关键词： Bearings   fault diagnosis   induction motors   orientation   progression of scratches   spectral analysis   support vector machine (SVM)  

摘要： Bearing faults are a major source of failure in an induction motor, and early detection of fault becomes necessary because of its industrial application. A range of analytical methods has been used to detect, identify, and diagnose bearing faults, including vibrational analysis. Most analyses have used pitting as the fault, whereas in the industrial environment, scratches are a more common problem. This paper investigates such scratches, applying two types of fault analysis: fault progression and fault orientation. A support vector machine (SVM) algorithm is used to classify and diagnose the different types of bearing fault. The frequency-domain features obtained from a fast Fourier transform of the load current is used to train the SVM algorithm. The proposed diagnostic method is tested experimentally using induced outer race faults under different load conditions. The method is shown to be successful in diagnosing faults, suggesting potential applications in real industrial settings.

关键词： Bivalve immunity   Pattern recognition receptors   Crassostrea gigas   Transcriptome   RNA-Seq  

摘要： Pattern recognition receptors (PRRs) are essential in recognizing specific pathogen-associated molecular patterns (PAMPs) on microbes and triggering responses to eliminate the invading pathogens. Previous genomic studies have revealed a great number of PRR genes in the Pacific oyster Crassostrea gigas, a sessile and filter-feeder marine bivalve belonging to the phylum Mollusca. On the survey of PRRs in the assembly oyster reference genome version 9, a total of 1084 PRRs were identified, which were composed of at least 12 gene families. Some of the gene families were significantly expanded, including C-type lectins (CTLs), fibrinogen-related proteins (FREPs), scavenger receptor cysteine-rich repeat protein (SRCRs), leucine-rich repeat (LRR)-only proteins (LRRops), and especially Clq domain-containing proteins (ClqDCs). The transcriptomic profiles of these abundant PRRs in response to PAMP treatments were investigated by RNA-Seq using the SOLiD EZ BeadTM system. Compared to the control library, there were 6,655, 7,273, 7,593, 6,830, 6687 and 8250 differentially expressed genes in the haemocytes of oysters in response to lipopolysaccharide (LPS) stimulation for 6 h, 12 h and 24 h, and peptidoglycan (PGN), glucan (GLU) and poly I:C (IC) stimulation for 12 h, respectively. After stimulation for 12 h, there were 134, 97, 114 and 159 genes up-regulated in the LPS, PGN, GLU and IC library, respectively. Most of the gene families involved in immune response towards PAMPs were ClqDCs, CTLs and FREPs, while only a few members of LRR and immunoglobin-containing proteins (LRRIGs), retinoic acid-inducible gene I [RIG-I]-like receptors (RLRs) and Toll like receptors (TLRs) were up-regulated. After LPS stimulation, the expression level of 258 non-redundant PRR genes in oyster haemocytes increased significantly with different expression pattern, and most of them were ClqDCs, CTLs, LRRops and FREPs. The transcriptomic analyses indicated that there was a dynamic and orchestrated speci

关键词： Intuitionistic fuzzy set   divergence measure   Jensen-Tsalli intuitionistic fuzzy divergence measure   medical diagnosis   pattern recognition  

摘要： Vagueness in scientific studies poses a challenge. Intuitionistic Fuzzy Set (IFS) theory has emerged as a powerful and flexible tool to counter such challenge. So, there is a need to develop such measures which can not only measure the vagueness but also quantify the differences in underlying IFSs. The aim of this communication is to introduce one such divergence measure called Intuitionistic Fuzzy Jensen-Tsalli Divergence measure in the settings of IFS theory. The presence of parameters makes the proposed divergence measure flexible and competent for applications. Besides discussing some of its major properties, the findings are applied in pattern recognition problem and in medical diagnosis of some diseases with same set of symptoms. The performance of the proposed measure is genuinely compared with some other existing measures in literature through numerical examples based on medical diagnosis and pattern recognition.

摘要： We have entered the Noisy Intermediate-Scale Quantum Era. A plethora of quantum processor prototypes allow evaluation of potential of the Quantum Computing paradigm in applications to pressing computational problems of the future. Growing data input rates and detector resolution foreseen in High-Energy LHC (2030s) experiments expose the often high time and/or space complexity of classical algorithms. Quantum algorithms can potentially become the lower-complexity alternatives in such cases. In this work we discuss the potential of Quantum Associative Memory (QuAM) in the context of LHC data triggering. We examine the practical limits of storage capacity, as well as store and recall errorless efficiency, from the viewpoints of the state-of-the-art IBM quantum processors and LHC real-time charged track pattern recognition requirements. We present a software prototype implementation of the QuAM protocols and analyze the topological limitations for porting the simplest QuAM instances to the public IBM 5Q and 14Q cloud-based superconducting chips.

关键词： Genetics   Small molecules   Molecular structure   Nucleic acid structure   Receptors  

摘要： Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.

