Understanding the role of teachers’ facial expressions in students’ learning is helpful to improve online teaching. Therefore, this study explored the effects of teacher’s facial expressions on students’ learning through analyzing three groups of video lectures. Participants were 78 students enrolled in three groups: one with an enhanced-expression teacher, one with a conventional-expression teacher, and one with the teacher’s audio only. ANOVA was used to explore whether video lectures instructed by the enhanced-expression teacher were better than those instructed by the (...) conventional-expression teacher and the audio-only teacher for facilitating students’ learning, and what is the role of the teacher’s emotions in students’ perceived social presence, arousal level, cognitive load, and learning. The results showed that the video lecture by the enhanced-expression teacher was better than those with the conventional-expression teacher and with the audio-only for facilitating students’ social presence, arousal level, and long-term learning. Interestingly, it was found that the teacher’s emotions could relieve students’ cognitive load. These results explained the inconsistency of existing studies by exploring the mechanism of teachers’ emotions in students’ learning. It also provides teachers with practical guidance for video lecture design. (shrink)

For synchronization of a class of chaotic systems in the presence of nonvanishing uncertainties, a novel time-varying gain observer-based sliding mode control is proposed. First, a novel time-varying gain disturbance observer is developed to estimate the uncertainties. Then, by using the output of TVGDO to modify sliding mode control, a new TVGDO-based SMC scheme is developed. Although the observation and control precision of conventional fixed gain disturbance observer-based control for chaotic systems can be guaranteed by a high observer gain, the (...) undesirable spike problem may be caused by the high gain if the initial values of estimate and true states are not equal. The most attractive feature of this work is that the newly proposed TVGDO can eliminate the spike problem by developing a time-varying gain scheme. Finally, the effectiveness of the proposed method is demonstrated by the numerical simulation. (shrink)

As the most frequently used tool for measuring empathy, the Interpersonal Reactivity Index (IRI) is often scored by researchers arbitrarily and casually. Many commonly used IRI scoring approaches and their corresponding measurement models are unverified, which may make the conclusions of subsequent variable relation studies controversial and even misleading. We make the first effort to summarize these measurement models and to evaluate rationality of the common scoring methods of the IRI by confirmatory factor analysis, focusing on model fitting, factor loading, (...) and model-based reliability simultaneously. The results show that most of these models do not fit well, indicating that the scoring approaches of the IRI corresponding to these models may be problematic. Relatively speaking, better scoring approaches of the IRI include summing empathic concern and perspective taking as the total score of the IRI and reporting the score of perspective taking as cognitive empathy. (shrink)

In 2011, Jiangsu Province set up the guidance fund for sports industry. In 2016, Jiangsu Provincial Finance Department jointly issued the document with Jiangsu Provincial Sports Bureau, which was changed to “Jiangsu Special Fund for Sports Industry Development.” By 2019, Jiangsu Province has funded 1,009 sports industry development projects with a total investment of 796.6 million yuan. The effect of the investment has attracted extensive attention from the government, society, and enterprises. Entrusted by Jiangsu Sports Industry Guidance Center, this research (...) team spent one year on the performance research of 1,009 projects supported by special funds for the development of sports industry, from the construction of evaluation index system to the design, issuance, collection, and processing of questionnaires. Using the methods of literature, questionnaire, expert interview, and mathematical statistics, this paper takes the performance management of the special funds for the development of sports industry in Jiangsu Province as the research object, based on the investigation and analysis of the current situation of the special funds for the development of sports industry in Jiangsu Province. It analyzes the special funds from four aspects: the rate of funds in place, the ratio of funds pulled, the completion rate of project implementation, and the rate of fund prerecovery. Then, this paper expounds the current situation, effectiveness, and problems of the performance management of the special funds for the development of sports industry and puts forward some countermeasures and suggestions for improvement. (shrink)

Based on the social identity theory, the relationship and influencing mechanism between high-performance human resource practices and employees’ voice behavior were explored by constructing a moderated mediation model, and the relationship between the field of human resources and the field of organizational behavior was also established. Through 1,178 paired samples of supervisor-employee survey and multilevel linear model analysis technology, it was found that HPHRPs had a positive impact on employees’ voice behavior; perceived insider status played a mediating role between HPHRPs (...) and voice behavior; voice efficacy played a moderating role between perceived insider status and voice behavior; and voice efficacy played a mediating role in the relationship between “HPHRPs-perceived insider status-voice behavior.”. (shrink)

