The COVID-19 pandemic has caused tremendous loss starting from early this year. This article aims to investigate the change of anxiety severity and prevalence among non-graduating undergraduate students in the new semester of online learning during COVID-19 in China and also to evaluate a machine learning model based on the XGBoost model. A total of 1172 non-graduating undergraduate students aged between 18 and 22 from 34 provincial-level administrative units and 260 cities in China were enrolled onto this study and asked (...) to fill in a sociodemographic questionnaire and the Self-Rating Anxiety Scale twice, respectively, during February 15 to 17, 2020, before the new semester started, and March 15 to 17, 2020, 1 month after the new semester based on online learning had started. SPSS 22.0 was used to conduct t-test and single factor analysis. XGBoost models were implemented to predict the anxiety level of students 1 month after the start of the new semester. There were 184 and 221 students who met the cut-off of 50 and were screened as positive for anxiety, respectively, in the two investigations. The mean SAS scores in the second test was significantly higher than those in the first test. Significant differences were also found among all males, females, and students majoring in arts and sciences between the two studies. The results also showed students from Hubei province, where most cases of COVID-19 were confirmed, had a higher percentage of participants meeting the cut-off of being anxious. This article applied machine learning to establish XGBoost models to successfully predict the anxiety level and changes of anxiety levels 4 weeks later based on the SAS scores of the students in the first test. It was concluded that, during COVID-19, Chinese non-graduating undergraduate students showed higher anxiety in the new semester based on online learning than before the new semester started. More students from Hubei province had a different level of anxiety than other provinces. Families, universities, and society as a whole should pay attention to the psychological health of non-graduating undergraduate students and take measures accordingly. It also confirmed that the XGBoost model had better prediction accuracy compared to the traditional multiple stepwise regression model on the anxiety status of university students. (shrink)
This study examines whether community social capital in US counties, as captured by strength of civic norms and density of social networks in the counties, affects corporate social responsibility of resident corporations headquartered in the counties. Analyses of longitudinal data from 3688 unique US firms between 1997 and 2009 provide strong empirical support for the propositions that community social capital facilitates positive CSR activities that benefit non-shareholder stakeholders and constrains negative CSR activities that are detrimental to non-shareholder stakeholders. Additionally, we (...) explore the effects of institutional logics arising from community isomorphism on positive and negative CSR activities, respectively. And, we explore the respective effects of corporate engagement in positive and negative CSR activities on corporate financial performance. Firms undertake more positive CSR activities when such activities are more prevalent among other local corporations headquartered in the same county. But, there is no systematic relationship between negative CSR activities and the community-level corporate engagement in negative CSR activities. Positive CSR activities enhance a firm’s future financial performance, and the positive effect is more prominent among firms headquartered in counties with high community social capital. However, negative CSR activities only reduce a firm’s future financial performance among firms headquartered in counties with high community social capital; negative CSR activities do not affect performance among firms headquartered in counties with lower levels of community social capital. Collectively, these results highlight the distinct effects of local social institutions, namely community social capital, on positive CSR activities and negative CSR activities, respectively. (shrink)
Children bring intuitive arithmetic knowledge to the classroom before formal instruction in mathematics begins. For example, children can use their number sense to add, subtract, compare ratios, and even perform scaling operations that increase or decrease a set of dots by a factor of 2 or 4. However, it is currently unknown whether children can engage in a true division operation before formal mathematical instruction. Here we examined the ability of 6- to 9-year-old children and college students to perform symbolic (...) and non-symbolic approximate division. Subjects were presented with non-symbolic or symbolic dividends ranging from 32 to 185, and non-symbolic divisors ranging from 2 to 8. Subjects compared their imagined quotient to a visible target quantity. Both children and adults were successful at the approximate division tasks in both dots and numeral formats. This was true even among the subset of children that could not recognize the division symbol or solve simple division equations, suggesting intuitive division ability precedes formal division instruction. For both children and adults, the ability to divide non-symbolically mediated the relation between Approximate Number System acuity and symbolic math performance, suggesting that the ability to calculate non-symbolically may be a mechanism of the relation between ANS acuity and symbolic math. Our findings highlight the intuitive arithmetic abilities children possess before formal math instruction. (shrink)
In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, (...) the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)
