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The natural environment spectrum and equivalent conversion relationship are important input parameters for the complication of aircraft acceleration test environment spectrum. Due to the large discrete nature of environmental data and the small number of sample data, traditional parameter estimation methods are no longer suitable for compilation of natural environment spectra. Based on the idea of small sample parameter estimation, this paper established a high confidence natural environment spectrum through Bootstrap data expansion and grey confidence interval estimation. Subsequently, electrochemical tests were carried out on 7050 aluminum alloy and TC18 titanium alloy, which were typical dissimilar metal connection materials for aircraft, and their equivalent conversion coefficients were calculated at the temperature of accelerated test environment based on the principle of isoelectric quantity. On this basis, the accelerated test environment spectrum of aluminum-titanium alloy joint structure was given, which could provide a reference for the engineering of calendar life assessment of aircraft dissimilar metal joint structure.

The mining disturbance between multiple working faces will induce rock burst disaster, and regional harmonic mining is one of the key means to prevent this kind of rock burst. In order to verify the rationality and effectiveness of regional harmonic mining to prevent rock burst, taking Yima Mining Area where rock burst occurs frequently as an example, based on the harmonic mining principles and parameter values obtained from simulation, the harmonic mining scheme in the area between Yuejin and Changcun coal mines is formulated, and the effect of harmonic mining is evaluated by comparing the stress transfer characteristics and rock burst characteristics in the area with different harmonic degrees. The results show that the thickness of coal seam and huge thick conglomerate of Yuejin 23092 face and Changcun 21162 face are smaller in the area between Yuejin and Changcun coal mines. The width of coal pillar between 23092-21162 and 21170-21162 working faces are larger, and the horizontal distance and vertical offset between the two faces are further, so the 23092 and 21162 working faces between the two coal mines are the optimal continuous working faces. The degree of harmonic mining in the area between Yuejin and Changcun coal mines is higher than that of Gengcun and Qianqiu coal mines. The frequency and intensity of stress transfer caused by rock burst and mining among working faces are all significantly reduced with harmonic mining, and the range of stress transfer significantly is reduced, so the effect of harmonic mining is obvious.

The variations in the reference evapotranspiration (ET0) are closely related to meteorological factors. The purpose of this study is to explore the relationships between the meteorological factors and the ET0. Based on meteorological data from 26 meteorological stations in the Yiluo River Basin (YLRB) and its surrounding areas from 1958 to 2020, in this study, the temporal and spatial variations and driving factors of the ET0 in the YLRB are investigated. The results are as follows. Spatially, the annual ET0 decreases from the northeast to the southwest in the YLRB. Temporally, the annual ET0 exhibits a fluctuating decreasing trend rather than a monotonic decreasing trend during the entire period. The trend of the ET0 contains two mutation points, in 1972 and 1994. Thus, the research period can be divided into three periods. It is concluded that the variations in the ET0 are the most sensitive to the relative humidity, but the driving factor that contributes the most to the variations in the ET0 is the wind speed. The driving factors are closely related to the rates of relative change of the meteorological factors.

The single‐atom Fe−N−C catalyst has shown great promise for the oxygen reduction reaction (ORR), yet the intrinsic activity is not satisfactory. There is a pressing need to gain a deeper understanding of the charge configuration of the Fe−N−C catalyst and to develop rational modulation strategies. Herein, we have prepared a single‐atom Fe catalyst with the co‐coordination of N and O (denoted as Fe−N/O−C) and adjacent defect, proposing a strategy to optimize the d‐orbital spin‐electron filling of Fe sites by fine‐tuning the first coordination shell. The Fe−N/O−C exhibits significantly better ORR activity compared to its Fe−N−C counterpart and commercial Pt/C, with a much more positive half‐wave potential (0.927 V) and higher kinetic current density. Moreover, using the Fe−N/O−C catalyst, the Zn‐air battery and proton exchange membrane fuel cell achieve peak power densities of up to 490 and 1179 mW cm−2, respectively. Theoretical studies and in situ electrochemical Raman spectroscopy reveal that Fe−N/O−C undergoes charge redistribution and negative shifting of the d‐band center compared to Fe−N−C, thus optimizing the adsorption free energy of ORR intermediates. This work demonstrates the feasibility of introducing an asymmetric first coordination shell for single‐atom catalysts and provides a new optimization direction for their practical application. [ABSTRACT FROM AUTHOR]

With the advancement in living standards, there has been a significant surge in the quantity and diversity of household waste. To safeguard the environment and optimize resource utilization, there is an urgent demand for effective and cost-efficient intelligent waste classification methodologies. This study presents MRS-YOLO (Multi-Resolution Strategy-YOLO), a waste detection and classification model. The paper introduces the SlideLoss_IOU technique for detecting small objects, integrates RepViT of the Transformer mechanism, and devises a novel feature extraction strategy by amalgamating multi-dimensional and dynamic convolution mechanisms. These enhancements not only elevate the detection accuracy and speed but also bolster the robustness of the current YOLO model. Validation conducted on a dataset comprising 12,072 samples across 10 categories, including recyclable metal and paper, reveals a 3.6% enhancement in mAP50% accuracy compared to YOLOv8, coupled with a 15.09% reduction in volume. Furthermore, the model demonstrates improved accuracy in detecting small targets and exhibits comprehensive detection capabilities across diverse scenarios. For transparency and to facilitate further research, the source code and related datasets used in this study have been made publicly available at GitHub. [ABSTRACT FROM AUTHOR]

The spatter generated by the interaction between laser and powder during Powder Bed Fusion-Laser Melting (PBF-LM) can significantly affect the quality of printed parts. A high-speed camera is used to observe the dynamic process of spatter's behavior under different layer thickness and laser powers during the printing process, and to analyze the printed samples' surface roughness, microstructure, and mechanical properties. In terms of spatter image processing, employing an optical flow approach to track and quantify the number of spatters efficiently eliminates statistical redundancy and improves statistical correctness. It is found that under the same laser power, the number of spatters produced by the laser scan direction with the gas flow (LSD-W) is more than that by the laser scan direction against the gas flow (LSD-A), and the number of spatters produced increases with the increase of laser power. Analyzing the mechanical properties and surface roughness of the printed samples under different process parameters quantitatively reveals that differences in the spatter amount generated under different process parameters in the PBF-LM process is not the determining factor affecting the difference in tensile strength of printed parts. During LSD-W, the number of spatters generated at laser power of 170 W and layer thickness of 0.03 mm is 87, and the tensile strength of the printed sample is 618 MPa. During LSD-W, the number of spatters generated at laser power of 320 W and layer thickness of 0.05 mm is 211, and the tensile strength of the printed sample is 680 MPa. Instead, spatter generation has a more direct impact on the surface roughness of printed parts. The layer thickness is 0.03 mm, the laser power is 170 W, and (Ra = 2.372 μm) is the surface roughness of the sample. The layer thickness is 0.05 mm, the laser power is 320 W, and (Ra = 8.163 μm) is the surface roughness of the sample. [ABSTRACT FROM AUTHOR]