PurposeDrawing upon the stimulus-organism-response model, this paper aims to investigate the effects of stores’ environmental components on Chinese consumers’ emotions and intentions to purchase luxury brands.Design/Methodology/ApproachData were collected from Chinese consumers who have purchased luxury brands from retail stores. Partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis were employed for data analysis.FindingsThe results of PLS-SEM indicated that three dimensions of the store environment directly and significantly influenced Chinese consumers’ emotions. However, fsQCA revealed greater heterogeneity among respondents by highlighting (...) stores’ environmental components and Chinese consumers’ emotions.Originality/ValueThis study makes significant contributions to the marketing literature by examining the S-O-R model alongside fsQCA approach to conditionally predict outcomes in a luxury brand context. The present study may be one of the first to examine the effects of stores’ environmental components on Chinese consumers’ emotions and purchase intentions, applying both symmetrical test and asymmetrical test approaches to determine significant components of the store environment as well as component combinations that predict Chinese consumers’ emotions and purchase intentions. (shrink)

It is largely acknowledged that natural languages emerge not just from human brains but also from rich communities of interacting human brains (Senghas, ). Yet the precise role of such communities and such interaction in the emergence of core properties of language has largely gone uninvestigated in naturally emerging systems, leaving the few existing computational investigations of this issue at an artificial setting. Here, we take a step toward investigating the precise role of community structure in the emergence of linguistic (...) conventions with both naturalistic empirical data and computational modeling. We first show conventionalization of lexicons in two different classes of naturally emerging signed systems: (a) protolinguistic “homesigns” invented by linguistically isolated Deaf individuals, and (b) a natural sign language emerging in a recently formed rich Deaf community. We find that the latter conventionalized faster than the former. Second, we model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals' actual sign use, following an independently motivated model of language learning (Yang, , ). Simulations suggest that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network, like that of homesign systems. We discuss our behavioral and computational results in light of other work on language emergence, and other work of behavior on complex networks. (shrink)

Fecal microbiota transplantation is reportedly the most effective therapy for relapsing Clostridium Difficile infection and a potential therapeutic option for many diseases. It also poses important ethical concerns. This study is an attempt to assess clinicians’ perception and attitudes towards ethical and social challenges raised by fecal microbiota transplantation. A questionnaire was developed which consisted of 20 items: four items covered general aspects, nine were about ethical aspects such as informed consent and privacy issues, four concerned social and regulatory issues, (...) and three were about an FMT bank. This was distributed to participants at the Second China gastroenterology and FMT conference in May 2015. Basic descriptive statistical analyses and simple comparative statistical tests were performed. Nearly three quarters of the 100 respondents were gastro-enterologist physicians. 89% of all respondents believed FMT is a promising treatment modality for some diseases and 88% of whom chose clinical efficacy as the primary reason for recommending FMT. High expectation from patients and pressure on clinicians was reported as the most frequent reasons for not recommending FMT. The clinicians who had less familiarity with FMT reported significantly more worry related to the dignity and psychological impact of FMT compared to those who have high familiarity with FMT.More than half of the respondents were concerned about the commercialization of FMT, although almost one in five respondents did not see this as a problem. We found most respondents have positive attitudes towards FMT but low awareness of published evidence. Informed consent for vulnerable patients, privacy and protection of donors were perceived as the most challenging ethical aspects of FMT. This study identified areas of limited knowledge and ways of addressing ethical issues and indicates the need to devise the education and training for clinicians on FMT. (shrink)

