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A fault diagnosis method for rolling bearing based on gram matrix and multiscale convolutional neural network.
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December 2024
College of Information Engineering, SuQian University, SuQian, 223800, China.
The safety and reliability of rotating machinery hinge significantly on the proper functioning of rolling bearings. In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. However, the vibration signals collected by machines are inevitably affected by irrelevant noise because of the complex working environments of bearings.
View Article and Find Full Text PDFDCLRE1B as a novel prognostic biomarker associated with immune infiltration: a pancancer analysis.
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Department of Orthopedics, The Second Affiliated hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
The DNA cross-link repair 1B (DCLRE1B) gene is involved in repairing cross-links between DNA strands, including those associated with Hoyeraal-Hreidarsson syndrome and congenital dyskeratosis. However, its role in tumours is not well understood. DCLRE1B expression profiles were examined in tumour tissues and normal tissues using TCGA, GTEx, and TARGET datasets.
View Article and Find Full Text PDFLyophilization of ASFV vaccine candidate ASFV-G-ΔI177L offers long term stability.
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Plum Island Animal Disease Center, Agricultural Research Service, USDA, Greenport, NY, 11944, USA.
For over a century African swine fever (ASF) has been causing outbreaks leading to devastating losses for the swine industry. The current pandemic of ASF has shown no signs of stopping and continues to spread causing outbreaks in additional countries. Currently control relies mostly on culling infected farms, and strict biosecurity procedures.
View Article and Find Full Text PDFA lightweight and precision dual track 1D and 2D feature fusion convolutional network for machinery equipment fault diagnosis.
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December 2024
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, 325035, China.
Addressing the issues of a single-feature input channel structure, scarcity of training fault data, and insufficient feature learning capabilities in noisy environments for intelligent diagnostic models of mechanical equipment, we propose a method based on a one-dimensional and two-dimensional dual-channel feature information fusion convolutional neural network (1D_2DIFCNN). By constructing a one-dimensional and two-dimensiona dual-channel feature information fusion convolutional network and introducing a Convolutional Block Attention Mechanism, we utilize Random Overlapping Sampling Technique to process raw vibration signals. The model takes as inputs both one-dimensional data and two-dimensional Continuous Wavelet Transform images.
View Article and Find Full Text PDFDeep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness.
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December 2024
BAOBAB Unit, NeuroSpin center, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Decoding states of consciousness from brain activity is a central challenge in neuroscience. Dynamic functional connectivity (dFC) allows the study of short-term temporal changes in functional connectivity (FC) between distributed brain areas. By clustering dFC matrices from resting-state fMRI, we previously described "brain patterns" that underlie different functional configurations of the brain at rest.
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