229 research outputs found

    Multi-fault diagnosis for rolling element bearings based on intrinsic mode function screening and optimized least squares support vector machine

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    Multi-fault diagnosis of rolling element bearing is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of nonstationarity and nonlinearity, the detection, extraction and classification of the fault feature turn into a challenging task. This paper presents a novel method based on redundant second generation wavelet packet transform (RSGWPT), ensemble empirical mode decomposition (EEMD) and optimized least squares support vector machine (LSSVM) for fault diagnosis of rolling element bearings. Firstly, this method implements an analysis combining RSGWPT-EEMD to extract the crucial characteristics from the measured signal to identify the running state of rolling element bearings, the vibration signal is adaptively decomposed into a number of modified intrinsic mode functions (modified IMFs) by two step screening processes based on the energy ratio; secondly, the matrix is formed by different level modified IMFs and singular value decomposition (SVD) is used to decompose the matrix to obtain singular value as eigenvector; finally, singular values are input to LSSVM optimized by particle swarm optimization (PSO) in the feature space to specify the fault type. The effectiveness of the proposed multi-fault diagnosis technique is demonstrated by applying it to both simulated signals and practical bearing vibration signals under different conditions. The results show that the proposed method is effective for the condition monitoring and fault diagnosis of rolling element bearings

    Chinese herbal medicine Guizhi Fuling Formula for treatment of uterine fibroids : a systematic review of randomized clinical trials

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    Background: Guizhi Fuling Formula is widely applied for uterine fibroids in China. Many clinical trials are reported. This study assessed the efficacy and safety of Guizhi Fuling Formula for the treatment of uterine fibroids. Methods: PubMed, Cochrane CENTRAL, EMBASE, and four Chinese databases were searched through May 2013. We included randomised controlled trials (RCTs) that tested Guizhi Fuling Formula for uterine fibroids, compared with no intervention, placebo, pharmaceutical medication, or other Chinese patent medicines approved by the State Food and Drug Administration of China. Authors extracted data and assessed the quality independently. We applied RevMan 5.2.0 software to analyse data of included randomised trials. Results: A total of 38 RCTs involving 3816 participants were identified. The methodological quality of the included trials was generally poor. Meta-analyses demonstrated that Guizhi Fuling Formula plus mifepristone were more effective than mifepristone alone in reducing the volume of fibroids (in total volume of multiple fibroids, MD −19.41 cm3, 95% CI −28.68 to −10.14; in average volume of multiple fibroids, MD −1.00 cm3, 95% CI −1.23 to −0.76; in average volume of maximum fibroids, MD −3.35 cm3, 95% CI −4.84 to −1.87, I2 = 93%, random effects model). Guizhi Fuling Formula significantly improved symptoms of dysmenorrhea either when it was used alone (RR 2.27, 95% CI 1.04 to 4.97) or in combination with mifepristone (RR 2.35, 95% CI 1.15 to 4.82). No serious adverse events were reported. Conclusions: Guizhi Fuling Formula appears to have additional benefit based on mifepristone treatment in reducing volume of fibroids. However, due to high risk of bias of the trials, we could not draw confirmative conclusions on its benefit. Future clinical trials should be well-designed and avoid the issues that are identified in this study

    A BRCA2 germline mutation and high expression of immune checkpoints in a TNBC patient

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    : Triple-negative breast cancer (TNBC) is the most aggressive subtype of mammary carcinoma. Here, we describe a case of an 81-year-old female diagnosed with ductal triple negative breast cancer with a germline pathogenic variant in BReast CAncer gene2 (BRCA2). Genetic testing also revealed the presence of four somatic mutations in the ephrin type-A receptor 3 (EphA3), TP53, BRCA1-associated protein (BAP1), and MYB genes. The BRCA2, TP53, and BAP1 gene mutations are highly predictive of a defective homologous recombination repair system and subsequent chromosomal instability in this patient. Coherently, the patient displayed a strong homologous recombination deficiency signature and high tumor mutational burden status, which are generally associated with increased probability of immune neoantigens formation and presentation, and with tumor immunogenicity. Analysis of immune checkpoint revealed high expression of programmed cell death ligand 1 (PD-L1), programmed cell death ligand 2 (PD-L2), programmed death 1 (PD1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA 4), suggesting that the patient might likely benefit from immunotherapies. Altogether, these findings support an unveiled link between BRCA2 inactivation, HR deficiency and increased expression of immune checkpoints in TNBC. This clinical case highlights the importance of screening TNBC patients for genetic mutations and TMB biomarkers in order to predict the potential efficacy of immunotherapy

    Peregrine: A Pattern-Aware Graph Mining System

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    Graph mining workloads aim to extract structural properties of a graph by exploring its subgraph structures. General purpose graph mining systems provide a generic runtime to explore subgraph structures of interest with the help of user-defined functions that guide the overall exploration process. However, the state-of-the-art graph mining systems remain largely oblivious to the shape (or pattern) of the subgraphs that they mine. This causes them to: (a) explore unnecessary subgraphs; (b) perform expensive computations on the explored subgraphs; and, (c) hold intermediate partial subgraphs in memory; all of which affect their overall performance. Furthermore, their programming models are often tied to their underlying exploration strategies, which makes it difficult for domain users to express complex mining tasks. In this paper, we develop Peregrine, a pattern-aware graph mining system that directly explores the subgraphs of interest while avoiding exploration of unnecessary subgraphs, and simultaneously bypassing expensive computations throughout the mining process. We design a pattern-based programming model that treats "graph patterns" as first class constructs and enables Peregrine to extract the semantics of patterns, which it uses to guide its exploration. Our evaluation shows that Peregrine outperforms state-of-the-art distributed and single machine graph mining systems, and scales to complex mining tasks on larger graphs, while retaining simplicity and expressivity with its "pattern-first" programming approach.Comment: This is the full version of the paper appearing in the European Conference on Computer Systems (EuroSys), 202

    Antibiotics and antibiotic resistance genes in global lakes:A review and meta-analysis

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    Lakes are an important source of freshwater, containing nearly 90% of the liquid surface fresh water worldwide. Long retention times in lakes mean pollutants from discharges slowly circulate around the lakes and may lead to high ecological risk for ecosystem and human health. In recent decades, antibiotics and antibiotic resistance genes (ARGs) have been regarded as emerging pollutants. The occurrence and distribution of antibiotics and ARGs in global freshwater lakes are summarized to show the pollution level of antibiotics and ARGs and to identify some of the potential risks to ecosystem and human health. Fifty-seven antibiotics were reported at least once in the studied lakes. Our meta-analysis shows that sulfamethoxazole, sulfamerazine, sulfameter, tetracycline, oxytetracycline, erythromycin, and roxithromycin were found at high concentrations in both lake water and lake sediment. There is no significant difference in the concentration of sulfonamides in lake water from China and that from other countries worldwide; however, there was a significant difference in quinolones. Erythromycin had the lowest predicted hazardous concentration for 5% of the species (HC5) and the highest ecological risk in lakes. There was no significant difference in the concentration of sulfonamide resistance genes (sul1 and sul2) in lake water and river water. There is surprisingly limited research on the role of aquatic biota in propagation of ARGs in freshwater lakes. As an environment that is susceptible to cumulative build-up of pollutants, lakes provide an important environment to study the fate of antibiotics and transport of ARGs with a broad range of niches including bacterial community, aquatic plants and animals

    Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

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    Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30MM_{\odot} for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

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

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    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

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed
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