Few-shot fault diagnosis based on multi-scale graph convolution filtering for industry

Industrial equipment fault diagnosis often encounter challenges such as the scarcity of fault data, complex operating conditions, and varied types of failures. Signal analysis, data statistical learning, and conventional deep learning techniques face constraints under these conditions due to their substantial data requirements and the necessity for transfer learning to accommodate new failure modes. To effectively leverage information and extract the intrinsic characteristics of faults across different domains under limited sample conditions, this paper introduces a fault diagnosis approach employing Multi-Scale Graph Convolution Filtering (MSGCF). MSGCF enhances the traditional Graph Neural Network (GNN) framework by integrating both local and global information fusion modules within the graph convolution filter block. This advancement effectively mitigates the over-smoothing issue associated with excessive layering of graph convolutional layers while preserving a broad receptive field. It also reduces the risk of overfitting in few-shot diagnosis, thereby augmenting the model's representational capacity. Experiments on the University of Paderborn bearing dataset (PU) demonstrate that the MSGCF method proposed herein surpasses alternative approaches in accuracy, thereby offering valuable insights for industrial fault diagnosis in few-shot learning scenarios.Comment: 6 pages, 2 figures, 2 tables, 63rd IEEE Conference on Decision and Contro

Proliferative Activity and Neuroprotective Effect of Ligustrazene Derivative by Irritation of Vascular Endothelial Growth Factor Expression in Middle Cerebral Artery Occlusion Rats

Purpose: To investigate the proliferative activity and neuroprotective effect of a newly identified ligustrazine derivative (4-((3,5,6-trimethylpyrazine-2 yl)methoxyl)-3-methox-ybenzoic acid-3,5,6- trimethylpyrazin- 2-methyl ester, T VA) and the possible mechanism related to vascular endothelial growth factor (VEGF) in cerebral ischemic injury.Methods: The pharmacological activity of T-VA was evaluated using MTT ((3 (4,5-dimethylthiazolyl2- yl)-2,5-diphenyltetrazolium bromide)) assay, while cellular morphology was observed with hematoxylin and eosin (HE) staining. Chick chorioallantoic membrane (CAM) model, immuno-histochemical analysis, and enzyme-linked immunosorbent assay (ELISA) were used to determine the expression of VEGF. Middle cerebral artery occlusion (MCAO) model was used to investigate both VEGF expression and the survival rate after treatment with T-VA.Results: T-VA promoted neuron activity, and the doses of 15 and 30 μM showed more significant effect (p < 0.05). The viability of PC12 cells increased significantly in T-VA (30 and 60 μM) groups (p < 0.05) and increased in a dose dependent manner. Immunohistochemical analysis showed stimulated VEGF expression, and CAM model results showed that T-VA (20 mg/egg) significantly promoted microangiogenesis (p < 0.01). Moreover, in MCAO model, the survival rate of T-VA (60 mg/kg) group reached 86.7 % while for the ischemia group it was 60.0 %. In addition, ELISA results showed that T-VA promoted the expression of VEGF (p < 0.05).Conclusion: These findings indicate that T-VA helps to prevent ischemic injury by increasing VEGF expression.Keywords: Ligustrazine, Neuron, PC12 cell, Chick Chorioallantoic Membrane, Middle Cerebral Artery Occlusion, Vascular Endothelial Growth Facto

A novel fault localization with data refinement for hydroelectric units

Due to the scarcity of fault samples and the complexity of non-linear and non-smooth characteristics data in hydroelectric units, most of the traditional hydroelectric unit fault localization methods are difficult to carry out accurate localization. To address these problems, a sparse autoencoder (SAE)-generative adversarial network (GAN)-wavelet noise reduction (WNR)- manifold-boosted deep learning (SG-WMBDL) based fault localization method for hydroelectric units is proposed. To overcome the data scarcity, a SAE is embedded into the GAN to generate more high-quality samples in the data generation module. Considering the signals involving non-linear and non-smooth characteristics, the improved WNR which combining both soft and hard thresholding and local linear embedding (LLE) are utilized to the data preprocessing module in order to reduce the noise and effectively capture the local features. In addition, to seek higher performance, the novel Adaptive Boost (AdaBoost) combined with multi deep learning is proposed to achieve accurate fault localization. The experimental results show that the SG-WMBDL can locate faults for hydroelectric units under a small number of fault samples with non-linear and non-smooth characteristics on higher precision and accuracy compared to other frontier methods, which verifies the effectiveness and practicality of the proposed method.Comment: 6pages,4 figures,Conference on Decision and Control(CDC) conferenc

Addition of Sodium Pyruvate to Stored Red Blood Cells Attenuates Liver Injury in a Murine Transfusion Model

