Advancing school dropout early warning systems: the IAFREE relational model for identifying at-risk students.

Introduction: There is a global effort to address the school dropout phenomenon. The urgency to act on it comes from the harmful evidence that school dropout has on societal and individual levels. Early Warning Systems (EWS) for school dropout at-risk student identification have been developed to anticipate and help schools have a better chance of acting on it.

An Inverse Problem Approach for Parameter Estimation of Cardiovascular System Models.

Left ventricular assist devices (LVADs) are mechanical pumps that help patients with chronic heart failure waiting for a heart transplant. Mathematical models of these devices can be used along cardiovascular system (CVS) models to evaluate the assistance performance under different operating modes. The estimation of the CVS model parameters for a particular patient and numerical simulations allow the implementation of adequate LVAD operation mode.

Simulating cardiac disorders with a lumped parameter synergistic model.

A lumped parameter synergistic model of the human cardiovascular system (CVS) is proposed to integrate the heart's electrical activity with its mechanical activity. This model can represent the physiological condition of a patient in an effective way, whether it is considered normal or with some cardiac disorders. The electrical activity is coupled to the CVS model through electrocardiogram (ECG) signals in the suggested model.

A variable gain physiological controller for a rotary left ventricular assist device.

This paper deals with designing a physiological adaptive control law for a turbodynamic ventricular assist device (TVAD) using a lumped parameter time-varying model that describes the cardiovascular system. The TVAD is a rotary blood pump driven by an electrical motor. The system simulation also includes the adaptive feedback controller, which provides a physiologically correct cardiac output under different preload and afterload conditions.