It can be a great challenge for second language learners to comprehend meanings that are implied in utterances rather than the surface meaning of what was said. Moreover, L2 learners’ attitudes toward pragmatic learning are unknown. This mixed-methods study investigates L2 learners’ ability to comprehend conversational implicatures. It also explores their beliefs about and intentions to develop this ability using Ajzen’s theory of planned behavior. A total of 498 freshmen from a public university in China participated in the study. Data (...) were collected using a web-based test, stimulated recall tasks and semi-structured interviews. Results show that the participants differed in recognizing the intended meanings. Complicated factors account for the variations. In addition to the types of implicature, learners’ beliefs about developing pragmatic comprehension also influence their learning intention, and subsequent performance. These beliefs include learners’ multi-layered, complex attitudes toward the outcomes of pragmatic learning, perceived self-efficacy beliefs regarding language proficiency and L2 cultural knowledge, actual behavioral control over opportunities and resources for pragmatic learning, and perceptions of less social pressure on pragmatic learning. The use of TPB may help language teachers and test designers to understand learners’ beliefs about L2 pragmatic learning in the English as a foreign language context. Understanding the factors influencing learners’ intention will help design more effective teaching curricula that may integrate pragmatic instruction and testing in the future. (shrink)

Fall prediction using machine learning has become one of the most fruitful and socially relevant applications of computer vision in gerontological research. Since its inception in the early 2000s, this subfield has proliferated into a robust body of research underpinned by various machine learning algorithms (including neural networks, support vector machines, and decision trees) as well as statistical modeling approaches (Markov chains, Gaussian mixture models, and hidden Markov models). Furthermore, some advancements have been translated into commercial and clinical practice, with (...) companies in various stages of development capitalizing on the aging population to develop new commercially available products. Yet despite the marvel of modern machine learning-enabled fall prediction, little research has been conducted to shed light on the security and privacy concerns that such systems pose for older adults. The present study employs an interdisciplinary lens in examining privacy issues associated with machine learning fall prediction and exploring the implications of these models in elderly care and the Internet of Medical Things (IoMT). Ultimately, a justice-informed set of best practices rooted in social geroscience is suggested to help fall prediction researchers and companies continue to advance the field while preserving elderly privacy and autonomy. (shrink)

Yang returns to the problem of referential ambiguity, addressed in the opening paper by Gleitman and Trueswell. Using a computational approach, he argues that “big data” approaches to resolving referential ambiguity are destined to fail, because of the inevitable computational explosion needed to keep track of contextual associations present when a word is uttered. Yang tests several computational models, two of which depend on one‐trial learning, as described in Gleitman and Trueswell’s paper. He concludes that such models outperform (...) cross‐situational learning models, thereby formalizing, reinforcing, and advancing the conclusions offered by Gleitman and Trueswell. (shrink)

In the film “Kaili Blues” by Bi Gan, intricate clues create complex connections between the plots steered by various characters. This relationship manifests in splitting time and alternating between dream and reality. This article analyzes Bi Gan’s approach to temporality and dreams by focusing on how he employs various film metaphors to deal with poetic narratives in his films. The article consists of three sections: First, it introduces the (puzzle) storytelling form of “Kaili Blues” as a promising area in many (...) Chinese films. Second, it examines how puzzle films contribute to the ambiguity (plots) between characters from the perspective of infinite games. Moreover, third, the article discusses the two levels of metaphors in “Kaili Blues” that result from the condensation and displacement of metaphors, including the mutual projection of roles caused by the time-forking effect and the audience’s associations caused by the significance of dreams in Chinese tradition (or local) culture. (shrink)

This study explored the relationship between social support and job satisfaction in kindergarten teachers, and the mediating role of coping styles in this relationship. A sample of 617 kindergarten teachers from kindergartens in mainland China completed questionnaires measuring social support, job satisfaction, and coping style. The results showed that social support was positively related to job satisfaction and positive coping style was positively associated with social support and job satisfaction. Furthermore, the results revealed that positive coping style, but not negative (...) coping style, had a mediating effect on the relationship between kindergarten teachers’ social support and job satisfaction. This study provides initial evidence that coping style mediates the link between social support and job satisfaction in kindergarten teachers, and suggests that increasing social support and encouraging positive coping style could improve kindergarten teachers’ job satisfaction. (shrink)

