Quaternion Orthogonal Transformer for Facial Expression Recognition in the Wild

Facial expression recognition (FER) is a challenging topic in artificial intelligence. Recently, many researchers have attempted to introduce Vision Transformer (ViT) to the FER task. However, ViT cannot fully utilize emotional features extracted from raw images and requires a lot of computing resources. To overcome these problems, we propose a quaternion orthogonal transformer (QOT) for FER. Firstly, to reduce redundancy among features extracted from pre-trained ResNet-50, we use the orthogonal loss to decompose and compact these features into three sets of orthogonal sub-features. Secondly, three orthogonal sub-features are integrated into a quaternion matrix, which maintains the correlations between different orthogonal components. Finally, we develop a quaternion vision transformer (Q-ViT) for feature classification. The Q-ViT adopts quaternion operations instead of the original operations in ViT, which improves the final accuracies with fewer parameters. Experimental results on three in-the-wild FER datasets show that the proposed QOT outperforms several state-of-the-art models and reduces the computations.Comment: This paper has been accepted to ICASSP202

Perceived COVID-19 stress and online aggression among Chinese first-year college students: a moderated mediation model

PurposeFew studies have explored factors that may account for potential mechanisms between perceived coronavirus disease 2019 (COVID-19) stress and online aggression. The current study examined a moderated mediation model with anxiety as a mediator and perceived anonymity as a moderator.MethodsA cross-sectional study was conducted. 3,069 participants across China completed scales assessing perceived COVID-19 stress, anxiety, online aggression, and perceived anonymity.ResultsPerceived COVID-19 stress was positively related to online aggression. The association between perceived COVID-19 stress and online aggression was mediated by anxiety. Besides, the relationship between perceived COVID-19 stress and online aggression, as well as the relationship between anxiety and online aggression were moderated by perceived anonymity.ConclusionThis study explains the possible potential mechanisms for reducing online aggression in the context of COVID-19. In order to intervene in online aggression, psychological strategies are supposed to be drawn to reduce anxiety and perceived anonymity

Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM

In the past few years, more and more AI applications have been applied to edge devices. However, models trained by data scientists with machine learning frameworks, such as PyTorch or TensorFlow, can not be seamlessly executed on edge. In this paper, we develop an end-to-end code generator parsing a pre-trained model to C source libraries for the backend using MicroTVM, a machine learning compiler framework extension addressing inference on bare metal devices. An analysis shows that specific compute-intensive operators can be easily offloaded to the dedicated accelerator with a Universal Modular Accelerator (UMA) interface, while others are processed in the CPU cores. By using the automatically generated ahead-of-time C runtime, we conduct a hand gesture recognition experiment on an ARM Cortex M4F core.Comment: CODAI 2022 Workshop - Embedded System Week (ESWeek

Sevoflurane Pre-conditioning Ameliorates Diabetic Myocardial Ischemia/Reperfusion Injury Via Differential Regulation of p38 and ERK.

Diabetes mellitus (DM) significantly increases myocardial ischemia/reperfusion (MI/R) injury. During DM, cardioprotection induced by conventional pre-conditioning (PreCon) is decreased due to impaired AMP-activated protein kinase (AMPK) signaling. The current study investigated whether PreCon with inhaled anesthetic sevoflurane (SF-PreCon) remains cardioprotective during DM, and identified the involved mechanisms. Normal diet (ND) and high-fat diet (HFD)-induced DM mice were randomized into control and SF-PreCon (3 cycles of 15-minute period exposures to 2% sevoflurane) groups before MI/R. SF-PreCon markedly reduced MI/R injury in DM mice, as evidenced by improved cardiac function (increased LVEF and ±Dp/dt), decreased infarct size, and decreased apoptosis. To determine the relevant role of AMPK, the effect of SF-PreCon was determined in cardiac-specific AMPKα2 dominant negative expressing mice (AMPK-DN). SF-PreCon decreased MI/R injury in AMPK-DN mice. To explore the molecular mechanisms responsible for SF-PreCon mediated cardioprotection in DM mice, cell survival molecules were screened. Interestingly, in ND mice, SF-PreCon significantly reduced MI/R-induced activation of p38, a pro-death MAPK, without altering ERK and JNK. In DM and AMPK-DN mice, the inhibitory effect of SF-PreCon upon p38 activation was significantly blunted. However, SF-PreCon significantly increased phosphorylation of ERK1/2, a pro-survival MAPK in DM and AMPK-DN mice. We demonstrate that SF-PreCon protects the heart via AMPK-dependent inhibition of pro-death MAPK in ND mice. However, SF-PreCon exerts cardioprotective action via AMPK-independent activation of a pro-survival MAPK member in DM mice. SF-PreCon may be beneficial compared to conventional PreCon in diabetes or clinical scenarios in which AMPK signaling is impaired

Autoantibodies against eukaryotic translation elongation factor 1 delta in two patients with autoimmune cerebellar ataxia

