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This study proposes a teaching resource recommendation method (TRRDLMF) based on deep learning and probabilistic matrix decomposition, aiming to improve teaching resource recommendation’s accuracy and personalization level. The study combines hybrid neural network feature extraction of teaching resources and user feature extraction based on extended noise-reducing self-encoder and extended probabilistic matrix decomposition-based teaching resource recommendation technique. The study validates the model’s effectiveness by conducting empirical analyses on four online learning platform datasets of different sizes. The recommendation system can effectively track learners’ knowledge mastery status and learning preferences, and provide corresponding teaching resources. Test question similarity and difficulty analysis results show that the model can accurately capture the correlation between test questions and provide complementary data in education. The personalized recommendation analysis reveals the learners’ knowledge preference states that change with learning, demonstrating the model’s ability to give explanations at the level of learners’ knowledge preferences. The analysis of the impact of data size on recommendation results shows that the recommender system can achieve up to 73.12% accuracy and 97.89% recall for different TOP-K recommendation lists, with the best F-value at TOP-6. The personalized recommendation system for teaching resources based on the joint probability matrix decomposition model and CNN improvement algorithm proposed by the research demonstrates significant effects in improving the accuracy and personalization level of teaching resources recommendation, which helps learners to acquire suitable learning resources more efficiently, and has high practical value and promotion potential.

There is an interdependent symbiotic relationship between humans and water; scientific and effective assessment of the human–water symbiosis relationship is of great significance for the promotion of sustainable development. This study developed a novel framework of the human–water symbiosis relationship under an integrated perspective, which included theoretical interpretation, quantitative assessment, pattern discrimination, and an attribution analysis. Based on the symbiosis theory, the theoretical analysis of the human–water relationship was carried out to analyze the three basic elements of the human–water system, and then the evaluation index system of the human–water symbiosis system was constructed to quantitatively assess the development level of the human system and the water system. The Lotka–Volterra model was used to identify the symbiotic pattern, and the human–water symbiosis index was calculated to characterize the health state of the human–water symbiosis system. The main influencing factors of the human–water symbiosis system were further identified through an attribution analysis. Finally, a case study was carried out with 18 cities in Henan Province. Results reveal that (a) the proposed method can effectively realize the quantitative characterization of the human–water symbiosis relationship, with good applicability and obvious advantages; (b) the human–water symbiosis pattern of cities in Henan Province is dominated by the "human system parasitizes water system (H+W−)" pattern, and more attention should be paid to the water system in the subsequent development of it; and (c) the main factors influencing the human system, the water system, and the human–water symbiosis system are the research and development (R&D) personnel equivalent full-time (H7), per capita water resources (W1), and proportion of water conservancy and ecological water conservancy construction investment (W6), respectively. The findings can provide theoretical and methodological support for the study of the human–water symbiosis relationship and sustainable development in other regions. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is not only an important ecological barrier and an important grain production core area, but also a key area for China to win the battle of poverty alleviation. 【Objective】 Scientifically evaluate the high-quality development level of the Yellow River Basin and analyze its key constraints. 【Method】 Based on the study and understanding of the major national strategies of the Yellow River, this paper gave the definition and connotation interpretation of the concept of high-quality development, and proposed the judgment criteria for high-quality development, including social harmony and stability, orderly economic growth, safe supply of resources, ecological health and livability and culture advanced leadership (collectively referred to as the “Five Criteria”). Based on the “Five Criteria”, this paper built a high-quality development evaluation system and evaluated the high-quality development level of the Yellow River Basin from 2008 to 2018. 【Result】 The results show: ①The level of high-quality development of the Yellow River Basin is increasing, from a low level in 2008 to a medium level; ②In the standard level, “ecological health and livability” is the main restrictive criterion, while “safe supply of resources” is the primary advantage criterion for the high-quality development of the Yellow River Basin; ③The spatial and temporal differences of high-quality development level in the Yellow River Basin are obvious. Among the provinces, Shandong is the most stable. In the time dimension, the differences among provinces are the first gradually shrink after expansion. 【Conclusion】 The level of high-quality development in the Yellow River Basin needs to be further improved.