Appropriate passage distribution makes it possible to improve the operation condition for highly loaded thermal components.
Each section for each subspecies is broken down into passages on distribution, biology, evolution, classification and conservation.
The first-passage probability distribution is used to represent the probability distribution of the peak responses.
The passage time distribution must be, with high confidence, shorter than the timescales of mucus clearance to maximize drug uptake.
Each structural element is characterized by the passage time distribution function calculated with taking into account the correlations of flows passing through the neighboring pores.
To make the general expressions more concrete it is necessary to introduce a model of structural elements (pores) which determines the passage time distribution.
In [3, 4], certain explicit moment relations derived from the Laplace transform of the first-passage time distribution are applied, but these are only valid under stimulation (supra-threshold regime).
First we describe an idealized scenario — a homogeneous viscous fluid of uniform depth with a particle undergoing passive normal diffusion — where the theory of Brownian motion affords the ability to rigorously specify particle size distributions to meet a prescribed, one-sided, diffusive passage time distribution.
The simplicity of such models is also appealing from a theoretical perspective, and for a threshold described by an Ornstein Uhlenbeck process it has recently been shown that analytical (and non-perturbative) expressions for the first-passage time distribution can be obtained [20].
If we use a first order Taylor approximation, the first passage time distribution (h(t)) is then given by h(t)=-frac{partial S t)}{partial t}, (18) and the relation between the cumulative distribution (S t)) and the FPTD (between two arbitrary times (t_{1}) and (t_{2})) is [35, 36] S(t_{1} -S(t_{2})= int_{t_{1} -St_{2}}hbigl(t^{prime} bigr),dt^{prime}.
