As cyberspace has become an important factor in modern-day life, the impact of the Internet on residents has also attracted more attention. Based on the data of China Family Panel Studies, this study empirically examines the impact of Internet use on Chinese residents’ subjective well-being from a multi-dimensional perspective. The research found that Internet use had a significant impact on residents’ SWB, which was mainly reflected in job satisfaction, happiness, social ties, and future confidence. The impacts of the Internet’s different (...) application fields are not consistent. Applying its use more in studying, working, socialize and commercial activities has a stronger effect, but has no significant impact on entertainment. Further heterogeneity tests also found that the marginal effect of Internet use increases with age, male and low-income groups can obtain greater benefit from the Internet, and there is almost no difference between urban and rural areas. This research provides micro evidence of the social effects of Internet use and provides enlightenment for how to further promote the quality of Internet use to better benefit people. (shrink)

Rationale and objectives: Medical humanities are becoming increasingly recognized as positively impacting medical education and medical practice. However, the extent of medical humanities teaching in medical schools is largely unknown. We reviewed medical school curricula in Canada, the UK and the US. We also explored the relationship between medical school ranking and the inclusion of medical humanities in the curricula. -/- Methods: We searched the curriculum websites of all accredited medical schools in Canada, the UK and the US to check (...) which medical humanities topics were taught, and whether they were mandatory or optional. We then noted rankings both by Times Higher Education and U.S. News and World Report and calculated the average rank. We formally explored whether there was an association between average medical school ranking and medical humanities offerings using Spearman's correlation and inverse variance weighting meta-analysis. -/- Results: We identified 18 accredited medical school programmes in Canada, 41 in the UK, and 154 in the US. Of these, nine (56%) in Canada, 34 (73%) in the UK and 124 (80%) in the US offered at least one medical humanity that was not ethics. The most common medical humanities were medical humanities (unspecified), history, and literature (Canada); sociology and social medicine, medical humanities (unspecified), and art (UK); and medical humanities (unspecified), literature and history (US). Higher ranked medical schools appeared less likely to offer medical humanities. -/- Conclusions: The extent and content of medical humanities offerings at accredited medical schools in Canada, the UK and the US varies, and there appears to be an inverse relationship between medical school quality and medical humanities offerings. Our analysis was limited by the data provided on the Universities' websites. Given the potential for medical humanities to improve medical education and medical practice, opportunities to reduce this variation should be exploited. (shrink)

Coronavirus disease 2019 has not only resulted in immeasurable life and property losses worldwide but has also impacted individuals’ development, especially teenagers. After the COVID-19 pandemic, individual rumination as an important cognitive process should be given more attention because of its close associations with physical and mental health. Previous studies have shown that creativity as an antecedent variable can predict people’s mental health or adaptation. However, few studies have focused on the relationship between creativity and individual cognitive rumination after traumatic (...) events, and the mechanism underlying this relationship remains unclear. By using the Runco Ideational Behavior Scale, the Event Related Rumination Inventory, and the Questionnaire of Adolescent Emotional Resilience, the current study explored the relationship between creativity and intrusive rumination among 1488 Chinese teenagers during the COVID-19 pandemic and analyzed the moderating effect of emotional resilience on the relationship. The results showed that creativity, as assessed by the RIBS, was positively related to teenagers’ intrusive rumination, which implied that a higher level of creative performance could predict more intrusive rumination. Moreover, emotional resilience acted as a moderator in the relationship between creativity and intrusive rumination; the correlation was stronger when emotional resilience was low. These findings provide more evidence of the relationship between creativity and mental health and show the effect of this traumatic event on teenagers. (shrink)

Previous studies have noted that personality traits are important predictors of well-being, but how big five personality influences social well-being is still unknown. This study aims to examine the link between big five personality and five dimensions of social well-being in the Chinese cultural context and whether social support can play the mediating effect in the process. This study included 1,658 participants from different communities in China, and regression analyses were conducted. Results revealed that five personality traits were significantly related (...) to overall social well-being; extraversion was significantly related to social integration; agreeableness was positively related to all five dimensions of social well-being; conscientiousness was positively related to social actualization, social coherence, and social contribution; neuroticism was negatively related to social integration, social acceptance, social actualization, and social coherence; openness was positively related to social integration, social acceptance, social coherence, and social contribution. Social support plays mediating roles in the relationships between extraversion/agreeableness/conscientiousness/neuroticism/openness and social well-being, respectively. (shrink)

