scholarly journals A mass transport model with a simple non-factorized steady-state distribution

2017 ◽  
Vol 2017 (6) ◽  
pp. 063201 ◽  
Author(s):  
Jules Guioth ◽  
Eric Bertin
Keyword(s):  
Steady State ◽  
Mass Transport ◽  
Transport Model ◽  
Steady State Distribution ◽  
State Distribution ◽  
Mass Transport Model

FRACTAL LIMIT DISTRIBUTIONS IN RANDOM TRANSPORTS

Fractals ◽  
1996 ◽  
Vol 04 (03) ◽  
pp. 257-264 ◽  
Author(s):  
HIDEKI TAKAYASU ◽  
TAKUO KAWAKAMI ◽  
Y. -H. TAGUCHI ◽  
TOMOO KATSUYAMA
Keyword(s):  
Steady State ◽  
Transport Model ◽  
Mean Value ◽  
Symmetric Case ◽  
Continuous Change ◽  
Steady State Distribution ◽  
State Distribution ◽  
Fluid Turbulence ◽  
Scalar Quantity ◽  
The Mean

We analyze a random transport model of a scalar quantity on a discrete space-time. By changing a parameter which is a portion of the quantity transported at a time, we observe a continuous change of steady-state distribution of fluctuations from Gaussian to a power-law when the mean value of the scalar quantity is not zero. In the symmetric case with zero mean, the steady-state converges either to a trivial no fluctuation state or to a Lorentzian fluctuation state with diverging variance independent of the parameter. We discuss a possible origin of the intermittent behaviors of fully-developed fluid turbulence as an application.

Kinetic analysis of mechanism of intestinal Na+-dependent sugar transport

1985 ◽  
Vol 248 (5) ◽  
pp. C498-C509 ◽  
Author(s):  
D. Restrepo ◽  
G. A. Kimmich
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Sugar Transport ◽  
Enzyme Kinetic ◽  
Steady State Distribution ◽  
State Distribution ◽  
Least Squares Fit ◽  
Coupling Stoichiometry ◽  
Rate Limiting ◽  
Kinetics Of

Zero-trans kinetics of Na+-sugar cotransport were investigated. Sugar influx was measured at various sodium and sugar concentrations in K+-loaded cells treated with rotenone and valinomycin. Sugar influx follows Michaelis-Menten kinetics as a function of sugar concentration but not as a function of Na+ concentration. Nine models with 1:1 or 2:1 sodium:sugar stoichiometry were considered. The flux equations for these models were solved assuming steady-state distribution of carrier forms and that translocation across the membrane is rate limiting. Classical enzyme kinetic methods and a least-squares fit of flux equations to the experimental data were used to assess the fit of the different models. Four models can be discarded on this basis. Of the remaining models, we discard two on the basis of the trans sodium dependence and the coupling stoichiometry [G. A. Kimmich and J. Randles, Am. J. Physiol. 247 (Cell Physiol. 16): C74-C82, 1984]. The remaining models are terter ordered mechanisms with sodium debinding first at the trans side. If transfer across the membrane is rate limiting, the binding order can be determined to be sodium:sugar:sodium.

PROCESSOR SHARING G-QUEUES WITH INERT CUSTOMERS AND CATASTROPHES: A MODEL FOR SERVER AGING AND REJUVENATION

2017 ◽  
Vol 31 (4) ◽  
pp. 420-435 ◽  
Author(s):  
J.-M. Fourneau ◽  
Y. Ait El Majhoub
Keyword(s):  
Steady State ◽  
Product Form ◽  
Processor Sharing ◽  
Service Capacity ◽  
Steady State Distribution ◽  
State Distribution ◽  
Signal Arrival ◽  
Open Networks ◽  
Networks Of Queues

We consider open networks of queues with Processor-Sharing discipline and signals. The signals deletes all the customers present in the queues and vanish instantaneously. The customers may be usual customers or inert customers. Inert customers do not receive service but the servers still try to share the service capacity between all the customers (inert or usual). Thus a part of the service capacity is wasted. We prove that such a model has a product-form steady-state distribution when the signal arrival rates are positive.

Morphology-dependent mass transport model for mechanoelectrochemistry of polypyrrole

2018 ◽  
Vol 28 (1) ◽  
pp. 015001 ◽  
Author(s):  
Vijay Venkatesh ◽  
Noriko Katsube ◽  
Vishnu Baba Sundaresan
Keyword(s):  
Mass Transport ◽  
Transport Model ◽  
Mass Transport Model ◽  
Dependent Mass
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