Pyrolysis of tea and coffee wastes: effect of physicochemical properties on kinetic and thermodynamic characteristics.

Unlabelled: Physicochemical properties, kinetic pyrolysis and thermodynamic study of spent green tea, pure spent coffee grounds, spent coffee grounds blended with 50% torrefied barley and coffee husk were experimentally investigated using thermogravimetric analysis under an inert atmosphere to evaluate their thermochemical application. Five isoconversional methods were applied to determine effective activation energy ( ) of the pyrolysis processes. All methods showed good agreement by determining fluctuating values (150-500 kJ mol).

Mid-term subclinical myocardial injury detection in patients who recovered from COVID-19 according to pulmonary lesion severity.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) may cause damage to the cardiovascular system during the acute phase of the infection. However, recent studies reported mid- to long-term subtle cardiac injuries after recovering from acute coronavirus disease 2019 (COVID-19). This study aimed to determine the relationship between the severity of chest computed tomography (CT) lesions and the persistence of subtle myocardial injuries at mid-term follow-up of patients who recovered from COVID-19 infection.

Automated method for real-time AMD screening of fundus images dedicated for mobile devices.

Aged macular degeneration (AMD) leads to a progressive decline in visual acuity until reaching blindness. It is considered as an irreversible pathology where an early diagnosis remains crucial. However, the lack of ophthalmologists, the permanent increase in elderly people, and their limited mobility involves a delay in AMD diagnosis.

Fast and efficient retinal blood vessel segmentation method based on deep learning network.

The segmentation of the retinal vascular tree presents a major step for detecting ocular pathologies. The clinical context expects higher segmentation performance with a reduced processing time. For higher accurate segmentation, several automated methods have been based on Deep Learning (DL) networks.

A Spatiotemporal exploration and 3D modeling of blood flow in healthy carotid artery bifurcation from two modalities: Ultrasound-Doppler and phase contrast MRI.

In the present study, we investigated the velocity profile over the carotid bifurcation in ten healthy volunteers by combining velocity measurements from two imaging modalities (PC-MRI and US-Doppler) and hemodynamic modeling in order to determine the optimal combination for the most realistic velocity estimation. The workflow includes data acquisition, velocity profile extraction at three sites (CCA, ECA and ICA), the arterial geometrical model reconstruction, a mesh generation and a rheological modeling. The results showed that US-Doppler measurements yielded higher velocity values as compared to PC-MRI (about 26% shift in CCA, 52% in ECA and 53% in ICA).

Real time QRS complex detection using DFA and regular grammar.

Background: The sequence of Q, R, and S peaks (QRS) complex detection is a crucial procedure in electrocardiogram (ECG) processing and analysis. We propose a novel approach for QRS complex detection based on the deterministic finite automata with the addition of some constraints. This paper confirms that regular grammar is useful for extracting QRS complexes and interpreting normalized ECG signals.