Because of difficulty processing the electronic medical record data of patients with cerebrovascular disease, there is little mature recognition technology capable of identifying the named entity of cerebrovascular disease. Excellent research results have been achieved in the field of named entity recognition, but there are several problems in the pre processing of Chinese named entities that have multiple meanings, of which neglecting the combination of contextual information is one. Therefore, to extract five categories of key entity information for diseases, symptoms, (...) body parts, medical examinations, and treatment in electronic medical records, this paper proposes the use of a BERT-BiGRU-CRF named entity recognition method, which is applied to the field of cerebrovascular diseases. The BERT layer first converts the electronic medical record text into a low-dimensional vector, then uses this vector as the input to the BiGRU layer to capture contextual features, and finally uses conditional random fields to capture the dependency between adjacent tags. The experimental results show that the F1 score of the model reaches 90.38%. (shrink)

In public health emergencies, people are more willing to save money rather than spending it, which is not conductive to economic development and recovery. Due to the absence of relevant research, the internal logic of this phenomenon is not clear. In the context of the COVID-19 pandemic, this study systematically explored whether and why public health emergencies stimulate consumers' preference for saving. We conducted two online surveys and used methods including stepwise regression analysis and bootstrapping to test the hypotheses. The (...) first survey, with 1,511 participants from China in February 2020, indicates that the severity of emergencies has a significant positive impact on the populations' willingness to save. Risk perception plays a mediating role between the severity of emergencies and consumers' saving willingness. Materialism plays a moderating role between risk perception and an individual's saving willingness, individuals who are more materialistic have a lower saving willingness when they perceive the risks of the pandemic. To verify the duration of the above effects, we conducted a follow-up survey consisted of 466 instances in August 2020. It is noteworthy that the above effects are not significant during the post-pandemic period. Thus, spending behavior in public health emergencies can be motived by reducing risk perception and increasing materialism. These findings can provide a valuable inspiration for public health, crisis management, and economic recovery during public health emergencies. (shrink)

Green innovation has been attracting much attention from academia and practice, but the influence of religion as an important informal institutional factor has not been fully investigated in existing studies. Taking Chinese listed companies from 2008 to 2019 as a sample, this study attempts to examine the relationship between religious atmosphere and corporate green innovation performance. The empirical results indicate that a religious atmosphere (Buddhism and Taoism as a whole) can significantly improve corporate green innovation performance, particularly high-quality green innovation. (...) The positive association between religion and green innovation performance is attenuated by pervasive formal institutions (i.e., environmental regulation), indicating that there is a substitutive effect between religion and formal institutions. We also find that Taoism mainly supports these results, while Buddhism has a limited impact, showing that there is a heterogeneous effect between different religions. We further find that the positive impact of religious atmosphere on green innovation performance is more pronounced in low-governance enterprises and low-polluting industries. This study contributes to research on the antecedents of corporate green innovation and the consequence of religion, which is of great significance to the value of religion in business practice. (shrink)

The purpose of this study is to explore why workplace deviance behavior among employees has increased during Corona Virus Disease 2019 from the perspective of insecure attachment style. Based on attachment theory, we propose and test the effect of insecure attachment style on deviance behavior via organization-based self-esteem using 422 data from Chinese employees. And we further examine the moderating role of leader–member exchange in reducing workplace deviance behavior. The findings show that attachment anxiety and attachment avoidance are both positively (...) related to workplace deviance behavior. Attachment anxiety and attachment avoidance both indirectly predict organizational deviance behavior through organization-based self-esteem. Moreover, leader–member exchange can moderate the indirect effects of both attachment anxiety and attachment avoidance on organizational deviance behavior via organization-based self-esteem. This research highlights the fact that employees with insecure attachment style need more care from the organization during the COVID-19 pandemic and demonstrates that one of the key ways in which insecure attachment style increases organization-based self-esteem is by facilitating the development of high-quality leader–member exchange. (shrink)

