Aiming at the difficult problem of describing the abandoned river channel and point dam sand body under the condition of dense well network in the late stage of extra-high water content, applying the core, logging and dynamic production data, and adopting the method of “discussing the present and discussing the past, and predicting the model”, the modern deposition clarifies that there are 4 types of abandoned river channel: the neck-cutting type, the breach and diversion type, the scaled abandonment, and the gully abandonment. The method summarizes 3 types of small, medium and medium-large point dam sands, and realizes the fine depiction of abandoned channels and point dam sands by using modern deposition as a guide, and finely depicts that the abandoned channels in the study area are mainly of the scale and rerouting type, and the point dam sands are mainly of the medium type, and the method is able to accurately depict abandoned channels and point dam sands and the results of the depictions provide a precise description of underground meanders in the large sandstone oil fields. The results of the description provide a geological basis for the accurate dredging of the remaining oil in the sand body layer of large sandstone oil fields.

In this study, different turbulence parameterization schemes are simulated and compared using a single-column model to investigate their effects on the surface sensible heat flux. The Wangara Boundary Layer Experiment and The First International Satellite Land Surface Climatology Project Field Experiment (FIFE) were used. Eight different turbulence closure schemes were used for validation and comparison. These include six first-order closure schemes, one turbulent kinetic energy (TKE) closure scheme and the Reynolds stress second-order closure scheme. In this paper, the results of the second-order closure solved by the Reynolds stress equation are used as a benchmark. Since different turbulence closure schemes have different ability to capture turbulence, which in turn affects the turbulence transport ability and influences the heat transport process. The simulation results show that the difference in simulated temperature profiles between different turbulence parameterization schemes is not significant as the complexity of turbulence parameterization increases. However, this difference feeds back to the surface temperature, turbulent velocity scale and turbulent temperature scale, which affects the variation of the sensible heat flux. As the simulation integration time changes, the difference between the first-order closure scheme and the Reynolds stress scheme gradually increases due to the lack of turbulence portrayal. The results of the TKE scheme and the Reynolds stress scheme are more closely matched with the tendency of the root-mean-square error being smaller, and on the second day both schemes simulate the turbulence better.

Light pollution has profound implications on human physiological rhythms, ecological balances in wildlife, and traffic safety, with its adverse effects becoming increasingly pronounced in the context of escalating urban lighting. In order to conduct a thorough analysis and assessment of the risks associated with light pollution, this study establishes a Light Pollution Risk Level Evaluation System. Grounded in the current light pollution scenario in the United States, we precisely define 20 fundamental indicators for light pollution risk levels. Through Principal Component Analysis, we identify ten major indicators, subsequently utilizing the FCM-PSO algorithm to cluster these indicators into five core parameters: Nocturnal radiation intensity, Population density, GDP, Built-up area, and Light intensity. Furthermore, employing the entropy weight method combined with the TOPSISfusion model, we conduct weighted calculations on these five core indicators to enhance the applicability of the evaluation system. According to the evaluation criteria, the computed weights for each indicator in the light pollution index are as follows: Radiation intensity 0.31, Light intensity 0.289, GDP 0.232, Population density 0.093, Built-up area 8%. This model not only provides a comprehensive assessment of light pollution risks but also serves as a valuable methodological reference for similar studies in the future.

In the development process of the mining industry, tunnel excavation and support technology has been widely applied, which not only ensures the safe and stable progress of engineering, but also improves engineering efficiency. This article mainly focuses on the field of underground mine roadway safety and proposes an innovative method for mine roadway safety monitoring and support design. This method achieves targeted adjustment and optimization by deeply studying the characteristics of rock layers, effectively improving support stability, further strengthening mine safety, and providing more solid support for workers.

The application of intelligent data simulation and predictive analysis shows great potential in improving the efficiency and effectiveness of soybean breeding programs. Based on the research of intelligent data simulation and predictive analysis, the information of complex genetic and environmental factors affecting soybean traits was analyzed, and the application of advanced data simulation technology and predictive analysis method in soybean breeding was discussed. The findings not only contribute to the scientific understanding of soybean breeding, but also provide practical recommendations for harnessing the power of data-driven approaches in agricultural research and breeding programs.

Qinghai Lake, located on the Qinghai-Tibet Plateau in China, is the highest and largest inland lake in geography. This paper takes Qinghai Lake as the research object and Landsat 8 OLI_TIRS remote sensing image as the data source to obtain image data of Qinghai Lake from 2013 to 2018. NDWI (Normalized Differential Water Body Index) method is used to extract water body information, and then statistics the area change from 2013 to 2018. The experimental results show that the surface area of Qinghai Lake has an overall increasing trend in these five years.

