Online informal learning spreads quickly in the COVID-19 Pandemic. Studies have predicted that both online and workplace IL have potential value to individual and organization development, whereas the study on its link with innovation remains scarce. IL is an individualized learning pattern different from formal learning, and its functioning mechanism on innovation will deepen our understanding of the relationship between learning and innovation. Self-efficacy and autonomous motivation are considered as two streams of motivational mediating mechanisms to innovation. However, previous studies (...) have proceeded largely in separation from each other. Researchers highlight the need to develop a more fine-grained theory of motivation and innovation. In addressing these literature gaps, this paper takes college teachers as the sample and focuses on the motivational mediating mechanism between online IL and innovation. The results showed that teachers IL could positively predict innovative teaching performance. Personal teaching efficacy and autonomous motivation played as sequential mediators on the link between IL and innovative teaching performance. This study extends the literature of IL–innovation relationship and enriches understanding of cognition-oriented motivation theory, highlighting one's internal autonomous construction is the key to innovation. Theoretical and practical implications for psychological empowerment are discussed. (shrink)

BackgroundIndividuals with mind-wandering experience their attention decoupling from their main task at hand while others with flow experience fully engage in their task with the optimum experience. There seems to be a negative relationship between mind-wandering and flow. However, it remains unclear to what extent mind-wandering exerts an impact on flow. And it is also elusive whether physical activity and mindfulness, which are as important factors that affected individuals’ attentional control and psychological health, are beneficial in explaining the association between (...) mind-wandering and flow. The current study investigated the relationship between mind-wandering and flow, and the potential mediation effects of physical activity and mindfulness in this association.MethodsA cross-sectional exploratory study design, including multiple scales such as the Mind-Wandering Questionnaire, the International Physical Activity Questionnaire Short Form, Mindfulness Attention and Awareness Scale, and the Short Dispositional Flow Scale was applied. Descriptive statistics and bivariate correlation coefficients were applied in the analysis of these data. A multiple mediation model was used to examine the relationships between mind-wandering, flow, physical activity, and mindfulness.ResultsMind-wandering was inversely associated with physical activity, mindfulness and flow, respectively; and flow was positively related to physical activity and mindfulness, respectively. Moreover, multiple mediation results demonstrated that physical activity and mindfulness, respectively, mediated the relationship between mind-wandering and flow.ConclusionThese findings are helpful to understand how our minds attend to the present moment, and the crucial roles of physical activity and mindfulness in the association between mind-wandering and flow. An implication of these is the possibility that the effective strategies aimed at enhancing both the levels of physical activity and mindfulness are needed to reduce the negative impact of mind-wandering on flow. (shrink)

This paper affords a critical and historical reappraisal of Bakhtin’s theory of polyphony. It addresses the issue of the subjectivity of interpretation in the reception and formulation of this highly influential theory in literary semiotics. Following a revaluation of three major patterns of interpretation of polyphony that have emerged in the global field of literary theory since 1929, as well as Bakhtin’s shift in emphasis in 1963, we find that Bakhtin’s theorizing of polyphony, based on his seemingly inconsistent interpretation of (...) Dostoevsky’s novels, was defined by his own subjectivity as well. An obvious consequence of such subjective predispositions in both the reception of Bakhtin’s theory and his own treatment of Dostoevsky’s polyphonic novels is that they have instigated a type of perpetuating availability bias in approaching the theory of polyphony. This revelation is key to understanding the wholeness of the theory of polyphony from a diachronic perspective. By tracing the cultural and intellectual sources of Dostoevsky’s polyphonic creation, this paper attempts to reframe and restore the Bakhtinian idea of polyphony to its fullness, which we believe can be encapsulated in one phrase: harmony without uniformity. (shrink)

Previous studies only considered the impact of personal or environmental factors on intensive smartphone use separately, while largely ignoring the impact of person-environment fit on it. Drawing on the P-E fit theory, we proposed that perceived overqualification, an indicator of person-job misfit, positively affects intensive smartphone use via job boredom, and affective commitment moderates this indirect effect. We examined our hypotheses using four-wave time-lag data of 450 workers from 62 teams. The results revealed that POQ raised job boredom of an (...) individual and thus increased their intensive smartphone use. In addition, when the affective commitment was high, the indirect effect from POQ to intensive smartphone use via job boredom was weaker. The implications, limitations, and future directions of this research were discussed. (shrink)

