Search

Under the Gaussian noise assumption, the probability hypothesis density (PHD) filter represents a promising tool for tracking a group of moving targets with a time-varying number. However, inaccurate prior statistics of the random noise will degrade the performance of the PHD filter in many practical applications. This paper presents an adaptive Gaussian mixture PHD (AGM-PHD) filter for the multi-target tracking (MTT) problem in the scenario where both the mean and covariance of measurement noise sequences are unknown. The conventional PHD filters are extended to jointly estimate both the multi-target state and the aforementioned measurement noise statistics. In particular, the Normal-inverse-Wishart and Gaussian distributions are first integrated to represent the joint posterior intensity by transforming the measurement model into a new formulation. Then, the updating rule for the hyperparameters of the model is derived in closed form based on variational Bayesian (VB) approximation and Bayesian conjugate prior heuristics. Finally, the dynamic system state and the noise statistics are updated sequentially in an iterative manner. Simulations results with both constant velocity and constant turn model demonstrate that the AGM-PHD filter achieves comparable performance as the ideal PHD filter with true measurement noise statistics. [ABSTRACT FROM AUTHOR]

Background: Acute paraquat poisoning-induced multiple organ dysfunction syndrome (MODS) leads to the high mortality. This study aimed to investigate the clinical significance of microRNA-200b-3p (miR-200b-3p), an upstream inhibitor of high-mobility group box 1 (HMGB1), in acute paraquat poisoning patients for the prediction of MODS and survival. Methods: This study enrolled 80 patients with MODS induced by paraquat and 94 healthy volunteers. The interaction between miR-200b-3p and HMGB1 was identified by luciferase reporter assay. miR-200b-3p levels were measured by quantitative real-time (QRT) PCR. High-mobility group box 1 levels were measured by enzyme-linked immune sorbent assay (ELISA). Receiver operating characteristic analysis was used to evaluate the diagnostic value of miR-200b-3p in screening MODS patients. The relationship between miR-200b-3p and the 28-day survival of MODS patients was evaluated by Kaplan–Meier curves and log-rank test. Cox regression analysis was used to assess the prognostic value of miR-200b-3p. Correlation between miR-200b-3p and HMGB1 was confirmed by Pearson's correlation analysis. Results: miR-200b-3p directly target HMGB1. miR-200b-3p, decreased in MODS patients, had high diagnostic value to screen MODS patients from healthy controls. Additionally, serum miR-200b-3p was decreased in non-survivors, and patients with low miR-200b-3p level had poor 28-day survival. Serum miR-200b-3p could independently predict the survival prognosis. Moreover, serum HMGB1 level was increased in MODS patients, and was negatively correlated with miR-200b-3p level. Conclusion: Decreased miR-200b-3p may function as a biomarker for the diagnosis and survival prognosis of MODS patients, and miR-200b-3p may be involved in the progression of acute paraquat-induced MODS via regulating inflammatory responses by targeting HMGB1. [ABSTRACT FROM AUTHOR]