77 research outputs found
Structure determination of the intermediate phase of PbSe using experiments and calculations
No full text
The Instability Criterion for Bicrystal at Nanoscale
No full textAtomistic simulations are performed to predict the plastic yield using the instability criterion under thermal effect. The results show the instability criterion is applicable at low temperature (0~100 K) and invalid at a higher temperature (>200 K) due to the influence of thermal vibration. The tensile stress, minimum eigenvalue of matrix A, and atom configurations are compared to investigate the instability criterion in bicrytals. The instability criterion can successfully capture the plastic deformation initiation for bicrystal at 0 K
Optimization of Visual Detection Algorithms for Elevator Landing Door Safety-Keeper Bolts
No full textAs the safety requirements of elevator systems continue to rise, the detection of loose bolts and the high-precision segmentation of anti-loosening lines have become critical challenges in elevator landing door inspection. Traditional manual inspection and conventional visual detection often fail to meet the requirements of high precision and robustness under real-world conditions such as oil contamination and low illumination. This paper proposes two improved algorithms for detecting loose bolts and segmenting anti-loosening lines in elevator landing doors. For small-bolt detection, we introduce the DS-EMA model, an enhanced YOLOv8 variant that integrates depthwise-separable convolutions and an Efficient Multi-scale Attention (EMA) module. The DS-EMA model achieves a 2.8 percentage point improvement in mAP over the YOLOv8n baseline on our self-collected dataset, while reducing parameters from 3.0 M to 2.8 M and maintaining real-time throughput at 126 FPS. For anti-loosening-line segmentation, we develop an improved DeepLabv3+ by adopting a MobileViT backbone, incorporating a Global Attention Mechanism (GAM) and optimizing the ASPP dilation rate. The revised model increases the mean IoU to 85.8% (a gain of 5.4 percentage points) while reducing parameters from 57.6 M to 38.5 M. Comparative experiments against mainstream lightweight models, including YOLOv5n, YOLOv6n, YOLOv7-tiny, and DeepLabv3, demonstrate that the proposed methods achieve superior accuracy while balancing efficiency and model complexity. Moreover, compared with recent lightweight variants such as YOLOv9-tiny and YOLOv11n, DS-EMA achieves comparable mAP while delivering notably higher recall, which is crucial for safety inspection. Overall, the enhanced YOLOv8 and DeepLabv3+ provide robust and efficient solutions for elevator landing door safety inspection, delivering clear practical application value
Experimental evidence of low-density liquid water upon rapid decompression
No full textSignificance
To understand water’s anomalous behavior, a two-liquid model with a high-density liquid and a low-density liquid (LDL) has been proposed from theoretical simulations, and is gradually gaining ground. However, it has been experimentally challenging to probe the region of the phase diagram of H
2
O where the LDL phase is expected to occur. We overcome the experimental challenge by using a technique of rapid decompression integrated with fast synchrotron measurements, and show that the region of LDL is accessible via decompression of a high-pressure crystal. We report the experimental evidence of the LDL from in situ X-ray diffraction and its crystallization process, providing a kinetic pathway for the appearance of LDL as an intermediate phase in the crystal–crystal transformation upon decompression.
</jats:p
New nanomicelle curcumin formulation for ocular delivery: improved stability, solubility, and ocular anti-inflammatory treatment
No full text- …