In the era of eLearning 4.0, many researchers have suggested that multimodal input helps to enhance second language vocabulary learning. However, previous studies on the effects of multimodal teaching have failed to yield definitive conclusions. Furthermore, only few studies on the multimodal input of vocabulary learning have aimed at junior high school students and have focused on explicit vocabulary instruction in class. To explore the effects of multimodal input on English as a foreign language learners’ vocabulary learning and summarize effective (...) methods, this study adopts a mixed-method approach. Based on dual coding theory and cognitive load theory, the teaching materials in this study were designed using the resources provided by the multimodal corpus iWeb and other websites. A total of 60 junior high school students who learned EFL and had a similar English proficiency level were divided into an experimental group and a control group. Target words were selected through questionnaire I. During the experiment, the CG learned from monomodal materials while the EG received multimodal input, and an immediate post-test was delivered to the two groups. Questionnaire II was distributed in the EG, and five students of the EG were randomly selected for an interview. One week later, a delayed post-test was conducted on the EG and CG. The results showed that the EG performed better in the post-test but did worse than the CG in the delayed post-test. The results of the questionnaire and the interview suggest that students held both positive and negative attitudes toward the multimodal input approach in vocabulary learning. The study concludes with some implications for choosing a multimodal input approach in vocabulary learning, along with a number of suggestions on how to optimize its positive influence and minimize its negative effects. (shrink)

Partner selection is the primary aspect of the formation of knowledge collaboration teams. We propose a method of partner selection for KCTs based on a weighted social network analysis method in which the individual knowledge competence and the collaboration performance of candidates are both considered. To select the desired partners, a biobjective 0-1 model is built, integrating the knowledge competence and collaboration performance, which is an NP-hard problem. Then, a multiobjective genetic algorithm is developed to solve the proposed model. Finally, (...) a real-world example is provided to illustrate the applicability of the model, and the MOGA is implemented to search for Pareto solutions of partner selection for KCT in this case. Moreover, some simulation examples are used to test the efficiency of the algorithm. The results suggest that the proposed method can support effective and practical partner selection. (shrink)

In recent years, supply chain finance is exploited to solve the financing difficulties of small- and medium-sized enterprises. SME credit risk assessment is a critical part in the SCF system. The diffusion of SME credit risk may cause serious consequences, leading the whole supply chain finance system unstable and insecure. Compared with traditional credit risk assessment models, the supply chain relationship, credit condition of SME, and core enterprises should all be considered to rate SME credit risk in SCF. Traditional methods (...) mix all indicators from different index systems. They cannot give a quantitative result on how these index systems work. Furthermore, traditional credit risk assessment models are heavily dependent on the number of annotated SME data. However, it is implausible to accumulate enough credit risky SMEs in advance. In this paper, we propose an adaptive heterogenous multiview graph learning method to tackle the small sample size problem for SMEs’ credit risk forecasting. Three graphs are constructed by using indicators from supply chain operation, SME financial indicator, and nonfinancial indicator individually. All the graphs are integrated in an adaptive manner, providing a quantitative explanation on how the three parts cooperate. The experimental analysis shows that the proposed method has good performance for determining whether SME is risky or nonrisky in SCF. From the perspective of SCF, SME financing ability is still the main factor to determine the credit risk of SME. (shrink)

Smart grids are rolling out internationally, with the United States nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act. The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China (...) research effort, the Climate Change Working Group Implementation Plan, Smart Grid. We present comparative benefits assessments of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: the University of California, Irvine campus, which consists of two distinct demonstrations: Southern California Edison’s Irvine Smart Grid Demonstration Project and the UCI campus itself; and the Navy Yard area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city and the Shenzhen Bay Technology and Ecology City. In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy Smart Grid Computational Tool, which is built on methods developed by the Electric Power Research Institute. The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis developed by the State Grid Corporation of China based on the analytic hierarchy process with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid. (shrink)

Knowledge graphs entity typing aims to predict the potential types to an entity, that is,. Recently, several embedding models are proposed for KG entity types prediction according to the existing typing information of the tuples in KGs. However, most of them unreasonably assume that all existing entity typing instances in KGs are completely correct, which ignore the nonnegligible entity type noises and may lead to potential errors for the downstream tasks. To address this problem, we propose ConfE, a novel confidence-aware (...) embedding approach for modeling the tuples, which takes tuple confidence into consideration for learning better embeddings. Specifically, we learn the embeddings of entities and entity types in separate entity space and entity type space since they are different objects in KGs. We utilize an asymmetric matrix to specify the interaction of their embeddings and incorporate the tuple confidence as well. To make the tuple confidence more universal, we consider only the internal structural information in existing KGs. We evaluate our model on two tasks, including entity type noise detection and entity type prediction. The extensive experimental results in two public benchmark datasets demonstrate that our proposed model outperforms all baselines on all tasks, which verify the effectiveness of ConfE in learning better embeddings on noisy KGs. The source code and data of this work can be obtained from https://github.com/swufenlp/ConfE. (shrink)