RBCs undergo numerous changes during storage and stored RBCs may induce adverse effects, ultimately resulting in organ injury in transfusion recipients. We tested the hypothesis that the addition of SP to stored RBCs would improve the quality of the stored RBCs and mitigate liver injury after transfusion in a murine model. RBCs were harvested from C57BL/6J mice and stored for 14 days in CPDA-1 containing either a solution of SP in saline or saline alone. Haemolysis, the 24-hour posttransfusion recovery, the oxygen-carrying capacity, and the SOD activity of stored RBCs were evaluated. The plasma biochemistry, hepatic MDA level, MPO activity, IL-6, TNF-α concentrations, and histopathology were measured two hours after the transfusion of stored RBCs. Compared with RBCs stored in CPDA-1 and saline, the addition of SP to stored RBCs restored their oxygen-carrying capacity and SOD activity, reduced the AST activity, BUN concentrations, and LDH activity in the plasma, and decreased the MDA level, MPO activity, and concentrations of IL-6 and TNF-α in the liver. These data indicate that the addition of SP to RBCs during storage has a beneficial effect on storage lesions in vitro and subsequently alleviates liver injury after the transfusion of stored RBCs in vivo

The Calcineurin-TFEB-p62 Pathway Mediates the Activation of Cardiac Macroautophagy by Proteasomal Malfunction

Rationale: The ubiquitin-proteasome system (UPS) and the autophagic-lysosomal pathway (ALP) are pivotal to proteostasis. Targeting these pathways is emerging as an attractive strategy for treating cancer. However, a significant proportion of patients who receive a proteasome inhibitor-containing regime show cardiotoxicity. Moreover, UPS and ALP defects are implicated in cardiac pathogenesis. Hence, a better understanding of the cross-talk between the two catabolic pathways will help advance cardiac pathophysiology and medicine.Objective: Systemic proteasome inhibition (PSMI) was shown to increase p62/SQSTM1 expression and induce myocardial macroautophagy. Here we investigate how proteasome malfunction activates cardiac ALP.Methods and Results: Myocardial macroautophagy, transcription factor EB (TFEB) expression and activity, and p62 expression were markedly increased in mice with either cardiomyocyte-restricted ablation of Psmc1 (an essential proteasome subunit gene) or pharmacological PSMI. In cultured cardiomyocytes, PSMI-induced increases in TFEB activation and p62 expression were blunted by pharmacological and genetic calcineurin inhibition and by siRNA-mediated Molcn1 silencing. PSMI induced remarkable increases in myocardial autophagic flux in wild type (WT) mice but not p62 null (p62-KO) mice. Bortezomib-induced left ventricular wall thickening and diastolic malfunction was exacerbated by p62 deficiency. In cultured cardiomyocytes from WT mice but not p62-KO mice, PSMI induced increases in LC3-II flux and the lysosomal removal of ubiquitinated proteins. Myocardial TFEB activation by PSMI as reflected by TFEB nuclear localization and target gene expression was strikingly less in p62-KO mice compared with WT mice.Conclusions: (1) The activation of cardiac macroautophagy by proteasomal malfunction is mediated by the Mocln1-calcineurin-TFEB-p62 pathway; (2) p62 unexpectedly exerts a feed-forward effect on TFEB activation by proteasome malfunction; and (3) targeting the Mcoln1-calcineurin-TFEB-p62 pathway may provide new means to intervene cardiac ALP activation during proteasome malfunction

Borane-mediated polyhedral expansion to access metal-free neutral and cationic derivatives of closo-heptaboranes

Boranes with closed polyhedral structures feature peculiar bonding and structural characteristics, rendering them widely applicable in diverse research areas ranging from basic functionalization reactions to applications such as medicine, nanomaterials, molecular electronics, and neutron capture therapy. Among the closed borane family, the neutral and cationic heptaborane B7 clusters have been missing in contemporary boron cluster chemistry to date. Herein, we report a polyhedral expansion protocol to construct a neutral derivative of closo-heptaborane (B7) from closo-hexaborane (B6) mediated by borane. Conversion of the neutral derivative of closo-heptaborane to a cationic derivative is also demonstrated. X-ray crystallographic and spectroscopic analyses with the aid of quantum chemical calculations reveal that both neutral and cationic derivatives of closo-heptaborane exhibit a pentagonal-bipyramidal geometry and involve the delocalized σ skeletal electrons, leading to three-dimensional aromaticity. Moreover, the B7 core of the former undergoes a complexation reaction with silver tetrafluoroborate, representing the first experimental demonstration of the nucleophilic nature of the closo-heptaborane.Nanyang Technological UniversityNational Research Foundation (NRF)Submitted/Accepted versionWe are grateful to Nanyang Technological University (NTU)and the National Research Foundation, Singapore (NRF-NRFI07-2021-0002), and Nippon Shokubai for financial support