PubMed · 11638246
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C Bonnet-Cadilhac. 1989. [Not Available].. https://pubmed.ncbi.nlm.nih.gov/11638246/
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Ediacara fossils are among the oldest known macroscopic and complex life forms. Their bodyplan, ecology, and phylogenetic affinities have been controversial. On the basis of taphonomic observations, Seilacher [Seilacher, A. (1989) Lethaia 22, 229-239] proposed that the core elements of the Ediacara biota, the vendobionts, were constructed with serially or fractally arranged quilts or tube-like units. However, anatomy of quilt walls has been rarely reported, because most Ediacara fossils are preserved as casts and molds in siliciclastic rocks with inadequate morphological resolution. Here, we report an Ediacara form, uniquely preserved in situ and in three dimensions with its organic walls cast by early diagenetic calcite, from bituminous limestone of the 551- to 542-mega-annum Dengying Formation of South China. Despite diagenetic tampering, serial sections show that the Dengying form consists of biserially arranged, tube-like quilts, each with two vertical side walls, a floor, a roof, and an open distal end. Three-dimensional morphological complexity of the Dengying form excludes a microbial interpretation but is broadly consistent with vendobionts. Unlike classic frondose vendobionts sensu Seilacher, however, the Dengying form probably lacked a smooth margin and had distally open quilts. It probably lived procumbently at or near the water-sediment interface and shows evidence for substrate utilization. Despite its uncertain phylogeny, ontogeny, and functional biology, the Dengying form adds to Ediacaran biodiversity, places key constraints on the ecology and extinction of Ediacara organisms, and points to the need to explore an alternative taphonomic window for Ediacara biology.
Diffuse optical tomography (DOT) poses a typical ill-posed inverse problem with a limited number of measurements and inherently low spatial resolution. In this paper, we propose a hierarchical Bayesian approach to improve spatial resolution and quantitative accuracy by using a priori information provided by a secondary high resolution anatomical imaging modality, such as magnetic resonance (MR) or x-ray. In such a dual imaging approach, while the correlation between optical and anatomical images may be high, it is not perfect. For example, a tumour may be present in the optical image, but may not be discernable in the anatomical image. The proposed hierarchical Bayesian approach allows incorporation of partial a priori knowledge about the noise and unknown optical image models, thereby capturing the function-anatomy correlation effectively. We present a computationally efficient iterative algorithm to simultaneously estimate the optical image and the unknown a priori model parameters. Extensive numerical simulations demonstrate that the proposed method avoids undesirable bias towards anatomical prior information and leads to significantly improved spatial resolution and quantitative accuracy.
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