Senior executives in major corporations have drawn attention in recent years for a range of unethical activities. Despite a rise in measures to protect against such lapses, executives still make decisions whether or not to comply with reporting standards, best practices, industry norms and legislation. The prior literature in this area addresses individual characteristics of decision makers and social networks between executives and boards of directors, but to this point has largely overlooked group dynamics of the executive team. Our study (...) addresses this gap and examines the relationship between an occupational community of top executives and the quality of internal control. We construct a unique measure for the executive occupational community based on CEO and CFO’s joint tenure. Our findings show that the number of years of CEO/cfo’s joint tenure is significantly and negatively associated with internal control weakness, suggesting that the longer the executive relationship, the lower the likelihood of internal control weakness. Our study indicates that the presence of an occupational community contributes to better internal control. (shrink)

In this paper, we propose a method to design the pseudorandom number generator using three kinds of four-wing memristive hyperchaotic systems with different dimensions as multientropy sources. The principle of this method is to obtain pseudorandom numbers with good randomness by coupling XOR operation on the three kinds of FWMHSs with different dimensions. In order to prove its potential application in secure communication, the security of PRNG based on this scheme is analyzed from the perspective of cryptography. In addition, PRNG (...) has passed the NIST 800.22 and ENT test, which shows that PRNG has good statistical characteristics. Finally, an image encryption algorithm based on PRNG is adopted. In the encryption algorithm, the optimized Arnold matrix scrambling method and the diffusion processing based on XOR are used to obtain the final encrypted image. Through the evaluation of encryption performance, it is concluded that there is no direct relationship between the pristine image and encrypted image. The results show that the proposed image encryption scheme has good statistical output characteristics and security performance in line with cryptography. (shrink)

Cognitive and neural processes underlying visual creativity have attracted substantial attention. The current research uses a critical time point analysis to examine how spontaneous activity in the primary visual area is related to visual creativity. We acquired the functional magnetic resonance imaging data of 16 participants at the resting state and during performing a visual creative synthesis task. According to the CTPA, we then classified spontaneous activity in the PVA into critical time points, which reflect the most useful and important (...) functional meaning of the entire resting-state condition, and the remaining time points. We constructed functional brain networks based on the brain activity at two different time points and then subsequently based on the brain activity at the task state in a separate manner. We explore the relationship between resting-state and task-fMRI functional brain networks. Our results found that: the pattern of spontaneous activity in the PVA may associate with mental imagery, which plays an important role in visual creativity; in comparison with the RTPs-based brain network, the CTP-network showed an increase in global efficiency and a decrease in local efficiency; the regional integrated properties of the CTP-network could predict the integrated properties of the creative-network while the RTP-network could not. Thus, our findings indicated that spontaneous activity in the PVA at CTPs was associated with a visual creative task-evoked brain response. Our findings may provide an insight into how the visual cortex is related to visual creativity. (shrink)

The human brain shows neuroplastic adaptations induced by motor skill training. However, the description of the plastic architecture of the whole-brain network in resting-state is still limited. In the present study, we aimed to detect how motor training affected the density distribution of whole-brain resting-state functional connectivity (FC) brain in fast-ball student-athletes using resting-state functional magnetic resonance imaging (fMRI) data of student-athletes (SA), and non-athlete healthy controls (NC). The voxel-wise data-driven graph theory approach, namely global functional connectivity density (gFCD) mapping (...) was applied. The results showed that the SA group exhibited significantly decreased gFCD in brain regions centered at left triangular part of inferior frontal gyrus (IFG), extending to opercular part of left IFG and middle frontal gyrus (MFG) compared with NC group. The findings supported the idea of an increased neural efficiency of athletes’ brain in the brain regions associated with attentional-motor modulation and executive control. Furthermore, the behavioral results demonstrated that in the SA group, faster executive control reaction time was associated with smaller gFCD values in left IFG. The findings implied that the motor skill training would decrease the numbers of FC in IFG to accelerate the execution control with high attentional demands, and focus the attention to the target detection the athletes are interested in. (shrink)

Playing an important role in electromechanical systems, hydraulic servo system is crucial to mechanical systems like engineering machinery, metallurgical machinery, ships, and other equipment. Fault diagnosis based on monitoring and sensory signals plays an important role in avoiding catastrophic accidents and enormous economic losses. This study presents a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF method. From the point of view of feature selection, the scheme utilizes CRSR method to determine the most stable feature (...) combination that contains the most adequate information simultaneously. Based on the feature selection structure of ReliefF, CRSR employs feature integration rules in the compressed domain. Meanwhile, CRSR substitutes information entropy and fuzzy membership for traditional distance measurement index. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. To demonstrate the effectiveness of the proposed CRSR method, a hydraulic servo system joint simulation model is constructed by HyPneu and Simulink, and three fault modes are injected to generate the validation data. (shrink)

