Abstract: To address the reservoir classification requirements of the Hutubihe Formation in Luliang Oilfield, this paper constructs an intelligent classification model based on deep neural networks. By automatically learning the complex nonlinear relationships among seven parameters—porosity, permeability, gamma ray, resistivity, oil saturation, density, and thickness—the deep neural network replaces traditional manual weight assignment methods and achieves multi-parameter collaborative characterization of reservoir properties. Based on the data-driven concept, an adaptive deep neural network architecture is adopted to realize intelligent reservoir classification. The accuracy of this method is verified through core analysis and neural network methods. Finally, the classification results are presented in radar charts, significantly improving the objectivity and accuracy of reservoir classification. Research shows that the deep learning model can automatically extract deep features from reservoir parameters. Core experiments indicate that the matching degree between reservoir categories and pore structure and flow capacity exceeds 90%, while the classification error of key parameters (porosity and permeability) is less than 5%. This method breaks through the limitations of traditional classification methods, achieves intelligent and precise classification of multi-layer reservoirs in Luliang Oilfield, and provides a more reliable decision-making basis for optimizing development adjustment plans. It verifies the superior performance of deep learning algorithms in complex heterogeneous reservoir classification and demonstrates significant practical value for refined residual oil potential tapping and intelligent development decision-making in mature oilfields. Read More

Abstract: This paper investigates the challenges of power supply and equipment mounting when using point-type current meters for velocity measurement in marine environments. The Vectrino Doppler point-type current meter manufactured by Norway's Nortek was employed for measurements, offering advantages such as high sampling frequency, excellent accuracy, and compact size. To meet the demand for long-term continuous power supply at sea, an MT1000S uninterruptible power supply (UPS) combined with four 100AH batteries was selected, enabling over 24 hours of uninterrupted system operation. For the mounting bracket, a removable galvanized steel structure was designed. Stability was enhanced through rectangular interlocking and wire fastening, supplemented by galvanized steel pipes to minimize measurement vibration. The study also summarizes key considerations for practical measurements, including equipment waterproofing, heat dissipation, sampling rate selection, and measurement safety. These measures effectively ensure data quality and continuity, providing a viable technical solution for ocean current velocity monitoring. Read More

Abstract: Fish behavioral responses to external stimuli serve as a critical basis for designing and optimizing fishing methods, directly impacting catch efficiency, resource assessment, and fisheries management. Since the 1950s, international academic circles have advanced this field through major conferences (e.g., Hamburg 1957, London 1963) and systematic research, notably led by the United States, Russia, Japan, and Norway. China has published works such as Fish Behavior and Fishing Technology and Fish Ethology since the 1980s, achieving significant progress in phototaxis, acoustic-electrical stimulation, and feeding behavior. Research has progressively expanded into interdisciplinary applications including aquaculture, ecological conservation, and bionics. Fish responses to external stimuli (light, sound, electromagnetic fields, water currents, etc.) vary by species. For instance, the sixline wrasse exhibits extreme sensitivity to water currents, the American whitefish detects ultrasonic waves to warn of predators, and Japanese eels rely on geomagnetic navigation for spawning. Building on these behavioral traits, fisheries have developed multiple behavioral control technologies: reducing bycatch through net-based isolation barriers, guiding migratory fish away from hydroelectric turbine units using underwater strobes, protecting dolphins from gillnet entanglement via ultrasonic devices, and employing phototaxis and electric field effects for light-based trapping and electrofishing techniques. However, existing technologies still face challenges, such as isolation devices affecting trawl efficiency and fish developing adaptations to persistent stimuli. Future research should focus on understanding fish perception mechanisms (e.g., auditory sensitivity and directional orientation), optimizing stimulus signal types and sustainability, and deepening fundamental studies on behavioral memory to advance the precision and ecological friendliness of fishing methods. Read More

Abstract: This paper addresses the corrosion issues of buried pipelines by constructing a corrosion rate prediction model based on neural network algorithms, integrating multi-source data such as in-situ soil physicochemical parameters. Key input parameters of the model were identified through feature analysis, and the model was trained and validated using historical monitoring data. The results demonstrate that the model effectively captures the nonlinear relationships between multiple factors and corrosion rate with high prediction accuracy, particularly in the low corrosion rate range. Furthermore, the paper systematically reviews pipeline anti-corrosion maintenance decision-making methods based on maintenance timing, strategies, and evaluation metrics, comparing the applicability and limitations of reactive, periodic, and predictive maintenance strategies. It emphasizes that an intelligent maintenance system integrating multidisciplinary approaches such as machine learning, risk assessment, and reliability analysis can achieve closed-loop management of pipeline corrosion protection. This approach enhances the economy, safety, and sustainability of maintenance practices, providing theoretical support and decision-making guidance for the intelligent operation and maintenance of oil and gas station pipelines. Read More