This paper investigates a distributed coordination control for a class of high-order uncertain multiagent systems. Under the framework of iterative learning control, a novel fully distributed learning protocol is devised for the coordination problem of MASs including time-varying parameter uncertainties as well as actuator saturations. Meanwhile, the learning updating laws of various parameters are proposed. Utilizing Lyapunov theory and combining with Graph theory, the proposed algorithm can make each follower track a leader completely over a limited time interval even though (...) each follower is without knowing the dynamics of the leader. Moreover, the extension to formation control is made. The validity and feasibility of the algorithm are verified conclusively by two examples. (shrink)

System justification theory holds that disadvantaged groups rationalize the current social system, even if it is unfavorable to them. Epistemic, relational, and existential needs are factors that explain this phenomenon. However, the literature has not yet examined and explained when disadvantaged groups no longer rationalize current social systems. This study uses a questionnaire survey method to study the moderating effect of collectivism on disadvantaged mindset and system-justifying beliefs. It found that collectivism can influence the predictive effect of disadvantaged mindset on (...) system-justifying beliefs. For people who scored low in collectivism, a disadvantaged mindset can significantly negatively predict system-justifying beliefs; for those who scored high in collectivism, a disadvantaged mindset no longer predicts system-justifying beliefs. Therefore, these results show that collectivist values are important for explaining system justification in disadvantaged groups. When collectivist values decline, the level of rationalization of the social system by disadvantaged groups also decreases. (shrink)

The concept of digital twinning has become a hot topic in the manufacturing industry in recent years. The emerging digital twin technology is an intelligent technology that makes full use of multimodels, big data, and interdisciplinary knowledge, which provides some new approaches for the field of the intelligent manufacturing industry. The job shop scheduling problem has been an important research field in the discrete manufacturing industry. Digital twin technology is adopted to solve the problem of job shop scheduling, which provides (...) the possibility for the intelligent development of workshops. Based on digital twin technology and combined with the actual problem of production line scheduling, we propose a new intelligent scheduling platform to solve the shop scheduling problems above. Meanwhile, based on the prediction and diagnosis of multisource dynamic interference in the workshop production process by big data analysis technology, the corresponding interference strategy is formulated in advance by the scheduling cloud platform. The model simulation experiment of intelligent dispatching cloud platform was carried out, and some enterprises in intelligent manufacturing workshop were taken as examples to verify the superiority of the dispatching cloud platform. Finally, we look forward to the future research direction of intelligent manufacturing based on digital twin technology. (shrink)

In this paper, we track the motion of multiple targets in sports videos by a machine learning algorithm and study its tracking technique in depth. In terms of moving target detection, the traditional detection algorithms are analysed theoretically as well as implemented algorithmically, based on which a fusion algorithm of four interframe difference method and background averaging method is proposed for the shortcomings of interframe difference method and background difference method. The fusion algorithm uses the learning rate to update the (...) background in real time and combines morphological processing to correct the foreground, which can effectively cope with the slow change of the background. According to the requirements of real time, accuracy, and occupying less video memory space in intelligent video surveillance systems, this paper improves the streamlined version of the algorithm. The experimental results show that the improved multitarget tracking algorithm effectively improves the Kalman filter-based algorithm to meet the real-time and accuracy requirements in intelligent video surveillance scenarios. (shrink)

This study examined the effect of emotional context on the semantic memory of subsequent emotional words during discourse comprehension in two eye-tracking experiments. Four-sentence discourses were used as experimental materials. The first three sentences established an emotional or neutral context, while the fourth contained an emotional target word consistent with the preceding emotional context's valence. The discourses were presented twice using the text change paradigm, where the target words were replaced with strongly - or weakly-related words during the second presentation. (...) Thus, four conditions were included in the present study: Emotional-strongly-related, Emotional-weakly-related, Neutral-strongly-related and Neutral-weakly-related. In Experiment 1, negative contexts and negative target words were used, whereas in Experiment 2, positive contexts and positive target words were used. The results revealed a semantic relatedness effect, whereby the strongly-related words have lower change detection accuracy, longer reading times and more fixations in both Experiments 1 and 2. Furthermore, across both experiments, the magnitude of the semantic relatedness effect was greater in the emotionally congruent contexts than in the neutral contexts. These results suggest that emotional context could increase efforts to change the discrimination of subsequent words and demonstrate an important role of emotional context on semantic memory during discourse processing. (shrink)

