62 research outputs found
Parameters estimation of a model for baroreflex control of unstressed volume
No full textThe baroreflex involves a number of control pathways. In this chapter we consider in greater detail the role of the control of unstressed volume mobilization. We also consider an alternative approach for choosing parameters most likely to be estimable and we apply this method to a model incorporating the control of unstressed volume and compare to data
V-Proximal Trustworthy Banach Spaces
No full textIn a recent work (2016), the first author proved the fuzzy sum rule for the V-proximal subdifferential under some natural assumptions on an equivalent norm of the Banach spaces. In the present paper, we are going to prove that the class of Banach spaces satisfying the fuzzy sum rule is very large and contains all Lp spaces 1<p<∞ as well as the sequence spaces lp1<p<∞, the Sobolev spaces Wp,n1<p<∞, and the Schatten trace ideals Cp1<p<∞
Development of patient specific cardiovascular models predicting dynamics in response to orthostatic stress challenges
No full textPhysiological realistic models of the controlled cardiovascular systemare constructed and validated against clinical data. Special attention is paidto the control of blood pressure, cerebral blood flow velocity, and heartrate during postural challenges, including sit-to-stand and head-up tilt. Thisstudy describes development of patient specific models, and how sensitivityanalysis and nonlinear optimization methods can be used to predict patientspecific characteristics when analyzed using experimental data. Finally, wediscuss how a given model can be used to understand physiological changesbetween groups of individuals and how to use modeling to identify biomarker
Introduction to stochastic models in biology
No full textThis chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exposed to influences that are not completely understood or not feasible to model explicitly. Ignoring these phenomena in the modeling may affect the analysis of the studied biological systems. Therefore there is an increasing need to extend the deterministic models to models that embrace more complex variations in the dynamics. A way of modeling these elements is by including stochastic influences or noise. A natural extension of a deterministic differential equations model is a system of stochastic differential equations (SDEs), where relevant parameters are modeled as suitable stochastic processes, or stochastic processes are added to the driving system equations. This approach assumes that the dynamics are partly driven by noise
Nonlinear Fredholm equations in modular function spaces
No full textWe investigate the existence of solutions in modular function spaces of the Fredholm integral equation
Φ(θ) = g(θ) + ∫10 ƒ(θ, σ, Φ(σ)) dσ,
where Φ(θ), g(θ) ∈ Lρ, θ ∈ [0, 1], ƒ : [0, 1] x [0, 1] x Lρ → ℝ. An application in the variable exponent Lebesgue spaces is derived under minimal assumptions on the problem data.Mathematic
Contribution à l'étude des équations différentielles à retard avec impulsions: approche par la théoriedes semigroupes intégrés
No full textNonlinear Fredholm equations in modular function spaces
No full textWe investigate the existence of solutions in modular function spaces
of the Fredholm integral equation
where .
An application in the variable exponent Lebesgue spaces is
derived under minimal assumptions on the problem data
The Variation of Constants Formula in Lebesgue Spaces with Variable Exponents
No full textThis study looks closely into the analysis of the variation of constants formula given by Φ(t)=S(t)Φ(0)+∫0tS(t−σ)F(σ,Φ(σ))dσ, for t∈[0,T],T>0, within the context of modular function spaces Lρ. Additionally, this research explores practical applications of the variation of constants formula in variable exponent Lebesgue spaces Lp(·). Specifically, the study examines these spaces under certain conditions applied to the exponent function p(·) and the functions F as well as the semigroup S(t), utilizing the symmetry properties of the algebraic semigroup. This investigation sheds light on the intricate interplay between parameters and functions within these mathematical frameworks, offering valuable insights into their behavior and properties in Lp(·)
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