Hemodynamic force assessment by cardiovascular magnetic resonance in HFpEF: A case-control substudy from the HFpEF stress trial.

BACKGROUND: The diagnosis of heart failure with preserved ejection fraction (HFpEF) remains challenging. Exercise-stress testing is recommended in case of uncertainty; however, this approach is time-consuming and costly. Since preserved EF does not represent normal systolic function, we hypothesized comprehensive cardiovascular magnetic resonance (CMR) assessment of cardiac hemodynamic forces (HDF) may identify functional abnormalities in HFpEF. METHODS: The HFpEF Stress Trial (DZHK-17; Clinicaltrials.gov: NCT03260621) prospectively recruited 75 patients with exertional dyspnea, preserved EF (≥50%) and signs of diastolic dysfunction (E/e' ≥8) on echocardiography. Patients underwent rest and exercise-stress right heart catheterisation, echocardiography and CMR. The final study cohort consisted of 68 patients (HFpEF n = 34 and non-cardiac dyspnea n = 34 according to pulmonary capillary wedge pressure (PCWP)). HDF assessment included left ventricular (LV) longitudinal, systolic peak and impulse, systolic/diastolic transition, E-wave deceleration as well as A-wave acceleration forces. Follow-up after 24 months evaluated cardiovascular mortality and hospitalisation (CVH) - only two patients were lost to follow-up. FINDINGS: HDF assessment revealed impairment of LV longitudinal function in patients with HFpEF compared to non-cardiac dyspnoea (15.8% vs. 18.3%, p = 0.035), attributable to impairment of systolic peak (38.6% vs 51.6%, p = 0.003) and impulse (20.8% vs. 24.5%, p = 0.009) forces as well as late diastolic filling (-3.8% vs -5.4%, p = 0.029). Early diastolic filling was impaired in HFpEF patients identified at rest compared with patients identified during stress only (7.7% vs. 9.9%, p = 0.004). Impaired systolic peak was associated with CVH (HR 0.95, p = 0.016), and was superior to LV global longitudinal strain assessment in prediction of CVH (AUC 0.76 vs. 0.61, p = 0.048). INTERPRETATION: Assessment of HDF indicates impairment of LV systolic ejection force in HFpEF which is associated with cardiovascular events. FUNDING: German Centre for Cardiovascular Research (DZHK).

Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis.

As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel artificial neural network model with a 3-3-1 tangent sigmoid architecture to predict biomasses' higher heating values from only their proximate analyses, requiring minimal specificity as compared to models based on elemental composition. The model presented has a considerably higher correlation coefficient (0.963) and lower root mean square (0.375), mean absolute (0.328), and mean bias errors (0.010) than other models presented in the literature which, at least when applied to the present data set, tend to under-predict the combustion enthalpy.

Application of artificial neural networks to co-combustion of hazelnut husk-lignite coal blends.

The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000°C at different heating rates in air to study co-combustion of hazelnut husk (HH)-lignite coal (LC) blends of various composition. The heating rate, blend ratio and temperature were used in the ANN analysis to predict the TG curves of the blends as parameters that affect the thermal behavior during combustion. The ANN model provides a good prediction of the TG curves for co-combustion with a coefficient of determination for the developed model of 0.9995. The agreement between the experimental data and the predicted values substantiated the accuracy of the ANN calculation.

Potentiometric monitoring of cobalt in beer sample by solid contact ion selective electrode.

A new solid contact cobalt selective electrode was constructed with 4-tert-butylthiacalix[4]arene as ionophore. The best performance was observed with the membrane having an ionophore/polyvinyl chloride/sodium tetraphenylborate/nitrophenyl octyl ether ratio of 3.5:33:1.5:62 (w/w; mg). The electrode, under steady-state conditions, exhibited a working concentration range of 1 × 10-1 - 1 × 10-6 mol/L with a near-Nernstian slope of 25.3 mV/decade and a detection limit of 3.5 × 10-7 mol/L. The electrode had a very short response time (<10 seconds) and good reproducibility at a working pH range of 4.0-6.5. The electrode was used for 4 months without any significant change in its sensitivity. The potentiometric performance of the electrode in partially nonaqueous medium [up to 20 % (v/v) alcohol] was found satisfactory. The performance of the prepared electrode for the analysis of beer samples using direct potentiometric method is very encouraging.