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Soybean–maize intercropping system can improve the utilization rate of farmland and the sustainability of crop production systems. However, there is a significant gap in understanding the interaction mechanisms between soil carbon (C), nitrogen (N), and phosphorus (P) cycling functional genes, rhizosphere microorganisms, and nutrient availability. To reveal the key microorganisms associated with soil nutrient utilization and C, N, and P cycling function in the soybean–maize intercropping system, we investigated the changes in soil properties, microbial community structure, and abundance of functional genes for C, N, and P cycling under soybean–maize intercropping and monocropping at different fertility stages in a pot experiment. We found that there was no significant difference in the rhizosphere microbial community between soybean–maize intercropping and monocropping at the seeding stage. As the reproductive period progressed, differences in microbial community structure between intercropping and monocropping gradually became significant, manifesting the advantages of intercropping. During the intercropping process of soybean and maize, the relative abundance of beneficial bacteria in soil rhizosphere significantly increased, particularly Streptomycetaceae and Pseudomonadaceae. Moreover, the abundances of C, N, and P cycling functional genes, such as abfA, mnp, rbcL, pmoA (C cycling), nifH, nirS-3, nosZ-2, amoB (N cycling), phoD, and ppx (P cycling), also increased significantly. Redundancy analysis and correlation analysis showed that Streptomycetaceae and Pseudomonadaceae were significantly correlated with soil properties and C, N, and P cycling functional genes. In brief, soybean and maize intercropping can change the structure of microbial community and promote the proliferation of beneficial bacteria in the soil rhizosphere. The accumulation of these beneficial bacteria increased the abundance of C, N, and P cycling functional genes in soil and enhanced the ability of plants to fully utilize environmental nutrients and promoted growth. [ABSTRACT FROM AUTHOR]

Under the background of a green, low carbon economy, it is significant to accurately estimate the future CO2 emissions of countries with significant CO2 emissions for developing the world's green economy. A new Nonlinear Grey Bernoulli and BP neural network combined model (BP-ONGBM (1,1) model) have been proposed to study the CO2 emissions of China, the USA, the European Union, India and Japan. Firstly, the Particle Swarm Optimization (PSO) algorithm is optimized using the Artificial Fish Swarm Algorithm (AFSA). Then, the background value of the ONGBM (1,1) model is dynamically optimized. Based on the linearization of the model, the time response function is derived. Then, the ONGBM (1,1) model is combined with the BP neural network model. An improved PSO algorithm determines the combined weight and the background value coefficient. Finally, according to the observation data from 2010 to 2021 in the Emissions Database for Global Atmospheric Research 2022, the model is established to calculate the CO2 emissions of the selected countries from 2022 to 2026 and compared with the prediction results provided by multiple competitive models. The empirical application shows that the proposed BP-ONGBM (1,1) model is significantly better than other competitive models. [ABSTRACT FROM AUTHOR]

Hydrogen-based, boron-based, and carbon-based compounds have been the focus of previous investigations in the process of searching for electron–phonon high temperature superconductors. In this paper, the exploration of superconductivity of the hole doping of metal covalent carbon–nitrogen compound MgCN2 within virtual-crystal approximation treatment is proposed based on first-principles calculations. For the hole-doped Mg0.9Li0.1CN2, the electron–phonon coupling strength λ and the superconducting transition temperature T C are predicted to be 0.66 and 14.4 K, respectively. This shows that the metal covalent carbon–nitrogen compound is a potential candidate for electron–phonon superconducting material. [ABSTRACT FROM AUTHOR]

Hydrogen-based, boron-based, and carbon-based compounds have been the focus of previous investigations in the process of searching for electron–phonon high temperature superconductors. In this paper, the exploration of superconductivity of the hole doping of metal covalent carbon–nitrogen compound MgCN2 within virtual-crystal approximation treatment is proposed based on first-principles calculations. For the hole-doped Mg0.9Li0.1CN2, the electron–phonon coupling strength λ and the superconducting transition temperature T C are predicted to be 0.66 and 14.4 K, respectively. This shows that the metal covalent carbon–nitrogen compound is a potential candidate for electron–phonon superconducting material. [ABSTRACT FROM AUTHOR]