In order to solve the efficiency issues in distributed load responses to frequency regulation commands, an innovative strategy was introduced based on reinforcement learning for load aggregators’ pricing incentives in response to frequency commands. Within this strategy, a game-theoretic model between the load aggregators and load clusters was constructed, and the load aggregators adjust incentive prices based on frequency commands and their pricing strategies, while loads adjust their power consumption based on their own electricity costs to flexibly respond to the frequency commands. The multi-agent soft actor-critic (MASAC) algorithm was used to investigate the solution. The results show that the pricing incentive method enables effective load response to frequency commands, and the use of the MASAC algorithm not only optimizes the decision-making process but also significantly reduces computational complexity, achieving efficient dynamic adjustment. It is concluded that this method provides an effective solution for frequency regulation in power systems, offering significant theoretical significance and practical value.

When the integrated energy system (IES) participates in electricity spot market transactions, the transaction price is uncertain due to changes in market supply and demand. In order to deal with this problem, a detailed analysis of the operating marginal cost of the integrated energy system was used to investigate the optimal dispatch strategy that fully utilizes the flexible resources of the integrated energy system to participate in the market. Firstly, the typical scenarios of market price uncertainty under the external spot market environment were analyzed, and the internal multiple source-load adjustable resources and operation cost structure of the integrated energy system were investigated. Secondly, a trading optimization model considering the marginal cost of the system under the condition of price uncertainty in the electric power market was established, and the sand cat swarm optimization algorithm was proposed to solve the problem. Finally, simulation verification was conducted based on actual cases. The result shows that this strategy can not only reduce the operating cost of IES, but also enhance its adaptability to market price uncertainty. The strategy provides new ideas for the operation of integrated energy systems in the power spot market environment, which is also helpful to realize the double optimization of economy and reliability of energy system participating in the market scheduling.

Based on the reservoir conditions of tight conglomerate reservoirs in the Mahu area of the Junggar Basin, an experiment was conducted to study the interaction between tight conglomerates, CO₂, and water. The results indicate that after CO₂ dissolves in water to form carbonic acid, it primarily reacts chemically with feldspar and calcite in the cement between the conglomerate grains. This leads to significant around-grain dissolution, with dissolution being the main process and precipitation being secondary. Ultimately, this increases the porosity and permeability of the rock, enhancing the reservoir fluid seepage capacity. The maximum increases in porosity and permeability are 3.65% and 87.36%, respectively. Additionally, the surface roughness of the rock increases after the interaction, with hydrophilic mineral quartz exposed on the surface. The water-phase wetting contact angle of the rock decreases by 7.4°, enhancing hydrophilicity. The CO₂ huff and puff process has a positive effect on improving oil recovery, with the main oil-increasing mechanisms being the enlargement of pore space to enhance fluid seepage capacity and the improvement of rock water-phase wettability, which increases reservoir water-phase imbibition capacity and crude oil mobility, thereby improving oil recovery.

Muscle dysfunction, as one of the common extrapulmonary manifestations of COPD (chronic obstructive pulmonary disease), limits the exercise capacity, cardiorespiratory health, and quality of life of COPD patients, leading to poor prognosis. PBMT (photobiomodulation therapy) an emerging adjunctive treatment for COPD-related muscle dysfunction, has been widely promoted and utilized in clinical practice. It positively affects muscle inflammation, alleviates muscle fatigue, improves muscle metabolism, enhances muscle endurance, and accelerates muscle healing. The comprehensive review of the rehabilitation mechanisms and current application status of PBMT (photobiomodulation therapy) in addressing COPD (chronic obstructive pulmonary disease)-related muscle dysfunction, both domestically and internationally, is conducted to offer insights and guidance for the application of PBMT in the rehabilitation treatment of COPD-related muscle dysfunction.