After the COVID-19 outbreak, the health status of the general population has suffered a huge threat, and the health system has also encountered great challenges. As critical members of human capital in the health sector, medical students with specialized knowledge and skills have positively fought against the epidemic by providing volunteer services that boosted the resilience of the health system. Although volunteer behavior is associated with individual internal motivation, there is sparse evidence on this relationship among medical students, especially regarding (...) potential mechanisms. Therefore, this study had two main objectives: to examine the influence of prosocial motivation of medical students on their VB; and to verify the chain-mediating role of calling and vocation as well as social responsibility in the relationship between PM and VB. Study I: a total of 2454 Chinese full-time medical students were invited to complete an online survey. Data analysis was performed using descriptive statistics, Pearson’s correlation coefficient, and multiple linear regression analysis. The results demonstrated that PM significantly affected VB in medical students ; CV as well as SR chain-mediated the relationship between PM and VB. PM promoted the formation of SR by positively evoking CV of medical students, further resulting in increased VB. Study II: A 28 person qualitative interview was conducted. Qualitative data are added to reduce the limitations of online questionnaires. At the same time, we can also critically study the VB of Chinese medical students during COVID-19. The results showed that there were various reasons for medical students to volunteer in the process of fighting against COVID-19, and the experience of volunteer service and the impact on their future life were different. Lastly, the current findings suggest that fostering volunteerism among medical students requires the joint effort of the government, non-profit organizations, and medical colleges. (shrink)

Globalization and informatization are reshaping human life and social behaviors. The purpose is to explore the worldwide strategies to cultivate international talents with a global vision. As a global language with the largest population, English, and especially its learning effect, have always been the major concerns of scholars and educators. This work innovatively studies the combination of immersion-based English teaching with virtual reality technology. Then, based on the experimental design mode, 106 students from a Chinese school were selected for a (...) quasi-experimental study for 16 weeks. The collected data were analyzed by computer statistical software, and hypotheses are verified. The results showed that there is a significantly positive correlation between VR and immersion-based language teaching. There is a significantly positive correlation between immersion-based language teaching and academic achievement, and VR is positively correlated with learning outcome. Compared with other state-of-art research methods, this work modifies the students’ oral test through the analysis and comparison with the system database, and the students’ learning effect is greatly improved. Finally, some suggestions are put forward according to the research results to provide an experimental reference for English teachers and future linguistics teaching. (shrink)

A scientific paper’s citation represents its influence, which is the most intuitive indicator to access the quality of papers. This paper mainly adopts the social network analysis method, using the authors and the keywords of sports industry papers in China to constitute the networks of collaboration and knowledge, to explore effects of the degree centrality of authors and keywords and the structural hole of authors and keywords on the citation of papers in the collaboration and knowledge networks and draw the (...) following conclusions: as for collaboration networks, the degree centrality at the paper level is positively correlated with citations; in the collaboration network, the positive correlation between the structural hole at the paper level and citations does not exist; within knowledge networks, an inverted- U shape was found between degree centrality and paper’s citation; and within knowledge networks, a positive correlation is in existence between the structural hole of papers and their citation. This study synthesizes the already widely used collaboration network with the knowledge network constructed through keywords, distinguishes from the previous network features focusing at the author level, and explores research projects of Chinese Sports Industry from the paper level, providing a new perspective for the research of sports industry in China, complementing the methods and ideas of sports industry research, as well as providing a reference for the research in other disciplinary fields. (shrink)

This paper aims at investigating the dynamic characteristics of a microring driven by dual arch electrodes because they are basic elements of microelectrostatic motors. The dual arch electrodes surround the periphery of the microring and are arranged symmetrically to the center of the ring. The electrodes are fixed while the microring is flexible. The electrostatic force will deform the microring, while the deflection of the microring changes the gap between the microring and the electrodes, thereby changing the electrostatic force. Therefore, (...) this is an electromechanical coupling effect. The nonlinear partial-differential equation that governs the motion of the microring is derived based on thin shell theory. Then, based on the assumption of small deflection, the nonlinear governing equation is linearized by truncating the higher-order terms of the Taylor series expansion of the nonlinear electrostatic force. After that, the linearized governing equation is discretized into a set of ordinary differential equations using Galerkin method in which the mode shape functions of the ring are adopted. The influences of the structural damping of the microring and the span of the arch electrodes on the forced response and dynamical stabilities of the microring are investigated. The results show that the damping ratio has a great influence on the system instability during high-frequency excitation. The unstable region of the system can increase with the increase of the electrode span; the response amplitude can also be increased within a certain range. (shrink)