ObjectiveTo investigate the characteristics of sleep disorders and anxiety in patients with tinnitus, their influencing factors, and the role of sleep disorders as mediators.MethodsThe general conditions and disease characteristics of 393 patients with tinnitus presented to the Changzheng Hospital of the Naval Medical University from 2018 to 2021 were collected. All patients accepted questionnaires such as Tinnitus Handicap Inventory, Pittsburgh Sleep Quality Index and Self-rating Anxiety Scale, and then the characteristics and the influencing factors of sleep disorders and anxiety were (...) analyzed.ResultsAmong the 393 tinnitus patients, 213 cases were diagnosed with sleep disorders, and 78 cases were diagnosed with anxiety, including 25 men and 53 women. Binary regression showed that gender, hearing loss, tinnitus severity, and sleep disorders severity were positively associated with anxiety. Multiple logistic regression analysis showed that female gender, hearing loss and sleep disorders were the independent risk factors of anxiety. The mediating effect of sleep disorders between tinnitus severity and anxiety accounted for 27.88% of the total effect size.ConclusionFemales patients with hearing loss, moderate to severe tinnitus, and sleep disorders were at greater risk for anxiety, with sleep disorders partially mediating the anxiety associated with tinnitus. (shrink)

Cognitive neuroscience research has found that individuals from different cultures have different neural responses and emotional perceptions. Differences in executives’ perception of external pay gaps in different cultures can affect their work attitudes and behavior. In this study, we explore the direct relationship between executive compensation fairness and executive innovation motivation. We also investigate the moderating effects of Confucian culture and western culture between executive compensation fairness and executive innovation motivation. Data were collected from the Chinese listed firms from 2011 (...) to 2019 and test the relationship using the fixed-effect panel regression models. The results demonstrate that executive compensation fairness positively influences the executive innovation motivation. This effect is more pronounced in Confucian culture regions, while Western culture weakens this effect. The findings of this study confirmed that executive compensation fairness, provide a cross-cultural comparison for compensation research, validate the findings of cultural neuroscience, and provide useful insights into the research of common prosperity. To improve the corporate compensation structure, it is necessary to consider the relative pay equity with firms in the same region and the influence of corporate culture. (shrink)

With the continuous improvement of the level of science and technology, the popularization of the Internet and the development of applications, online consumption has become a major force in personal consumption. As a result, digital consumption is born, and digital consumption is not only reflected in transaction consumption at the monetary level. Like some intangible services similar to the use of dating software, it can also become digital consumption. In this environment, a new economic concept, the digital economy, has emerged (...) as the times require. The digital economy helps to achieve the rapid optimal allocation and regeneration of resources and achieve high-quality economic development. Therefore, as a new economic form, the digital economy has penetrated into all fields of human society. The Canopy algorithm is a fast clustering technique that requires only one pass through the data technology to get the results. But it is inaccurate for large-scale data clustering. Therefore, when analyzing the data, it is necessary to use the Canopy algorithm for preliminary clustering, and then combine with other algorithms or model software for refinement. This article introduces the development of the digital economy in the Internet era. It conducts a theoretical discussion on consumer psychology in the context of the digital economy. It introduces the basic calculation formula of the clustering algorithm and the algorithm flow of the Canopy clustering algorithm. It does model optimization for the Canopy clustering algorithm. On this basis, it designs questionnaires for experimental design. The indicators are divided into commodity attributes and consumer psychology. It builds a consumer psychology prediction model and tests the prediction results. The results show that the maximum difference between the prediction results of digital economy consumption psychology based on the Canopy clustering algorithm and the actual results is 0.047. It can be shown that the psychological prediction model of digital economy consumption based on the Canopy clustering algorithm has certain practicability. (shrink)

