Motion measurements of explosive shock waves based on an event camera.

Shock wave measurement is vital in assessing explosive power and designing warheads. To obtain satisfactory observation data of explosive shock waves, it is preferable for optical sensors to possess high-dynamic range and high-time resolution capabilities. In this paper, the event camera is first employed to observe explosive shock waves, leveraging its high dynamic range and low latency. A comprehensive procedure is devised to measure the motion parameters of shock waves accurately. Firstly, the plane lines-based calibration method is proposed to compute the calibration parameters of the event camera, which utilizes the edge-sensitive characteristic of the event camera. Then, the fitted ellipse parameters of the shock wave are estimated based on the concise event data, which are gained by utilizing the characteristics of the event triggering and shock waves' morphology. Finally, the geometric relationship between the ellipse parameters and the radius of the shock wave is derived, and the motion parameters of the shock wave are estimated. To verify the performance of our method, we compare our measurement results in the TNT explosion test with the pressure sensor results and empirical formula prediction. The relative measurement error compared to pressure sensors is the lowest at 0.33% and the highest at 7.58%. The experimental results verify the rationality and effectiveness of our methods.

Decoding the molecular landscape: A novel prognostic signature for uveal melanoma unveiled through programmed cell death-associated genes.

Uveal melanoma (UM) is a rare but aggressive malignant ocular tumor with a high metastatic potential and limited therapeutic options, currently lacking accurate prognostic predictors and effective individualized treatment strategies. Public databases were utilized to analyze the prognostic relevance of programmed cell death-related genes (PCDRGs) in UM transcriptomes and survival data. Consensus clustering and Lasso Cox regression analysis were performed for molecular subtyping and risk feature construction. The PCDRG-derived index (PCDI) was evaluated for its association with clinicopathological features, gene expression, drug sensitivity, and immune infiltration. A total of 369 prognostic PCDRGs were identified, which could cluster UM into 2 molecular subtypes with significant differences in prognosis and clinicopathological characteristics. Furthermore, a risk feature PCDI composed of 11 PCDRGs was constructed, capable of indicating prognosis in UM patients. Additionally, PCDI exhibited correlations with the sensitivity to 25 drugs and the infiltration of various immune cells. Enrichment analysis revealed that PCDI was associated with immune regulation-related biological processes and pathways. Finally, a nomogram for prognostic assessment of UM patients was developed based on PCDI and gender, demonstrating excellent performance. This study elucidated the potential value of PCDRGs in prognostic assessment for UM and developed a corresponding risk feature. However, further basic and clinical studies are warranted to validate the functions and mechanisms of PCDRGs in UM.