Deep convolutional neural networks for Bearings failure predictionand temperature correlation

Rolling elements bearings (REBs) is one of the most sensitive components and the common failure unit in mechanical equipment. Bearings failure prognostics, which aims to achieve an effective way to handle the increasing requirements for higher reliability and in the same time reduce unnecessary costs, has been an area of extensive research. The accurate prediction of bearings Remaining Useful Life (RUL) is indispensable for safe and lifetime-optimized operations. To monitor this vital component and planning repair work, a new intelligent method based on Wavelet Packet Decomposition (WPD) and deep learning networks is proposed in this paper. Firstly, features extraction from WPD used as input data. Secondly, these selected features are fed into deep Convolutional Neural Networks (CNNs) to construct the Health Indicator (HI). This study focuses on analysing the relationships such as correlations between the HI and temperature. We develop a solution for the Connectiomics contest dataset of bearings under different operating conditions and severity of defects. The performance of the proposed method is verified by four bearing data sets collected from experimental setup called “PRONOSTIA”. The results show that the health indicator obtains fairly high monotonicity and correlation values and it is beneficial to bearing life prediction. In addition, it is experimentally demonstrated that the proposed method is able to achieve better performance than a traditional neural network based method

Exposure to secondhand and thirdhand smoke in private vehicles : Measurements in air and dust samples

This study aimed to estimate airborne nicotine concentrations and nicotine, cotinine, and tobacco-specific nitrosamines (TSNAs) in settled dust from private cars in Spain and the UK. We measured vapor-phase nicotine concentrations in a convenience sample of 45 private cars from Spain (N = 30) and the UK (N = 15) in 2017-2018. We recruited non-smoking drivers (n = 20), smoking drivers who do not smoke inside the car (n = 15), and smoking drivers who smoke inside (n = 10). Nicotine, cotinine, and three TSNAs (NNK, NNN, NNA) were also measured in settled dust in a random subsample (n = 20). We computed medians and interquartile ranges (IQR) of secondhand smoke (SHS) and thirdhand smoke (THS) compounds according to the drivers' profile. 24-h samples yielded median airborne nicotine concentrations below the limit of quantification (LOQ) (IQR: <LOQ - <LOQ) in non-smokers' cars, 0.23 μg/m (IQR:0.18-0.45) in cars of smokers not smoking inside, and 3.53 μg/m, (IQR:1.74-6.38) in cars of smokers smoking inside (p < 0.001). Nicotine concentrations measured only while travelling increased to 21.44 μg/m (IQR:6.60-86.15) in cars of smokers smoking inside. THS concentrations were higher in all cars of smokers, and specially in cars of drivers smoking inside (nicotine: 38.9 μg/g (IQR:19.3-105.7); NNK: 28.5 ng/g (IQR:26.6-70.2); NNN: 23.7 ng/g (IQR:14.3-55.3)), THS concentrations being up to six times those in non-smokers' cars. All cars of smokers had measurable SHS and THS pollution, the exposure levels markedly higher in vehicles of drivers where smoking took place. Our results evidence the need for policies to prohibit smoking in vehicles, but also urge for more comprehensive strategies aiming towards the elimination of tobacco consumption

Abordando la exposición a las emisiones del tabaco y de los cigarrillos electrónicos: protocolo del proyecto TackSHS

Objective: The TackSHS project aims to comprehensively elucidate the impact that exposure to second-hand smoke (SHS) from cigarettes and second-hand aerosols (SHA) from electronic cigarettes have on the respiratory health of the European population according to socioeconomic characteristics and other determinants. Method: The TackSHS project involves a series of coordinated studies carried out by 11 academic and public health organisations from six European countries. The project will investigate: a) the determinants of SHS and SHA exposure assessed at the individual level (surveys on representative general population samples) and in common environments (environmental sampling in specific settings); b) the overall disease burden, mortality and morbidity attributable to such exposure; and c) its economic impact in terms of direct health care costs. The project will also examine specific acute respiratory health changes in healthy individuals and patients with respiratory diseases exposed to SHS and SHA. In addition, the project will examine the effectiveness of a novel intervention to reduce SHS exposure in households where smoking is permitted. All these studies are inter-related and involve collaborative coordination among the participant organisations. Conclusion: The comprehensive, integrated approach of the TackSHS project will enable a significant step forward from the current status quo in the understanding of the impact of SHS and SHA exposure on health and provide the basis for health policy recommendations to help European countries to further reduce the harm caused by SHS and SHA exposure

Limiting temperatures for collective motion: The giant dipole resonance in very hot nuclei

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