Multiplex networks have been widely used in information diffusion, social networks, transport, and biology multiomics. They contain multiple types of relations between nodes, in which each type of the relation is intuitively modeled as one layer. In the real world, the formation of a type of relations may only depend on some attribute elements of nodes. Most existing multiplex network embedding methods only focus on intralayer and interlayer structural information while neglecting this dependence between node attributes and the topology of (...) each layer. Attributes that are irrelevant to the network structure could affect the embedding quality of multiplex networks. To address this problem, we propose a novel multiplex network embedding model with high-order node dependence, called HMNE. HMNE simultaneously considers three properties: intralayer high-order proximity of nodes, interlayer dependence in respect of nodes, and the dependence between node attributes and the topology of each layer. In the intralayer embedding phase, we present a symmetric graph convolution-deconvolution model to embed high-order proximity information as the intralayer embedding of nodes in an unsupervised manner. In the interlayer embedding phase, we estimate the local structural complementarity of nodes as an embedding constraint of interlayer dependence. Through these two phases, we can achieve the disentangled representation of node attributes, which can be treated as fined-grained semantic dependence on the topology of each layer. In the restructure phase of node attributes, we perform a linear fusion of attribute disentangled representations for each node as a reconstruction of original attributes. Extensive experiments have been conducted on six real-world networks. The experimental results demonstrate that the proposed model outperforms the state-of-the-art methods in cross-domain link prediction and shared community detection tasks. (shrink)

Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected pattern graph is extracted from a pattern graph (...) to construct a dominance-partitioned pattern hypergraph, which divides a pattern graph as multiple fish-shaped pattern subgraphs. Secondly, a dominance-driven spectrum clustering strategy is used to gather the pattern subgraphs into multiple clusters. Thirdly, the dominance-partitioned subgraph matching algorithm is designed to conduct all isomorphic subgraphs on a cluster-partitioned RDF graph. Finally, experimental evaluation verifies that our strategy has higher time-efficiency of complex queries, and it has a better scalability on multiple machines and different data scales. (shrink)

Artificial intelligence (AI) technology has brought new opportunities and challenges to the judicial field, which dramatically improves judicial efficiency and may even change the judiciary's way. The concept of judicial justice in the information age has a natural affinity with artificial intelligence. As artificial intelligence continues to make breakthroughs in judicial data sorting and deep learning knowledge, judicial artificial intelligence has gradually become a reality. Artificial intelligence can conduct legal argumentation, interpret calculation results, human–computer collaboration, and judicial judgment. At the (...) same time, the development of artificial intelligence technology also has potential risks, such as algorithm black boxes, algorithm discrimination, etc., to help judges achieve judicial justice, the value of judicial justice should be pursued to the limit of its judicial application. Therefore, artificial intelligence justice should be constrained by social relations, legal rationality, and code operation. (shrink)

This research investigated how interpersonal communication with a large audience can influence communicators’ attitudes. Research on the saying-is-believing effect has shown that when an individual’s attitude is perceived in advance by a communicator, the communicator tunes the message to the person, which biases the communicator’s attitude toward the person’s attitude. In this study, we examined the conditions under which audience tuning and attitude bias can occur with audiences containing more than one individual. We manipulated communicators’ perceived group entity for a (...) large audience and the audience’s prior attitudinal valence and measured the audience’s epistemic trust. The results showed that communicators tuned their messages to the audience’s attitude when they perceived group entitativity and epistemic trust. Furthermore, tuning the message to the audience was found to bias communicators’ subsequent impressions of the topic in a direction closer to the audience’s attitude. These results suggest that perceiving a large audience as a group influences the subsequent impressions of electronic word-of-mouth product or service communicators. (shrink)

In alphabetic writing systems (such as English), the spaces between words mark the word boundaries, and the basic unit of reading is distinguished during visual-level processing. The visual-level information of word boundaries facilitates reading. Chinese is an ideographic language whose text contains no intrinsic inter-word spaces as the marker of word boundaries. Previous studies have shown that the basic processing unit of Chinese reading is also a word. However, findings remain inconsistent regarding whether inserting spaces between words in Chinese text (...) promotes reading performance. Researchers have proposed that there may be a trade-off between format familiarity and the facilitation effect of inter-word spaces. In order to verify this, this study manipulated the format familiarity via reversing the Chinese reading direction from right to left to investigate this issue in Experiment 1 and Experiment 2. The purpose of Experiment 1 was to examine whether inter-word spaces facilitated Chinese reading in an unfamiliar format. Experiment 1 was conducted that 40 native Chinese undergraduates read Chinese sentences from right to left on four format conditions. The results showed faster reading speed and shorter total reading time for the inter-word spaced format. Based on this finding, Experiment 2 examined whether the facilitation effect of inter-word spaces would reduce or disappear after improving the format familiarity; this experiment was conducted that 40 native Chinese undergraduates who did not participate in Experiment 1 read Chinese sentences from right to left on four format conditions after ten-day reading training. There was no significant difference between the total reading time and reading speed in the inter-word spaced format and unspaced format, which suggests that the facilitation effect of inter-word spaces in Chinese reading changed smaller. The combined results of the two experiments suggest that there is indeed a trade-off between format familiarity and the facilitation of word segmentation, which supports the assumption of previous studies. (shrink)