In economic researches, much effort was devoted to the problem of how to increase the economics of countries. However, the development of a country may fluctuate a lot due to international and domestic problems. Thus, we should also evaluate the robustness of countries against unexpected economic recessions. In this paper, we use perturbation to quantify the robustness of countries using two renowned algorithms: method of reflections and fitness-complexity method. The robustness characterizes the stability of countries’ competitiveness against economic recessions. The (...) experiments in the international trade networks show that FCM could characterize the robustness better than MR. High fitness countries of FCM have strong robustness against economic crises, which enlarges the application fields of FCM. Additionally, we simulate the trade conflict between USA and China. The simulation results show that China suffers much in the trade conflict, while USA loses very little and has strong robustness in this conflict. (shrink)

This paper uses panel OLS, IV, and system GMM methods to empirically study the effects of manufacturing and producer service corporate co-agglomeration on green economy efficiency in China. Chinese panel data from 2000 to 2019 are collected to assess the GEE and co-agglomeration degrees. The regression results show that there is an “inverted U-shaped” relationship between co-agglomeration and GEE. However, regional heterogeneity is found in the effects of corporate co-agglomeration on GEE. The mediating analysis indicates that corporate co-agglomeration could increase (...) GEE through business entrepreneurship and innovation entrepreneurship. Variables such as transportation infrastructure, human capital, foreign direct investment, and environmental regulations are also found to have an elevating effect on GEE, whereas local fiscal expenditure on environmental protection has little effect. The findings in this paper indicate that entrepreneurship plays an important role in the process of co-agglomeration impacting GEE which differs in different regions and thus provide references for corporate and regional sustainable development. (shrink)

This paper investigates a composite learning prescribed performance control scheme for uncertain strict-feedback system. Firstly, a prescribed performance boundary condition is developed for the tracking error, and the original system is transformed into an equivalent one by using a transformation function. In order to ensure that the tracking error satisfies the PPB, a sufficient condition is given. Then, a control scheme of PPC combined with neural network and backstepping technique is proposed. However, the unknown functions cannot be guaranteed to estimate (...) accurately by this method. To solve this problem, predictive errors are defined by applying online recorded date and instantaneous date. Furthermore, novel composite learning laws are proposed to update NN weights based on a partial persistent excitation condition. Subsequently, the stability of the closed-loop system is guaranteed and all signals are kept bounded by using composite learning PPC method. Finally, simulation results verify the effectiveness of the proposed methods. (shrink)

In late 2019, the COVID-19 pandemic began to spread over the world, causing millions of deaths. In the first few months of the pandemic, several countries prevented the spread of the pandemic successfully. By contrast, the pandemic in many other countries was not controlled well. For example, India encountered a second serious outbreak of COVID-19 from April 2021 due to the poor resistance measures implemented by the government. To figure out the effective countermeasures to the pandemic, this research proposes a (...) COVID-19 pandemic and its response system, which consists of the infection subsystem, the quarantine subsystem, and the medical subsystem. On this basis, an improved SEIR-SD model is established which is utilized to analyze the response measures to the pandemic quantitatively. This model successfully simulates the actual epidemic scenarios in Wuhan, which verifies its effectiveness. Afterward, the impact of hospital administration rate, quarantine rate, average contact number, and contact infection rate on the cumulative number of infections and deaths are analyzed by simulation. The results show that both the medical and administrative efforts, especially in the early stage of the epidemic, are significant in reducing the number of infections and shortening the epidemic period. In the medical aspect, the more stringent quarantine brings the earlier inflection point of the epidemic; more importantly, improving the treatment rate significantly reduces the scale of the epidemic. In the administrative aspect, enforcing individual protection and strict community closure can effectively cut off the transmission of the virus and curb the spread of the epidemic. Finally, this research proposes several practical suggestions in response to the COVID-19 pandemic. The main contribution of this research is that the effects of different response measures on the number of new infections daily and the cumulative number of deaths of a country or region in the COVID-19 pandemic are estimated quantitatively based on modeling and simulation. (shrink)