Previous behavioral studies have identified the significant role of subliminal cues in creative problem solving. However, neural mechanisms of such unconscious processing remain poorly understood. Here we utilized an event-related potential approach and sandwich mask technique to investigate cerebral activities underlying the unconscious processing of cues in creative problem solving. College students were instructed to solve divergent problems under three different conditions . Our data showed that creative problem solving can benefit from unconscious cues, although not as much as from (...) conscious cues. More importantly, we found that there are crucial ERP components associated with unconscious processing of cues in solving divergent problems. Similar to the processing of conscious cues, processing unconscious cues in problem solving involves the semantic activation of unconscious cues in the right inferior parietal lobule , new association formation in the right parahippocampal gyrus , and mental representation transformation in the right superior temporal gyrus . The present results suggest that creative problem solving can be modulated by unconscious processing of enlightening information that is weakly diffused in the semantic network beyond our conscious awareness. (shrink)
The term “clear and distinct” is used by both Descartes and Husserl when they talk about the truth of an idea and the evidence of judgment. Although the words “clear” and “distinct” are juxtaposed with the conjunction “and,” this does not mean that their status is equal. If the concept of “evidence” can be used to characterize the hierarchical relationship between them, then we can say that, for Descartes, distinct evidence is higher than clear evidence. For Husserl, on the contrary, (...) clear evidence is higher than distinct evidence. Their opposing views concerning the hierarchy between clarity and distinctness is symptomatic of the differences between their two understandings of the epistemological relationship between intellect and sensibility, as well as of their respective ontological reach. (shrink)
In order to explore the correlation between students’ seat choice and interaction preference in the open gamification scenario, an experiment has been carried out on the platform of provincial virtual simulation experiment teaching center of a university, and tested the relationship between absolute distance, seat type, workstation type, and students’ interaction preference. The results show that in the virtual-reality fusion gamification scenario where students can move freely: The inner circle students can stimulate the outer circle students’ willingness to invest in (...) learning. The task attribute and the seat distribution of the group may lead to the difference of students’ interaction preference. Students are more likely to learn knowledge and skills by interacting with “people” rather than “object.” Gender and major influence students’ experience of participating in gamified teaching. The results confirm that the interactive engagement effect of location does exist in immersive virtual-reality fusion gamification teaching scenario, and suggestions are put forward to adjust the effect of location through instructional design and teacher intervention. (shrink)
Despite the vast academic interest in workplace helping, little is known about the impact of different types of helping behaviors on physiological and behavioral ramifications of helpers. By taking the actor-centric perspective, this study attempts to investigate the differential impacts of three kinds of helping behaviors on helpers themselves from the theory of resource conservation. To test our model, 512 Chinese employees were surveyed, utilizing a three-wave time-lagged design, and we found that caring and coaching helping were negatively associated with (...) workplace deviance, whereas substituting helping was positively associated with subsequent workplace deviance. Emotional exhaustion mediated the effects of three helping behaviors on subsequent workplace deviance. Moreover, employees' extrinsic career goals influenced the strength of the relationship between three helping behaviors and emotional exhaustion and the indirect effects of three helping behaviors on subsequent workplace deviance via emotional exhaustion. We discuss the implications of our findings for both theories and practices. (shrink)
BackgroundHigh levels of moral distress in nursing professionals, of which oncology nurses are particularly prone, can negatively impact patient care, job satisfaction, and retention.Aim“Positive Attitudes Striving to Rejuvenate You: PASTRY” was developed at a tertiary cancer center to reduce the burden of moral distress among oncology nurses.Research DesignA Quality Improvement (QI) initiative was conducted using a pre- and post-intervention design, to launch PASTRY and measure its impact on moral distress of the nursing unit, using Hamric’s Moral Distress Scale–Revised (MDS-R.) This (...) program consisted of monthly 60-minute sessions allowing nurses to address morally distressing events and themes, such as clinicians giving “false hope” to patients or families. The PASTRY program sessions were led by certified clinicians utilizing strategies of discussion and mind-body practices.ParticipantsClinical nurses working on an adult leukemia/lymphoma unit.Ethical considerationsThis was a QI initiative, participation was voluntary, MDS-R responses were collected anonymously, and the institution’s Ethics Committee oversaw PASTRY’s implementation.FindingsWhile improvement in moral distress findings were not statistically significant, the qualitative and quantitative findings