A novel approach to determine upper tolerance limit of non-stationary vibrations during rocket launch

This paper firstly introduces a locally stationary model to analyze non-stationary environmental vibrations during a rocket launch. Then based on this model, a novel method is proposed to estimate the upper tolerance limit of expected non-stationary environmental vibrations, which can be used to evaluate whether equipments on rocket can experience environmental vibrations in safe. Compared with available method, the proposed method can characterize non-stationary vibration better

MDA GAN: Adversarial-Learning-based 3-D Seismic Data Interpolation and Reconstruction for Complex Missing

The interpolation and reconstruction of missing traces is a crucial step in seismic data processing, moreover it is also a highly ill-posed problem, especially for complex cases such as high-ratio random discrete missing, continuous missing and missing in fault-rich or salt body surveys. These complex cases are rarely mentioned in current sparse or low-rank priorbased and deep learning-based approaches. To cope with complex missing cases, we propose Multi-Dimensional Adversarial GAN (MDA GAN), a novel 3-D GAN framework. It employs three discriminators to ensure the consistency of the reconstructed data with the original data distribution in each dimension. The feature splicing module (FSM) is designed and embedded into the generator of this framework, which automatically splices the features of the unmissing part with those of the reconstructed part (missing part), thus fully preserving the information of the unmissing part. To prevent pixel distortion in the seismic data caused by the adversarial learning process, we propose a new reconstruction loss Tanh Cross Entropy (TCE) loss to provide smoother gradients. We experimentally verified the effectiveness of the individual components of the study and then tested the method on multiple publicly available data. The method achieves reasonable reconstructions for up to 95% of random discrete missing, 100 traces of continuous missing and more complex hybrid missing. In surveys of fault-rich and salt bodies, the method can achieve promising reconstructions with up to 75% missing in each of the three directions (98.2% in total).Comment: This work has been submitted to journal for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

The exposure-response relationship between temperature and childhood hand, foot and mouth disease: A multicity study from mainland China.

BACKGROUND: Hand, foot and mouth disease (HFMD) is a rising public health issue in the Asia-Pacific region. Numerous studies have tried to quantify the relationship between meteorological variables and HFMD but with inconsistent results, in particular for temperature. We aimed to characterize the relationship between temperature and HFMD in various locations and to investigate the potential heterogeneity. METHODS: We retrieved the daily series of childhood HFMD counts (aged 0-12 years) and meteorological variables for each of 143 cities in mainland China in the period 2009-2014. We fitted a common distributed lag nonlinear model allowing for over dispersion to each of the cities to obtain the city-specific estimates of temperature-HFMD relationship. Then we pooled the city-specific estimates through multivariate meta-regression with city-level characteristics as potential effect modifiers. RESULTS: We found that the overall pooled temperature-HFMD relationship was shown as an approximately inverted V shape curve, peaking at the 91th percentile of temperature with a risk ratio of 1.30 (95% CI: 1.23-1.37) compared to its 50th percentile. We found that 68.5% of the variations of city-specific estimates was attributable to heterogeneity. We identified rainfall and altitude as the two main effect modifiers. CONCLUSIONS: We found a nonlinear relationship between temperature and HFMD. The temperature-HFMD relationship varies depending on geographic and climatic conditions. The findings can help us deepen the understanding of weather-HFMD relationship and provide evidences for related public health decisions

Monitoring of the central blood pressure waveform via a conformal ultrasonic device.

Continuous monitoring of the central-blood-pressure waveform from deeply embedded vessels, such as the carotid artery and jugular vein, has clinical value for the prediction of all-cause cardiovascular mortality. However, existing non-invasive approaches, including photoplethysmography and tonometry, only enable access to the superficial peripheral vasculature. Although current ultrasonic technologies allow non-invasive deep-tissue observation, unstable coupling with the tissue surface resulting from the bulkiness and rigidity of conventional ultrasound probes introduces usability constraints. Here, we describe the design and operation of an ultrasonic device that is conformal to the skin and capable of capturing blood-pressure waveforms at deeply embedded arterial and venous sites. The wearable device is ultrathin (240 μm) and stretchable (with strains up to 60%), and enables the non-invasive, continuous and accurate monitoring of cardiovascular events from multiple body locations, which should facilitate its use in a variety of clinical environments