Bearing performance degradation assessment and prediction based on EMD and PCA-SOM

Bearings are used in a wide variety of rotating machineries. Bearing vibration signals are non-stationary signals. According to the non-stationary characteristics of bearing vibration signals, a bearing performance degradation assessment/prediction and fault diagnosis method based on empirical mode decomposition (EMD) and principal component analysis (PCA)-self organizing map (SOM) is proposed in this paper. First, vibration signals are decomposed into a finite number of intrinsic mode functions, after which the EMD energy feature vector, which is composed of all the IMF energy, is obtained. PCA is then introduced to reduce the dimension of feature vectors. After that, the reduced feature vectors are selected as input vectors of the SOM neural network for performance degradation and fault diagnosis. Finally, the degradation trend of bearing is predicted by Elman neural network. The analysis results from bearings with different fault degrees or degradation trend and fault patterns show that the proposed method can assess and predict the degradation of bearing suitably and achieve a fault recognition rate of over 95 % for various bearing fault patterns

Health assessment and fault diagnosis for centrifugal pumps using Softmax regression

Real-time health monitoring of industrial components and systems that can detect, classify, and predict impending faults is critical to reduce operating and maintenance costs. This paper presents a softmax regression-based prognostic method for on-line health assessment and fault diagnosis. System conditions are evaluated by processing the information gathered from access controllers or sensors mounted at different points in the system, and maintenance is performed only when the failure or malfunction prognosis is indicated. Wavelet packet decomposition and fast Fourier transform techniques are used to extract features from non-stationary vibration signals. Wavelet packet energies and fundamental frequency amplitude are used as features, and principal component analysis is used for feature reduction. Reduced features are input into softmax regression models to assess machine health and identify possible failure modes. The gradient descent method is used to determine the parameters of softmax regression models. The effectiveness and feasibility of the proposed method are illustrated by applying to a real application

Genome-wide characterization of L-aspartate oxidase genes in wheat and their potential roles in the responses to wheat disease and abiotic stresses

L-aspartate oxidase (AO) is the first enzyme in NAD+ biosynthesis and is widely distributed in plants, animals, and microorganisms. Recently, AO family members have been reported in several plants, including Arabidopsis thaliana and Zea mays. Research on AO in these plants has revealed that AO plays important roles in plant growth, development, and biotic stresses; however, the nature and functions of AO proteins in wheat are still unclear. In this study, nine AO genes were identified in the wheat genome via sequence alignment and conserved protein domain analysis. These nine wheat AO genes (TaAOs) were distributed on chromosomes 2, 5, and 6 of sub-genomes A, B, and D. Analysis of the phylogenetic relationships, conserved motifs, and gene structure showed that the nine TaAOs were clustered into three groups, and the TaAOs in each group had similar conserved motifs and gene structure. Meanwhile, the subcellular localization analysis of transient expression mediated by Agrobacterium tumetioniens indicated that TaAO3-6D was localized to chloroplasts. Prediction of cis-elements indicated that a large number of cis-elements involved in responses to ABA, SA, and antioxidants/electrophiles, as well as photoregulatory responses, were found in TaAO promoters, which suggests that the expression of TaAOs may be regulated by these factors. Finally, transcriptome and real-time PCR analysis showed that the expression of TaAOs belonging to Group III was strongly induced in wheat infected by F. graminearum during anthesis, while the expression of TaAOs belonging to Group I was heavily suppressed. Additionally, the inducible expression of TaAOs belonging to Group III during anthesis in wheat spikelets infected by F. graminearum was repressed by ABA. Finally, expression of almost all TaAOs was induced by exposure to cold treatment. These results indicate that TaAOs may participate in the response of wheat to F. graminearum infection and cold stress, and ABA may play a negative role in this process. This study lays a foundation for further investigation of TaAO genes and provides novel insights into their biological functions

Causative agent distribution and antibiotic therapy assessment among adult patients with community acquired pneumonia in Chinese urban population

