A mathematical model for preventing HIV virus from proliferating inside CD4 T brownian cell using Gaussian jump nanorobot

2019 ◽  
Vol 12 (07) ◽  
pp. 1950076 ◽  
Author(s):  
Mohamed Abd Allah El-Hadidy ◽  
Alaa A. Alzulaibani

We present a statistical distribution of a nanorobot motion inside the blood. This distribution is like the distribution of A and B particles in continuous time random walk scheme inside the fluid reactive anomalous transport with stochastic waiting time depending on the Gaussian distribution and a Gaussian jump length which is detailed in Zhang and Li [J. Stat. Phys., Published Online with https://doi.org/10.1007/s10955-018-2185-8 , 2018]. Rather than estimating the length parameter of the jumping distance of the nanorobot, we normalize the Probability Density Function (PDF) and present some reliability properties for this distribution. In addition, we discuss the truncated version of this distribution and its statistical properties, and estimate its length parameter. We use the estimated distance to study the conditions that give a finite expected value of the first meeting time between this nanorobot in the case of nonlinear flow with independent [Formula: see text]-dimensional Gaussian jumps and an independent [Formula: see text]-dimensional CD4 T Brownian cell in the blood ([Formula: see text]-space) to prevent the HIV virus from proliferating within this cell.

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Long Shi ◽  
Zuguo Yu ◽  
Zhi Mao ◽  
Aiguo Xiao

In continuum one-dimensional space, a coupled directed continuous time random walk model is proposed, where the random walker jumps toward one direction and the waiting time between jumps affects the subsequent jump. In the proposed model, the Laplace-Laplace transform of the probability density functionP(x,t)of finding the walker at positionxat timetis completely determined by the Laplace transform of the probability density functionφ(t)of the waiting time. In terms of the probability density function of the waiting time in the Laplace domain, the limit distribution of the random process and the corresponding evolving equations are derived.


2012 ◽  
Vol 26 (23) ◽  
pp. 1250151 ◽  
Author(s):  
KWOK SAU FA

In this paper, we model the tick-by-tick dynamics of markets by using the continuous-time random walk (CTRW) model. We employ a sum of products of power law and stretched exponential functions for the waiting time probability distribution function; this function can fit well the waiting time distribution for BUND futures traded at LIFFE in 1997.


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