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Error factors in the encoded sun sensor (ESS) are analyzed and simulated. Based on the analysis results, an ESS error compensation model containing structural errors and fine-code algorithm errors is established, and the corresponding calibration method for model parameters is proposed. As external parameters, installation deviation between ESS and calibration equipment are introduced to the ESS calibration model, so that the model parameters can be calibrated accurately. The experimental results show that within plus/minus 60 degree of incident angle, the ESS measurement accuracy after compensation is three times higher on average than that before compensation.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3658741 | PMC |
http://dx.doi.org/10.3390/s130303217 | DOI Listing |
Sci Rep
March 2025
College of Data Science and Application, Inner Mongolia University of Technology, Hohhot, 010080, China.
The rapid increase in carbon emissions from the logistics transportation industry has underscored the urgent need for low-carbon logistics solutions. Electric logistics vehicles (ELVs) are increasingly being considered as replacements for traditional fuel-powered vehicles to reduce emissions in urban logistics. However, ELVs are typically limited by their battery capacity and load constraints.
View Article and Find Full Text PDFComput Biol Med
March 2025
School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS, United Kingdom; Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China. Electronic address:
Cancer segmentation in whole-slide images is a fundamental step for estimating tumor burden, which is crucial for cancer assessment. However, challenges such as vague boundaries and small regions dissociated from viable tumor areas make it a complex task. Considering the usefulness of multi-scale features in various vision-related tasks, we present a structure-aware, scale-adaptive feature selection method for efficient and accurate cancer segmentation.
View Article and Find Full Text PDFSkelet Muscle
March 2025
Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Background: SELENON-Congenital Myopathy (SELENON-CM) is a rare congenital myopathy caused by mutations of the SELENON gene characterized by axial muscle weakness and progressive respiratory insufficiency. Muscle histopathology may be non-specific, but commonly includes multiminicores or a dystrophic pattern. The SELENON gene encodes selenoprotein N (SelN), a selenocysteine-containing redox enzyme located in the endo/sarcoplasmic reticulum membrane where it colocalizes with mitochondria-associated membranes.
View Article and Find Full Text PDFBMC Cancer
March 2025
Department of Pancreatobiliary Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, 510060, P. R. China.
Background: Conventional epidemiological studies have reported inconsistent results regarding the potential adverse effects of long-term use of antihypertensive drugs on cancer risk. Nevertheless, evidence of their impact on pancreatic cancer risk is limited and deserves further elucidation.
Methods: We selected genetic variants from the genes encoding the target proteins (angiotensin-converting enzyme, beta-1 adrenergic receptor, and solute carrier family 12 member 3) of the examined antihypertensive drugs as instruments based on expression quantitative trait loci (eQTL) studies.
Accurately extracting lesions from medical images is a fundamental but challenging problem in medical image analysis. In recent years, methods based on convolutional neural networks and Transformer have achieved great success in the medical image segmentation field. Combining the powerful perception of local information by CNNs and the efficient capture of global context by Transformer is crucial for medical image segmentation.
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