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Under the background of the new normal economy, ecotourism maintains a good momentum of development. Therefore, it can be foreseen that industrial integration is an inevitable trend in the development of contemporary industries, and the integration of cultural industries and tourism industries will bring good effects to regional economic development. In order to fully study the impact of ecotourism and its applied technologies on regional economy and culture, this paper proposes research on the application of virtual reality technology in the coordination and interaction of regional economy and culture in the sustainable development of ecotourism. The approach of this paper is to study VR technology in digital tourism and then to evaluate the sustainability of ecotourism and economic culture. The role of these methods is to study the interaction process between the tourism industry, regional economy, and cultural industry. It explores the law of action between the three so as to achieve the purpose of system optimization. Taking Henan Province, China, as an example, this paper discusses the application of virtual reality technology in ecotourism and studies the impact of ecotourism on economy and culture. The experimental results show that the average value of ecotourism-economic-cultural coordination degree in Henan Province is 0.399, and it is urgent to apply virtual reality technology in ecotourism. [ABSTRACT FROM AUTHOR]

In order to carry out a quantitative analysis of the teaching effect of college English courses based on multivariate matrix evaluation model, this paper takes as research objects 87-year 2020-enrolled undergraduate students from a university in Zhengzhou City, Henan Province, central China. On the basis of summarizing and analyzing previous research works, this study expounded the research status and significance of quantitative analysis of the teaching effect of college English courses, elaborated the development background, current status, and future challenges of multivariate matrix evaluation model, introduced the data source and the subjects, contents, and means of teaching effect quantification in this research, analyzed the feedback and guiding function of the teaching effect quantification result of college English courses, discussed the motivation and diagnosis function of the teaching effect quantification result of college English courses, conducted analyses of factors affecting the teaching effect quantification of college English courses, constructed the quantitative dimension of teaching effect of college English courses based on the multivariate matrix evaluation model, and finally designed the quantification system of teaching effect of college English courses based on the multivariate matrix evaluation model. The research results show that the quantitative analysis process of the teaching effect of college English courses has the characteristics of complex structure and many hierarchies, and there are also mutual influences and functions between its subsystems. In order to ensure the rationality and effectiveness of comprehensive quantification, the index system construction of the multivariate matrix evaluation model follows scientific, systematic, and focused principles. The teaching effect quantification process combines four influencing factors of perspective, content, mode, and method with the quantification standard, and constructs a hierarchical quantification structure with target layer, restriction factor layer, and restriction sub-factor layer. The tools it uses usually include observations, interviews, self-evaluation, mutual evaluation, student files, reading notes, project presentations, etc. Teachers adjust teaching goals and plans in time by observing the quantification results of students at all levels, which will help improve students' enthusiasm for learning and give full play to students' autonomy and initiative in English courses. [ABSTRACT FROM AUTHOR]

A rock burst accident occurred on coalface 13230 of the Gengcun Coal Mine in Henan Province. Through a field investigation, theoretical analysis, and microseismic monitoring, we studied how the rock burst, which was caused by overall seam floor slip and instability, occurring under an ultrathick conglomerate. Because the overlying ultrathick conglomerate in the mined-out zone close to coalface 13230 had been inadequately mined, the leading section of the coalface was under a high level of stress. Combined with the tectonic stresses from the F16 faultage and the soft floor structure, these factors caused the floor of this coalface to trigger the overall slip-type rock burst. In this paper, an estimation model of the ultimate bearing capacity of a seam floor under an ultrathick conglomerate and the advancing abutment pressure on the coalface is presented. This model is used to show that the ultimate bearing capacity of the seam floor on coalface 13230 is 26.3 MPa, and the abutment pressure is far more than the floor bearing capacity. We also present pressure relief and reinforced supporting measures, which can effectively prevent floor slip-type rock bursts from occurring. The results of this study provide a reference for the prevention and control of floor slip-type rock bursts in coal mining under an ultrathick conglomerate. [ABSTRACT FROM AUTHOR]

Regional agricultural drought vulnerability (RADV) is a complex nonlinear problem caused by the interaction of multiple factors, and an objective and systematic method is proposed by this paper to identify its influencing factors, which plays an important role in preventing and regulating the risks of regional agricultural drought. Firstly, to provide a reference for the evaluation problem in selecting the number of factors, the influencing factors affecting RADV are revealed by using the method of phase space reconstruction (PSR). Secondly, to rank the importance of influencing factors, a grey trend relational analysis (TGRA) method is proposed, considering the dynamic development relationship between the RADV index and the influencing factors and integrating the absolute and relative variation of sequences in each corresponding period. Finally, to reduce the collinearity between the influencing factors, a grey trend relational clustering (TGRC) analysis method is proposed. According to the above steps, the process of identifying factors based on PSR-TGRC method is formed. Taking Henan Province as an example, 14 main influencing factors and their effects on RADV are identified from all 42 factors, and the identification results which are consistent with the actual drought relief work show the rationality and practicality of PSR-TGRC method and provide theoretical support for formulating strategies of regional agricultural disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]