Sokratis Anagnostopoulos

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Offshore wind farm modelling has been an area of rapidly increasing interest over the last two decades, with numerous analytical as well as computational-based approaches developed, in an attempt to produce designs that improve wind farm efficiency in powe ...

Tracheomalacia (TM) is a condition characterized by a weak tracheal cartilage and/or muscle, resulting in excessive collapse of the airway in the newborns. Current treatments including tracheal reconstruction, tracheoplasty, endo- and extra-luminal stents ...

Wind farm modelling is an area of rapidly increasing interest with numerous analytical and computational-based approaches developed to extend the margins of wind farm efficiency and maximise power production. In this work, we present the novel ML framework ...

Aortic diastolic pressure decay (DPD) has been shown to have considerable pathophysiological relevance in the assessment of vascular health, as it is significantly affected by arterial stiffening. Nonetheless, the aortic pressure waveform is rarely availab ...

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

Sokratis Anagnostopoulos

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Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation

Wet adhesive hydrogels to correct malacic trachea (tracheomalacia) A proof of concept

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

On the similarity between aortic and carotid pressure diastolic decay: a mathematical modelling study

Novel theory and potential applications of central diastolic pressure decay time constant

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population