Rotor fault classification technique and precision analysis with kernel principal component analysis and multi-support vector machines

To solve the diagnosis problem of fault classification for aero-engine vibration over standard during test, a fault diagnosis classification approach based on kernel principal component analysis (KPCA) feature extraction and multi-support vector machines (SVM) is proposed, which extracted the feature of testing cell standard fault samples through exhausting the capability of nonlinear feature extraction of KPCA. By computing inner product kernel functions of original feature space, the vibration signal of rotor is transformed from principal low dimensional feature space to high dimensional feature spaces by this nonlinear map. Then, the nonlinear principal components of original low dimensional space are obtained by performing PCA on the high dimensional feature spaces. During muti-SVM training period, as eigenvectors, the nonlinear principal components are separated into training set and test set, and penalty parameter and kernel function parameter are optimized by adopting genetic optimization algorithm. A high classification accuracy of training set and test set is sustained and over-fitting and under-fitting are avoided. Experiment results indicate that this method has good performance in distinguishing different aero-engine fault mode, and is suitable for fault recognition of a high speed rotor

Quantum Discord for Investigating Quantum Correlations without Entanglement in Solids

Quantum systems unfold diversified correlations which have no classical counterparts. These quantum correlations have various different facets. Quantum entanglement, as the most well known measure of quantum correlations, plays essential roles in quantum information processing. However, it has recently been pointed out that quantum entanglement cannot describe all the nonclassicality in the correlations. Thus the study of quantum correlations in separable states attracts widely attentions. Herein, we experimentally investigate the quantum correlations of separable thermal states in terms of quantum discord. The sudden change of quantum discord is observed, which captures ambiguously the critical point associated with the behavior of Hamiltonian. Our results display the potential applications of quantum correlations in studying the fundamental properties of quantum system, such as quantum criticality of non-zero temperature.Comment: 4 pages, 4 figure

Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation

Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA) is very attractive for real world applications. By learning from large-scale unlabeled samples, self-supervised learning has now become a new trend in deep learning. It is worth noting that both self-supervised learning and multi-source domain adaptation share a similar goal: they both aim to leverage unlabeled data to learn more expressive representations. Unfortunately, traditional multi-task self-supervised learning faces two challenges: (1) the pretext task may not strongly relate to the downstream task, thus it could be difficult to learn useful knowledge being shared from the pretext task to the target task; (2) when the same feature extractor is shared between the pretext task and the downstream one and only different prediction heads are used, it is ineffective to enable inter-task information exchange and knowledge sharing. To address these issues, we propose a novel \textbf{S}elf-\textbf{S}upervised \textbf{G}raph Neural Network (SSG), where a graph neural network is used as the bridge to enable more effective inter-task information exchange and knowledge sharing. More expressive representation is learned by adopting a mask token strategy to mask some domain information. Our extensive experiments have demonstrated that our proposed SSG method has achieved state-of-the-art results over four multi-source domain adaptation datasets, which have shown the effectiveness of our proposed SSG method from different aspects

Recurrent exercise-induced acute kidney injury by idiopathic renal hypouricemia with a novel mutation in the SLC2A9 gene and literature review

OBJETIVO: Comparar a sensibilidade do método de difusão em ágar e do método de extração utilizando as linhagens celulares RC-IAL (células fibroblásticas de rim de coelho) e HeLa (células epiteliais de carcinoma do colo do útero humano), na avaliação da citotoxicidade "in vitro" de materiais de uso médico-hospitalar. MATERIAL E MÉTODO: Foram testadas 50 amostras escolhidas por sorteio, entre as já conhecidamente positivas e negativas e identificadas como: algodão, espuma, borracha, látex, celulose e acrílico. Além, das amostras citadas foram testadas experimentalmente várias concentrações de SDS (duodecil sulfato de sódio) nas culturas celulares RC-IAL e HeLa. RESULTADOS: Das 50 amostras testadas , 44 (88%) foram positivas para os dois métodos. Mas quando comparado o SDS nos dois métodos foram observados resultados positivos nas concentrações de 0,5 a 0,05 µg/ml no método de difusão em ágar e no método de extração somente foi observado efeito citotóxico até a concentração de 0,25 µg/ml. CONCLUSÃO: Os resultados encontrados são similares aos observados por outros autores que testaram materiais como, por exemplo, ligas metálicas. Quando foi usado o SDS observou-se, nas duas linhagens celulares, diferenças favoráveis ao método de difusão em ágar em duas concentrações, isto é, a sensibilidade deste método foi significantemente maior, por inspecção, em relação ao método de extração, além de se constituir em método mais simples de ser realizado

Anti-inflammatory and anti-oxidative effects of corilagin in a rat model of acute cholestasis

BACKGROUND: Nowadays, treatments for cholestasis remain largely nonspecific and often ineffective. Recent studies showed that inflammatory injuries and oxidative stress occur in the liver with cholestasis. In this study, we would use corilagin to treat the animal model of acute cholestasis in order to define the activity to interfere with inflammation-related and oxidative stress pathway in cholestatic pathogenesis. METHODS: Rats were administrated with alpha-naphthylisothiocyanate to establish model of cholestasis and divided into corilagin, ursodeoxycholic acid, dexamethasone, model and normal groups with treatment of related agent. At 24h, 48h and 72h time points after administration, living condition, serum markers of liver damage, pathological changes of hepatic tissue, nuclear factor (NF)-kappaB, myeloperoxidase (MPO), malondialdehyde (MDA), superoxide dismutase (SOD) and nitric oxide (NO) were examined and observed. RESULTS: Compared to model group, corilagin had remarkable effect on living condition, pathological manifestation of liver tissue, total bilirubin, direct bilirubin, (P<0.01), but no effect on alanine aminotransferase (ALT) and aspartate aminotransferase (AST). With corilagin intervention, levels of MPO, MDA and translocation of NF-κB were notably decreased, and levels of SOD and NO were markedly increased (P<0.05 or P<0.01). CONCLUSIONS: It is shown that corilagin is a potential component to relieve cholestasis through inflammation-related and oxidation-related pathway

Multi-target siRNA based on DNMT3A/B homologous conserved region influences cell cycle and apoptosis of human prostate cancer cell line TSU-PR1

Abnormal genome hypermethylation participates in the tumorigenesis and development of prostate cancer. Prostate cancer cells highly express DNA methyltransferase 3 (DMNT3) family genes, essential for maintaining genome methylation. In the present study, multi-target siRNA, based on the homologous region of the DNMT3 family, was designed for the in vitro investigation of its effects on the proliferation, migration, and invasion of TSU-PR1 prostate cancer cells. The consequential cell-cycle derangement, through DNMT3A/B or only DNMT3B silencing, was partially efficient, without affecting apoptosis. DNMT3A silencing had absolutely no effect on changing TSU-PR1 cell biological behavior. Hence, DNMT3B alone apparently plays a key role in maintaining the unfavorable behavior of prostate-cancer cells, thereby implying its potential significance as a promising therapeutic target, with DNMT3A simply in the role of helper

Suppression of Laccase 2 severely impairs cuticle tanning and pathogen resistance during the pupal metamorphosis of Anopheles sinensis (Diptera: Culicidae)

Amino acid sequence identity of Cu-oxidase domains of LAC2 orthologs. (PDF 109 kb