BackgroundAutoantibodies are useful biomarkers for the early detection and diagnosis of autoimmune cerebellar ataxia (ACA).ObjectiveTo identify novel autoantibody candidates in ACA patients.MethodsPatients with cerebellar ataxia of unknown cause were recruited from July 2018 to February 2023. Anti-neural autoantibodies in patient samples were detected by tissue-based indirect immunofluorescence assay (TBA) on rat cerebellum sections. TBA-positive samples were further screened for well-established anti-neural autoantibodies using commercial kits. Tissue-immunoprecipitation (TIP) and subsequent mass spectrometric (MS) analysis were used to explore the target antigens of autoantibodies in samples that were TBA-positive but negative for known autoantibodies. The specific binding between autoantibodies and the identified target antigen was confirmed by neutralization experiments, recombinant cell-based indirect immunofluorescence assay (CBA), and western blotting experiments.ResultsThe eukaryotic translation elongation factor 1 delta (EEF1D) protein was identified as a target antigen of autoantibodies in samples from a 43-year-old female ACA patient, while the specific binding of autoantibodies and EEF1D was confirmed by subsequent experiments. A second anti-EEF1D autoantibody-positive ACA patient, a 59-year-old female, was detected in simultaneous screening. The main clinical manifestations in each of the two patients were cerebellar syndrome, such as unsteady walking and limb ataxia. Both patients received immunotherapy, including corticosteroids, intravenous immunoglobulin, and mycophenolate mofetil. Their outcomes provided evidence to support the effectiveness of immunotherapy, but the cerebellar atrophy that occurred before treatment may be irreversible.ConclusionIn the current study, we identified anti-EEF1D autoantibody as a novel autoantibody candidate in ACA. Its pathological roles and diagnostic value need to be further verified in larger-scale studies

Methylation Profile of Single Hepatocytes Derived from Hepatitis B Virus-Related Hepatocellular Carcinoma

BACKGROUND: With the development of high-throughput screening, a variety of genetic alterations has been found in hepatocellular carcinoma (HCC). Although previous studies on HCC methylation profiles have focused on liver tissue, studies using isolated hepatocytes are rare. The heterogeneity of liver composition may impact the genuine methylation status of HCC; therefore, it is important to clarify the methylation profile of hepatocytes to aid in understanding the process of tumorigenesis. METHODS AND FINDINGS: The global methylation profile of single hepatocytes isolated from liver tissue of hepatitis B virus (HBV) related HCC (HBHC) was analyzed using Illumina Infinium Human Methylation27 BeadChips, and combined bisulfite restriction analysis (COBRA) and bisulfite sequencing were used to validate the 20 significant hypermethylated genes identified. In this study, we found many noteworthy differences in the genome-wide methylation profiles of single hepatocytes of HBHC. Unsupervised hierarchical clustering analysis showed that hepatocyte methylation profiles could be classified according to three cell types: hepatocytes of HCC, adjacent hepatocytes and normal hepatocytes. Among the 20 most hypermethylated genes in the hepatocytes of HBHC, 7 novel genes (WNK2, EMILIN2, TLX3, TM6SF1, TRIM58, HIST1H4Fand GRASP) were found to be hypermethylated in HBHC and hypomethylated in paired adjacent liver tissues; these findings have not been reported in previous studies on tissue samples. CONCLUSION: The genome-wide methylation profile of purified single hepatocytes of HBHC was aided in understanding the process of tumorigenesis, and a series of novel methylated genes found in this study have the potential to be biomarkers for the diagnosis and prognosis of HBHC

Ferroptosis-Related Gene-Based Prognostic Model and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. Ferroptosis plays a vital role in ccRCC development and progression. We did an update of ferroptosis-related multigene expression signature for individualized prognosis prediction in patients with ccRCC. Differentially expressed ferroptosis-related genes in ccRCC and normal samples were screened using The Cancer Genome Atlas. Univariate and multivariate Cox regression analyses and machine learning methods were employed to identify optimal prognosis-related genes. CARS1, CD44, FANCD2, HMGCR, NCOA4, SLC7A11, and ACACA were selected to establish a prognostic risk score model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these genes were mainly enriched in immune-related pathways; single-sample Gene Set Enrichment Analysis revealed several immune cells potentially related to ferroptosis. Kaplan–Meier survival analysis demonstrated that patients with high-risk scores had significantly poor overall survival (log-rank P = 7.815 × 10–11). The ferroptosis signature was identified as an independent prognostic factor. Finally, a prognostic nomogram, including the ferroptosis signature, age, histological grade, and stage status, was constructed. Analysis of The Cancer Genome Atlas-based calibration plots, C-index, and decision curve indicated the excellent predictive performance of the nomogram. The ferroptosis-related seven-gene risk score model is useful as a prognostic biomarker and suggests therapeutic targets for ccRCC. The prognostic nomogram may assist in individualized survival prediction and improve treatment strategies

Constructing Heterostructure through Bidentate Coordination toward Operationally Stable Inverted Perovskite Solar Cells

It has been reported that one of the influencing factors leading to stability issues in iodine-containing perovskite solar cells is the iodine loss from the perovskite layer. Herein, bidentate coordination is used with undercoordinated I− of the perovskite surface to construct the stable perovskite-based heterostructure. This strong halogen bonding effectively inhibits interfacial migration of I− into functional layers such as C60 and Ag. Moreover, passivation of the undercoordinated I− suppresses the release of I2 and further delays the formation of voids at the perovskite surface. The resulting inverted perovskite solar cell exhibits a power conversion efficiency of 22.59% and the unencapsulated device maintains 96.15% of its initial value after continuous operation for 500 h under illumination.journal articl