Application of EMD-WVD and particle filter for gearbox fault feature extraction and remaining useful life prediction

Fault feature extraction and remaining useful life (RUL) prediction are important to condition based maintenance (CBM). In order to realize the fault feature extraction of gearbox vibration signal presenting nonlinear and non-Gaussian, the integration of empirical mode decomposition (EMD) and Wigner-Ville distribution (WVD) are proposed in this paper. Taking the kurtosis as standard, the WVD is applied to some IMFs with larger kurtosis to calculate the time-frequency distribution, with an effective suppress on mode mixing and the cross-term interference. Afterwards, particle filter (PF) with the state space model based on Wiener process is proposed to predict the RUL of gearbox considering degradation feature, gearbox teeth wear and nonlinear and non-Gaussian system. The gearbox life cycle test shows that the EMD-WVD method can extract the valued characteristics of vibration signal accurately, and the particle filter can provide an effective way to predict the RUL of gearbox

Oxidative Stress in Neurodegenerative Diseases: From Molecular Mechanisms to Clinical Applications

Increasing numbers of individuals, particularly the elderly, suffer from neurodegenerative disorders. These diseases are normally characterized by progressive loss of neuron cells and compromised motor or cognitive function. Previous studies have proposed that the overproduction of reactive oxygen species (ROS) may have complex roles in promoting the disease development. Research has shown that neuron cells are particularly vulnerable to oxidative damage due to their high polyunsaturated fatty acid content in membranes, high oxygen consumption, and weak antioxidant defense. However, the exact molecular pathogenesis of neurodegeneration related to the disturbance of redox balance remains unclear. Novel antioxidants have shown great potential in mediating disease phenotypes and could be an area of interest for further research. In this review, we provide an updated discussion on the roles of ROS in the pathological mechanisms of Alzheimer’s disease, Huntington’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and spinocerebellar ataxia, as well as a highlight on the antioxidant-based therapies for alleviating disease severity

Ligand-Hole in SnI6 Unit and Origin of Band Gap in Photovoltaic Perovskite Variant Cs2SnI6

This paper has been published in Bulletin of the Chemical Society of Japan, which can be viewed at the following URL: http://doi.org/10.1246/bcsj.20150110 Cs2SnI6, a variant of perovskite CsSnI3, is expected for a photovoltaic material. Based on a simple ionic model, it is expected that Cs2SnI6 is composed of Cs+, I-, and Sn4+ ions and that the band gap is primarily made of occupied I- 5p6 valence band maximum (VBM) and unoccupied Sn4+ 5s conduction band minimum (CBM) similar to SnO2. In this work, we performed density functional theory (DFT) calculations and revealed that the real oxidation state of the Sn ion in Cs2SnI6 is +2 similar to CsSnI3. The +2 oxidation state of Sn originates from 2 ligand holes in the [SnI6]2- octahedron unit, where the ligand [I6] cluster has the apparent [I66-L+2]4- oxidation state, because the band gap is formed mainly by occupied I 5p VBM and unoccupied I 5p CBM. The +2 oxidation state of Sn and the band gap are originated from the intracluster hybridization and stabilized by the strong covalent interaction between Sn and I

Exotic electronic states in gradient-strained untwisted graphene bilayers

Many exotic electronic states were discovered in moire superlattices hosted in twisted homo-bilayers in the past decade, including unconventional superconductivity and correlated insulating states. However, it is technically challenging to precisely and orderly stack two or more layers into certain twisting angles. Here, we presented a theoretical strategy that introduces moire superlattices in untwisted homo-bilayers by applying different in-plane strains on the two layers of a graphene homo-bilayer, respectively. Our density functional theory calculations indicate that the graphene bilayer exhibits substantial out-of-plane corrugations that form a coloring-triangular structure in each moire supercell under gradient in-plane strains. Such structure leads to a set of kagome bands, namely one flat-band and, at least, one Dirac band, developing along the M-K path after band-folding. For comparison, uniformly applied in-plane strain only yields a nearly flat band within path K-G, which is originated from local quantum confinement. These findings highlight the gradient strain as a route to feasibly fabricate exotic electronic states in untwisted flexible homo-bilayers.Comment: 15 pages, 4 figure

MnmE, a Central tRNA-Modifying GTPase, Is Essential for the Growth, Pathogenicity, and Arginine Metabolism of Streptococcus suis Serotype 2

Streptococcus suis is an important pathogen in pigs and can also cause severe infections in humans. However, little is known about proteins associated with cell growth and pathogenicity of S. suis. In this study, a guanosine triphosphatase (GTPase) MnmE homolog was identified in a Chinese isolate (SC19) that drives a tRNA modification reaction. A mnmE deletion strain (ΔmnmE) and a complementation strain (CΔmnmE) were constructed to systematically decode the characteristics and functions of MnmE both in vitro and in vivo studies via proteomic analysis. Phenotypic analysis revealed that the ΔmnmE strain displayed deficient growth, attenuated pathogenicity, and perturbation of the arginine metabolic pathway mediated by the arginine deiminase system (ADS). Consistently, tandem mass tag -based quantitative proteomics analysis confirmed that 365 proteins were differentially expressed (174 up- and 191 down-regulated) between strains ΔmnmE and SC19. Many proteins associated with DNA replication, cell division, and virulence were down-regulated. Particularly, the core enzymes of the ADS were significantly down-regulated in strain ΔmnmE. These data also provide putative molecular mechanisms for MnmE in cell growth and survival in an acidic environment. Therefore, we propose that MnmE, by its function as a central tRNA-modifying GTPase, is essential for cell growth, pathogenicity, as well as arginine metabolism of S. suis

A model of impaired Langerhans cell maturation associated with HPV induced epithelial hyperplasia.

Funder: National Health and Medical Research CouncilLangerhans cells (LC) are skin-resident antigen-presenting cells that regulate immune responses to epithelial microorganisms. Human papillomavirus (HPV) infection can promote malignant epithelial transformation. As LCs are considered important for controlling HPV infection, we compared the transcriptome of murine LCs from skin transformed by K14E7 oncoprotein and from healthy skin. We identified transcriptome heterogeneity at the single cell level amongst LCs in normal skin, associated with ontogeny, cell cycle, and maturation. We identified a balanced co-existence of immune-stimulatory and immune-inhibitory LC cell states in normal skin that was significantly disturbed in HPV16 E7-transformed skin. Hyperplastic skin was depleted of immune-stimulatory LCs and enriched for LCs with an immune-inhibitory gene signature, and LC-keratinocyte crosstalk was dysregulated. We identified reduced expression of interleukin (IL)-34, a critical molecule for LC homeostasis. Enrichment of an immune-inhibitory LC gene signature and reduced levels of epithelial IL-34 were also found in human HPV-associated cervical epithelial cancers

Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper