Dense bubble flow in a silo: an unusual flow of a dispersed medium.

The dense flow of air bubbles in a two-dimensional silo (through an aperture D) filled with a liquid is studied experimentally. A particle tracking technique has been used to bring out the main properties of the flow: displacements of the bubbles, transverse, and axial velocities. The behavior of the air bubbles is observed to present similarities with nondeformable solid grains in a granular flow. Nevertheless, a correlation between the bubble velocities and their deformations has been evidenced. Moreover, a new discharge law (Beverloo like) must be considered for such a system, where the flow rate is observed to vary as D(1/2) and depends on the deformability of the particles.

A video multitracking system for quantification of individual behavior in a large fish shoal: advantages and limits.

The capability of a new multitracking system to track a large number of unmarked fish (up to 100) is evaluated. This system extrapolates a trajectory from each individual and analyzes recorded sequences that are several minutes long. This system is very efficient in statistical individual tracking, where the individual's identity is important for a short period of time in comparison with the duration of the track. Individual identification is typically greater than 99%. Identification is largely efficient (more than 99%) when the fish images do not cross the image of a neighbor fish. When the images of two fish merge (occlusion), we consider that the spot on the screen has a double identity. Consequently, there are no identification errors during occlusions, even though the measurement of the positions of each individual is imprecise. When the images of these two merged fish separate (separation), individual identification errors are more frequent, but their effect is very low in statistical individual tracking. On the other hand, in complete individual tracking, where individual fish identity is important for the entire trajectory, each identification error invalidates the results. In such cases, the experimenter must observe whether the program assigns the correct identification, and, when an error is made, must edit the results. This work is not too costly in time because it is limited to the separation events, accounting for fewer than 0.1% of individual identifications. Consequently, in both statistical and rigorous individual tracking, this system allows the experimenter to gain time by measuring the individual position automatically. It can also analyze the structural and dynamic properties of an animal group with a very large sample, with precision and sampling that are impossible to obtain with manual measures.

Comparing the EthoVision 2.3 system and a new computerized multitracking prototype system to measure the swimming behavior in fry fish.

Coming from the framework of unmarked fry tracking, we compared the capacities, advantages, and disadvantages of two recent video tracking systems: EthoVision 2.3 and a new prototype of multitracking. The EthoVision system has proved to be impressive for tracking a fry using the detection by gray scaling. Detection by subtraction has given less accurate results. Our video multitracking system is able to detect and track more than 100 unmarked fish by gray scaling technique. It permits an analysis at the group level as well as at the individual level. The multitracking program is able to attribute a number to each fish and to follow each one for the whole duration of the track. Our system permits the analysis of the movement of each individual, even if the trajectories of two fish cross each other. This is possible thanks to t hetheoretical estimation of th e trajectory of each fish, which can becompared with the real trajectory (analysis with feedback). However, the period of the track is limited for our system (about 1 min), whereas EthoVision is able to track for numerous hours. In spite of these limitations, these two systems allow an almost continuous automatic sampling of the movement behaviors during the track.