Text-oriented Modality Reinforcement Network for Multimodal Sentiment Analysis from Unaligned Multimodal Sequences

Multimodal Sentiment Analysis (MSA) aims to mine sentiment information from text, visual, and acoustic modalities. Previous works have focused on representation learning and feature fusion strategies. However, most of these efforts ignored the disparity in the semantic richness of different modalities and treated each modality in the same manner. That may lead to strong modalities being neglected and weak modalities being overvalued. Motivated by these observations, we propose a Text-oriented Modality Reinforcement Network (TMRN), which focuses on the dominance of the text modality in MSA. More specifically, we design a Text-Centered Cross-modal Attention (TCCA) module to make full interaction for text/acoustic and text/visual pairs, and a Text-Gated Self-Attention (TGSA) module to guide the self-reinforcement of the other two modalities. Furthermore, we present an adaptive fusion mechanism to decide the proportion of different modalities involved in the fusion process. Finally, we combine the feature matrices into vectors to get the final representation for the downstream tasks. Experimental results show that our TMRN outperforms the state-of-the-art methods on two MSA benchmarks.Comment: Accepted by CICAI 2023 (Finalist of Best Student Paper Award

Taxonomic status of Populus wulianensis and P. ningshanica (Salicaceae)

Species delimitation in the genus Populus is particularly challenging due to high levels of intraspecific polymorphism as well as frequent interspecific hybridisation and introgression. In this study, we aimed to examine the taxonomic status of Populus ningshanica and P. wulianensis using an integrative taxonomy that considers multiple operational criteria. We carried out morphometric analyses of leaf traits and genetic examinations (including sequence variations at five barcoding DNAs and polymorphisms at 14 nuclear microsatellite SSR primers) at the population level between them and two closely related species P. adenopoda and P. davidiana. Results suggest that P. wulianensis belongs to the polymorphic species, P. adenopoda and should be considered as a synonym of the latter. P. ningshanica may have arisen as a result on the hybridisation between P. adenopoda and P. davidiana and therefore should be treated as P. × ningshanica. This study highlights the importance of the integrated evidence in taxonomic decisions of the disputed species

Multiple Gravity Assist Spacecraft Trajectories Design Based on BFS and EP_DE Algorithm

The paper deals with the multiple gravity assist trajectories design. In order to improve the performance of the heuristic algorithms, such as differential evolution algorithm, in multiple gravity assist trajectories design optimization, a method combining BFS (breadth-first search) and EP DE (differential evolution algorithm based on search space exploring and principal component analysis) is proposed. In this method, firstly find the possible multiple gravity assist planet sequences with pruning based BFS and use standard differential evolution algorithm to judge the possibility of all the possible trajectories. Then select the better ones from all the possible solutions. Finally, use EP DE which will be introduced in this paper to find an optimal decision vector of spacecraft transfer time schedule (launch window and transfer duration) for each selected planet sequence. In this paper, several cases are presented to prove the efficiency of the method proposed

Association between sleep duration and quality with rapid kidney function decline and development of chronic kidney diseases in adults with normal kidney function: The China health and retirement longitudinal study

Research have shown that sleep is associated with renal function. However, the potential effects of sleep duration or quality on kidney function in middle-aged and older Chinese adults with normal kidney function has rarely been studied. Our study aimed to investigate the association of sleep and kidney function in middle-aged and older Chinese adults. Four thousand and eighty six participants with an eGFR ≥60 ml/min/1.73 m2 at baseline were enrolled between 2011 and 2015 from the China Health and Retirement Longitudinal Study. Survey questionnaire data were collected from conducted interviews in the 2011. The eGFR was estimated from serum creatinine and/or cystatin C using the Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPI). The primary outcome was defined as rapid kidney function decline. Secondary outcome was defined as rapid kidney function decline with clinical eGFR of <60 ml/min/1.73 m2 at the exit visit. The associations between sleep duration, sleep quality and renal function decline or chronic kidney disease (CKD) were assessed based with logistic regression model. Our results showed that 244 (6.0%) participants developed rapid decline in kidney function, while 102 (2.5%) developed CKD. In addition, participants who had 3–7 days of poor sleep quality per week had higher risks of CKD development (OR 1.86, 95% CI 1.24–2.80). However, compared with those who had 6–8 h of night-time sleep, no significantly higher risks of rapid decline in kidney function was found among those who had <6 h or >8 h of night time sleep after adjustments for demographic, clinical, or psychosocial covariates. Furthermore, daytime nap did not present significant risk in both rapid eGFR decline or CKD development. In conclusion, sleep quality was significantly associated with the development of CKD in middle-aged and older Chinese adults with normal kidney function

