Automatic dynamic mask extraction for PIV images containing an unsteady interface, bubbles, and a moving structure

When performing Particle Image Velocimetry (PIV) measurements in complex fluid flows with moving interfaces and a two-phase flow, it is necessary to develop a mask to remove non-physical measurements. This is the case when studying, for example, the complex bubble sweep-down phenomenon observed in oceanographic research vessels. Indeed, in such a configuration, the presence of an unsteady free surface, of a solid–liquid interface and of bubbles in the PIV frame, leads to generate numerous laser reflections and therefore spurious velocity vectors. In this note, an image masking process is developed to successively identify the boundaries of the ship and the free surface interface. As the presence of the solid hull surface induces laser reflections, the hull edge contours are simply detected in the first PIV frame and dynamically estimated for consecutive ones. As for the unsteady surface determination, a specific process is implemented like the following: i) the edge detection of the gradient magnitude in the PIV frame, ii) the extraction of the particles by filtering high-intensity large areas related to the bubbles and/or hull reflections, iii) the extraction of the rough region containing these particles and their reflections, iv) the removal of these reflections. The unsteady surface is finally obtained with a fifth-order polynomial interpolation. The resulted free surface is successfully validated from the Fourier analysis and by visualizing selected PIV images containing numerous spurious high intensity areas. This paper demonstrates how this data analysis process leads to PIV images database without reflections and an automatic detection of both the free surface and the rigid body. An application of this new mask is finally detailed, allowing a preliminary analysis of the hydrodynamic flow.

Bacterial community structure of the marine diatom Haslea ostrearia

The marine diatom Haslea ostrearia produces a water-soluble blue-pigment named marennine of economic interest (e.g. in aquaculture for the greening of oysters). Up to date the studies devoted to ecological conditions under which this microalga develops never took into account the bacterial-H. ostrearia relationships. In this study the bacterial community was analysed by PCR-TTGE before and after H. ostrearia isolation cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community. The bacterial structure of the phycosphere differed strongly from that of the bulk sediment. The similarity between bacteria recovered from the biofilm and the suspended bacteria did not exceed 10% (vs. > 90% amongst biofilms). The differences in genetic fingerprints, more especially high between two H. ostrearia isolates showed also the highest differences in the bacterial structure as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture. At the scale of a culture cycle in laboratory conditions, the bacterial community was specific to the growth stage. When H. ostrearia was subcultured for 9 months, a shift in the bacterial structure was shown from 3-months subculturing and the bacterial structure stabilized afterwards (70-86% similarities). A first insight of the relationships between H. ostrearia and its surrounding bacteria was shown for a better understanding of the ecological feature of this diatom.

Preliminary metabolomic approach on the bacterial structure community of Haslea ostrearia

The marine diatom Haslea ostrearia [1] produces a water-soluble blue-pigment named marennine [2] of economic interest. But the lack of knowledge of the ecological conditions, under which this microalga develops in its natural ecosystem, more especially bacteria H. ostrearia interactions, prevents any optimization of its culture in well-controlled conditions. The structure of the bacterial community was analyzed by PCR-TTGE before and after the isolation of H. ostrearia cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community at two time-scales. The differences in genetic fingerprints, more especially high between two H. ostrearia isolates (HO-R and HO-BM) showed also the highest differences in the bacterial structure [3] as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture Here we present a Q-TOF LC/MS metabolomic fingerprinting approach [3]: - to investigate differential metabolites of axenic versus non axenic H. ostrearia cultures. - to focus on the specific metabolites of a bacterial surrounding associated with the activation or inhibition of the microalga growing. The Agilent suite of data processing software makes feature finding, statistical analysis, and identification easier. This enables rapid transformation of complex raw data into biologically relevant metabolite information.