Phase Transformation and Performance of Mg-Based Hydrogen Storage Material by Adding ZnO Nanoparticles.

ZnO nanoparticles in a spherical-like structure were synthesized via filtration and calcination methods, and different amounts of ZnO nanoparticles were added to MgH2 via ball milling. The SEM images revealed that the size of the composites was about 2 µm. The composites of different states were composed of large particles with small particles covering them. After the absorption and desorption cycle, the phase of composites changed. The MgH2-2.5 wt% ZnO composite reveals excellent performance among the three samples. The results show that the MgH2-2.5 wt% ZnO sample can swiftly absorb 3.77 wt% H2 in 20 min at 523 K and even at 473 K for 1 h can absorb 1.91 wt% H2. Meanwhile, the sample of MgH2-2.5 wt% ZnO can release 5.05 wt% H2 at 573 K within 30 min. Furthermore, the activation energies (Ea) of hydrogen absorption and desorption of the MgH2-2.5 wt% ZnO composite are 72.00 and 107.58 KJ/mol H2, respectively. This work reveals that the phase changes and the catalytic action of MgH2 in the cycle after the addition of ZnO, and the facile synthesis of the ZnO can provide direction for the better synthesis of catalyst materials.

Lumped-Parameter Circuit Platform for Simulating Typical Cases of Pulmonary Hypertensions from Point of Hemodynamics.

Pulmonary hypertension (PH) presents unusual hemodynamic states characterized by abnormal high blood pressure in pulmonary artery. The objective of this study is to simulate how the hemodynamics develops in typical PH cases without treatment. A lumped-parameter circuit platform of human circulation system is set up to simulate hemodynamic abnormalities of PH in different etiologies and pathogenesis. Four typical cases are considered, which are distal pulmonary artery stenosis, left ventricular diastolic dysfunction, ventricular septal defect, and mitral stenosis. The authors propose regulation laws for chambers and vessels to adapt the abnormal hemodynamic conditions for each PH case. The occurrence and development of each PH case are simulated over time using the lumped-parameter circuit platform. The blood pressure, blood flow, pressure-volume relations for chambers and vessels are numerically calculated for each case of PH progression. The model results could be a quite helpful to understand the hemodynamic mechanism of typical PHs. Graphical Abstract.

PCG Classification Using Multidomain Features and SVM Classifier.

This paper proposes a method using multidomain features and support vector machine (SVM) for classifying normal and abnormal heart sound recordings. The database was provided by the PhysioNet/CinC Challenge 2016. A total of 515 features are extracted from nine feature domains, i.e., time interval, frequency spectrum of states, state amplitude, energy, frequency spectrum of records, cepstrum, cyclostationarity, high-order statistics, and entropy. Correlation analysis is conducted to quantify the feature discrimination abilities, and the results show that "frequency spectrum of state", "energy", and "entropy" are top domains to contribute effective features. A SVM with radial basis kernel function was trained for signal quality estimation and classification. The SVM classifier is independently trained and tested by many groups of top features. It shows the average of sensitivity, specificity, and overall score are high up to 0.88, 0.87, and 0.88, respectively, when top 400 features are used. This score is competitive to the best previous scores. The classifier has very good performance with even small number of top features for training and it has stable output regardless of randomly selected features for training. These simulations demonstrate that the proposed features and SVM classifier are jointly powerful for classifying heart sound recordings.