Understanding some biological phenomena from control and mathematical biology standpoints: analysis aspects of cell population dynamics and optimisation of stains selection in photobioreactors.
In the first part of this talk, we introduce some interesting biological mechanisms, like hematopoiesis, which is the process of blood cell formation and continuous replenishment of all hematopoietic cells. Our main objective is to show how can mathematical modeling and analysis tools be used in order to better understand some biological phenomena, including cancer. For that purpose, we revisit some models of the cell cycle and cell proliferation in living organisms. Next, we investigate some basic properties of the resulting models, including stability and stabilization features. In the second phase, we introduce an optimal control problem associated to a model of microalgae growth. Then, we illustrate the efficiency of optimization tools in order to control the biological system and select some microalgae stains according to some useful biological/ecological criteria.
Keltoum Chahour (ACUMES)
Title Blood flow simulation in stenosed coronary arteries: Fractional flow reserve computation.
Blood flow simulation can provide an efficient tool to clinicians in the phase of diagnosis. Accurate characterization of the blood flow and pressure into the arteries helps to identify ischemia caused by stenosis, or to quantify the severity of a lesion through the fractional flow reserve (FFR) measure. In this view, we introduce the FFR and give a preliminary 2D results of the flow based on a Non-Newtonian model, carried with simplified geometries in a first approach. Next, we consider a patient-specific stenotic left coronary artery, extracted from a 2D angiography. In this case, adapted boundary conditions were prescribed. The values of the coronary pressure are used to estimate the fractional flow reserve (FFR) distal to the lesion.
The secrets of the Moon rocks, a basic idea of remanent magnetization and how to approximate it with rational analysis
Ferromagnetic materials (like iron) have ''memory''! This is in the form of natural remanent magnetization. Paleomagnetic studies, take advantage of that ''memory'' and try to understand the evolution of the magnetic field in our planet and other planets / planetary objects. In our case Moon rocks have ''memory'' of an ancient global magnetic field that no longer exist. In the talk we will see how we can use rational approximation techniques to recover that ''memory'' and why this is important!
Patryk Filipiak (ATHENA)
Title Proactive Evolutionary Algorithms for Dynamic Optimization Problems
Dynamic optimization problems are problems that change as time goes by, e.g. high-frequency financial portfolio optimization or robotic arm movement planning. They are often addressed with reactive evolutionary algorithms that continuously explore a search space looking for new optima and trace the ones that were found so far. Algorithms equipped with such a mechanism are always one step back with a dynamic environment, since they can only detect the changes that already happened. The proposed proactive paradigm alleviates that issue by exploiting a dedicated forecasting model that anticipates a future landscape based on past observations. As a result, algorithms that apply this scheme can get ready for the changes to come, e.g. by directing some individuals into future promising regions.