The BP neural network model is a hot issue in recent academic research, and it has been successfully applied to many other fields, but few researchers apply the BP neural network model to the field of automobile insurance. The main method that has been used in the prediction of the total claim amount in automobile insurance is the generalized linear model, where the BP neural network model could provide a different approach to estimate the total claim loss. This paper uses (...) a genetic algorithm to optimize the structure of the BP neural network at first, and the calculation speed is significantly improved. At the same time, by considering the overfitting problem, an early stop method is introduced to avoid the overfitting problem. In the model, a three-layer BP neural network model, which includes the input layer, hidden layer, and output layer, is trained. With consideration of various factors, a total claim amount prediction model is established, and the trained BP neural network model is used to predict the total claim amount of automobile insurance based on the data of the training set. The results show that the accuracy of the prediction by using the BP neural network model to both the data of Shandong Province and to the data of six cities is over 95%. Then, the predicted total claim amount is used to calculate premiums for five cities in Shandong Province according to credibility theory. The results show that the average premium of the five cities is slightly higher than the actual claim amount of the city. The combination of BP neural network and credibility theory can perform accurate claim amount estimation and pricing for automobile insurance, which can effectively improve the current situation of the automobile insurance business and promote the development of insurance industry. (shrink)

Patients with advanced Alzheimer's disease experience cognitive impairment and physical disabilities in daily life. Currently, there are no treatments available to slow down the course of the disease, and limited treatments exist only to treat symptoms. However, deep brain stimulation of the nucleus basalis of Meynert has been reported to improve cognitive function in individuals with AD. Here, we report the effects of NBM-DBS on cognitive function in a subject with severe AD. An 80-year-old male with severe AD underwent surgery (...) for bilateral NBM-DBS electrode placement. After 10 weeks of stimulation, Mini-Mental State Examination assessment improved from a score of 5 to 9 points, and assessment using the Alzheimer's Disease Assessment Scale–Cognitive Subscale showed a marked reduction in total score from 43 to 33 points, suggesting cognitive benefits from NBM-DBS. The patient's postoperative course was complicated by a subdural effusion that occurred several days after surgery, with complete recovery. Interestingly, the subject also displayed abnormal thermoregulation with stimulation initiation and stimulation parameter modifications. NBM-DBS may serve as a potential therapy for severe AD patients.Clinical Trial Registration: ChiCTR1900022324. (shrink)

This study investigated the differences in morphometry and functional plasticity characteristics of the brain after long-term training of different intensities. Results showed that an aerobic group demonstrated higher gray matter volume in the cerebellum and temporal lobe, while an anaerobic group demonstrated higher gray matter volume in the region of basal ganglia. In addition, the aerobic group also showed significantly higher fractional amplitude of low-frequency fluctuation and degree centrality in the motor area of the frontal lobe and parietal lobe, and (...) the frontal gyrus, respectively. At the same time, the anaerobic group demonstrated higher fALFF and DC in the cerebellum posterior lobe. These findings may further prove that different brain activation modes respond to different intensities of physical activity and may help to reveal the neural mechanisms that can classify athletes from different intensity sports. (shrink)

In a commercialised and globalised China, museum institutions are pivotal elements in public strategies to present and create national self‐consciousness, insofar as their vast collections provide symbols of cultural identification on a national as well as an international level. This article will explore Chinese public museum policy and impact, firstly by describing the current status of the system as background information; secondly, by presenting the most recent trends in museum strategies and finally, by replacing the challenges and complexities of the (...) museum system in a broader context. The analysis will draw from first hand material from interviews and informal conversations with museum professionals, small‐scale visitor surveys as well as the most recent facts and figures, and it will be illustrated by examples and supported by secondary sources. (shrink)

Member selection to form an effective collaboration new product development team is crucial for a successful NPD. Existing researches on member selection mostly focus on the individual attributes of candidates. However, under the background of collaboration, knowledge complementarity and collaboration performance among candidates are important but overlooked. In this paper, we propose a multi-objective optimization model for member selection of a Co-NPD team, considering comprehensively the individual knowledge competence, knowledge complementarity, and collaboration performance. Then, to solve the model, an improved (...) adaptive genetic algorithm is developed. Finally, a real case is provided to illustrate the application of the model, and the IAGA is implemented to select the desired team members for optimal team composition. Additionally, the standard generic algorithm and particle swarm optimization are used to compare with the IAGA to further verify the effectiveness of the IAGA. (shrink)

This paper uses agent-based modelling to study the frequent booms and busts in Chinese agricultural markets. First, an artificial agricultural commodity market consisting of heterogeneous agents, such as producers, consumers, and speculators, is built. A numerical simulation suggests that speculation can cause large price fluctuations via nonlinear price dynamics. Then, parameters are estimated by the simulated method of moments using garlic and ginger price data in China from 2006Q2 to 2018Q3. The estimation yields a statistically significant speculative behavior parameter, supporting (...) speculators’ existence. Based on the well-estimated model, a low-cost policy experiment aiming at market stabilization is carried out. The essence of this policy is to release the theoretical steady state of the estimated model as the government-guided price to producers. The guided price, even partially followed by producers, can reduce simulated price variances and weaken speculators’ negative impact on market stability. Robustness tests show that the effect of policy experiment is robust under a 20% change in any parameter value or a 5% change in the guided price. (shrink)