MFF-Net: Deepfake Detection Network Based on Multi-Feature Fusion

Significant progress has been made in generating counterfeit images and videos. Forged videos generated by deepfaking have been widely spread and have caused severe societal impacts, which stir up public concern about automatic deepfake detection technology. Recently, many deepfake detection methods based on forged features have been proposed. Among the popular forged features, textural features are widely used. However, most of the current texture-based detection methods extract textures directly from RGB images, ignoring the mature spectral analysis methods. Therefore, this research proposes a deepfake detection network fusing RGB features and textural information extracted by neural networks and signal processing methods, namely, MFF-Net. Specifically, it consists of four key components: (1) a feature extraction module to further extract textural and frequency information using the Gabor convolution and residual attention blocks; (2) a texture enhancement module to zoom into the subtle textural features in shallow layers; (3) an attention module to force the classifier to focus on the forged part; (4) two instances of feature fusion to firstly fuse textural features from the shallow RGB branch and feature extraction module and then to fuse the textural features and semantic information. Moreover, we further introduce a new diversity loss to force the feature extraction module to learn features of different scales and directions. The experimental results show that MFF-Net has excellent generalization and has achieved state-of-the-art performance on various deepfake datasets

Multiple Gravity Assist Spacecraft Trajectories Design Based on BFS and EP_DE Algorithm

The paper deals with the multiple gravity assist trajectories design. In order to improve the performance of the heuristic algorithms, such as differential evolution algorithm, in multiple gravity assist trajectories design optimization, a method combining BFS (breadth-first search) and EP_DE (differential evolution algorithm based on search space exploring and principal component analysis) is proposed. In this method, firstly find the possible multiple gravity assist planet sequences with pruning based BFS and use standard differential evolution algorithm to judge the possibility of all the possible trajectories. Then select the better ones from all the possible solutions. Finally, use EP_DE which will be introduced in this paper to find an optimal decision vector of spacecraft transfer time schedule (launch window and transfer duration) for each selected planet sequence. In this paper, several cases are presented to prove the efficiency of the method proposed

Nano-metal diborides-supported anode catalyst with strongly coupled TaOx/IrO2 catalytic layer for low-iridium-loading proton exchange membrane electrolyzer

Abstract The sluggish kinetics of oxygen evolution reaction (OER) and high iridium loading in catalyst coated membrane (CCM) are the key challenges for practical proton exchange membrane water electrolyzer (PEMWE). Herein, we demonstrate high-surface-area nano-metal diborides as promising supports of iridium-based OER nanocatalysts for realizing efficient, low-iridium-loading PEMWE. Nano-metal diborides are prepared by a novel disulphide-to-diboride transition route, in which the entropy contribution to the Gibbs free energy by generation of gaseous sulfur-containing products plays a crucial role. The nano-metal diborides, TaB2 in particular, are investigated as the support of IrO2 nanocatalysts, which finally forms a TaOx/IrO2 heterojunction catalytic layer on TaB2 surface. Multiple advantageous properties are achieved simultaneously by the resulting composite material (denoted as IrO2@TaB2), including high electrical conductivity, improved iridium mass activity and enhanced corrosion resistance. As a consequence, the IrO2@TaB2 can be used to fabricate the membrane electrode with a low iridium loading of 0.15 mg cm−2, and to give an excellent catalytic performance (3.06 A cm−[email protected] V@80 oC) in PEMWE―the one that is usually inaccessible by unsupported Ir-based nanocatalysts and the vast majority of existing supported Ir-based catalysts at such a low iridium loading

Inhibition of Fatty Acid β-Oxidation by Fatty Acid Binding Protein 4 Induces Ferroptosis in HK2 Cells Under High Glucose Conditions

Background Ferroptosis, which is caused by an iron-dependent accumulation of lipid hydroperoxides, is a type of cell death linked to diabetic kidney disease (DKD). Previous research has shown that fatty acid binding protein 4 (FABP4) is involved in the regulation of ferroptosis in diabetic retinopathy. The present study was constructed to explore the role of FABP4 in the regulation of ferroptosis in DKD. Methods We first detected the expression of FABP4 and proteins related to ferroptosis in renal biopsies of patients with DKD. Then, we used a FABP4 inhibitor and small interfering RNA to investigate the role of FABP4 in ferroptosis induced by high glucose in human renal proximal tubular epithelial (HG-HK2) cells. Results In kidney biopsies of DKD patients, the expression of FABP4 was elevated, whereas carnitine palmitoyltransferase-1A (CP-T1A), glutathione peroxidase 4, ferritin heavy chain, and ferritin light chain showed reduced expression. In HG-HK2 cells, the induction of ferroptosis was accompanied by an increase in FABP4. Inhibition of FABP4 in HG-HK2 cells changed the redox state, sup-pressing the production of reactive oxygen species, ferrous iron (Fe2+), and malondialdehyde, increasing superoxide dismutase, and reversing ferroptosis-associated mitochondrial damage. The inhibition of FABP4 also increased the expression of CPT1A, reversed lipid deposition, and restored impaired fatty acid β-oxidation. In addition, the inhibition of CPT1A could induce ferroptosis in HK2 cells. Conclusion Our results suggest that FABP4 mediates ferroptosis in HG-HK2 cells by inhibiting fatty acid β-oxidation