In this paper, a novel time of arrival (TOA) estimation method is proposed based on an iterative cleaning process to extract the first path signal. The purpose is to address the challenge in dense multipath indoor environments that the power of the first path component is normally smaller than other multipath components, where the traditional matchfiltering (MF) based TOA estimator causes huge errors. Along with parameter estimation, the proposed process is trying to detect and extract the first path component by eliminating the strongest multipath component using a band-elimination filter in fractional Fourier Domain (FrFD) at each iterative procedure. To further improve the stability, a slack threshold and a strict threshold are introduced. Six simple and easily calculated termination criteria are proposed to monitor the iterative process. When the iterative 'cleaning' process is done, the outputs include the enhanced first path component and its estimated parameters. Based on these outputs, an optimal reference signal for the matchfiltering (MF) estimator can be constructed, and a more accurate TOA estimation can be conveniently obtained. The results from numerical simulations and experimental investigations verified that, for acoustic chirp signal TOA estimation, the accuracy of the proposed method is superior to those obtained by the conventional MF estimators.

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Objective This study aims to examine the levels of and associations between perceived stigma, self‐efficacy, and psychosocial adjustment (PA) among nasopharyngeal carcinoma (NPC) survivors, and to identify the mediating role of self‐efficacy between stigma and PA and explore the influencing factors of PA. Methods A cross‐sectional survey was conducted and 307 NPC survivors were recruited by convenience sampling method in Southern China from July 2019 to January 2020. Data analyses were performed with the SPSS WIN 25.0 program and PROCESS macro version 3.3. Results Stigma and self‐efficacy were positively associated with PA among Chinese NPC survivors. Tumor‐free survival time, late toxicities (fatigue, dizziness and headache, and hearing loss), stigma, and self‐efficacy entered the final regression model and explained 55.9% of the variance of PA. The total and direct effects of stigma on PA and its subscales were significant (p < 0.05). Positive indirect effects were found for stigma on PA via self‐efficacy (point estimate = 0.159, SE = 0.032, 95% CI [0.102 to 0.229]). Conclusions Stigma and self‐efficacy are significantly associated with PA, and self‐efficacy is also a mediating variable between stigma and PA among NPC survivors. Medical staff could improve the PA of NPC survivors by alleviating their stigma, enhancing their self‐efficacy, and relieving their late toxicities (fatigue, dizziness and headache, and hearing loss).

In order to solve the problem of accurately predicting the remaining useful life (RUL) of crusher roller sleeve under the partially observable and nonlinear nonstationary running state, a new method of RUL prediction based on Dempster-Shafer (D-S) data fusion and support vector regression-particle filter (SVR-PF) is proposed. First, it adopts the correlation analysis to select the features of temperature and vibration signal, and subsequently utilize wavelet to denoising the features. Lastly, comparing the prediction performance of the proposed method integrates temperature and vibration signal sources to predict the RUL with the prediction performance of single source and other prediction methods. The experiment results indicate that the proposed prediction method is capable of fusing different data sources to predict the RUL and the prediction accuracy of RUL can be improved when data are less available.

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