The poor denoising effect for noisy grayscale images with traditional processing methods would be obtained under strong noise condition, and some image details would be lost. In this paper, a parallel array model of Fitzhugh–Nagumo neurons was proposed, which can restore noisy grayscale images well with low peak signal-to-noise ratio conditions and the image details are better preserved. Firstly, the row-column scanning method was used to convert the 2D grayscale image into a 1D signal, and then the 1D signal was (...) converted into a binary pulse amplitude modulation signal by signal modulation. The modulated signal was input to an FHN parallel array for stochastic resonance. Finally, the array output signal was restored to a 2D gray image, and the image restoration effect was analyzed based on the PSNR and Structural SIMilarity index. It is shown that the SR effect can be exhibited in an array of FHN neuron nonlinearities by increasing the array size, and the image restoration effect is significantly better than the traditional image restoration method, and larger PSNR and SSIM can be obtained. It provides a new idea for grayscale image restoration in a low PSNR environment. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

Includes translations of the important manuscripts in silk found at the famous Mawangdui Tomb in 1973.

In sprint track events, the starting reaction time is an important professional capacity of the athletes, and it is closely related to their performance. This study examines the reaction time and the results of the male and female sprinters participating in the World Athletics Championships from 2011 to 2019 in the 100 m, 200 m, 100 m, and 110 m hurdles. The researchers used least squares estimation, multivariate analysis of variance, and other methods and theories to construct a double logarithmic (...) model and a multivariate analysis of a variance model. The researchers used Econometrics Views and SPSS software programs to analyze the correlation between the performance and the starting reaction time, as well as the patterns in the changes of the reaction time of athletes of both genders in different types of and rounds in the competitions. Research results show that there is a direct correlation between the reaction time and the performance, and the degrees of correlation vary depending on the gender of the athlete, year of competition, type of competition, and round of competition. There is a correlation between the foul types and the type of competition, but there is no correlation between foul types and the gender of the athlete. The research results are science-based and are of practical value and thus can be used as a reference by coaches in sprint running to offer more professional guidance to the athletes. (shrink)

Drawing from the stimulus-organism-response model, this study examines how and under what circumstances perceived environmental corporate social responsibility affects innovative behavior of employees in the context of environmental protection. Using a sample of 398 employees from different firms in the high energy-consuming industry of China, the results indicate that, at first, perceived ECSR provides a positive effect on organizational identification. Secondly, organizational identification has a positive influence on the innovative behavior of employees. Thirdly, organizational identification plays an important mediating effect (...) between perceived ECSR and the innovative behavior of employees. Fourthly, both the effect of perceived ECSR on organizational identification and the indirect effect of perceived ECSR on the innovative behavior of the employees via organizational identification will be stronger when the levels of organizational trust are high. These findings add new insights into the perceived ECSR-employees’ innovative behavior relationship and provide important managerial implications for enhancing ECSR perception to improve the innovative behavior of employees. (shrink)

Technostress as an antecedent factor exploring knowledge hiding continues to be seldomly discussed in the digital era. Based on the job demand-resource theory, this article introduces work exhaustion as a mediator variable and constructs a model that the five sub-dimensions of technostress affect knowledge hiding for R&D employees. Similarly, this study analyzes the moderation of workplace friendship as the resource buffering effect. Based on data from the 254 questionnaires of the two-stage survey, empirical results show that: Techno-invasion, techno-insecurity, and techno-complexity (...) have significant positive effects on work exhaustion, and techno-invasion has the greatest effect. However, techno-overload and techno-uncertainty have no significant relationship with work exhaustion. Work exhaustion plays a mediating role in the relationships between the three aspects of technostress and knowledge hiding; However, its mediating effects are insignificant in the relationships between the two aspects of technostress and knowledge hiding. Workplace friendship negatively moderates the relationships between the two aspects of technostress and work exhaustion, leading to less knowledge hiding. Nonetheless, its negative moderation for the relationships between the two aspects of technostress and work exhaustion are insignificant. Empirical results further show that workplace friendship positively moderates the relationship between techno-complexity and work exhaustion. (shrink)

Fingerprint recognition is the most widely used identification method at present. However, it still falls short in terms of cross-platform and algorithmic complexity, which exerts a certain effect on the migration of fingerprint data and the development of the system. The conventional image recognition methods require offline standard databases constructed in advance for image access efficiency. The database can provide a pre-processed image via a specific method that probably is compatible merely with the specific recognition algorithm. Then, the specific recognition (...) algorithm starts the process of retrieving these specific pre-proessing images for recognition and inevitably will be blocked from other datasets. The proposed method in this research designed an embedded image processing algorithm based on a Siamese neural network in the recognition method that allows the proposed method to recognize images from any source without constructing a database for image storage in advance. In this research, the proposed method was applied to fingerprint recognition and evaluation of the proposed method was evaluated. The results showed that the accuracy of the proposed algorithm was up to 92%, and its F1 score was up to 0.87. Compared with the conventional fingerprint matching methods, its significant advantage in the FRR, FAR, and CR jointly indicated the remarkable correct recognition rate of the proposed method. (shrink)