<p>Abstract</p> <p>Background</p> <p>Knowledge of predominant microbial patterns in community-acquired pneumonia (CAP) constitutes the basis for initial decisions about empirical antimicrobial treatment, so a prospective study was performed during 2003–2004 among CAP of adult Chinese urban populations.</p> <p>Methods</p> <p>Qualified patients were enrolled and screened for bacterial, atypical, and viral pathogens by sputum and/or blood culturing, and by antibody seroconversion test. Antibiotic treatment and patient outcome were also assessed.</p> <p>Results</p> <p>Non-viral pathogens were found in 324/610 (53.1%) patients among whom <it>M. pneumoniae </it>was the most prevalent (126/610, 20.7%). Atypical pathogens were identified in 62/195 (31.8%) patients carrying bacterial pathogens. Respiratory viruses were identified in 35 (19%) of 184 randomly selected patients with adenovirus being the most common (16/184, 8.7%). The nonsusceptibility of <it>S. pneumoniae </it>to penicillin and azithromycin was 22.2% (Resistance (R): 3.2%, Intermediate (I): 19.0%) and 79.4% (R: 79.4%, I: 0%), respectively. Of patients (312) from whom causative pathogens were identified and antibiotic treatments were recorded, clinical cure rate with β-lactam antibiotics alone and with combination of a β-lactam plus a macrolide or with fluoroquinolones was 63.7% (79/124) and 67%(126/188), respectively. For patients having mixed <it>M. pneumoniae </it>and/or <it>C. pneumoniae </it>infections, a better cure rate was observed with regimens that are active against atypical pathogens (e.g. a β-lactam plus a macrolide, or a fluoroquinolone) than with β-lactam alone (75.8% vs. 42.9%, <it>p </it>= 0.045).</p> <p>Conclusion</p> <p>In Chinese adult CAP patients, <it>M. pneumoniae </it>was the most prevalent with mixed infections containing atypical pathogens being frequently observed. With <it>S. pneumoniae</it>, the prevalence of macrolide resistance was high and penicillin resistance low compared with data reported in other regions.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Health assessment and fault diagnosis for centrifugal pumps using Softmax regression

Real-time health monitoring of industrial components and systems that can detect, classify, and predict impending faults is critical to reduce operating and maintenance costs. This paper presents a softmax regression-based prognostic method for on-line health assessment and fault diagnosis. System conditions are evaluated by processing the information gathered from access controllers or sensors mounted at different points in the system, and maintenance is performed only when the failure or malfunction prognosis is indicated. Wavelet packet decomposition and fast Fourier transform techniques are used to extract features from non-stationary vibration signals. Wavelet packet energies and fundamental frequency amplitude are used as features, and principal component analysis is used for feature reduction. Reduced features are input into softmax regression models to assess machine health and identify possible failure modes. The gradient descent method is used to determine the parameters of softmax regression models. The effectiveness and feasibility of the proposed method are illustrated by applying to a real application

Cumulative Effect and Content Variation of Toxic Trace Elements in Human Hair around Xiaoqinling Gold Mining Area, Northwestern China

The harm of toxic trace element polluted living environments to human health in mining areas has attracted extensive attention. In this study, human hair samples from a toxic trace element polluted area (village A) in a mineral processing area collected in 2015 and 2019 were studied in detail and the nonpolluted human hair samples from a contrast area (village B) with a relatively clean environment were also collected for comparison. The Hg and As in human hair samples were analyzed by Atomic Fluorescence Spectrometry (AFS) and the Pb, Cd, Cr, and Cu in human hair samples were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The single cumulative index (Pi) and the Nemerrow index (Pz) were used to evaluate the single and comprehensive cumulative pollution index. The results indicated that the average toxic trace element contents in human hair from different ages in the polluted area exhibited certain statistical significance. The average single cumulative indexes indicated a significant accumulation of Hg, Pb, and Cd in human hair of both genders and different ages from the polluted area, and the comprehensive cumulative pollution indexes revealed higher accumulation of toxic trace elements in the hair of males than in females. In general, the content of toxic trace elements in human hair from polluted area was still growing in accumulation. The high content of toxic trace elements in human hair shows a notable correlation with human health, and the environmental pollution in gold mining areas is seriously harmful to human health

The Impacts of Molybdenum Exploration on Cd and Zn Contents in Surface Water: Evidence from a Molybdenum Mine in the Xiaoqinling Mountains

In order to study the impact of molybdenum ore development in a large molybdenum mining area in the Xiaoqinling Mountains on the water and sediment quality of the Wenyu stream, surface water, sediment, and surrounding rock samples were collected, and the Cd and Zn contents were analyzed. The pollution status and ecological risk degree of river water and sediment samples in the Wenyu stream watershed were evaluated using the single element pollution index method, geoaccumulation index method, Hakanson potential ecological risk assessment method, potentially toxic elements (PTEs) health risk assessment, and PTEs pollution comprehensive index method. Finally, the impact of mining development on the contents of Cd and Zn in the Wenyu stream were discussed, and the sources of pollution were identified. The study revealed that the levels of Cd and Zn in 23 water samples collected from the primary channel of the Wenyu stream were markedly higher compared to the unaffected contrast area. Similarly, the concentrations of Cd and Zn in the 17 sediment samples were significantly elevated compared to the average values in the reference area. These findings indicated that The Wenyu stream was heavily impacted by the molybdenum mining activities, resulting in a high ecological risk associated with the sediment in the primary channel. Acid mine drainage in the mining area, sediment release activities, and atmospheric dust fall are considered to be the main sources of PTEs polluting the Wenyu stream watershed. Relevant personnel should complete a thorough river water quality investigation and perform ecological environment restoration so as to ensure sustainable economic development