Abstract: Ultra-high performance concrete (UHPC), as a new generation of cement-based composite, features ultra-high strength, excellent toughness, and outstanding durability, demonstrating tremendous application potential in civil engineering. This paper systematically reviews the development history, preparation technologies, performance mechanisms, engineering applications, and future trends of UHPC. By analyzing recent research achievements at home and abroad, it summarizes significant progress in material composition optimization, process improvement, performance enhancement, and engineering applications. Results indicate that UHPC technology is becoming increasingly mature, with expanding applications in bridges, buildings, and marine engineering. Nevertheless, further research is needed in cost control, standardization, and long-term performance evaluation. With the deepening concepts of green construction and sustainable development, UHPC is expected to play an increasingly important role in infrastructure construction. Read More

Abstract: In recent years, the increasing frequency and intensity of extreme climate events worldwide have attracted widespread attention. Studies have shown that due to climate change caused by human activities, extreme climate events are becoming more common and severe. In China, studies on extreme temperature events have revealed that since the 21st century, extreme high-temperature events have increased significantly, while extreme low-temperature events have shown a decreasing trend. Therefore, geographers at home and abroad are more inclined to study extreme high-temperature and drought events. Such extreme climate changes not only affect the stability of the climate system but also pose challenges to social and economic development. Therefore, to effectively mitigate the impact of climate change on extreme climate events, countries around the world need to work together, strengthen international cooperation, and formulate and implement effective climate change policies and measures. Only through global cooperation can we better protect the global environment and ensure the sustainable development of humans and other organisms. Read More

Abstract: To investigate the technique of developing rural plant landscapes against the backdrop of urbanisation, this study uses Yandang Mountain in Yueqing City, Zhejiang Province, as a case study. Through field research and type analysis, we methodically categorised the spatial characteristics of the production-living-ecological space of rural plant landscapes in Yandang Mountain, as well as their current state, from the perspective of integrating ecological, living, and production spaces in the countryside. According to the study, the five principles of wholeness, culture, ecology, pragmatism, and art should be combined with native plant resources to maximise plant configuration and landscape structure. The findings demonstrate that by encouraging industrial integration, maximising living space, and preserving ecological balance, Yandang Mountain can achieve the multiple benefits of plant landscapes in environmental conservation, economic development, and cultural heritage.  It has been determined that rural plant landscapes are a key component of rural rehabilitation, and Yandang Mountain's landscape development practices offer a model for similar areas. Read More

Abstract: Global warming is a serious challenge facing the world today. This study confirms that greenhouse gas emissions from human activities are the main driving factors. By systematically analyzing the source-sink balance of greenhouse gases such as carbon dioxide (CO2) and methane (CH4), it is clarified that the significant imbalance caused by the surge in emissions and the weakening of carbon sink capacity is the key mechanism for accelerated climate warming. Furthermore, from the perspective of chemical reaction kinetics, the synergistic effects among the three key greenhouse gases of hydroxyl radical (OH) regulation mechanism, nitrogen cycle cascade effect and sulfate aerosol effect were explained. On this basis, the economic benefit index (CEI) is innovatively constructed, and the above synergistic effects are integrated into the accounting framework. Taking CO and CH as an example, the paradigm of quantitative analysis using CEI is set up, and it is speculated that the synergistic reaction can significantly improve the CEI estimation. Finally, based on the quantitative results of CEI, a differentiated emission reduction strategy is proposed: give priority to the implementation of high CEI measures, and plan the long-term development path of low CEI technology. This study constructs a complete research system from cause analysis, chemical mechanism exploration to economic evaluation and strategy formulation, aiming to provide a theoretical framework and decision support for global climate governance. Read More

Abstract: With the continuous development of coal mining into deeper strata in China, the effective support of deep soft rock roadways has become one of the key challenges restricting safe and efficient mine production. In response to the complex engineering conditions of the deep soft rock at the 140505 working face of Kouzidong Coal Mine, a non-uniform bolting-grouting support technology was adopted, which combines conventional bolting and grouting reinforcement with additional strengthening at the shoulder zones. Numerical simulation results demonstrate that after the implementation of the bolting-grouting support, the maximum roof subsidence was reduced from 762 mm to 242 mm, and the floor heave decreased from 404 mm to 106 mm, indicating effective control of the surrounding rock deformation. This approach provides a reliable guarantee for safe and efficient mine production. Read More