Background: Interpersonal sensitivity is a prominent mental health problem facing college students today. Trait mindfulness is a potential positive factor that may influence interpersonal relationships. However, the precise relationship between trait mindfulness and interpersonal sensitivity remains elusive, which limits the optimization and further application of mindfulness-based intervention schemes targeting interpersonal sensitivity. This study aimed to explore whether negative emotions mediate the relationship between trait mindfulness and interpersonal sensitivity and whether the relationship among trait mindfulness, negative emotions, and interpersonal sensitivity is (...) moderated by effectiveness/authenticity. We hypothesize that negative emotions mediate the relationship between trait mindfulness and interpersonal sensitivity, and effectiveness/authenticity moderates the indirect association between trait mindfulness and interpersonal sensitivity through negative emotions.Methods: One thousand four hundred nineteen Chinese college students, aged from 17 to 23, participated in this study. Their trait mindfulness, negative emotions, the effectiveness/authenticity, and interpersonal sensitivity were measured using well-validated self-report questionnaires.Results: Correlational analyses indicated that both trait mindfulness and effectiveness/authenticity were significantly and negatively associated with interpersonal sensitivity. Mediation analyses uncovered a partial mediating role of negative emotions in the relationship between trait mindfulness and interpersonal sensitivity. Moderated mediation analyses showed that in college students with high effectiveness/authenticity, the relationship between trait mindfulness and negative emotions was stronger, whereas the relationship between negative emotions and interpersonal sensitivity was weaker.Conclusion: Negative emotion is a mediator of the relationship between trait mindfulness and interpersonal sensitivity, which in turn is moderated by effectiveness/authenticity. These findings suggest a potential mechanism through which trait mindfulness influences interpersonal sensitivity. Mindfulness-based interventions have the potential to decrease interpersonal sensitivity and offer a basis for predicting individual differences in response to mindfulness-based interventions among individuals. (shrink)

Background: As one of the main participants in health care, nurses are esteemed an important driving force for the vigorous health care development. Studies report that nurses’ proactive personality has positive effects on their job performance; however, this relationship acquires further understanding.Objective: A cross-sectional study was performed to explore the relationship between nurses’ proactive personality and job performance; the mediating role of nurses’ competency and work engagement in this relationship was also evaluated.Methods: The study was performed in a large third-degree (...) general hospital in October 2019, Xi’an, PR, China. A sample of 246 nurses participated in this cross-sectional study. Proactive personality was assessed with the Proactive Personality Questionnaire, job performance was assessed by Heilman three-item measurements, nurse competence was estimated with Nurse Competency Scale, and work engagement was assessed with the Utrecht Work Engagement Scale. The structural equation model was used to test the main hypotheses.Results: Structural equation model analysis revealed that work engagement partially mediated the association between proactive personality and job performance. The serial two-mediator model which was used to explore the association between proactive personality and job performance through competency and work engagement, in sequence, was demonstrated.Conclusion: This study demonstrates that work engagement partially mediated the association between nurses’ proactive personality and their job performance. The serial two-mediator model demonstrated that proactive personality was associated with job performance via competency and work engagement. This study also revealed the critical role of nursing managers in understanding the nurses’ proactive personality, which would facilitate them to enhance the latter’s competency and promote their work engagement. All these will in turn constantly improve the overall quality of nursing and advance professional development of nursing and benefits for patients. (shrink)

This paper presents an in-depth analysis and research on the spatial distribution pattern of the urban landscape in the Central Plains digital landscape form and proposes an optimization scheme. Based on the basic theories of systematics and complexity, this paper analyzes the self-similar characteristics of urban morphology, establishes the concept of schema, and constructs a multiscale and multilevel morphological map research framework by drawing on the “planar pattern” morphological analysis method of the school and the “matrix, patch, and corridor” spatial (...) expression model of landscape ecology. The framework of morphological map research at multiple scales has been established, and the theory and method of describing, understanding, judging, and analyzing morphological evolution have been formed. Cities have self-similarity at different scales, and urban evolution is a process of recursion from small-scale hierarchy to large-scale hierarchy, and hierarchy is a phenomenon presented by the natural evolution of cities. After any morphological process is completed, it can only be transformed into the other two ways, so the static morphological description can be transformed into dynamic morphological process analysis. (shrink)

