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Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Medical Research Center Oulu and Biocenter Oulu, University of Oulu, Oulu, Finland.
Myelodysplastic neoplasia with complex karyotype (CK-MDS) poses significant clinical challenges and is associated with poor survival. Detection of structural variants (SVs) is crucial for diagnosis, prognostication, and treatment decision-making in MDS. However, the current standard-of-care (SOC) cytogenetic testing, relying on karyotyping, often yields ambiguous results in cases with CK.
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Department of Chemical Engineering, Columbia University, New York, NY 10027. Electronic address:
Membrane fusion is central to fundamental cellular processes such as exocytosis, when an intracellular machinery fuses membrane-enclosed vesicles to the plasma membrane for contents release. The core machinery components are the SNARE proteins. SNARE complexation pulls the membranes together, but the fusion mechanism remains unclear.
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College of Communication Engineering, Jilin University, Changchun 130012, China.
A moving ground-target recognition system can monitor suspicious activities of pedestrians and vehicles in key areas. Currently, most target recognition systems are based on devices such as fiber optics, radar, and vibration sensors. A system based on vibration sensors has the advantages of small size, low power consumption, strong concealment, easy installation, and low power consumption.
View Article and Find Full Text PDFClassification and Monitoring of Salt Marsh Vegetation in the Yellow River Delta Based on Multi-Source Remote Sensing Data Fusion.
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School of Oceanography and Spatial Information, China University of Petroleum East China-Qingdao Campus, Qingdao 266580, China.
Salt marsh vegetation in the Yellow River Delta, including (), (), and (), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta.
View Article and Find Full Text PDFA Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier.
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Cognitive Systems Lab, University of Bremen, 28359 Bremen, Germany.
This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descriptors, including MSER (Maximally Stable Extremal Regions), SURF (Speeded-Up Robust Features), distance transform, and DOF (Degrees of Freedom), were applied to skeleton points, while BRIEF (Binary Robust Independent Elementary Features), HOG (Histogram of Oriented Gradients), FAST (Features from Accelerated Segment Test), and Optical Flow were used on silhouettes or full-body points to capture both geometric and motion-based features.
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