Sumários
Did not take place - 115.º aniversário da FCUL
22 Abril 2026, 13:30 • Rafael Neto Henriques
Class did not take place due to commemorative section of 115th anniversary of the faculty of science
Structural Models – Non-Linear Compartmental Models (Part 2) and Time-Varying Models
22 Abril 2026, 11:00 • Rafael Neto Henriques
Building upon the previous session's framework, the first half of this class focused on analyzing specific clinical applications of Non-Linear Compartmental Models. Students explored Bergman’s non-linear minimal model for the glucose-insulin system, alongside a non-linear compartmental model for thyroid regulation. The second half of the class transitioned into a new category of structural representation: Time-Varying Models. To illustrate systems where physiological parameters inherently change over time, the session concluded with an in-depth examination of a cardiovascular model, specifically focusing on the time-varying elastances of the heart ventricles and the aorta.
Structural Models – Non-Linear Compartmental Models (Part 1)
22 Abril 2026, 10:00 • Rafael Neto Henriques
Continuing the exploration of non-linear structural models, this theoretical class introduced the fundamentals of Compartmental Models. The session began by formally defining the concept of a "compartment" and outlining the general architecture of compartmental modeling. Students learned how to design system diagrams that accurately represent physiological control effects, which frequently give rise to non-linear differential equations. To solidify these concepts, the class applied these diagramming techniques to create an alternative, more generalized representation of the Bolie model for the glucose-insulin system, illustrating how control interactions between variables can be conceptually mapped.
Advanced Numerical Methods – Runge-Kutta Implementation
22 Abril 2026, 08:30 • Rafael Neto Henriques
This session advanced the students' computational skills by introducing higher-order Runge-Kutta numerical methods for solving ordinary differential equations in their projects. The class began with a theoretical overview of the Runge-Kutta approach, explaining how it achieves greater accuracy and stability compared to the foundational Euler method. Instructors then demonstrated the application of these methods across various physiological modeling scenarios. Students learned how to implement these algorithms from scratch using custom-developed code, as well as how to leverage optimized, built-in ODE solvers available in MATLAB and Python packages to efficiently simulate their compartmental models.