Objective: To investigate the prevalence of and risk factors associated with mental health symptoms in psychiatric outpatients and their family members in China during the COVID-19 pandemic.Methods: This cross-sectional, survey-based, region-stratified study collected demographic data and mental health measurements for depression, anxiety and acute stress from 269 psychiatric patients and 231 family members in the Second Xiangya Hospital in China from April 27, 2020 to May 8, 2020. Binary logistic regression analysis was performed to identify risk factors associated with mental (...) health outcomes.Result: The results of this survey revealed that symptoms of depression, anxiety, and acute stress were highly prevalent symptoms in the psychiatric patient group. Respondents who were female, unmarried or highly educated were significantly more likely to have the above symptoms. In the family member group, more than half of them felt that the burden of nursing had increased during the epidemic. Subjects with a high degree of burden of care were significantly more likely to exhibit the above mental health symptoms, while females were significantly more likely to have acute stress.Conclusions: The results of this survey revealed a high prevalence of mental health disorder symptoms among psychiatric patients and an increased burden of nursing among their family members after the COVID-19 outbreak in China. Understanding the risk factors in those particular groups of people help improve the public health service system for mental health problems during public health events. For further study, exploration of the needs of mental health services and dynamic change tracking will be needed. (shrink)

Most complex real systems are found to have multiple layers of connectivity and required to be modelled as multiplex networks. One of the extremely critical problems is to reduce the congestion and enhance the transfer capacity, especially in real communication networks with a big data environment. A novel and effective strategy to improve traffic and control congestion is proposed by adding edges according to their weights which are defined by the topology structural properties. Furthermore, which layer is more effective when (...) our strategy is applied is discussed based on its topology structure. Adding edges between nodes whose product of multiplex network betweenness is the highest is confirmed to be more effective, particularly in the layer with stronger community structure. Simulation experiments on both computer-generated and real-world networks demonstrate that our strategy can enhance the transfer capacity of multiplex networks significantly, which is in good agreement with our analysis. (shrink)

This study used priming paradigm with lexical decision task to examine the effects of different levels of semantic relatedness on the identification of Chinese phonetic–semantic compound characters. Unlike previous studies that simply classify Chinese compound characters as semantically transparent or opaque, we categorize the semantic relatedness between semantic radicals and the target characters containing them into five levels: highly related, moderately related, minimally related, unrelated but sharing the semantic radical, and unrelated without sharing the semantic radical. Moreover, three stimulus-onset asynchrony (...) s were used in this study to dissociate the radical- and character-level semantic priming effects. Results revealed a graded priming effect of the semantic radical on character recognition in Chinese readers for all SOAs. More specifically, the facilitative effect of the semantic radical on character processing was most evident for the high condition, followed by the minimal, form-only, and control conditions. This suggests a graded priming effect of the semantic radical on character identification. (shrink)

In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for (...) multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model. (shrink)

Positioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoelectric ceramics and the influence on the control accuracy. In order to solve this problem, backpropagation algorithm based on whale optimization algorithm is used to model the hysteresis, which is directly used as a feedforward controller to compensate the hysteresis effect, and (...) the robust adaptive moving average control method is used for feedback control. The results show that the hysteresis model of backpropagation algorithm based on the whale optimization algorithm can fit the hysteresis curve well, and the maximum fitting error is 0.2050 μm, only 0.256%. By adopting feedforward and feedback, feedforward robust adaptive moving average control algorithm decreases the hysteresis from 17.64% to 2.51%, which enables the output of the piezoelectric ceramic controller to track the expected displacement well and makes it possible to improve the scanning accuracy. (shrink)