In order to explore the role of mechanized soybean cultivation technology in the structural reform of agricultural supply side, this paper analyzes the impact of mechanized planting technology on the soybean industry through comprehensive literature review and empirical research, and provides theoretical support and practical guidance for the structural reform of agricultural supply side. The results show that the mechanized cultivation technology of soybean can improve the efficiency of agricultural production and realize the high-quality, green and standardized supply of agricultural products. In addition, soybean mechanized planting technology can also reduce the labor intensity of agricultural practitioners, improve their income level, and promote rural economic development. The research results have certain theoretical and practical significance for promoting the structural reform of China’s agricultural supply side, and also provide reference for the agricultural development of other countries and regions.

Sulfur quantum dots have been widely used in fluorescence detection, bioimaging, and sensing due to the advantages of simple preparation, biocompatibility, good luminescence performance, and low toxicity. An overview of the the preparation methods of SQDs for applied research. The preparation methods of SQDs can be categorized into bottom-up and top-down methods, in which the top-down method is more widely used in the research and the fluorescence quantum yield of synthesized sulfur quantum dots is higher. Finally, the urgent problems to be solved in the synthesis and application of sulfur quantum dots are discussed, and the future research directions are envisioned.

In order to achieve real-time defect detection technology, detection accuracy, prediction speed, and lightweight deployment models are important issues. Traditional object detection methods often fail to achieve a balanced effect on all aspects. Therefore, a detection model based on lightweight convolutional neural network YOLOv7 is proposed. Firstly, lightweight convolutional Ghost conv is introduced to lighten the backbone network; Secondly, adding CBAM attention mechanism to suppress invalid information and enhance feature extraction ability; Finally, a new measurement method is introduced at the regression loss function α- Replacing IoU with SIoU accelerates algorithm convergence and improves detection efficiency for defect targets. The experiment shows that the accuracy P of the detection model reaches 96.27%, the mAP index is 83.84%, the detection speed is 23.83ms, and the model size is only 19.10MB, effectively balancing the accuracy, real-time performance, and lightweight deployment of defect detection.

With the increasing use of cars, the problem of engine burning oil has become a phenomenon of concern. Taking the burning oil of automobile engine as an example, the causes of this problem, including piston ring damage, poor valve sealing and cylinder head sealing problems. For these reasons, corresponding fault maintenance countermeasures are proposed, such as regular oil and filter element replacement, checking and replacing piston rings, maintaining the sealing of valve and valve catheter, and checking and replacing of cylinder head seals. These countermeasures aim to solve the problem of oil combustion, improve the engine performance, and provide practical reference for the relevant personnel.

In recent years, the ecological management of Hulun Lake has achieved positive protection and management results through a number of effective management measures, and has reproduced its beautiful scene like a fairyland. In order to further improve the effectiveness of ecological governance of Hulun Lake, this paper uses Marx’s community thought to guide the construction of an ecological governance community based on common ideas, with common interests as the key, and with common action as the core, so as to promote the systematic and modern development of ecological governance of Hulun Lake.

In recent years, the construction of marine ranches in China has entered a rapid development stage, gradually advancing towards deep and distant sea areas. Considering the complexity of the deep-sea environment and the need for marine ecological protection, it is necessary to introduce multi-source heterogeneous big data monitoring technology to achieve comprehensive collection and accurate detection of marine environmental data. In order to further scientifically develop marine resources and expand the construction of marine ranches, this article analyzes the collection and integration of multi-source heterogeneous big data and intelligent monitoring of marine environment based on big data. It explores the application strategies of big data in breeding varieties and ranch operation management, in order to promote the construction and development of modern marine ranches.

Climate change is closely related to the global carbon cycle, and the carbon cycle of terrestrial ecosystems and its driving mechanism is of great significance to the study of the global carbon cycle. This paper puts forward suggestions to realize the goal of carbon neutrality from three aspects: to carry out wetland carbon accounting, to increase the area of wetlands, and to strengthen the research on wetland carbon enhancement technology.

In recent years, China’s soybean planting area has been expanding continuously. However, soybean farming faces various challenges, one of which is how to improve nitrogen fixation efficiency. It is important to study the effect of different mechanical treatments on nitrogen fixation efficiency of soybean root nodules. The nitrogen fixation efficiency of soybean seed after milling and ultrasonic treatment was observed. The experimental results showed that the nitrogen fixation efficiency of soybean root nodules was significantly improved after mechanical treatment. Further analysis showed that mechanical treatment changed the shape and internal structure of soybean root nodules, increased the contact area between root nodules and air, and promoted the growth of nitrogen-fixing bacteria. It is concluded that mechanical treatment has an important effect on nitrogen fixation efficiency of soybean root nodules. The research results have important theoretical and practical significance for improving the nitrogen fixation efficiency of soybean, and provide scientific basis for the sustainable development of soybean industry.