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

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 (E a) of the pyrolysis processes. All methods showed good agreement by determining fluctuating E a values (150-500 kJ mol-1). Complex E a profiles with conversion were divided into four stages corresponding to thermal degradation of main biomass constituents (extractives, hemicellulose, cellulose and lignin), indicating that extractives decomposition was the least demanding reaction while lignin decomposition was the most demanding. The kinetic process was verified by reconstruction according to the Friedman parameters. The thermodynamic parameters were evaluated to determine the energy demand and efficiency throughout the process. The values obtained for physicochemical properties such as volatile matter (> 68%) and higher heating value (> 17 MJ kg-1), average E a (223-319 kJ mol-1) and significant energy efficiency implied that these types of biomass waste have significant reactivity and consequently the highest potential for the production of bioenergy and a range of high-value chemicals and materials. Supplementary Information: The online version contains supplementary material available at 10.1007/s10973-022-11878-4.

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. Methods: All patients with COVID-19 were enrolled prospectively in this study. Sensitive troponin T (hsTnT) and chest CT scans were performed on all patients during the acute phase of COVID-19 infection. At the mid-term follow-up, conventional transthoracic echocardiograph and global longitudinal strain (GLS) of the left and right ventricles (LV and RV) were determined and compared between patients with chest CT scan lesions of < 50% (Group 1) and those with severe chest CT scan lesions of greater or equal to 50% (Group 2). Results: The mean age was 55 ± 14 years. Both LV GLS and RV GLS values were significantly decreased in group 2 (p = 0.013 and p = 0.011, respectively). LV GLS value of more than -18 was noted in 43% of all the patients, and an RV GLS value of more than -20 was observed in 48% of them. The group with severe chest CT scan lesions included more patients with reduced LV GLS and reduced RV GLS than the group with mild chest CT scan lesions [(G1:29 vs. G2:57%, p = 0.002) and (G1:36 vs. G2:60 %, p = 0.009), respectively]. Conclusion: Patients with severe chest CT scan lesions are more likely to develop subclinical myocardial damage. Transthoracic echocardiography (TTE) could be recommended in patients recovering from COVID-19 to detect subtle LV and RV lesions.

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). This implies higher simulated velocities based on US-Doppler inlet as compared to simulated velocities based on PC-MRI inlet. Overall, PC-MRI inlet based simulations are closer to measurements than US-Doppler inlet based simulations. Moreover, the measured velocities showed that blood flow keeps a parabolic sectional profile distal from CCA, ECA and ICA, while being quite disturbed in the carotid sinus with a significant decrease in magnitude making this site very prone to atherosclerosis.

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. A QRS is assimilated to a pair of adjacent peaks which meet certain criteria of standard deviation and duration. RESULTS: The proposed method was applied on several kinds of ECG signals issued from the standard MIT-BIH arrhythmia database. A total of 48 signals were used. For an input signal, several parameters were determined, such as QRS durations, RR distances, and the peaks' amplitudes. σRR and σQRS parameters were added to quantify the regularity of RR distances and QRS durations, respectively. The sensitivity rate of the suggested method was 99.74% and the specificity rate was 99.86%. Moreover, the sensitivity and the specificity rates variations according to the Signal-to-Noise Ratio were performed. CONCLUSIONS: Regular grammar with the addition of some constraints and deterministic automata proved functional for ECG signals diagnosis. Compared to statistical methods, the use of grammar provides satisfactory and competitive results and indices that are comparable to or even better than those cited in the literature.