10,019 research outputs found
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 -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
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