The promulgation of the Curriculum Standards for ordinary high School (2017 edition, 2020 revision) has effectively promoted the reform of high school mathematics classroom. In order to cope with the change of textbook content in the new curriculum reform, it has become one of the important tasks for high school mathematics teachers to implement teaching activities better and sort out and analyze the differences between the old and new textbooks. This paper analyzes the differences between old and new textbooks from the three dimensions of system structure, course content and example exercises, and gives some reasonable teaching suggestions. Among them, the new textbook uses 2019 "Ordinary High School Textbook" person-taught A version of Compulsory Mathematics 1, and the old textbook uses 2004 "Ordinary High School Mathematics Curriculum Standard Experimental Textbook" person-taught A version of compulsory Mathematics 4. In general, the adjustment of the new teaching materials is more in line with the cognitive characteristics of students, pay attention to the penetration of mathematical culture and pay attention to the development of students' mathematical core literacy.

This article presents an analysis of Russia’s outward foreign direct investment based on the balance of payments. The country has been affected by the “Dutch disease,” characterized by a heavy reliance on the mining industry and revenues from oil and gas exports. The financial account reveals a consistent outflow of capital from Russia, surpassing inflows. A significant portion of domestic investment goes abroad, often to offshore destinations. This capital outflow has not been fully offset by foreign capital inflows. These findings underscore the challenges faced by Russia in managing its financial position, including the need to address capital outflows, diversify the economy, and reduce dependence on raw material exports. Furthermore, this article aims to identify the presence of Russian capital in OECD countries by comparing data from the Central Bank of Russia and the OECD. The analysis reveals significant discrepancies between the two datasets, primarily due to unavailable or confidential information in the OECD dataset. These variations can also be attributed to differences in methodology and the specific nature of Russian outward direct investments, particularly those involving offshore jurisdictions. As a result, accurately determining the extent of Russian capital in OECD countries based on the available data becomes a challenging task (including for the tourism industry as well).

Sketching on stimulus-organism-response theory, this study aims to investigate the mediating effect of environmental passion on the relationship of the environmentally specific servant leadership with employees’ green behavior. Using purposive sampling approach, the authors adopted one month time-lagged approach to collected data from 232 academic employees in higher education institutions of China. Response rate in this study is 46.40%. The partial least-structural equation modeling (PLS-SEM) analysis was conducted in the smartpls 4.0 software to test the proposed hypotheses. The current empirical findings confirm that environmentally specific servant leadership significantly positively influence employee’s environmental passion and environmental passion significantly positively affects the employee’s workplace green behaviors. This current finding offered support in favor of mediating impact of environmental passion on the “environmentally specific servant leadership-employees workplace green behaviors” relationship. To the best of authors, this study is among pioneers’ studies to investigate the integrated relationship of environmentally specific servant leadership, environmental passion and green behavior in higher education institutions context of China. Limitations and implication have been elaborated at the end.

The purpose of this paper is to explore the performance of ridge regression and the random forest model improved by genetic algorithm in predicting the Boston house price data set and conduct a comparative analysis. To achieve it, the data is divided into training set and test set according to the ratio of 70-30. The RidgeCV library is used to select the best regularization parameter for the Ridge regression model, and for the random forest model, the genetic algorithm is used to optimize the model's hyperparameters. The result shows that compared with ridge regression, the random forest model improved by genetic algorithm can perform better in the regression problem of Boston house prices.

In recent years, China has been emphasizing the importance of "mass entrepreneurship and innovation". Through such policies, more outstanding "great country craftsmen" should be cultivated, providing strong support for the overall industrial upgrading of our country. In order to achieve this grand national strategic goal, each university needs to conduct targeted exploration of the integration of innovation, entrepreneurship, and craftsmanship spirit based on its own actual situation. This article will explore the integrated cultivation mode of entrepreneurship and innovation+craftsmanship spirit from multiple aspects such as national policy guidance, student training plans, and training channels, based on the specific situation of the current development of entrepreneurship and innovation, combined with the research results of our school. In the process of entrepreneurship and innovation education, we will cultivate students' craftsmanship spirit and provide sufficient assistance for social development.

The advent of the era of big data has brought great changes to accounting work, and vocational colleges and universities, as the main place for cultivating application-oriented new business talents, need to change the way of talent training in time in the face of this change. By describing the impact of the era of big data on the demand for new business talents, this paper analyzes the analysis of the training of new business and scientific and technological talents in vocational colleges and universities in the era of big data from the perspectives of talent training target positioning, professional curriculum setting and teacher quality, accurately locates the talent training goals of new business professional groups in vocational colleges, scientifically sets up the curriculum system, and comprehensively improves the teaching staff.