A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos

Deep learning models have been widely used for anomaly detection in surveillance videos. Typical models are equipped with the capability to reconstruct normal videos and evaluate the reconstruction errors on anomalous videos to indicate the extent of abnormalities. However, existing approaches suffer from two disadvantages. Firstly, they can only encode the movements of each identity independently, without considering the interactions among identities which may also indicate anomalies. Secondly, they leverage inflexible models whose structures are fixed under different scenes, this configuration disables the understanding of scenes. In this paper, we propose a Hierarchical Spatio-Temporal Graph Convolutional Neural Network (HSTGCNN) to address these problems, the HSTGCNN is composed of multiple branches that correspond to different levels of graph representations. High-level graph representations encode the trajectories of people and the interactions among multiple identities while low-level graph representations encode the local body postures of each person. Furthermore, we propose to weightedly combine multiple branches that are better at different scenes. An improvement over single-level graph representations is achieved in this way. An understanding of scenes is achieved and serves anomaly detection. High-level graph representations are assigned higher weights to encode moving speed and directions of people in low-resolution videos while low-level graph representations are assigned higher weights to encode human skeletons in high-resolution videos. Experimental results show that the proposed HSTGCNN significantly outperforms current state-of-the-art models on four benchmark datasets (UCSD Pedestrian, ShanghaiTech, CUHK Avenue and IITB-Corridor) by using much less learnable parameters.Comment: Accepted to IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT

Amyloid-β peptide induces oligodendrocyte death by activating the neutral sphingomyelinase–ceramide pathway

Amyloid-β peptide (Aβ) accumulation in senile plaques, a pathological hallmark of Alzheimer's disease (AD), has been implicated in neuronal degeneration. We have recently demonstrated that Aβ induced oligodendrocyte (OLG) apoptosis, suggesting a role in white matter pathology in AD. Here, we explore the molecular mechanisms involved in Aβ-induced OLG death, examining the potential role of ceramide, a known apoptogenic mediator. Both Aβ and ceramide induced OLG death. In addition, Aβ activated neutral sphingomyelinase (nSMase), but not acidic sphingomyelinase, resulting in increased ceramide generation. Blocking ceramide degradation with N-oleoyl-ethanolamine exacerbated Aβ cytotoxicity; and addition of bacterial sphingomyelinase (mimicking cellular nSMase activity) induced OLG death. Furthermore, nSMase inhibition by 3-O-methyl-sphingomyelin or by gene knockdown using antisense oligonucleotides attenuated Aβ-induced OLG death. Glutathione (GSH) precursors inhibited Aβ activation of nSMase and prevented OLG death, whereas GSH depletors increased nSMase activity and Aβ-induced death. These results suggest that Aβ induces OLG death by activating the nSMase–ceramide cascade via an oxidative mechanism

Electrochemical performance and reaction mechanism investigation of V₂O₅ positive electrode material for aqueous rechargeable zinc batteries

The electrochemical performance and reaction mechanism of orthorhombic V$_2$O$_5$ in 1 M ZnSO$_4$ aqueous electrolyte are investigated. V$_2$O$_5$ nanowires exhibit an initial discharge and charge capacity of 277 and 432 mA h g$^{−1}$, respectively, at a current density of 50 mA g$^{−1}$. The material undergoes quick capacity fading during cycling under both low (50 mA g$^{−1}$) and high (200 mA g$^{−1}$) currents. V$_2$O$_5$ can deliver a higher discharge capacity at 200 mA g$^{−1}$ than that at 50 mA g$^{−1}$ after 10 cycles, which could be attributed to a different type of activation process under both current densities and distinct degrees of side reactions (parasitic reactions). Cyclic voltammetry shows several successive redox peaks during Zn ion insertion and deinsertion. In operando synchrotron diffraction reveals that V$_2$O$_5$ undergoes a solid solution and two-phase reaction during the 1st cycle, accompanied by the formation/decomposition of byproducts Zn$_3$(OH)$_2$V$_2$O$_7$·2(H$_2$O) and ZnSO$_4$Zn$_3$(OH)$_6$·5H$_2$O. In the 2nd insertion process, V$_2$O$_5$ goes through the same two-phase reaction as that in the 1st cycle, with the formation of the byproduct ZnSO$_4$Zn$_3$(OH)$_6$·5H$_2$O. The reduction/oxidation of vanadium is confirmed by in operando X-ray absorption spectroscopy. Furthermore, Raman, TEM, and X-ray photoelectron spectroscopy (XPS) confirm the byproduct formation and the reversible Zn ion insertion/deinsertion in the V$_2$O$_5$