The issue of soil erosion in the Loess Plateau was addressed, with a comprehensive analysis of the application and evolution of vegetation restoration technologies for loess slopes. The text highlights that vegetation restoration serves as an effective method to mitigate soil erosion and rejuvenate ecological functions. Vegetation restoration not only enhances soil stability but also boosts the ecological quality of slopes and contributes to the sustainable development of ecosystems. Considering the geographical characteristics of the Loess Plateau and the factors contributing to soil erosion, a review of the research history and current progress of vegetation restoration techniques in China was conducted. Detailed discussions on methods such as spray seeding and slope coverage restoration, each characterized by distinct benefits and drawbacks, were included. These techniques were selectively implemented based on specific site conditions and environmental characteristics, and were continuously refined to address any arising challenges during their application. Furthermore, the document outlined future directions for advancing vegetation restoration technology, stressing that a thoughtful integration of plant species selection, soil matrix enhancement, and technological innovation is essential for improving the ecological restoration outcomes on slopes. The adoption of modern technological tools like remote sensing and artificial intelligence for monitoring and managing geological hazards was recommended to enhance the effectiveness and accuracy of ecological restoration efforts. Finally, an interdisciplinary approach was advocated to spur innovative developments in slope management and ecological restoration technologies, with the goal of achieving ecological sustainability in the Loess Plateau.

Oil booms play a vital role in dealing with oil spills on water. Aiming at the single problem of existing oil booms in fast-flowing rivers, a new type of double-layer mesh fence was designed for oil spill recovery in fast-flowing rivers based on the parameters of traditional oil booms. Based on the mainstream CFD (computational fluid dynamics) software FLUENT, a two-dimensional numerical flume model was established to simulate the transient distribution of oil and water under the action of the new oil containment boom with VOF (volume of fluid) as the computational model, and the volume of oil intercepted was used as the monitoring data to explore the direction of optimizing the oil containment performance of the oil containment boom. Monitoring data was used to explore the optimization direction of oil containment performance of the oil containment boom. The results show that the optimised oil containment boom has a grid radius of 30 mm and a porosity of 0.3. Compared with the traditional boom, the new oil containment capacity of the new oil containment boom is better than that of the traditional boom, which provides an effective reference for the design of oil containment boom for fast-flowing rivers.

In order to scientifically assess the operational efficiency of airport surface movements, a departure flight taxi time prediction method considering runway and taxiway system configurations was proposed. Firstly, the definition of surface taxi time was provided, and an analysis of the historical operational data at the airport was conducted to identify more accurate factors influencing surface taxi-out time. Based on the conclusions drawn from correlation analysis, a random forest prediction model for departure flight surface taxi time was constructed. The method was illustrated using actual operational data from Shijiazhuang Zhengding Airport and Shenzhen Bao'an Airport, analyzing the characteristics of surface movement time under different runway system configurations. The results indicate that: Apart from taxi distance, the correlation results of factors influencing surface taxi-out time at airports with different runway and taxiway system configurations are generally consistent. When considering the same factors, the prediction of surface taxi time is better for single-runway airports compared to dual-runway airports. Surface taxi time at single-runway airports approaches unimpeded taxi time, while at dual-runway airports, there is a significant difference from unimpeded taxi time. The research findings are of significant importance for enhancing airport surface operation efficiency and achieving energy savings and emissions reduction.