Kawasaki disease (KD) is an acute self‐limiting vasculitis with coronary complications, usually occurring in children. The incidence of KD in children is increasing year by year, mainly in East Asian countries, but relatively stably in Europe and America. Although studies on KD have been reported, the pathogenesis of KD is unknown. With the development of high‐throughput sequencing technology, growing number of regulatory noncoding RNAs (ncRNAs) including microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) have been identified to involved (...) in KD. However, the role of ncRNAs in KD has not been comprehensively elucidated. Therefore, it is significative to study the regulatory role of ncRNA in KD, which might help to uncover new and effective therapeutic strategies for KD. In this review, we summarize recent studies on ncRNA in KD from the perspectives of immune disorders, inflammatory disorders, and endothelial dysfunction, and highlight the potential of ncRNAs as therapeutic targets for KD. (shrink)

Floods are one of the main natural disasters, which cause huge damage to property, infrastructure, and economic losses every year. There is a need to develop an approach that could instantly detect flooded extent. Satellite remote sensing has been useful in emergency responses; however, with significant weakness due to long revisit period and unavailability during rainy/cloudy weather conditions. In recent years, unmanned aerial vehicle systems have been widely used, especially in the fields of disaster monitoring and complex environments. This study (...) employs deep learning models to develop an automated detection of flooded buildings with UAV aerial images. The method was explored in a case study for the Kangshan levee of Poyang Lake. Experimental results show that the inundation for the focal buildings and vegetation can be detected from the images with 88% and 85% accuracy, respectively. And further, we can estimate the buildings’ inundation area according to the UAV images and flight parameters. The result of this study shows promising value of the accuracy and timely visualization of the spatial distribution of inundation at the object level for the end users from flood emergency response sector. (shrink)

Contemporary globalization is largely shaped by the predominant position and strength of the United States, and the concept of globalization is cast upon the polity and social aspects of P.R. China after Reform and Opening. Globalization, though substantially varied in a modern scene, is not without historical and cultural roots. The future holds anew, whereas newly arisen pieces of knowledge and information shed new light on the past, the blood and violence of the political progress on the Chinese soil. This (...) paper digs into the interactive aspect of the Chinese civilization with Western Civilization, and an empirical understanding on the evolvement of the country / nation to the recent shaping, with implication of which might change the dynamic of the Asian area after the global power politics whereof after World War II. (shrink)

With the advent of the era of artificial intelligence, “scenario” frequently appears in new product development and has gradually become an effective tool for analyzing user needs. However, the reasons for this phenomenon have not been explored in depth. New product development is a creative activity that requires product designers to imagine how people will live in the near future. So, we speculated that a familiar scenario that matches designers’ background can spark their entrepreneurial imaginativeness by empathic simulation and conducted (...) an experiment to research the impact of scenarios on the performance of entrepreneurial imaginativeness. Results of this study confirmed that a familiar scenario did indeed inspire entrepreneurial imaginativeness more than an unfamiliar scenario, especially for high entrepreneurial imaginativeness. This study provided a new respective for understanding the relationship between the empathy process and entrepreneurial opportunity recognition and evaluation processes and had practical implications for entrepreneurial practice, especially those that make human life better based on new digital technologies. Finally, we gave some suggestions on enhancing individuals’ entrepreneurial imaginativeness through different familiar scenarios and improving the team performance on creative tasks. (shrink)

Compared to a charging scheduling and management problem characterized by predetermined trip assignment, this study takes bus and driver scheduling into account, and mealtime windows must be guaranteed as one of the major labor regulations. A discretized mixed-integer linear programming model is developed based on a single electric bus route. We aim to obtain fast and high-quality global solutions for this problem, and the model can be easily executed by bus operators by directly invoking an available optimization solver such as (...) IBM ILOG CPLEX. We test our model on a real round-trip bus route. Numerical experiments show that CPLEX takes approximately 6 sec to obtain an optimal solution. The model can not only reasonably arrange daily trips for each electric bus and driver but also effectively determine the optimal charging schedule and management for an electric bus line. Besides, we analyze the sensitivity of the key parameters in the model. With the increase in the drivers’ maximum workload, the drivers’ average idle time decreases by approximately 11.25%. The objective value decreases by approximately 38.71% and 40.04% with increases in the battery capacity and fleet size, respectively, and the objective value increases by approximately 30.06% with the decrease in the initial battery driving range. In addition, we compare the effectiveness of our time discretization modeling method in solving the same case study to that from other similar studies, and the validity of our method can be verified by the calculation time. We also compare the computational efficiency of CPLEX in solving the same case study problem with and without implementing valid inequalities, and the computational efficiency of the valid inequality method is greatly improved. Finally, through the testing of a multiline network, the potential application of the model to a large-scale traffic network is verified. (shrink)

