14,964 research outputs found
Segregation in a fluidized binary granular mixture: Competition between buoyancy and geometric forces
Starting from the hydrodynamic equations of binary granular mixtures, we
derive an evolution equation for the relative velocity of the intruders, which
is shown to be coupled to the inertia of the smaller particles. The onset of
Brazil-nut segregation is explained as a competition between the buoyancy and
geometric forces: the Archimedean buoyancy force, a buoyancy force due to the
difference between the energies of two granular species, and two geometric
forces, one compressive and the other-one tensile in nature, due to the
size-difference. We show that inelastic dissipation strongly affects the phase
diagram of the Brazil nut phenomenon and our model is able to explain the
experimental results of Breu et al. (PRL, 2003, vol. 90, p. 01402).Comment: 5 pages, 2 figure
Critical neural networks with short and long term plasticity
In recent years self organised critical neuronal models have provided
insights regarding the origin of the experimentally observed avalanching
behaviour of neuronal systems. It has been shown that dynamical synapses, as a
form of short-term plasticity, can cause critical neuronal dynamics. Whereas
long-term plasticity, such as hebbian or activity dependent plasticity, have a
crucial role in shaping the network structure and endowing neural systems with
learning abilities. In this work we provide a model which combines both
plasticity mechanisms, acting on two different time-scales. The measured
avalanche statistics are compatible with experimental results for both the
avalanche size and duration distribution with biologically observed percentages
of inhibitory neurons. The time-series of neuronal activity exhibits temporal
bursts leading to 1/f decay in the power spectrum. The presence of long-term
plasticity gives the system the ability to learn binary rules such as XOR,
providing the foundation of future research on more complicated tasks such as
pattern recognition.Comment: 8 pages, 7 figure
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