This paper explores whether a Student’s choice of major leads to certain personality traits and the reasons for this phenomenon. Specifically, we look at evidence from two Chinese universities, both of which specialize in agricultural studies. Using the Sixteen Personality Factor questionnaire and the Neuroticism Extraversion Openness Five-Factor Inventory questionnaire, we collected data from two groups of students: those who study agriculture-related majors, and those who study non-agriculture-related majors. The surveys all showed no significant change in personality traits during Students’ (...) freshman year. However, after 3 years of university study, significant personality trait changes were noted between seniors in the ARM and NARM groups. Whereas ARM seniors tended to be socially shy and lower in communicative competence, NARM seniors were better at expressing themselves and communicating with others. Although a Student’s choice of profession has an influence on their personality traits, it is not the only factor. The differences between ARM and NARM training models and curricula are also undoubtedly significant. Moreover, the bias against ARM in Chinese society further magnifies the differences in personality traits among students with different majors. (shrink)

The energy hole is a severe problem for underwater acoustic distributed networks in that it affects the normal operations of the network and shortens the network’s life span. To deal with this problem, a loop-free routing control technique is proposed in this paper. The classical shortest-path routing control method is used to generate multiple disjointed routing tables. The residual energy of the nodes and the changing information of the uplink/downlink matrix are added to the data frames for distribution. The source (...) node specifies the routing path to transmit the data frames based on the changing information, and the relay nodes route the data frames strictly according to the routing path designated by the source node. Besides, the energy consumption of the relay node is saved by replying to the pseudo-ACK frame. Simulation experiments are implemented in four typical scenarios, and the results reflect that the proposed technique could extend the network’s life span by approximately 10% when compared to other mature techniques. Besides, it has no other negative effects on the normal operations of the network. (shrink)

The research on Tibetan speech synthesis technology has been mainly focusing on single dialect, and thus there is a lack of research on Tibetan multidialect speech synthesis technology. This paper presents an end-to-end Tibetan multidialect speech synthesis model to realize a speech synthesis system which can be used to synthesize different Tibetan dialects. Firstly, Wylie transliteration scheme is used to convert the Tibetan text into the corresponding Latin letters, which effectively reduces the size of training corpus and the workload of (...) front-end text processing. Secondly, a shared feature prediction network with a cyclic sequence-to-sequence structure is built, which maps the Latin transliteration vector of Tibetan character to Mel spectrograms and learns the relevant features of multidialect speech data. Thirdly, two dialect-specific WaveNet vocoders are combined with the feature prediction network, which synthesizes the Mel spectrum of Lhasa-Ü-Tsang and Amdo pastoral dialect into time-domain waveform, respectively. The model avoids using a large number of Tibetan dialect expertise for processing some time-consuming tasks, such as phonetic analysis and phonological annotation. Additionally, it can directly synthesize Lhasa-Ü-Tsang and Amdo pastoral speech on the existing text annotation. The experimental results show that the synthesized speech of Lhasa-Ü-Tsang and Amdo pastoral dialect based on our proposed method has better clarity and naturalness than the Tibetan monolingual model. (shrink)

The wanton dissemination of network pseudohealth information has brought great harm to people’s health, life, and property. It is important to detect and identify network pseudohealth information. Based on this, this paper defines the concepts of pseudohealth information, data block, and data block integration, designs an architecture that combines the latent Dirichlet allocation algorithm and data block update integration, and proposes the combination algorithm model. In addition, crawler technology is used to crawl the pseudohealth information transmitted on the Sina Weibo (...) platform during the “epidemic situation” from February to March 2020 for the simulation test on the experimental case dataset. The research results show that the LDA model can deeply mine the semantic information of network pseudohealth information, obtain the features of document-topic distribution, and classify and train topic features as input variables; the dataset partitioning method can effectively block data according to the text attributes and class labels of network pseudohealth information and can accurately classify and integrate the block data through the data block reintegration method; and considering that the combination model has certain limitations on the detection of network pseudohealth information, the support vector machine model can extract the granularity content of data blocks in pseudohealth information in real time, thus greatly improving the recognition performance of the combination model. (shrink)