In order to deeply understand the spatio-temporal distribution patterns of forest fires and reduce the adverse effects of forest fires on the ecological environment and human activities, the key parameters and dynamics of multi-source satellite for fire point identification was established using data from 8 domestic and foreign meteorological satellites and based on the classic context method. The satellite monitoring buffer zone radius verification method was used to verify the authenticity of forest hot spots retrieved from multi-source satellites, and the real forest hot spot data during the fire prevention period in 2021—2022 were used to analyze the spatio-temporal characteristics of forest fires. The results show as follows. The accuracy of satellite fire spot monitoring is 84.42%, and the fire point classification accuracy is 89.90%. The established inversion method is reasonable and reliable. The spatial distribution of forest fires in Hunan is “more in the southwest and less in the northeast”. At the same time the high-incidence areas are mainly distributed in southern Hunan, and the second-highest-incidence area is western Hunan. In summary, the risk of forest fires during the autumn prevention period is much greater than that during the spring prevention period. During the extreme high temperature and drought in 2022, forest fires were mainly distributed in the southern Hunan region and the Hengshao Basin. From the perspective of process distribution, the distribution of forest fires can be divided into four stages. The number of forest fires in the first three stages showed a significant increase trend, and in the third stage, the number of forest fires increased significantly. Fire risk is the most serious. In the fourth stage, due to the dual impact of precipitation and the province's fire ban, the risk of forest hot spots was significantly reduced.

Yuehai is the largest wetland in Yinchuan of poor water quality during spring, with a significant contribution from agricultural non-point source pollution. In order to gain a deeper understanding of the distribution characteristics of nitrogen and phosphorus in the Yuehai Lake and its eutrophication status, water samples from 28 representative sites in Yuehai Lake and its outflow river were collected during the spring irrigation period of 2021.The distribution characteristics and regularities of TN (total nitrogen) and TP (total phosphorus), as well as different forms of nitrogen and phosphorus in Yuehai Lake were analyzed. The differences in nitrogen and phosphorus concentration between Yuehai Lake and its outflowing river were revealed. The results showed that during the spring irrigation period, the TN concentrations at 78% of the sampling points in Yuehai Lake was lower than the Class III surface water standard, and the TN concentration at 57% of the sampling points belonged to the heavily eutrophic type. During the spring irrigation period, the TP concentration at all sampling points was lower than Class III surface water standard, and the TP concentration at 70% of the sampling points belonged to the heavily eutrophic type. There were differences in the sources and transformation processes of different nitrogen fractions in the water of the Yuehai Lake. pH and TDS (total dissolved solids) affect the concentration of nitrogen and phosphorus in the water, and DO(dissolved oxygen) does not have a significant effect on the nitrogen and phosphorus forms in the water of the Yuehai Lake. The distribution characteristics of nitrogen and phosphorus in the outflow river of the Yuehai and the Yuehai water were different, and the differences in nitrogen concentration and non-orthophosphate phosphorus concentration between the Yuehai Lake and its outflow river were not significant in the direction of river and lake water flow (north-south direction). The nitrogen and phosphorus pollutants in the Yuehai converged into the Yellow River along with the rivers out of the Yuehai Lake, and the nitrogen and non-orthophosphate phosphorus in the Yuehai Lake might impact on the water of the Ningxia section of the Yellow River and increase the risk of pollution of the Yellow River, and the control of the nitrogen and non-orthophosphate phosphorus in the Yuehai Lake should be strengthened. This work provides a reference for continuously and accurately improving the water quality in the middle and upper reaches of the Yellow River Basin.

Aiming at the technical problems of "untimely perception, poor transmission and difficult equipment deployment" in the monitoring and early warning of mountain disasters in the complex environment of the Qinghai-Tibetan Plateau, a UAV-throwing monitoring device, LoRa networking and edge computing gateway, as well as other embedded hardware and software equipment applicable to deformation and micro-motion monitoring of high-level and high-risk mountain disasters were developed, and focused on the research of the system low-power adaptive data acquisition algorithm and RF frequency adaptive technology, were developed the self-organised network routing algorithm based on LoRa and Beidou RDSS, as well as the multimodal communication intelligent switching technology, so as to solve the problems of timeliness of data perception in complex environments and the problems of low-power consumption and environmental adaptability. The results show that the developed system had a good on-site pilot application effect, which meeting the requirements for long-term monitoring of mountain disasters in alpine mountainous areas, and the average packet loss rate of data transmission in extreme environments is 2.328 8 percent, providing new technologies and methods for disaster prevention and mitigation in the construction and operation of major projects in alpine and complex mountainous areas.