以严复的中西文化观为核心,将中国与西欧这两大思想文化体系,在历史的纵向发展与时代的横向座标这一大背景下,作宏观与微观的对比分析。.

Visual programming language is a crucial part of learning programming. On this basis, it is essential to use visual programming to lower the learning threshold for students to learn about artificial intelligence to meet current demands in higher education. Therefore, a 3-h AI course with an RGB-to-HSL learning task was implemented; the results of which were used to analyze university students from two different disciplines. Valid data were collected for 65 students in the Science -student group and 39 students in (...) the Humanities -student group. Independent sample t-tests were conducted to analyze the difference between cognitive styles and computational thinking. No significant differences in either cognitive style or computational thinking ability were found after the AI course, indicating that taking visual AI courses lowers the learning threshold for students and makes it possible for them to take more difficult AI courses, which in turn effectively helping them acquire AI knowledge, which is crucial for cultivating talent in the field of AI. (shrink)

This study explores the impact of teachers? perception of trust in colleagues on their sense of empowerment in Mainland China, with a particular focus on the mediating role of teacher efficacy. The results of a survey of 1646 teachers indicate that although teachers scored positively on trust in colleagues, efficacy and empowerment, they had relatively lower scores on general teaching efficacy (GTE) and participation in decision-making. Trust in colleagues was a significant predictor of teacher empowerment. In addition, personal teaching efficacy (...) had a significant mediation effect on the relationship between trust in colleagues and teacher empowerment, while GTE had not. These findings lead to some implications for understanding the nature of GTE and the relationship between trust and teacher empowerment. (shrink)

The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the solution of (...) stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results. (shrink)

As a worldwide epidemic in the digital age, cyberbullying is a pertinent but understudied concern—especially from the perspective of language. Elucidating the linguistic features of cyberbullying is critical both to preventing it and to cultivating ethical and responsible digital citizens. In this study, a mixed-method approach integrating lexical feature analysis, sentiment polarity analysis, and semantic network analysis was adopted to develop a deeper understanding of cyberbullying language. Five cyberbullying cases on Chinese social media were analyzed to uncover explicit and implicit (...) linguistic features. Results indicated that cyberbullying comments had significantly different linguistic profiles than non-bullying comments and that explicit and implicit bullying were distinct. The content of cases further suggested that cyberbullying language varied in the use of words, types of cyberbullying, and sentiment polarity. These findings offer useful insight for designing automatic cyberbullying detection tools for Chinese social networking platforms. Implications also offer guidance for regulating cyberbullying and fostering ethical and responsible digital citizens. (shrink)

Teacher emotion has become an important issue in English language teaching as it is a crucial construct in understanding teachers' responses to institutional policies. The study explored teachers' emotion labor and its impact on teachers' pedagogical decision-making in English for Specific Purposes teaching in a university of Traditional Chinese Medicine in China. Drawing on a poststructural perspective, the study examined data from two rounds of semi-structured interviews, policy documents and teaching artifacts. The analysis of data revealed that the major emotion (...) labor facing the participants revolved around students' disengagement in class. Teachers experienced mixed feelings of anticipation, disappointment, anger, and empathy toward students and distanced themselves from institutional feeling rules enforcing objective assessment of students' performance and punishing students for lack of engagement in class. The study found that teacher emotion labor served as the site for their pedagogical modifications. ESP teachers' beliefs in the importance of attending to students' needs become a powerful discourse in supporting teachers to strategically subvert institutional feeling rules and critically reflect on the dysfunctions of curriculum, orienting teachers' agentic actions in modifying pedagogical practices. We thus underscore this empowering discourse as the bridge to connect teachers' policy negotiation and their actual classroom practices. We also highlight teachers' pedagogical decision-making as a process of the interactions of teacher emotion, teachers' reflexive practices, and power relations. The study ended by suggesting more longitudinal research where teachers' beliefs as previously appropriated discourses could be examined comprehensively as they were both the construct of emotion labor and the potential subverting power in supporting teachers' pedagogical decision-making in policy negotiation. (shrink)

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients (...) with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. (shrink)

Taiwan was affected by an outbreak of severe acute respiratory syndrome (SARS) in early 2003. A questionnaire survey was conducted to determine (1) the perceptions of risk of SARS infection in nurses; (2) the proportion of nurses considering leaving their job; and (3) work as well as non-work factors related to nurses' consideration of leaving their job because of the SARS outbreak. Nearly three quarters (71.9%) of the participants believed they were 'at great risk of exposure to SARS', 49.9% felt'an (...) increase in workload', and 32.4% thought that people avoided them because of their job; 7.6% of the nurses not only considered that they should not care for SARS patients but were looking for another job or considering resignation. The main predictors of nurses' consideration of leaving their job were shorter tenure, increased work stress, perceived risk of fatality from SARS, and affected social relationships. The findings are important in view of potential impending threats of pandemics such as avian influenza. (shrink)

The increasing number of quick response code mobile payment users heralds the coming of a cashless society. However, the extent to which the coronavirus disease 2019 pandemic accelerated the adoption of QR code mobile payment has not been sufficiently researched. Based on social learning theory, this study models how external interaction with the environment has affected the internal appraisal and behavioral intention to adopt QR code mobile payment during COVID-19. Empirical results from 248 respondents revealed that perceived severity and social (...) influence positively affected the perception of utilitarian and health benefits of respondents, which in turn influenced the behavioral intention to use the QR code mobile payment. The theoretical contribution and managerial implications of this study are also discussed. (shrink)

Although the management and planning of water resources are extremely significant to human development, the complexity of implementation is unimaginable. To achieve this, the high-precision water consumption prediction is actually the key component of urban water optimization management system. Water consumption is usually affected by many factors, such as weather, economy, and water prices. If these impact factors are directly combined to predict water consumption, the weight of each perspective on the water consumption will be ignored, which will be greatly (...) detrimental to the prediction accuracy. Therefore, this paper proposes a deep neural network-based complex system for urban water management. The essence of it is to formulate a water consumption prediction model with the aid of principal component analysis and the integrated deep neural network, which is abbreviated as UWM-Id. The PCA classifies the factors affecting water consumption in the original data into three categories according to their correlation and inputs them into the neural network model. The results in the previous step are assigned weights and integrated into the form of fully connected layer. Finally, analyzing the sensitivity of the proposed UWM-Id and comparing its performance with a series of commonly used baseline methods for data mining, a large number of experiments have proved that UWM-Id has good performance and can be used for urban water management system. (shrink)

本书写作背景主要介绍该书写作的缘起、写作的社会背景等。主要内容是按全书章节或按分类,详细介绍该著作的基本情况。主要思想主要介绍该书的主要观点、学术思想、争论的问题等。.

本书饱蘸着我军军魂所赋予我们的激情,与战友们一起追忆我军以往的辉煌历程,讴歌我军当今的伟大壮举,憧憬我军未来的丰功伟绩,漫议军人的理想、信仰、道德、信念、气节、情操、奉献、价值。.

该书分“修辞理论探索”、“双关新论”、“修辞文化论”、“语体风格论”、“修辞学史研究”、“争鸣与质疑”等七部分,收入相关论文34篇。.

Ben shu chan shu de nei rong shi zhi shi zhong ya fang wen hua de shen tou yu jiao liu.

本书共分佛学、宋明理学、清初朴学、专题探讨、附录五部分。主要内容包括: 自汉魏至宋初的儒佛道三教关系和道学的形成 ; 试说大乘佛教的兴起 ; 论张载思想 ; 程朱理学批判 ; 论王夫之思想 ; 论王廷相思想 ; 关于我国封建社会土地所有制的一些意见等.