In this article, a modeling extension for the description of wave propagation in porous media at low-mid frequencies is introduced. To better characterize the viscous and inertial interactions between the fluid and the structure in this regime, two additional terms described by two parameters and are taken into account in the representation of the dynamic tortuosity in a Laurent-series on frequency. The model limitations are discussed. A sensitivity analysis is performed, showing that the influence of and on the acoustic response of porous media is significant. A general Bayesian inference is then conducted to infer, simultaneously, the posterior probability densities of the model parameters. The proposed method is based on the measurement of waves transmitted by a slab of rigid porous material, using a temporal model for the direct and inverse transmission problem. Bayesian inference results obtained on three different porous materials are presented, which suggests that the two additional parameters are accessible and help reduce systematic errors in the identification of other parameters: porosity, static viscous permeability, static viscous tortuosity, static thermal permeability, and static thermal tortuosity.
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http://dx.doi.org/10.1121/1.5080561 | DOI Listing |
J Food Sci
January 2025
School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
Whole-grain foods (WGFs) constitute a large part of humans' daily diet, making risk identification of WGFs important for health and safety. However, existing research on WGFs has paid more attention to revealing the effects of a single hazardous substance or various hazardous substances on food safety, neglecting the mutual influence between individual hazardous substances and between hazardous substances and basic information. Therefore, this paper proposes a causal inference of WGFs' risk based on a generative adversarial network (GAN) and Bayesian network (BN) to explore the mutual influence between hazardous substances and basic information.
View Article and Find Full Text PDFComput Vis ECCV
November 2024
University of Minnesota, Minneapolis.
Diffusion models have emerged as powerful generative techniques for solving inverse problems. Despite their success in a variety of inverse problems in imaging, these models require many steps to converge, leading to slow inference time. Recently, there has been a trend in diffusion models for employing sophisticated noise schedules that involve more frequent iterations of timesteps at lower noise levels, thereby improving image generation and convergence speed.
View Article and Find Full Text PDFCommun Stat Theory Methods
February 2024
Department of Experimental Statistics, Room 173 Martin D. Woodin Hall, Louisiana State University, Baton Rouge, LA 70803-5606.
Mediation analysis is conducted to make inferences on effects of mediators that intervene the relationship between an exposure variable and an outcome. Bayesian mediation analysis (BMA) naturally considers the hierarchical structure of the effects from the exposure variable to mediators and then to the outcome. We propose three BMA methods on survival outcomes, where mediation effects are measured in terms of hazard rate, survival time, or log of survival time respectively.
View Article and Find Full Text PDFJ Biopharm Stat
January 2025
Department of Mathematics, The University of Manchester, Manchester, UK.
Biomarkers are measured repeatedly in clinical studies until a pre-defined endpoint, such as death from certain causes, is reached. Such repeated measurements may present a dynamic process for understanding when to expect the study's endpoint. Joint modelling is often employed to handle such a model.
View Article and Find Full Text PDFSci Total Environ
January 2025
Department of Biological and Agricultural Engineering, University of California, Davis, CA, USA; Department of Land, Air, and Water Resources, University of California, Davis, CA, USA. Electronic address:
Accurate evaluation of water resource systems is essential for informed planning and decision-making. Evapotranspiration (ET), a key component of water resource management, is often estimated using remote sensing techniques; however, such estimates can be subject to significant uncertainties under certain conditions. In this study, we present a novel approach to improving the accuracy of ET estimates in composite terrains.
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