关键词： Ship trajectory clustering   Douglas-peucker algorithm   DBSCAN   DTW  

摘要： Clustering analysis is applied extensively in pattern recognition. In marine traffic applications, the clustering results may exhibit a customary route and traffic volume distribution. In order to improve the clustering performance of ship trajectory data, which is characterized by a large data volume and distribution complexity, a method consisting of Douglas-Peucker (DP)-based compression and density -based clustering is proposed. In the first part of the proposed method, the appropriate parameters for the DP algorithm were determined according to the shape changes in the trajectories, which were used to compress the trajectories prior to calculating the dynamic time warping (DTW) distance matrix. In the second part, the density -based spatial clustering of applications with noise (DBSCAN) algorithm was improved in terms of determining the parameters. Based on the statistical characteristics of ship trajectory distribution, the appropriate DBSCAN parameters could be determined adaptively. Evaluation and comparison experiments were conducted based on massive real ship trajectories in the Chinese port of Beilun-Zhoushan. The results demonstrated that, compared to the traditional DTW distance, the proposed similarity measurement exhibits superior performance in terms of both time and quality. Furthermore, the results of the comparison experiment demonstrated that the improved DBSCAN outperforms two existing clustering methods in marine traffic c pattern recognition.

关键词： Japanese encephalitis virus   Transcriptome   RNA microarray   Proinflammatory mediators   Neuronal infection   CXCL11   RIG-1   MDA5  

摘要： Japanese encephalitis virus (JEV) causes central nervous system neuronal injury and inflammation. A clear understanding of neuronal responses to JEV infection remains elusive. Using the Affymetrix array to investigate the transcriptome of infected SK-N-MC cells, 1316 and 2737 dysregulated genes ( >= 2/ - 2 fold change, P < 0.05) were found at 48 hours post-infection (hpi) and 60 hpi, respectively. The genes were mainly involved in anti-microbial responses, cell signalling, cellular function and maintenance, and cell death and survival. Among the most highly upregulated genes ( >= 10 folds, P < 0.05) were chemokines CCL5, CXCL11, IL8 and CXCL10. The upregulation and expression of CXCL11 were confirmed by qRT-PCR and immunofluorescence. Pathogen recognition receptors retinoic acid-inducible gene-1 (RIG-1) and melanoma differentiation-associated protein 5 (MDA5) were also upregulated. Our results strongly suggest that neuronal cells play a significant role in immunity against JEV. CXCL11, RIG-1 and MDA5 and other cytokines may be important in neuropatho-genesis.

关键词： PATTERN perception   HEAVY metals   MOLECULAR probes  

摘要： Pattern recognition methods such as linear discriminant analysis and principal component analysis are useful tools for the identification of analytes such as metal ions. These typically use a number of distinct molecular probes that exhibit cross-reactivity. Here we report a single molecule that demonstrates varying response in different solvents, therefore enabling the combination of probe and solvent to generate the required array diversity. Seven toxic metal ions were introduced as aqueous samples, and PCA and LDA techniques applied. The array could correctly identify all metals in pure water samples, all metals in doped lake-water samples. Further, we have explored the limit of detection of the system for two metal ions, Cu(ii) and Hg(ii), confirming the promise of the system as a candidate to identify toxic metals in environmental water sources.

关键词： Multi-scale marginal spectrum entropy   Two-phase flow   Flow-pattern identification   Dynamic characteristics  

摘要： Rod bundles are widely used in energy chemical equipment. The prediction and dynamic characteristics of flow patterns have been expansively studied in the last few decades because of their significant influence on heat transfer. In most studies, flow patterns were usually predicted by analyzing the temperature distribution on the tube and by visualization using high-speed cameras. Further, the studies used a square channel composed of 6 x 6 rod bundles as the experimental section. However, owing to the limitations of various temperature sensors, the measurement accuracy is low and the experimental setup is unreliable. In the present study, fine bubble flow, fine churn-bubble flow, churn flow, and annular flow were experimentally observed, and the pressure difference signals for fast reaction flow patterns were collected. An innovative method based on multi-scale marginal spectrum entropy was developed to identify flow patterns precisely, and the results revealed the dynamic characteristics. Multi-scale marginal spectrum entropy is a characteristic quantity, and the input support vector machine can recognize the flow pattern. The results indicate that the new method is feasible for the identification of flow patterns and analysis of the dynamic characteristics of different gas-liquid two-phase flows, which provide a reliable guide for flow-pattern control design and the safe operation of equipment.

关键词： Wire fault diagnosis   time domain reflectometry   artificial neural network   analytical transmission line   pattern recognition  

摘要： The aim of this paper is to develop a new approach for wiring networks diagnosis. This approach is based on time domain reflectometry (TDR) and pattern recognition network all combined with a simple localisation and characterisation algorithm. The developed approach has the advantage of being fast, reliable and accurate. The TDR responses are generated using the analytical transmission line method. Furthermore, the manipulated data are reduced since only the main peaks are exploited. The performance of the proposed approach has been assessed using four cases, two using a simple Y-shaped network and two using a more complicated YY-shaped network. The obtained results are very satisfactory, and they show the applicability of the proposed approach for real systems.