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New‐type professional farmers are new‐type rural talents with scientific and cultural literacy and professional knowledge of agriculture under the background of rural revitalization. The new type of professional farmers is of great significance for accelerating agricultural modernization and promoting the construction of a powerful modern socialist country. In the process of cultivating new types of professional farmers in rural areas, it is necessary to break through the previous informatization constraints of poor information flow, and give full play to the role of advanced information technology to promote the sustainable economic development. This paper proposes a new type of professional farmer cultivation platform based on edge computing architecture to improve the cultivation efficiency of new type of professional farmers, so as to better promote the development of rural informatization. Aiming at the challenges of energy consumption under the edge platform architecture, this paper proposes a dynamic scheduling method for semi‐online tasks for edge computing platforms. In order to evaluate the effectiveness of the algorithm, the method in this paper is compared with the classic scheduling algorithm, and simulated and verified on the CloudSim platform. Experimental results show that the proposed method outperforms other algorithms in the task completion time metric. With the expansion of task scale, more energy consumption can be saved by using the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Artificial intelligence technology is constantly developing and changing. Due to the continuous development of technology and production of carbon emissions, various problems have occurred, forcing various regions to start promoting low‐carbon work. What kind of method can effectively and quickly improve the performance of carbon emissions has become one of the current research topics that has attracted much attention. In response to this problem, it is of great significance to study in the field of carbon emission performance improvement methods. With the in‐depth research on carbon emissions, the research on the intervention of water conservancy policies in carbon emissions has gradually been carried out, and its functional effects are of great significance to solve the problem of improving carbon emissions performance. This paper has aimed to study the impact and mechanism of water conservancy policy on carbon emission performance in the context of artificial intelligence. Through the analysis and research of the water conservancy policy under artificial intelligence, the double difference model (DID) is used to evaluate it, so that it can show the impact and mechanism on carbon emission performance, so as to solve the problem of improving carbon emission performance. This paper has analysed water policy, carbon emission performance and DID model under artificial intelligence. Its influence and mechanism have been experimentally analysed, and related theoretical formulas have been used to explain. The results have shown that the water conservancy policy has a significant and continuous driving effect on the reduction of carbon emission intensity, and its interaction coefficient under the control variable is −0.934, which is significantly negative. Further analysis of variables has shown that the energy intensity coefficient is 0.714, and the secondary industry coefficient is 0.924, which are both positive and significant. Water conservancy policies mainly reduce carbon intensity through the improvement of energy efficiency and industrial structure upgrading. It can be seen that water conservancy policies under artificial intelligence can meet the needs of improving carbon emission performance, and the level of economic growth and green development has been greatly improved. [ABSTRACT FROM AUTHOR]

Energy is unquestionably necessary for economic progress, but it also results in carbon emissions, which are the leading cause of environmental deterioration and climate change. From this perspective, clean energy can contribute to both sustainable development and ecological sustainability, as it consists of non‐carbohydrate energy sources that do not or rarely emit greenhouse gases. In this context, this paper investigates economic policy uncertainty (EPU), economic expansion (EE) and clean energy consumption (EC) on carbon dioxide (CO2) emissions in Russia from 1995 to 2021. The autoregressive distributed lag (ARDL) model was used to illustrate the interdependence of factors. The error correction model (ECM) is also used to check the relationship among the study's desired factors. The long‐term investigation found that EPU harms the environment by increasing emission levels. The economic expansion increases CO2 emissions and reduces the environmental quality, supporting the ecological modernization argument. The consumption of clean energy negatively impacts CO2 emission; hence its higher amount reduces the carbon. Thus, the study found a causal relationship between EPU, EC, EE and CO2 emissions. Based on the study's findings, a policy framework is proposed to address the sustainable development goals and environmental quality. Adding the other variables like environmental regulations can be taken as future direction. [ABSTRACT FROM AUTHOR]

Energy efficiency (EE) in the communication industry is the general trend of green communication development, and the base station sleep (BSS) strategy is crucial to improving EE. However, how to maximize the cell's EE and optimize the performance of users in the sleeping area after the BSS is a challenging problem. The sub‐6GHz and millimeter‐wave (mmWave) integrated networks are considered in this paper. The users' backhaul of the cell is jointly provided by the sub‐6 GHz band and the mmWave band. User reaccess algorithm based on multiple parameters access criterion is adopted when their severed base stations (BSs) are shut down. The authors also consider a resource allocation algorithm based on the semi‐dynamic Markov approximation (MA) algorithm, which is proposed to quickly allocate sub‐channels to reaccessed users and ensure the maximum throughput. The simulation results show that the proposed algorithm can improve the EE of the heterogeneous network and promptly meet the users' needs when some BSs are shut down. [ABSTRACT FROM AUTHOR]

The integrated energy system is an important prerequisite for the sustainable transformation to the low‐carbon power system. Therefore, this paper aims to provide readers with insights into the existing research about the planning and operation models of integrated energy systems. First, the general structure of integrated energy systems is elaborated, and the new issues faced by the low‐carbon planning and operation for the integrated energy systems are represented. Next, the technical framework and the general model are proposed. Furthermore, the typical models and solution technologies of the low‐carbon planning and operation are summarized based on specific models operating in multiple scenarios. Finally, based on the characteristics and framework of the integrated energy system, the future research direction is given, which is expected to guide the sustainable development and low‐carbon transformation of energy systems. [ABSTRACT FROM AUTHOR]