Industrial nameplates serve as a means of conveying critical information and parameters. In this work, we propose a novel approach for rectifying industrial nameplate pictures utilizing a probabilistic Hough transform. Our method effectively corrects for distortions and clipping, and features a collection of challenging nameplate pictures for analysis. To determine the corners of the nameplate, we employ a progressive probability Hough transform, which not only enhances detection accuracy but also possesses the ability to handle complex industrial scenarios. The results of our approach are clear and readable nameplate text, as demonstrated through experiments that show improved accuracy in model identification compared to other methods.

Through long-term Rayleigh lidar observations during 2010-2022, atmospheric gravity wave (AGW) activities in the middle atmosphere (30–65 km) are statistically investigated at Haikou (110.3°E, 19.9°N) in China. In total, 827 quasi-monochromatic AGW events are identified from the lidar dataset, and the vertical wavelength, observed wave period, and vertical propagation direction of dominant waves are extracted for each AGW event by analyzing the power spectra of wave-induced temperature perturbations. It is revealed that 81.7% of all AGW events were associated with upward-propagating waves, and the proportion of upward-propagating AGWs reached a maximum in autumn and a minimum in winter. The most common vertical wavelengths and wave periods were 6–11 km and 4–10 hours, respectively. In particular, 68 AGW events associated with simultaneous upward and downward propagating waves were observed by lidar, corresponding to 8.2% of the events. The occurrence of such special AGW phenomena is qualitatively discussed, and multiple formation mechanisms may exist. Comparisons are made with previously reported lidar observation results, and the statistical features of AGW activity in the low-latitude middle atmosphere may vary over a relatively wide range depending on the location and altitude. However, a majority of AGWs propagate upward in the middle atmosphere.

Background: A prognostic index validated for the outcomes of advanced high-grade serous ovarian cancer (HGSOC) patients with neoadjuvant chemotherapy (NACT) is still lacking. We therefore developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) to enhance predictive accuracy. Methods: We analyzed clinicopathologic feature of advanced HGSOC patients receiving platinum-based NACT. Blood inflammatory composite markers were calculated and binary-transformed by optimal cutoffs. The omental hematoxylin and eosin (H&E) stained slides were selected for the assessment of chemotherapy response score (CRS). Logistic regression analyses and Cox proportional hazard regression model were utilized to develop a prognostic index. Results: Multivariate analysis showed that CRS and neutrophils-to-lymphocyte ratio (NLR) are independent risk factors for platinum-chemotherapy response. Meanwhile, Kaplan–Meier and Cox regression analysis revealed that CRS score was significantly correlated with PFS and OS, and NLR-high patients was associated with poor OS. We further developed an ONCPI model based on the CRS score and NLR level. Survival analysis suggested that patients with score 0 and 1 of ONCPI were significantly associated with improved PFS and OS. Conclusions: The ONCPI score emerges as a significant prognostic marker for predicting NACT outcomes in advanced HGSOC patients. Its integration into clinical practice and risk-stratified trial design is conceivable.