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A deep understanding of the main factors affecting the insulating properties of polymers is essential for the progress of insulation components in various applications, including electric vehicles, electronic devices, and information technology. In this study, we used polybutylene terephthalate (PBT) samples with varying degrees of crystallinity as a model material to investigate the influence of aggregation structure on its electrical performance. The results revealed that increasing the crystallinity of PBT led to a simultaneous increase in the surface flashover voltage. We identified the amorphous region as the weak link in the aggregation structure of PBT. Compared to the amorphous region, the crystalline region exhibited superior resistance to charged ion bombardment, a higher degree of compactness, higher bulk resistivity, and lower surface resistivity. A comprehensive understanding of the relationship between the aggregation structure and electrical performance of polymers is fundamental for developing practical high‐performance insulation components. This study provides valuable guidance for controlling the electrical performance of polymers with high‐performance insulating properties, and is thus of great significance to the electrical aging field. [ABSTRACT FROM AUTHOR]

The reactivation of old landslides can be triggered by heavy destructive earthquakes, heavy rainfall, and ongoing human activities, thereby resulting in the occurrence of secondary landslides. However, most existing models are designed for detecting nascent landslides and there are few algorithms for old landslide detection. In this paper, we introduce a novel landslide detection model known as YOLOv8-CW, built upon the YOLOv8 (You Only Look Once) architecture, to tackle the formidable challenge of identifying old landslides. We replace the Complete-IoU loss function in the original model with the Wise-IoU loss function to mitigate the impact of low-quality samples on model training and improve detection recall rate. We integrate a CBAM (Convolutional Block Attention Module) attention mechanism into our model to enhance detection accuracy. By focusing on the southwest river basin of the Sichuan–Tibet area, we collect 558 optical remote sensing images of old landslides in three channels from Google Earth and establish a dataset specifically for old landslide detection. Compared to the original model, our proposed YOLOv8-CW model achieves an increase in detection accuracy of 10.9%, recall rate of 6%, and F1 score from 0.66 to 0.74, respectively. These results demonstrate that our improved model exhibits excellent performance in detecting old landslides within the Sichuan–Tibet area. [ABSTRACT FROM AUTHOR]

Designing of heterogeneous catalysts is very important for activating peroxymonosulfate (PMS) in oxidative degradation of organic pollutants. In this work, Cu/N–P-doped C (Cu/N–P–C) was synthesized by a sol–gel method where the precursor was calcined in a N2 atmosphere. The Cu/N–P–C prepared at 700 °C could activate PMS in oxidative degradation of 4-nitrophenol (4-NP) where 99.17% of 4-NP could be degraded in 4 minutes. The effects of the concentration of 4-NP, solution pH value, PMS dose, and catalyst dosage on the degradation of 4-NP were investigated, and the optimum pH value was determined to be 9. Electron paramagnetic resonance (EPR) and free radical quenching experiments showed that 1O2 was the primary reactive species, and ˙SO4− and ˙OH also contributed to the oxidation reaction, and a possible mechanism for this degradation was presented. The catalyst can be used five times in this oxidation system. Our study provides useful suggestions for designing catalysts with desirable activity. [ABSTRACT FROM AUTHOR]

This study uses survey data to compare rates of political participation between US physicians and nonphysicians from 2017 to 2021. [ABSTRACT FROM AUTHOR]