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Extracellular vesicles in dry eye disease and Sjogren syndrome: A systematic review on their diagnostic and therapeutic role.
Surv Ophthalmol
January 2025
Centre for Ocular Regeneration (CORE), L V Prasad Eye Institute, Hyderabad, Telangana, India; Prof. Krothapalli Ravindranath Ophthalmic Research Biorepository, LV Prasad Eye Institute, Hyderabad, Telangana, India.
Extracellular vesicles (EVs), defined as membrane-bound vesicles released from all cells, are being explored for their diagnostic and therapeutic role in dry eye disease (DED). We systematically shortlisted 32 articles on the role of EVs in diagnosing and treating DED. The systematic review covers the progress in the last 2 decades about the classification and isolation of EVs and their role in DED.
View Article and Find Full Text PDFDynamic classification and attention mechanism-based bidirectional long short-term memory network for daily runoff prediction in Aksu River basin, Northwest China.
J Environ Manage
January 2025
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China.
Inland river runoff variability is pivotal for maintaining regional ecological stability. Daily flow forecasting in arid regions is crucial in understanding water body ecological processes and promoting healthy river ecology. Precise daily runoff forecasting serves as a cornerstone for ecological evaluation, management, and decision-making.
View Article and Find Full Text PDFAutomated ultrasonography of hepatocellular carcinoma using discrete wavelet transform based deep-learning neural network.
Med Image Anal
January 2025
Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon, 440-746, South Korea. Electronic address:
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (DWT) to decompose US images into four sub-band images, a lesion detector for hierarchical lesion localization, and a pattern-augmented classifier for generating pattern-enhanced lesion images and subsequent classification. The lesion detection uses a hierarchical coarse-to-fine approach to minimize missed lesions.
View Article and Find Full Text PDFQuantum mixed-state self-attention network.
Neural Netw
January 2025
Mechanical, Electrical and Information Engineering College, Putian University, Putian, 351100, China.
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Quantum Mixed-State Self-Attention Network (QMSAN) for natural language processing tasks.
View Article and Find Full Text PDFA universal strategy for smoothing deceleration in deep graph neural networks.
Neural Netw
January 2025
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, 150001, China. Electronic address:
Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness in deep layers. Two key weaknesses of existing research on deep GNN models are: (1) ignoring the beneficial aspects of intra-class smoothing while focusing solely on reducing inter-class smoothing, and (2) inefficient computation of residual weights that neglect the influence of neighboring nodes' distributions. To address these weaknesses, we propose a novel Smoothing Deceleration (SD) strategy to reduce the smoothing speed rate of nodes as information propagates between layers, thereby mitigating over-smoothing.
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