In the context of the current uncertain, complex, and interdependent work systems, teams have become organizations’ substantial working unit, which in turn challenges the traditional view of employee performance and ultimately results in the emergence of team member work role performance. Employee team-oriented work role behaviors with proficiency, adaptivity, and proactivity, which are integrated by the new construct, are so crucial to team effectiveness that many organizations keenly expect to achieve team member work role performance through implementing a dispersed pay-for-performance (...) plan within a team. This study seeks to address the organizational practitioners’ main concern that whether pay dispersion among team members could actually help realize team member work role performance and further examines why and when an employee could respond to HPD within a team by engaging in team member work role behaviors from the perspective of the performance-shaping basis and team member’s workplace benign envy. Drawing on emotion-related theory, social comparison theory, legitimacy theory, expectation theory, and relative deprivation theory, it proposes that performance-based HPD could not only positively impact team member work role performance via workplace benign envy but also exert a direct-positive effect. Moreover, the activating effect of performance-based HPD on workplace benign envy and the mediating role are much stronger when a team member’s pay position is higher. The multi-source data including objective information and subjective perception among 362 ordinary employees within 66 Chinese organizational teams primarily supported the moderated mediation model. Yet, the direct-positive effect was not established. (shrink)

This work focuses on a multiagent system with time-varying interval uncertainty in the system matrix, where multiple agents interact through an undirected topology graph and only the bounding matrices on the uncertainty in the system matrix are known. A reduced-order interval observer, which is named the reduced-order neighborhood interval observer, is designed to estimate the relative state of each agent and those of its neighbors. It is shown that the reduced-order IO can guarantee the consensus of the uncertain multiagent system. (...) Finally, simulation examples are proposed to verify the theoretical findings. (shrink)

Growth mindset refers to our core belief that our talents can be developed through practice, which may influence our thoughts and behaviors. Growth mindset has been studied in a variety of fields, including education, sports, and management. However, few studies have explored whether differences in individuals’ growth mindsets influence college students’ self-reported mental health. Using the Growth Mindset Scale, Adolescent Self-rating Life Events Checklist, and SCL-90 Scale, data was collected from 2,505 freshmen in a University in China. Findings revealed that (...) the students within the growth mindset group scored significantly lower on “mental health issues” and “stress due to life events” than the students in the fixed mindset group. Our findings suggest that individuals with a growth mindset are less prone to mental health problems than individuals with a fixed mindset. (shrink)

In order to highlight the role of music teaching in the teaching of ideological and political courses, this study puts forward research on the integration of music teaching and ideological and political teaching. This study analyzes the promotion and necessity of college music teaching to ideological and political work, constructs a fusion model of college music teaching and ideological and political work, introduces deep learning methods, and weakens the influence of errors in the data of college music teaching and ideological (...) and political work. This study also optimized the integration mode of college music teaching and ideological and political work and realized the model research of college music teaching and ideological and political work. The experimental results show that the resource output amplitude controlled by the deep learning method has the best stability, and there is no large amplitude fluctuation during the experiment. The output amplitude and control time of the fusion resource are guaranteed and the fusion path of music teaching and ideological and political education is clearer. The maximum control time of the fusion resource of this method is 23.55 ms. (shrink)

本书的重点是谈作者对波普尔的看法,主要包括对波普尔思想的理解和对波普尔思想的评论和批评两部分。.

The present study examined the longitudinal association among the Big Five personality traits, maladaptive cognitions, and Internet addiction during the COVID-19 pandemic. A total of 481 Chinese university students were surveyed three times by using the Chinese version of the Big Five Personality Traits Scale, Maladaptive Cognitions Scale, and Internet Addiction Scale. The results of a cross-lagged panel analysis highlighted that extraversion, agreeableness, conscientiousness, and openness were negatively associated with maladaptive cognitions and Internet addiction, whereas neuroticism was found to be (...) positively associated with maladaptive cognitions and Internet addiction across time; associations among the Big Five personality traits, maladaptive cognitions, and Internet addiction were dynamic and bidirectional; and maladaptive cognitions played mediating roles in extraversion, agreeableness, conscientiousness, openness, and Internet addiction across time. The Big Five personality traits, maladaptive cognitions, and Internet addiction predicted each other across time, and maladaptive cognitions were likely to be the key mediating factor in the associations between the Big Five personality traits and Internet addiction, which supported and expanded the Davis’ cognitive–behavioral model. (shrink)

Di yi juan. Si wei xue, yuan li lun he zhe xue juan -- Di er juan. Mei xue juan -- Di san juan. Fu hao fen xi he yu yan fen xi juan -- Di si juan. Wen hua xue yu dao de zhe xue juan -- Di wu juan. Shi wen juan.