demonstrated consistent themes. The PASTRY program received strong support from nurses and institutional leaders, lowered the nursing unit’s moral distress, led to enhanced camaraderie, and improved nurses’ coping skills.DiscussionMeasurement of moral distress is innately challenging due to its complexity. This study reinforces oncology nurses have measurable moral distress. Interventions should be implemented for a safe and healing environment to explore morally distressing clinical experiences. Poor communication among multidisciplinary team members is associated with moral distress among nurses. Programs like PASTRY may empower nurses to build support networks for change within themselves and institutions.ConclusionThis QI initiative shows further research on moral distress reduction should be conducted to verify findings for statistical significance and so that institutional programs, like PASTRY, can be created. (shrink)
A shortage or backlog of inventory can easily occur due to the backward forecasting method typically used, which will affect the normal flow of funds in pharmacies. This paper proposes a replenishment decision model with back propagation neural network multivariate regression analysis methods. With the regular pattern between sales and individual variables, supplemented with the safety stock empirical formula, an accurate replenishment quantity can be obtained. In the case analysis, this paper takes the sales situation of a pharmacy as an (...) example and tests the accuracy and stability of the model. The results show that the model has good prediction accuracy which can be introduced into the intelligent pharmacy system and used in the replenishment of the intelligent pharmacy to prevent overstocking or a shortage of stock, thus improving the financial situation, reducing the manpower burden of typical retail pharmacy, and helping residents buy medicines. (shrink)
This study explored the effect of word knowledge facets on second language Chinese lexical inference by highlighting the moderating effect of language proficiency level and learners’ heritage status. L2 Chinese learners with a mixture of linguistic and cultural backgrounds completed a series of word-knowledge measurements as well as a lexical inferencing task. Through a moderated path model, the study demonstrated that word-general knowledge and word-specific knowledge contributed to L2 Chinese lexical inference. In addition, the study underlined the moderating effect of (...) heritage status on the correlation between word knowledge and lexical inference. Given the distinct patterns between heritage and non-heritage learners, morphological awareness may define the characteristics of reading profiles in the Chinese heritage learner population. (shrink)
As an emerging form of online display advertising, in-feed native advertising is increasingly employed in online news feed platforms. While many advertisers have largely embraced this new advertising format, the current research is full of controversy on whether the more native, the better the effect of in-feed native advertising. Based on recent studies on this emerging topic, the authors explore the effective in-feed native advertising persuasion strategies based on consumers’ dynamic online browsing modes. In study 1, the authors conducted an (...) archived-data analysis. Results show that the match between in-feed native advertising persuasion style and consumers’ real-time news feed browsing modes can improve ad performance. In study 2, the authors further explained why consumers under different browsing modes respond differently to specific in-feed native advertising persuasion. Our work explores the boundaries of agency theory from a dynamic perspective and helps advertisers conduct real-time and effective targeting strategies. (shrink)
This study aims to achieve the goal of cultivating and reserving emerging professional talents in social security law, improve the curriculum and mechanism of entrepreneurship education, and improve students’ entrepreneurial willingness and entrepreneurial ability. Deep learning technology is used to study the psychological effects of entrepreneurship education for college students majoring in social security law. Firstly, the concept of entrepreneurial psychology is elaborated and summarized. A related model is designed using the theory of proactive personality and planned behavior through questionnaire (...) survey and regression analysis to explore the relationship between students’ entrepreneurial psychology and entrepreneurial intention. Secondly, an entrepreneurship education method based on deep learning is proposed, and a teaching model of multi-dimensional collaborative entrepreneurship education practice is constructed. On this basis, the deep learning algorithm combines the characteristics of the personalized recommendation algorithm to construct an efficient Problem-Based Learning learning resource recommendation algorithm. Finally, the proposed method is tested. The results show that the Significant value of students who have participated in PBL deep learning courses is less than 0.05, indicating that PBL significantly improves students’ learning ability and the ability to deal with entrepreneurial environments. The results verify the impact of entrepreneurial learning on entrepreneurial intentions. The research on PBL online learning recommendation system shows that the proposed recommendation algorithm is superior to the traditional recommendation algorithm in both roots mean square error value and mean absolute error value on both datasets. The proposed method provides a new idea of reform and innovation to cultivate social security law professionals and the cultivation of the reserve model. (shrink)