Social anxiety and stress type can influence strong conformity among adolescents; however, the interaction between them is not clear. In this study, 152 adolescents were recruited and assigned one of two conditions: an interaction and a judgment condition. In the interaction condition, adolescents with high social anxiety (HSA) were less likely to conform when completing a modified Asch task, compared to adolescents who had low social anxiety. In the judgment condition, adolescents with HSA were more likely to conform to the (...) opinions from the unanimous majority. The results suggest that adolescents with HSA may show different styles of strong conformity with the change of stress type. We believe that socially anxious adolescents avoid potential social situations with weaker conformity, while avoiding negative evaluations from others with stronger conformity. These findings contribute to a better understanding of the social dysfunctions among adolescents with HSA and provide a new direction for clinical interventions. (shrink)

Background:When the contagious COVID-19 spread worldwide, the frontline staff faced unprecedented excessive work pressure and expectations of all of the society.Objective:The aim was to explore healthcare workers’ stress and influencing factors when caring for COVID-19 patients from an altruistic perspective.Methods:A cross-sectional, descriptive study was conducted in a tertiary hospital during the outbreak of COVID-19 between February and March 2020 in Wuhan, the capital city of Hubei province in China. Data were collected from 1208 healthcare workers. Descriptive statistics and multiple linear (...) regression were used to analyze the data.Ethical considerations:Research ethics approval (with the code of TJ-IRB20200379) was obtained from Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology. Written informed consent was also received from participants.Results:Less than 60% of participants chose moderate or severe stress on all stressors, indicating a low stress level among healthcare workers. The main source of stress among frontline healthcare workers caring for COVID-19 patients came from the fear of being infected, the fear of family members being infected, and the discomfort caused by protective equipment. Frontline staff who were nurses, were married, and had worked more than 20 days suffered higher stress, whereas rescue staff showed lower stress.Conclusion:The healthcare workers caring for patients with COVID-19 had low stress level, although they still had the fear of being infected or uncomfortable feeling caused by personal protective equipment. A low stress level among healthcare workers indicated their professional devotion and altruism during COVID-19 epidemic. Medical institutions and the government should continue to strengthen infection prevention measures and provide more comprehensive care involving families of frontline healthcare workers, especially nurses and married staff. It will be a lesson to other countries that awaking healthcare workers’ inside motivation and providing necessary support from government and society were significant. (shrink)

The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real-estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price-influencing factors. In this paper, an effective data-driven automated valuation framework is proposed for valuing real estate assets by combining a GIS and neural network technologies. This framework can automatically obtain the values of spatial factors affecting (...) land price from GIS and generate training set data for training the neural network to identify the complex relationship between all kinds of factors and benchmark land prices. The effectiveness and universality of the framework is verified via the data of benchmark land prices in Wuhan. The framework can be applied for automated benchmark land price valuation in other cities. (shrink)

Rapid and precise air operation mission planning is a key technology in unmanned aerial vehicles autonomous combat in battles. In this paper, an end-to-end UAV intelligent mission planning method based on deep reinforcement learning is proposed to solve the shortcomings of the traditional intelligent optimization algorithm, such as relying on simple, static, low-dimensional scenarios, and poor scalability. Specifically, the suppression of enemy air defense mission planning is described as a sequential decision-making problem and formalized as a Markov decision process. Then, (...) the SEAD intelligent planning model based on the proximal policy optimization algorithm is established and a general intelligent planning architecture is proposed. Furthermore, three policy training tricks, i.e., domain randomization, maximizing policy entropy, and underlying network parameter sharing, are introduced to improve the learning performance and generalizability of PPO. Experiments results show that the model in this work is efficient and stable, and can be adapted to the unknown continuous high-dimensional environment. It can be concluded that the UAV intelligent mission planning model based on DRL has powerful intelligent planning performance, and provides a new idea for researching UAV autonomy. (shrink)

At present, people mainly focus on health education for adolescents. The health education of adolescents is related to future of adolescents. In youth, their emotions are easily influenced. Therefore, this manuscript constructs an interactive health education model for adolescents through affective computing. Researchers in various countries have done a lot of research on human–computer interaction, and affective computing is one of the research hotspots. This manuscript aims to study the use of affective computing to construct an interactive health education model (...) for adolescents. It proposed an interactive emotional algorithm based on emotional computing and focuses on the ICABoost algorithm. The experimental results of this paper show that the surveyed junior high school students are divided into three grades: the first, second, and third grades. Among them, 11, 11, and 13 were mentally healthy, with a total percentage of only 18.5%; 16, 14, and 16 were moderately severe in health education, accounting for 24.3%. The percentage of severe cases was 29.6%. It can be seen that, through the investigation of this manuscript, it can be seen that today’s youth health education should be paid attention to. Only by constructing a corresponding interactive health education model for young people can we promote the comprehensive and healthy development of young people. (shrink)

