A stochastic model for cell probability in SMF
Stochastic model for tumor control probability: effects of cell cycle and (a)symmetric proliferation
... induce cell quiescence. Thus, an extension of our model is to include a transition from survived active cells to a quiescent state, as a function of radia- tion ...two-compartment model to take into ...
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A stochastic model for the probability of malaria extinction by mass drug administration
... a stochastic model, as in the real world, the infectious reservoir may reach zero as a result of chance ...of stochastic fluctuations to achieve elimination is of the order 1000, given ideal ...
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Ruin Probability for Non-standard Poisson Risk Model with Stochastic Returns
... Ruin Probability for Non-standard Poisson Risk Model with Stochastic Returns Tao Jiang ∗ Abstract —This paper investigates the finite time ruin probability in non-homogeneous Poisson risk ...
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Stochastic integral equations without probability
... to model turbulence in physics, stock price changes in mathematical ®nance, traf®c in high- speed networks, failure-generating mechanisms in reliability theory as well as various phenomena running under the ...
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7. Concepts in Probability, Statistics and Stochastic Modelling
... One method for generating multi-season flow sequences is to convert the time series of seasonal flows Q ty into a homogeneous sequence of normally distributed zero-mean unit-variance random variables Z ty . These can ...
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A stochastic model dissects cell states in biological transition processes
... our model provides immediate and detailed guid- ance for the design of future single-cell ...the model yields mean transition times between states, our results suggest specific times at which to ...
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A stochastic transcriptional switch model for single cell imaging data
... Fig. 1. A diagrammatic representation of the transfer of information from DNA to protein through transcription and translation and its relation to the measurement process through a reporter gene construct. Specifically, ...
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Cancer Cell Growth Under Radiotherapy Using Stochastic Model
... Cancer Cell Growth Under Radiotherapy Using Stochastic Model P Pandiyan, S Koventhan Abstract :A malignant (Cancer) cell is once formed in the human body then it will grow as a tumor by a ...
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Large Scale Stochastic Sampling from the Probability Simplex
... j=1 ω j = 1. Many popular models contain simplex parameters. For example, latent Dirichlet allocation (LDA) is defined by a set of topic-specific distributions on words and document-specific distributions on topics. ...
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Stochastic Derivation of an Integral Equation for Probability Generating Functions
... transformed probability generating functions are generally recognized as powerful analytical tools for establishing characterizations of discrete probability ...part model by incorporating an ...
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A Stochastic Differential Equation for Modeling the Classical Probability Distributions
... can model probability distributions that have no known probability ...the probability density is known, however, the characteristics of that distribution are not ...estimating ...
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Exact Simulation Techniques in Applied Probability and Stochastic Optimization
... M/G/c model under a random assignment (RA) discipline as an upper bound, but it has infinite expected termination ...RA model. They accomplish this by first exactly simulating the RA model in ...
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Transcriptional regulation of lineage commitment - a stochastic model of cell fate decisions
... lymphoid cell reprogramming to an erythroid fate, making it a likely candidate driver of erythroid ...fitted model parameters for each of the three genes through simulated annealing, followed by grid search ...
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Survival Probability in Patients with Sickle Cell Anemia Using the Competitive Risk Statistical Model.
... 6 Cardeza Foundation, Department of Medicine, Jefferson Medical College, Thomas Jefferson University, Philadelphia, PA, USA. Competing interests: The authors have declared that no competing interests exist. Abstract. The ...
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Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows
... hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable ...different model parameter sets for continu- ous simulation of discharge in an ...
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Robust filtering for a class of nonlinear stochastic systems with probability constraints
... the stochastic matrix Θ k describes the working status of these ...output model in this paper is more general than those in existing literature where a Bernoulli distributed stochastic sequence is ...
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The effect of nanoparticle size on the probability to cross the blood-brain barrier: an in-vitro endothelial cell model
... the probability to cross the BBB was investigated using the ...bEnd.3 model is the first barrier between the blood and the brain and has a crit- ical influence on the probability to cross the ...
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Stochastic gradient methods for stochastic model predictive control
... E k g k+1 = ∇f (x k ) (19) Instead of selecting the component function with equal prob- ability we then bias the sampling according to the distribution P[j k = ν] = p ν so to ensure (19). As a byproduct, the more ...
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Stochastic modeling of oligodendrocyte generation in cell culture: model validation with time-lapse data
... mathematical model as realistic as pos- sible, subject to certain constraints on its tractability and ...given model most typically emerge when it is in conflict with experi- mental data, the quest for ...
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Probability and Stochastic Processes: A Friendly Introduction
... success probability bability is is pq pq and and T T is is th thee nu numb mber er of of mi minu nute tess up up to to an and d in incl clud udin ing g th thee fir first st su succ cces ...
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