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SUMMARY:Three examples of the link between form\, function and evolution i
 n living systems
DTSTART:20191126T100000
DTEND:20191126T113000
DTSTAMP:20260407T064524Z
UID:66b699f899d6c95fe4c94de2803dae1b7abb8a49ddaabe8f82c90d29
CATEGORIES:Conferences - Seminars
DESCRIPTION:Christophe Eloy\nDuring this talk\, I will discuss three unrel
 ated projects that share the same curiosity‐driven objective: can we und
 erstand\, through physical modeling\, how evolution shaped form and functi
 on in living organisms ?\n\nTrees shaped by the wind. Trees are self‐sim
 ilar branching structures\, hierarchically organized with longer and thick
 er branches near the roots. With a mechanically‐based numerical model\, 
 I will show how this self‐similarity emerge through natural selection. I
 n this model\, trees grow into fractal structures to\npromote efficient ph
 otosynthesis and branch diameters increase in response to wind‐induced l
 oads. Remarkably\, the virtual trees emerging from this model have self‐
 similar properties similar to real trees.\n\nForm and function in fish swi
 mming. Undulatory swimming is used by most aquatic animals. To achieve pro
 pulsion\, these animals propagate a bending wave along their backbone down
  to their caudal fins. What is the optimal design for such an undulatory s
 wimmer? To address this question\, I will use a mechanical model and a gen
 etic algorithm to calculate the minimal energetic costs\, the maximal swim
 ming velocity or any trade‐off between the two.\n\nTracking odor in turb
 ulence. Life is tough for copepods! These millimetric crustaceans have abo
 ut 1000 neurons at their disposal. Yet they are able to locate their mate 
 by tracking the pheromone trail that they leave. That is no small feat for
  animals usually living in a turbulent environment and constantly washed b
 y the flow. How are they able to do that? I will propose a way to reverse
 ‐engineer this problem with reinforcement learning tools.
LOCATION:BSP 231 https://plan.epfl.ch/?room==BSP%20231
STATUS:CONFIRMED
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