Public value facilitates the democratization of public policy making, it should be the common-sense and bottom-line for policymakers. However, it has not been paid enough attention by the practical and theoretical circles. How to realize the transformation from individual value to public value and make public policies be in line with citizens’ preferences, is vital for the democratic politics. How individual value becomes public value in the agenda-setting stage during the policy-making process? What are the key influencing factors? Using the (...) case of Yangzhou Chemical Co. Youjia Program and interview data, this paper studies the mechanisms that could make individual value be transformed to public value through deeply observing and measuring individuals’ attitudes, demands, motivations, beliefs, and preferences. We argue that (1) public value is an essential foundation for agenda setting and guidance to policy making, whereas individual value cannot naturally substitute value orientation in the public sphere. (2) Transferring individual value to public value can reduce divergence appearing in the subsequent stage in policy activities. (3) Factors that can influence this transformation are policy subjects, relations, rule and expression channels with various determinants and conditions. (4) Public value can terminate irrational and unreasonable policies or drag the policy issues back into the agenda-setting stage. This paper provides unique insights into why individual citizens enter the public sphere to take public actions so that the Chinese government can recognize additional public opinions, which makes cooperative governance be realized. (shrink)

Currently, advancements in information and communication technology and an increased interest in using the Internet for educational purposes have led educators to work in new virtual settings. However, using technology in teaching requires the understanding and information of English educators. Technological Pedagogical Content Knowledge is an educator's knowledge concept regarding integrating technology into education. Also, how educators integrate technology effectively into their classes is a significant issue, as learning environments are influenced by rapid advances in instructional technology. Consistent with this (...) issue, it is critical for teacher development to integrate ICT into educational tasks in the design, application, and assessment of practices in a virtual setting. To this end, the objective of the present review is to consider the role of practice in the virtual platform in developing EFL teachers' TPACK. Ultimately, some implications are presented for the EFL educational stakeholders. (shrink)

Current development in a deep neural network has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real-time performance. There are many deep learning-based techniques that have been proposed for the holographic image reconstruction, but these deep learning-based methods can still lack in performance, time complexity, accuracy, and real-time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network (...) holography framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel-based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer-generated holograms. The experimental results have demonstrated that the proposed method outperforms the existing methods. (shrink)

Aim To synthesize qualitative research on perspectives and understandings of Intensive Care Unit (ICU) patients, family members, and staff regarding respect and dignity in ICU, in order to explore the connotations and meanings of respect and dignity in ICU. Design A qualitative meta-synthesis. Methods The Chinese and English databases were systematically searched, including PubMed, Web of Science, CINAHL, Embase, Cochrane Library, CNKI, Wangfang Data, VIP, and CBM from each database’s inception to July 22, 2023. Studies were critically appraised using the (...) Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Qualitative Research. Qualitative data were extracted, summarized, and meta-synthesized. (PROSPERO: CRD42023447218). Results A total of 9 studies from 6 countries were included in the meta-synthesis. Thirty-six main themes and 67 sub-themes were extracted, which were eventually integrated into 9 categories and 4 themes: (1) integrity of humanity; (2) autonomy; (3) equality; (4) environmental support. Conclusion To maintain patient dignity, it is necessary to create an environment of respect within the ICU where healthcare professionals uphold the concept of preserving human integrity and respect patients' autonomy and equality. Healthcare professionals need to value the dignity of ICU patients and treat them as unique individuals during treatment and care. Hospital managers should also strive to create a respectful environment to provide environmental support for dignity care implementation. (shrink)

This paper provides an in-depth analysis and discussion of the key issues of quality management, evaluation, and detection contained in big data for automotive application scenarios. A generalized big data quality management model and programming framework are proposed, and a series of data quality detection and repair interfaces are built to express the processing semantics of various data quality issues. Through this data quality management model and detection and repair interfaces, users can quickly build custom data quality detection and repair (...) tasks for different data quality requirements. To improve the operational efficiency of complex data quality management algorithms in large-scale data scenarios, corresponding parallelization algorithms are studied and implemented for detection and repair algorithms with long computation time, including priority-based multiconditional function-dependent detection and repair algorithms, entity detection, and extraction algorithms based on semantic information and chunking techniques, and plain Bayesian-based missing value filling algorithms, and this paper proposes a data validity evaluation algorithm and enhances the validity of the original data in practical applications by adding temporal weights, and finally it passed the experimental validation. Through the comprehensive detection process of data importance, network busyness, duration of transmission process, and failure situation, the efficiency has been increased by 20%, and an adaptive data integrity detection method based on random algorithm and encryption algorithm is designed. After experimental verification, this method can effectively detect the integrity of the data transmission process and improve the application of data value, and the final effect is increased by 30.5%. (shrink)