Taking the backfilling station for the Chifeng NFC Baiyinnuoer Mining Co. Ltd. as an example to resolve the problems of uneven bottom flow concentration and slow settling speed of tailings particles during the coagulation and settling process of total tailings, various candidate anionic polyacrylamide flocculants were subjected to tailings static coagulation and settling tests to select the most suitable flocculant type. Finally, the coagulation effect was verified through industrial experiments, and the addition parameters were optimized. The results show that the optimal flocculant type for settling the total tailings of the mine is SNF1055SH. When the concentration of the total tailings slurry is 14%, the flocculant solution concentration is 2.5‰, and the flocculant dosage is 30 g/t, it can ensure that the bottom flow mud layer of the deep cone thickener is uniform and the top overflow water is clear.

In construction projects, procurement suppliers not only affect the quality and progress of the project, but also directly affect the cost of the project. How to select high-quality suppliers that meet project requirements from numerous suppliers has become an urgent problem to be solved. Based on this, a research on the selection of construction project procurement suppliers based on ANP+VIKOR algorithm was proposed. Taking into account multiple factors, a multi-dimensional supplier selection indicator system was constructed, and the indicator data was standardized. The ANP algorithm was used to clarify the relationship between each indicator and the weights of the indicators were calculated. The VIKOR algorithm was used to calculate the group utility value and individual regret value of each supplier, and the compromise value of each supplier was obtained, and the suppliers were ranked. Case analysis shows that the studied method can stably select the optimal supplier and exhibits relative insensitivity to changes in decision mechanism coefficients, demonstrating its reliability and practicality in practical applications.

Technology-based talents are an important support for the development of new quality productivity. Local technology legislation should create a favorable legal environment for the development of technology-based talents. Based on legislative texts, a comparative analysis was conducted on the chapter design, standardized objects and regulatory content related to technology-based talents in the comprehensive science and technology regulations of eleven provinces and cities. On this basis, it is proposed that local efforts to strengthen legislation on technology-based talents should be regulated in the form of a whole chapter, clarify the legislative norms and form a complete legislative system with talent work as the main content, in order to provide useful inspiration for local construction of a technology-based talent legislative system that adapts to new quality productivity.

Based on the data of A-share listed companies from 2013 to 2022, the multi-period DID method and the central ecological environment protection inspection were used as a natural experiment to analyze the impact mechanism of the “combination of coercion and public participation” type of environmental accountability on the financialization of enterprises. The study finds that environmental accountability significantly inhibits the financialization of heavily polluting firms. Its path of action is realized through improving the quality of environmental information disclosure. Corporate technological innovation positively strengthens the inhibitory effect of accountability on financialization but does not modulate the mediating effect of information disclosure. The heterogeneity analysis shows that the inhibitory effect of environmental accountability is more significant under the high level of marketization and the strong linkage between the government and the enterprises.

Intellectual property protection and scientific research investment are important policy tools to promote scientific research in colleges and universities. Based on the perspective of policy mix, the relevant provincial data from 2008 to 2022 was used, and the propensity score matching method was applied to study the absolute effect and incentive effect of different policy mix on the scientific research output of universities, and heterogeneity test by region was conducted. The results show that the policy combination of high intellectual property protection and high scientific research investment has a significant role in promoting the scientific research output of universities. Compared with high IPR protection and low IPR protection and high IPR protection, high IPR protection and high IPR protection have a greater role in promoting the scientific research output of universities.

The policy of adding deduction for R&D expenses has a broad impact on high-tech enterprises, especially on their innovation activities.High-tech enterprises from 2014 to 2023 was taken as the research object to examine the impact of the R&D expense plus deduction policy on enterprise innovation. The results of the study show that enhancing the intensity of the policy has a more significant incentive effect on both R&D investment and innovation ability of high-tech enterprises. These effects are heterogeneous in terms of enterprise size, that is the incentive effect on innovation is better for large-scale enterprises. Based on the conclusions of the study, it is recommended to further increase the proportion of R&D expenses plus deduction, optimize the design of tax incentives to take into account enterprises of different sizes, and establish a perfect policy evaluation and feedback mechanism to provide a good platform for enterprise innovation.

With the increasingly widespread application of artificial intelligence (AI) technologies, more and more people are concerned about whether machine intelligence will replace traditional human labor. However, while there are concerns, the relationship between AI and traditional labor is not entirely mutually exclusive. They can cooperate under certain conditions. The BP neural network was applied to conduct a comprehensive evaluation of ChatGPT performance satisfaction, analyze the public's satisfaction with ChatGPT's performance, and provide references and suggestions for the future co-development of ChatGPT with humans. A satisfaction survey was conducted among 11 high-tech industrial parks and university students in Hangzhou, exploring the public's satisfaction with ChatGPT's generated language quality, knowledge accuracy, context understanding ability, model response speed, controllability and interpretability. In the prediction of public satisfaction, the BP neural network performs well in four indicators, such as accuracy, recall, harmonic mean and F1-score during model testing. The result shows that ChatGPT's context understanding ability, controllability and interpretability are important influencing factors of ChatGPT performance satisfaction. In the future, ChatGPT should further strengthen training and optimization in these three aspects.

In recent years, China has begun to regulate real estate prices based on monetary policy. In order to study the impact of monetary policy on real estate prices, the QVAR model was used to explore the impact of monetary policy factors on real estate price changes by using quantile impulse response graph and variance decomposition. The monetary policy used the quantitative monetary policy, the money supply M2 and the price-based monetary policy, the interbank interest rate as the standard, and the real estate price from 2003 to 2023 as the impact variables, and the M2 growth rate and the interbank interest rate were used to make quantile impulse response function graphs and variance decomposition analysis based on the QVAR model for real estate prices. The results show that quantitative monetary policy is negatively correlated with real estate prices in the short term and positively correlated in the long term, and price-based monetary policy is negatively correlated with real estate prices, and the influence of money supply on real estate prices accounts for a larger weight.

To study the mechanism of the effect of higher education on economic growth, Based on the panel data of 30 provinces in China (due to the lack of data, the statistical data mentioned here do not include the Tibet Autonomous Region, the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province) from 2010 to 2021 was used. This role of technological innovation in the impact mechanism of higher education was firstly explored by using the mediation effect, and then the relationship between higher education and economic growth was empirically analyzed by using the spatial error model. The results show that in the mediation effect test, all variables passed the significance test. From a spatial perspective, there are regional differences in the role of technological innovation in economic growth. Therefore, the mediating effect of technological innovation is the pathway through which higher education plays a role in economic growth.

The overall victory in the battle against poverty indicates that China has comprehensively solved the problem of poverty, but some residents still have the risk of returning to poverty. In order to avoid this phenomenon as much as possible, the Party Central Committee clearly proposed to actively establish a monitoring mechanism to prevent returning to poverty. It constructs the rural poverty return monitoring index system and EGM-Markov poverty return risk early warning model, forecasts the development trend and divides the early warning level, and takes YS County of Heilongjiang Province as a case to verify the feasibility of the model. In addition to establishing a long-term assistance mechanism, stimulating the endogenous motivation of the poor is very important to avoid returning to poverty.