Effect of Liquid Droplets on Turbulence Structure in a Round Gaseous Jet

A second-order model which predicts the modulation of turbulence in jets laden with uniform size solid particles or liquid droplets is discussed. The approach followed is to start from the separate momentum and continuity equations of each phase and derive two new conservation equations. The first is for the carrier fluid's kinetic energy of turbulence and the second for the dissipation rate of that energy. Closure of the set of transport equations is achieved by modeling the turbulence correlations up to a third order. The coefficients (or constants) appearing in the modeled equations are then evaluated by comparing the predictions with LDA-measurements obtained recently in a turbulent jet laden with 200 microns solid particles. This set of constants is then used to predict the same jet flow but laden with 50 microns solid particles. The agreement with the measurement in this case is very good

Rhythmic inhibition allows neural networks to search for maximally consistent states

Gamma-band rhythmic inhibition is a ubiquitous phenomenon in neural circuits yet its computational role still remains elusive. We show that a model of Gamma-band rhythmic inhibition allows networks of coupled cortical circuit motifs to search for network configurations that best reconcile external inputs with an internal consistency model encoded in the network connectivity. We show that Hebbian plasticity allows the networks to learn the consistency model by example. The search dynamics driven by rhythmic inhibition enable the described networks to solve difficult constraint satisfaction problems without making assumptions about the form of stochastic fluctuations in the network. We show that the search dynamics are well approximated by a stochastic sampling process. We use the described networks to reproduce perceptual multi-stability phenomena with switching times that are a good match to experimental data and show that they provide a general neural framework which can be used to model other 'perceptual inference' phenomena

Phase control of electromagnetically induced transparency and its applications to tunable group velocity and atom localization

We show that, by simple modifications of the usual three-level $\Lambda$-type scheme used for obtaining electromagnetically induced transparency (EIT), phase dependence in the response of the atomic medium to a weak probe field can be introduced. This gives rise to phase dependent susceptibility. By properly controlling phase and amplitudes of the drive fields we obtain variety of interesting effects. On one hand we obtain phase control of the group velocity of a probe field passing through medium to the extent that continuous tuning of the group velocity from subluminal to superluminal and back is possible. While on the other hand, by choosing one of the drive fields to be a standing wave field inside a cavity, we obtain sub-wavelength localization of moving atoms passing through the cavity field.Comment: To Appear in SPIE Proceedings Volume 573

Automatic detection of coronaries ostia in computed tomography angiography volume data

Background: Heart coronaries emerge from the ascending aorta lateral sides from two points called the coronaries ostia. To automatically segment the heart coronaries; there must be a starting point (seed) for the segmentation. In this paper we present a fully automatic approach to segment the coronaries ostia towards automatic seeding for heart coronaries segmentation.Methods: Our algorithm takes as an input a CTA volume of segmented aorta cross sections that represents our region of interest. Then the ostia detection algorithm traverses that volume looking for the ostia points in an automatic fashion. The proposed algorithm depends on the anatomical features of the ostia. The main anatomic feature of the ostia is that it appears like a curvature or corner on the segmented ascending aorta cross section. Therefore we adopted in our methodology a modified version of Harris Corner Detection; besides inducing some anatomical features of the ostia location with respect to the aortic valve.Results: The proposed algorithm is tested and validated on the computed tomography angiography database provided by the Rotterdam coronary artery algorithm evaluation framework. The proposed automatic ostia detection algorithm succeeded to detect both ostia points in all the test cases. Also, the detected ostia points’ coordinates are validated versus a ground truth provided by the same framework with deviation between the results of the detection process and the ground truth having a min of 0 pixels and a max of 10 pixels for all test cases.Conclusions: Thus the proposed algorithm gives accurate results in comparison with the ground truth, which proves the efficiency of the proposed algorithm and its applicability to be extended as a seed for heart coronaries segmentation