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• A method for constructing grayscale images of vibration signals has been proposed. • An unconventional convolutional kernel design method has been proposed. • The validity of the fault diagnosis method in this paper were verified. Rolling bearings are widely used in various industries, including rail transit, aerospace, and wind power generation, playing a critical role. However, bearing failures can lead to serious consequences, impacting equipment operation and even causing safety accidents. Hence, the diagnosis of bearing faults is of utmost importance. However, the variable speed conditions experienced during bearing operation pose significant challenges to fault diagnosis. To overcome the limitations of traditional methods in diagnosing bearing faults under variable speed conditions, this paper proposes a fault diagnosis method based on the gray-level co-occurrence matrix (GLCM) and Dual Channel Convolutional Neural Network (DCCNN). The method introduces a two-dimensional grayscale matrix construction (2D-GMC) technique to extract grayscale texture features for fault diagnosis. Additionally, an unconventional kernel design method, based on grayscale image contrast, is proposed to reduce the complexity associated with traditional square kernels. A new DCCNN architecture is developed accordingly. Furthermore, the transfer learning concept is utilized to train the proposed DCCNN model using fault signals at specific rotational speeds. The method intercepts the variable speed into multi-speed short-time series, then constructs gray image under different speed to realize the rapid fault diagnosis of bearings under variable speed conditions. [ABSTRACT FROM AUTHOR]

• A host circular RNA, circRNA_0050463, is up-regulated in influenza A virus (IAV)-infected lung epithelial (A549) cells. • CircRNA_0050463 knockdown suppresses IAV replication in A549 cells. • CircRNA_0050463 acts as an endogenous sponge of miR-33b-5p. • CircRNA_0050463 facilitates IAV replication via miR-33b-5p/EEF1A1 axis. Circular RNAs (circRNAs), a new class of widely expressed endogenous regulatory RNAs, are characterized by a covalently closed loop structure without a 5' cap or 3' tail. Increasing numbers of studies have shown that circRNAs play important roles in diverse physiological and pathological processes, including the dynamic interactions between viruses and hosts. However, their multifaceted roles in cellular responses to influenza A virus (IAV) infection remain largely unknown. Here, we analyzed the expression of circ_0050463, which is predominantly localized in cytoplasm, in response to IAV infection. Knockdown of circ_0050463 with siRNA in A549 cells inhibited IAV replication. In addition, the activation of nuclear factor κB (NF-κB) was involved in IAV-induced circ_0050463 expression, as revealed by assay using a NF-Kb inhibitor (Bay 11-7082). By performing biotin-labeled RNA pull-down and luciferase reporter assay, we demonstrated that circ_0050463 functioned as an endogenous microRNA-33b-5p sponge to sequester and inhibit miR-33b-5p activity, resulting in increased eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) expression with subsequent facilitation of IAV replication. Taken together, the results of our study indicate that the circ_0050463 promotes IAV replication via miR-33b-5p/EEF1A1 axis, thus providing evidence for the host circRNAs utilized by viruses to support their replication. [ABSTRACT FROM AUTHOR]