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Traditional methods of initiating oblique detonation waves (ODWs) using wedges and cones face a fundamental challenge in reconciling the need for rapid initiation with stable combustion, especially at low flight Mach numbers (Ma < 8). This study introduces an innovative initiation configuration involving a truncated cone. By utilizing Euler equations coupled with detailed hydrogen–air chemical reaction models, the wave dynamics induced by the truncated cone configuration are systematically explored. The findings reveal that the truncated cone configuration enables more rapid initiation of ODWs compared to conventional cones, while also preserving improved stability when contrasted with wedge. This behavior can be attributed to the planar flow characteristics in the post-shock field of truncated cone, generated by the upstream wedge-shaped shock, and the Taylor–Maccoll flow characteristics, caused by the downstream conical shock. Furthermore, the study delves into the initiation and morphological changes with respect to the inner radius and angle of the truncated cone. As inner radii or truncated cone angle increase, three initiation wave systems emerge: stable, oscillatory, and detached modes. Analysis of the dynamic variations in pressure and velocity within the induction zone highlights that the upstream oscillation originates from the flow velocity in the induction zone falling below the local Chapman–Jouguet velocity of normal detonation wave (NDW). However, the upstream region of the truncated cone exhibits more pronounced expansion effects, leading to momentum loss, and subsequently, the weakening and even vanishing of the NDW. This prompts the downstream oscillation of the initiation structure, instigating a cyclic oscillation pattern. [ABSTRACT FROM AUTHOR]

Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, exact measures cannot be obtained, and thus are left censored. The problem becomes more challenging when the censored data come from heterogeneous populations consisting of exposed and non‐exposed subjects. If the censored data come from non‐exposed subjects, their measures are always zero and hence censored, forming a latent class governed by a distinct censoring mechanism compared with the exposed subjects. The exposed group's censored measurements are always greater than zero, but less than the detection limit. It is very often that the exposed and non‐exposed subjects may have different disease traits or different relationships with outcomes of interest, so we need to disentangle the two different populations for valid inference. In this article, we aim to fill the methodological gaps in the literature by developing a novel joint modeling approach to not only address the censoring issue in predictors, but also untangle different relationships of exposed and non‐exposed subjects with the outcome. Simulation studies are performed to assess the numerical performance of our proposed approach when the sample size is small to moderate. The joint modeling approach is also applied to examine associations between plasma metabolites and blood pressure in Bogalusa Heart Study, and identify new metabolites that are highly associated with blood pressure. [ABSTRACT FROM AUTHOR]