Progressive prediction: Video anomaly detection via multi‐grained prediction

Abstract Video Anomaly Detection (VAD) has been an active research field for several decades. However, most existing approaches merely extract a single type of feature from videos and define a single paradigm to indicate the extent of abnormalities. A coarse‐to‐fine three‐level prediction is built by integrating different levels of spatio‐temporal representations, better highlighting the difference between normal and abnormal behaviors. First, an object‐level trajectory prediction is proposed to model human historical position using a graph transformer network. Subsequently, skeleton‐level prediction is achieved by incorporating the positional information from the trajectory prediction. More importantly, based on the predicted skeleton, a skeleton‐guided pixel‐level region prediction is performed. A novel Skeleton Conditioned Generative Adversarial Network (SCGAN) is designed to explore the correlation between skeleton‐level and pixel‐level motion prediction. Benefiting from SCGAN, the prediction of human regions is contributed by both coarse‐grained and fine‐grained motion features. This three‐level prediction, namely Progressive Prediction Video Anomaly Detection (P3VAD), enlarges the prediction error on irregular motion patterns. Besides, a pixel‐level analysis method is proposed to achieve Background‐bias Elimination (BE) and denoise the predicted region. Experimental results validate the effectiveness of P3VAD on the four benchmark datasets (ShanghaiTech, CUHK Avenue, IITB‐Corridor, and ADOC)

Investigation on Computing Method of Martian Dust Fluid Based on the Energy Dissipation Method

In this paper, an initiative Martian dust fluid simulating research based on the energy dissipation method was developed to simulate the deposition process of Martian dust fluid which was caused by surface adhesion between particles and Martian rovers. Firstly, an energy dissipation model of particles based on the Discrete Element Method (DEM) was established because of the characteristics of Martian dust particles such as tiny size and viscoelasticity. This model is based on the existing DMT model to analyze the collision deposition of dust fluid particles, including particle-spacecraft collision and particle-particle collision. Secondly, this paper analyzed the characteristics of particles after their first collision, then, established the stochastic model of critical wind speed for the particle deposition process. Finally, a series of simulations of the Martian dust fluid particle deposition process were done based on DEM-CFD. The results verified the accuracy of the energy dissipation model and the stochastic model, which could also verify the feasibility and effectiveness of the computing method of Martian dust fluid based on the DEM-CFD technology

Sulfatide Deficiency, an Early Alzheimer’s Lipidomic Signature, Causes Brain Ventricular Enlargement in the Absence of Classical Neuropathological Hallmarks

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by progressive memory loss and a decline in activities of daily life. Ventricular enlargement has been associated with worse performance on global cognitive tests and AD. Our previous studies demonstrated that brain sulfatides, myelin-enriched lipids, are dramatically reduced in subjects at the earliest clinically recognizable AD stages via an apolipoprotein E (APOE)-dependent and isoform-specific process. Herein, we provided pre-clinical evidence that sulfatide deficiency is causally associated with brain ventricular enlargement. Specifically, taking advantage of genetic mouse models of global and adult-onset sulfatide deficiency, we demonstrated that sulfatide losses cause ventricular enlargement without significantly affecting hippocampal or whole brain volumes using histological and magnetic resonance imaging approaches. Mild decreases in sulfatide content and mild increases in ventricular areas were also observed in human APOE4 compared to APOE2 knock-in mice. Finally, we provided Western blot and immunofluorescence evidence that aquaporin-4, the most prevalent aquaporin channel in the central nervous system (CNS) that provides fast water transportation and regulates cerebrospinal fluid in the ventricles, is significantly increased under sulfatide-deficient conditions, while other major brain aquaporins (e.g., aquaporin-1) are not altered. In short, we unraveled a novel and causal association between sulfatide deficiency and ventricular enlargement. Finally, we propose putative mechanisms by which sulfatide deficiency may induce ventricular enlargement

Electrochemical performance and reaction mechanism investigation of V2O5V_{2}O_{5} positive electrode material for aqueous rechargeable zinc batteries

The electrochemical performance and reaction mechanism of orthorhombic V$_2$O$_5$ in 1 M ZnSO$_4$ aqueous electrolyte are investigated. V$_2$O$_5$ nanowires exhibit an initial discharge and charge capacity of 277 and 432 mA h g$^{−1}$, respectively, at a current density of 50 mA g$^{−1}$. The material undergoes quick capacity fading during cycling under both low (50 mA g$^{−1}$) and high (200 mA g$^{−1}$) currents. V$_2$O$_5$ can deliver a higher discharge capacity at 200 mA g$^{−1}$ than that at 50 mA g$^{−1}$ after 10 cycles, which could be attributed to a different type of activation process under both current densities and distinct degrees of side reactions (parasitic reactions). Cyclic voltammetry shows several successive redox peaks during Zn ion insertion and deinsertion. In operando synchrotron diffraction reveals that V$_2$O$_5$ undergoes a solid solution and two-phase reaction during the 1st cycle, accompanied by the formation/decomposition of byproducts Zn$_3$(OH)$_2$V$_2$O$_7$·2(H$_2$O) and ZnSO$_4$Zn$_3$(OH)$_6$·5H$_2$O. In the 2nd insertion process, V$_2$O$_5$ goes through the same two-phase reaction as that in the 1st cycle, with the formation of the byproduct ZnSO$_4$Zn$_3$(OH)$_6$·5H$_2$O. The reduction/oxidation of vanadium is confirmed by in operando X-ray absorption spectroscopy. Furthermore, Raman, TEM, and X-ray photoelectron spectroscopy (XPS) confirm the byproduct formation and the reversible Zn ion insertion/deinsertion in the V$_2$O$_5$