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In the assembly, launch, and on-orbit operation of satellite optical communication terminals, small deviations are difficult to avoid, which can lead to pointing errors and challenges to the establishment of optical communication links. To estimate the pointing errors of on-orbit satellite terminals, a calibration algorithm is developed based on lunar surface imagery. First, a feature extraction algorithm for low-light images is employed to process consecutive frames of low-light images to obtain a lunar surface feature map. Then, by combining the feature map and error estimation model, predictions of direction errors and zero errors were achieved. The ground validation results demonstrate the effectiveness and feasibility of the proposed on-orbit error estimation algorithm under low-signal-to-noise-ratio conditions.
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http://dx.doi.org/10.1364/JOSAA.533672 | DOI Listing |
As integrated circuit (IC) manufacturing advances toward smaller technology nodes, conventional lithography methods are increasingly challenged by the diffraction-limited resolution, escalating process complexity, and rising costs. Among these challenges, overlays have a particularly pronounced impact on manufacturing quality. To address this issue, this paper proposes a high-order overlay correction model that employs a two-dimensional fifth-order polynomial to accurately fit and characterize the distribution of overlays.
View Article and Find Full Text PDFPrev Med Rep
October 2025
Guangxi Orthopedic Hospital, Nanning 530012, China.
Objective: Negative emotions during adolescence constitute a significant public health challenge requiring theoretically-grounded intervention approaches. This investigation examined sequential mediation mechanisms whereby physical exercise influences adolescent negative emotions through psychological benefits and social self-efficacy pathways, integrating neurobiological and social-cognitive theoretical frameworks.
Methods: Cross-sectional analysis of 1471 Chinese adolescents (Mean age = 13.
Stat Med
September 2025
Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.
Background: Binary endpoints measured at two timepoints-such as pre- and post-treatment-are common in biomedical and healthcare research. The Generalized Bivariate Bernoulli Model (GBBM) provides a specialized framework for analyzing such bivariate binary data, allowing for formal tests of covariate-dependent associations conditional on baseline outcomes. Despite its potential utility, the GBBM remains underutilized due to the lack of direct implementation in standard statistical software.
View Article and Find Full Text PDFEur Spine J
September 2025
Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Purpose: This study aims to address the limitations of radiographic imaging and single-task learning models in adolescent idiopathic scoliosis assessment by developing a noninvasive, radiation-free diagnostic framework.
Methods: A multi-task deep learning model was trained using structured back surface data acquired via fringe projection three-dimensional imaging. The model was designed to simultaneously predict the Cobb angle, curve type (thoracic, lumbar, mixed, none), and curve direction (left, right, none) by learning shared morphological features.
BMC Health Serv Res
September 2025
Department of Pharmacology, School of Pharmacy, College of Medicine and Health Sciences, Bahir Dar University, P. O. Box 79, Bahir Dar, Ethiopia.
Background: Adverse events resulting from medical care continue to be a significant cause of morbidity and mortality globally. Many individuals experience harm due to medical errors, particularly in developing nations. The primary objective of this study was to evaluate the patient safety culture among pharmacy professionals employed in public hospitals within Bahir Dar City, Ethiopia.
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