Faster R-CNN architecture is used to solve the problems of moving path uncertainty, changeable coverage, and high complexity in cold-air induced large-scale intensive temperature-reduction detection and classification, since those problems usually lead to path identification biases as well as low accuracy and generalization ability of recognition algorithm. In this paper, an improved recognition method of national ITR path in China based on faster R-CNN in complicated meteorological systems is proposed. Firstly, quality control of the original dataset of strong cooling processes (...) is carried out by means of data filtering. Then, according to the NITR standard and the characteristics of NITR, the NITR dataset in China is established by the intensive temperature-reduction areas located through spatial transformation. Meanwhile, considering that the selection of regularization parameters of Softmax classification method will cause the problem of probability calculation, support vector machine is used for path classification to enhance the confidence of classification. Finally, the improved faster R-CNN model is used to identify, classify, and locate the path of NITR events. The experimental results show that, compared to other models, the improved faster R-CNN algorithm greatly improves the performance of NITR’s path recognition, especially for the mixed NITR paths and single NITR paths. Therefore, the improved faster R-CNN model has fast calculation speed, high recognition accuracy, good robustness, and generalization ability of NITR path recognition. (shrink)

This study recruited English monolinguals, Mandarin monolinguals, and Mandarin–English (ME) bilinguals to examine whether native English and native Mandarin speakers think about time differently and whether the acquisition of L2 English could reshape native Mandarin speakers’ mental representations of temporal sequence. Across two experiments, we used the temporal congruency categorization paradigm which involved two-alternative forced-choice reaction time tasks to contrast experimental conditions that were assumed to be either compatible or incompatible with the internal spatiotemporal associations. Results add to previous studies (...) by confirming that native English and native Mandarin speakers do think about time differently, and the significant crosslinguistic discrepancy primarily lies in the vertical representations of time flow. However, current findings also clarify the existing literature, demonstrating that the acquisition of L2 English does not appear to affect native Mandarin speakers’ temporal cognition. ME bilinguals, irrespective of whether they attained elementary or advanced level of English proficiency, exhibited temporal thinking patterns commensurate with those of Mandarin monolinguals. Some theoretical implications regarding the effect of bilingualism on cognition in general can be drawn from the present study, a crucial one being that it provides evidence against the view that L2 acquisition can reshape habitual modes of thinking established by L1. (shrink)

In this study, we used data from the second wave of Midlife in the United States Study, MIDUS Biomarkers and MIDUS 3. We applied the serial mediation model to explore the serial mediating effects of perceived stress and depressive symptoms on the relationship between sleep quality and life satisfaction. A total of 945 participants were included in our study. The total indirect effect of sleep quality on life satisfaction through perceived stress, depressive symptoms and the combination of perceived stress and (...) depressive symptoms accounted for within the overall model was 45.5%. At the intervention level, programs designed to improve the level of life satisfaction among adults should focus on perceived stress and depressive symptoms. The prevention of perceived stress and depression contributes to improving life satisfaction and wellbeing. The serial mediation results should be confirmed by further longitudinal study. (shrink)

Before we investigate Mencius' art, should we not first define the term "art" [i-shu] and identify the essentials in Mencius' art?

In this paper, we prove that there exist computably enumerable degrees a and b such that $\mathbf{a} > \mathbf{b}$ and for any degree x, if x ≤ a and x is a minimal degree, then $\mathbf{x}.

