reliable with sufficient situations and participants. Moreover, through a series of ablation analyses, the inter-situation RSA further demonstrated the stability and specificity of the EEG representations for multivariate emotion experience. These findings highlight the importance of adopting a multivariate perspective for a comprehensive understanding of the neural representation of human emotion experience. (shrink)

The complex bursting oscillation and bifurcation mechanisms in coupling systems of different scales have been a hot spot domestically and overseas. In this paper, we analyze the bursting oscillation of a generalized Duffing–Van der Pol system with periodic excitation. Regarding this periodic excitation as a slow-varying parameter, the system can possess two time scales and the equilibrium curves and bifurcation analysis of the fast subsystem with slow-varying parameters are given. Through numerical simulations, we obtain four kinds of typical bursting oscillations, (...) namely, symmetric fold/fold bursting, symmetric fold/supHopf bursting, symmetric subHopf/fold cycle bursting, and symmetric subHopf/subHopf bursting. It is found that these four kinds of bursting oscillations are symmetric. Combining the transformed phase portrait with bifurcation analysis, we can observe bursting oscillations obviously and further reveal bifurcation mechanisms of these four kinds of bursting oscillations. (shrink)

Clustering algorithm is one of the important research topics in the field of machine learning. Neutrosophic clustering is the generalization of fuzzy clustering and has been applied to many fields. This paper presents a new neutrosophic clustering algorithm with the help of regularization. Firstly, the regularization term is introduced into the FC-PFS algorithm to generate sparsity, which can reduce the complexity of the algorithm on large data sets. Secondly, we propose a method to simplify the process of determining regularization parameters. (...) Finally, experiments show that the clustering results of this algorithm on artificial data sets and real data sets are mostly better than other clustering algorithms. Our clustering algorithm is effective in most cases. (shrink)

ObjectiveThe objective of the study was to explore the relationship between social support and fatigue as well as the mediating role of social functioning on that relationship.BackgroundPsychosocial factors such as social support and social functioning may influence patients’ fatigue symptoms. There is limited evidence on the relationship between social support, social functioning, and fatigue in liver transplant recipients.MethodsA total of 210 patients with liver transplants from two tertiary hospitals were enrolled in the current study. Questionnaires used include one for general (...) demographic data, the Perceived Social Support Scale, Social Disability Screening Schedule, and Fatigue Symptom Inventory.ResultsA total of 126 recipients reported fatigue. Gender, residence, BMI, and liver function were the primary factors affecting fatigue. Social support was positively correlated with social functioning and was negatively correlated with fatigue. The effect of social support on fatigue was partially mediated by social functioning.ConclusionThe fatigue of liver transplant recipients should be attended to. The higher the social support, the lower the fatigue of liver transplant recipients. Social support may also reduce fatigue through social functioning. The liver transplant team should help the liver transplant recipient establish a social support system, restore social functioning, and reduce fatigue symptoms. (shrink)