Golden Concord Group (China)

ABSTRACTDroplet boiling is a common occurrence in many industrial processes, but it can be hindered by the Leidenfrost effect. The Leidenfrost point (LP), defined as the temperature at which an accumulated and stagnant vapor forms between the liquid and the heated solid, consequently deteriorates cooling performance. In this study, inspired by nature, we demonstrate how using a nano‐micro hierarchical triple‐passage architecture with a higher aspect ratio enhances both vapor and liquid spreading dynamics, boosts heat transfer, and thus elevates the LP. Our results show that the LP is promoted to 273°C, which is a delay of approximately 130°C compared to the LP of 145°C on a copper surface. Through theoretical analysis, we develop a multi‐force competition model to reveal the underlying physics of this sustained nucleate boiling. Our findings challenge traditional wisdom, indicating that lower impact velocities of a droplet, though sacrificing the convection, delay the LP through impact pattern manipulation. Additionally, we adopt a physics‐informed deep neural network framework to accurately model the nonlinear behavior of droplet boiling (from nucleate boiling to LP) on various surfaces within an ≈11% error. The results here have potential applications in designing more efficient droplet‐based boiling heat transfer devices and in controlling droplet boiling at high temperatures.

This study aims to analyze and describe the effect of management capabilities and marketing strategies on business success. This type of research is quantitative. This research was conducted in the village of voluntary and the village of Rembitan, Central Lombok district, which became the subject of this study. The sample in this study was 300 respondents who are woven cloth entrepreneurs. The data collection technique is done using a questionnaire that has been tested for validity and reliability. The data analysis technique used is multiple regression. The results of this study indicate that: (1) management ability has a positive and significant effect on the success of the songket woven fabric business by 37.3% with a significance value (p) <0.05. (2) Marketing strategy has a positive and significant effect on business success by 38.7% with a significance value (p) <0.05

Although many degumming methods for fibrilia fiber have been established, the reaction priority of the gums and the influence of single gummy component removal/retention on the fiber property and the reaction behavior of the other components remain unclear. This study analyzed the above issues by the observing the change of fiber in microbial-mechanical ‘enzyme peeling’ and gas phase ozone treatment. Results showed that pectin removal could increase the fiber density significantly (∼60.3%) but would not cause damage to the fiber tenacity. The 2.5–4.5% pectin in untreated fiber could strongly restrict the removal of lignin and hemicellulose. Lignin had less influence on fiber density than pectin. The detailed composition of hemicellulose had a significant effect on fiber tenacity: the retention of xylan and mannan caused damage and benefit, respectively, to fiber tenacity. After the removal of 90.0% pectin and 23.0% hemicellulose, a deep delignification rate (>70.0%) could be obtained. The delignification rate of 70.0–80.0% was beneficial for the density decreasing and tenacity increasing of the fiber, while a delignification rate over 80.0% would cause the collapse of the cellulose structure and thus damage the fiber property.

Recently anomaly detection has drawn much attention in diagnosing ocular diseases. Most existing anomaly detection research in fundus images has relatively large anomaly scores in the salient retinal structures, such as blood vessels, optical cups and discs. In this paper, we propose a Region and Spatial Aware Anomaly Detection (ReSAD) method for fundus images, which obtains local region and long-range spatial information to reduce the false positives in the normal structure. ReSAD transfers a pre-trained model to extract the features of normal fundus images and applies the Region-and-Spatial-Aware feature Combination module (ReSC) for pixel-level features to build a memory bank. In the testing phase, ReSAD uses the memory bank to determine out-of-distribution samples as abnormalities. Our method significantly outperforms the existing anomaly detection methods for fundus images on two publicly benchmark datasets.

As the third largest gold ore-forming province in the world, the deep metallogenic potential of and exploration strategies for Jiaodong gold deposits have attracted substantial attention. By applying three-dimensional (3D) geological modelling to these super-giant and giant gold deposits, this study reveals the 3D morphological characteristics of the ore-bearing faults and the ore-related granites, analyses the relationships between ore body locations and slope dip angle changes in the faults, and discusses the coupling relationships among gold mineralisation, ore-controlling faults, and magmatic activities. In the 3D model, the dip angles of ore-controlling faults gradually decrease downwards and alternate between steep and gentle along the fault dip direction. The ore bodies mainly occur in areas with relatively high fault-dip-angle change rates. Hence, positions with fault dip angles of 20°–50° and change rates of ≥0.91 should be considered as target areas for prospecting deep gold ore bodies. In-depth analysis suggests that the ore-hosting faults, granites, and gold mineralisation resulted from regional thermal doming and extensional movements. Gold ore bodies in the Jiaodong Peninsula occur inside or on the periphery of Mesozoic granite. Strong magmatic activities during the transition from enriched to depleted mantle provided the necessary metallogenic and thermal dynamic environment for gold mineralisation. In particular, the magmatic evolution provided abundant ore-forming materials. The detachment faults with varied dip angles provided favourable space for gold mineralisation, as the fluctuations of ore-forming fluid pressure caused by sudden changes in these dip angles served as the primary mechanism underlying the step-like gold mineralisation pattern.

The choice of transportation system has an important impact on the production efficiency and economic behavior of underground mines. Trackless vehicle transportation has gradually become the main method in underground mines because mining companies have realized that mining efficiency can be improved using advanced vehicle mechanization and automation in the mining process. The extracted ore is loaded onto trucks by loaders in situ, then the trucks drive to ore passes for unloading Trucks load and unload ore in a cyclical manner between stopes and ore passes. Numerous trucks drive in tunnels simultaneously to achieve production targets, and there are interactions and influences among trucks, such as blocking and queuing, due to limited underground space. To address this issue, a transportation route model was built, and the ore transportation process was divided into three parts, including ore loading, truck transportation, and ore unloading. The simulation method was applied to optimize the number of loaders and trucks under the constraints of stope production capacity, transportation route and capacity, and vehicle capacity, to achieve the optimal vehicle utilization rate and transportation capability. The Monte Carlo simulation method was utilized to take the uncertainties of the transportation parameters into account to improve the robustness of the simulation results. The model was verified using the case study of an underground gold mine located in Shandong Province, China, with the objective of accomplishing optimal truck–loader matching considering various stopes in a mining area.