When navigating in a new environment, it is typical for people to resort to external guidance such as GPS, or people. However, in the real world, even though navigators have learned the route, they may still prefer to travel with external guidance. We explored how the availability of feedback and the source of external guidance affect navigation decision-making on experienced routes in the presence of external guidance. In three experiments, participants navigated a simulated route three times and then verbally confirmed (...) that they had learned it. They then travelled the same route again, accompanied with no, correct, or incorrect direction guidance, which latter two were provided by a GPS (Exp.1), a stranger (Exp.2), or a friend (Exp.3). Half of the participants received immediate feedback on their navigation decisions, while the other half without feedback did not know if they had selected the correct directions. Generally, without feedback, participants relied on external guidance, regardless of the direction sources. Results also showed that participants trusted the GPS the most, but performed best with their friends as a direction source. With feedback, participants did not show differences in performance between the correct and incorrect guidance conditions, indicating that feedback plays a critical role in evaluating the reliability of external guidance. Our findings suggest that incorrect guidance without any feedback might disturb navigation decision-making, which was further moderated by the perceived credibility of direction sources. We discuss these results within the context of navigation decision-making theory and consider implications for wayfinding behaviors as a social activity. (shrink)

The role of self-regulated learning in achieving academic success has been widely investigated for campus-based college students. However, research on online learners’ SRL is limited, while the number of online learners has been increasing tremendously in recent years, especially after the COVID-19 pandemic worldwide. As SRL is context-bound, differences caused by classroom and home environments may be expected. This study investigated the factor structures of online learners’ SRL in Chinese as a foreign language education and the existence of SRL profiles (...) in online learners. Data were collected from 378 international students enrolled in online Chinese language courses in 2020. Ten latent factors were revealed by exploratory factor analysis with motivation and learning strategies scales of the Motivated Strategies for Learning Questionnaire. A follow-up latent profile analysis showed three profiles of low, moderate, and high self-regulated learners. The study supports the context-bound nature of SRL and calls for developing adaptive training programs according to SRL profiles of Chinese language learners. (shrink)

A nonlinear coupled wing model subject to unknown external disturbances is proposed in this paper. Since the model is modeled by partial differential equations, the traditional control design scheme based on the ordinary differential equation model is not applicable, and the control law design becomes very complex. In this paper, a new antidisturbance boundary control scheme based on a finite time convergent disturbance observer is proposed. The control laws are designed based on the new disturbance observers to make the external (...) disturbance errors converge to zero in a finite time and ensure the uniformly bounded stability of the controlled system. Finally, the effectiveness of the controllers and the finite-time convergence of disturbance errors are verified by the simulation and comparison. (shrink)

This paper further extends the existing GARCH-MIDAS model to deal with the effect of microstructure noise in mixed frequency data. This paper has two highlights. First, according to the estimation of the long-term volatility components of the GARCH-MIDAS model, rAVGRV is adopted to substitute for the RV estimator. rAVGRV uses the rich data sources in tick-by-tick data and significantly corrects the impact of the microstructure noise on volatility estimation. Second, besides introducing macroeconomic variables, deposits in financial institutions, industrial value-added, and (...) M2), Chinese Economic Policy Uncertainty index and Infectious Disease Equity Market Volatility Tracker are introduced in the long-run volatility component of the GARCH-MIDAS model. As indicated by the results of this paper, the rAVGRV-based GARCH-MIDAS is slightly better than the RV model-based GARCH-MIDAS. In addition to the common macroeconomic variables significantly impacting stock market volatility, CEPU also substantially impacts stock market volatility. Nevertheless, the effect of EMV on the stock market is insignificant. (shrink)

As an unusual event, fasting can induce strong physiological and psychological reactions, but there is still no clear understanding of how previous fasting experiences affect people’s responses to current fasting. This study aimed to investigate the influence of previous fasting experiences on participants’ basic physiological and psychological responses in a fasting experiment conducted under intensive medical monitoring. For a 22-day experiment divided into four phases, a total of 13 persons participated; the participants were divided into a group with prior fasting (...) experience and a group without prior fasting experience. The results indicate no group differences in physiological responses ; however, differences in psychological states were observed, with the Newbie group showing more negative psychological states overall throughout the experiment. Hence, previous fasting experience may be a buffer against negative feelings during current fasting. For this reason, it is important to consider fasting experiences as a vital factor in future research. (shrink)