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It was far from the most random transition of the night, though probably the funniest.
Simultaneously, we present an alternative, reduced parameter CTRW formulation for general advective transport in heterogeneous porous media, which models early- and late-time transport by use of random transition times between sparse, imaginary planes normal to flow.
As the simulation results presented, two types of asymmetric flow physics incur strong side-loads: random transition between FSS and partial quasi-RSS due to fish tailing effect of the supersonic jet, axial flow oscillation across the nozzle lip due to relative movement between supersonic jet and front edge of the lower stage.
Then is called the random transition probability of a -indexed second-order nonhomogeneous Markov chain.
Then is called the random transition probability of a -indexed nonhomogeneous Markov chain.
As corollary, we obtain the property of the harmonic mean of random transition probability for a nonhomogeneous Markov chain.
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In turn, random transitions predominated between 1985 and 1999, probably in response to economic factors that acted suddenly on the landscape during the 80's, such as the woodchip export and aquaculture booms.
These local random transitions drive the network to a steady state which is the Gibbs distribution associated with the global energy and temperature T, that is to a state with the following distribution (in steady state): π T ( s ) = c · e − E ( s ) / T, with c a normalizing constant.
These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network.
Random transitions on the model lead to the generation of the net flux.
There are multiple cyclic paths on the model, and random transitions complete the cycles.
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