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At present, China's electricity market has been initially built, direct trading of electricity continues to increase, and the mode of "multiple purchase and multiple sale" has emerged in the market, which enables the electricity market to compete effectively and make the optimal allocation of resources. Therefore, it is necessary to evaluate the operation of the electricity market. The article firstly studied the indicators of power market operation from three aspects: economic value, green value and security value; secondly, established a three-level evaluation index system of power system; on this basis, proposed a comprehensive evaluation model of power market based on fuzzy comprehensive evaluation. It provides a reference basis for the evaluation of China's power grid operation and is of great significance to promote the healthy development of China's power market.

Academic stress has been proven to have a negative correlation with students' physical and psychological health. However, the specific mechanisms underlying this relationship among adolescents in mainland China have been rarely investigated. Using a multi-stage cluster random sampling, a total of 552 adolescents were recruited voluntarily to complete the questionnaire survey. Results demonstrated that high academic stress was associated with high level of anxiety, which mediated the relation between academic stress and aggression. Moreover, the mediating effect of anxiety was moderated by extracurricular participation. The specific association between academic stress and anxiety was weaker among adolescents with more extracurricular participation than those with less extracurricular participation. This study contributes to current knowledge by revealing the mechanisms among academic stress, anxiety, extracurricular participation, and adolescents' aggression. Findings also highlight the importance of extracurricular participation in mitigating the negative effect of academic stress on anxiety., Author(s): Chunkai Li [sup.1] , Xinwen Zhang [sup.2] , Xiaochun Cheng [sup.1] Author Affiliations: (1) grid.41156.37, 0000 0001 2314 964X, School of Social and Behavioral Sciences, Nanjing University, , Nanjing, [...]

This paper presents the ontological design and implementation of the differentiated learning environment in the domain model of an intelligent tutoring system for children with specific learning disabilities. It addresses the learners need for differentiated instruction in a preferential learning environment. The proposed model helps to identify the most affected learning domains and related multiple-criteria's which effects the learners. The learning resources and problems diagnosis questionnaires are organized and used with various learning strategies to create various learning environments such as case-based learning environment, game-based learning environment, practice-based learning environment and visual-based learning environment. Different techniques can define a set of rules to decide the most preferred learning environment. Here, multiple criteria decision analysis approach map the information, learning resources and learning environments to create a differentiated learning environment for the learning disabled. The contribution of proposed model is to reduce the gap between learner and learning habits with special needs. Our model is implemented as domain model of an intelligent tutoring system to develop learner-centric learning environment. In the designed intelligent tutoring system (ITS), the differentiated learning environment domain model is further evaluated and validated by a set of fuzzy rules. The pilot test result shows that proposed model enables an ITS to improve the implementation of appropriate learning strategies with high accuracy and sensitivity for both learning and non-learning-disabled users.

Sustainable quality education is a big challenge even for the developed countries. In response to this, education 4.0 is gradually expanding as a new era of education. This work intends to unfold some hidden parameters that are affecting the quality education ecosystem (QEE). Academic loafing, unawareness, non-participation, dissatisfaction, and incomprehensibility are the main parameters under this study. A set of hypothesis and surveys are exhibited to study the behavior of these parameters on quality education at the institution level. The bidirectional weighted sum method is deployed for precise and accurate results regarding boundary value analysis of the survey. The association between parameters understudy and quality education is illustrated with correlation and scatter diagrams. Academic loafing, the hidden and unintended rudiment that affects the QEE is also defined, intended and explored in this work. The study exhibits that the average percentage association between quality education and all the parameters under study is 93.32%, whereas awareness has the least association (82.63%) and academic loafing has the highest association (99.35%) with quality education. The paper proposes a cognitive-IoT (internet of things) based multilayered QEE as a remedial solution for sustainable quality education. The emerging demand of real-time data processing for the education 4.0 environment, makes MQEE suitable for education 4.0 environment. The IoT enabled heterogeneous-data preprocessing, integration, and analysis to foster the proposed model with robustness, scalability, and flexibility. The proposed abstraction mechanism, public/private reporting, and IoT-based data preprocessing system are rich enough to handle data management issues under education 4.0 environment.