The structure and optical properties of polyethylene oxide (PEO) doped with tin titanate (SnTiO3) nano-filler were studied by X-ray diffraction (XRD) and UV-Vis spectroscopy as non-destructive techniques. PEO-based composed polymer electrolytes inserted with SnTiO3 nano-particles (NPs) were synthesized through the solution cast technique. The change from crystalline phase to amorphous phase of the host polymer was established by the lowering of the intensity and broadening of the crystalline peaks. The optical constants of PEO/SnTiO3 nano-composite (NC), such as, refractive index (n), optical absorption coefficient (α), dielectric loss (εi), as well as dielectric constant (εr) were determined for pure PEO and PEO/SnTiO3 NC. From these findings, the value of n of PEO altered from 2.13 to 2.47 upon the addition of 4 wt.% SnTiO3NPs. The value of εr also increased from 4.5 to 6.3, with addition of 4 wt.% SnTiO3. The fundamental optical absorption edge of the PEO shifted toward lower photon energy upon the addition of the SnTiO3 NPs, confirming a decrement in the optical band gap energy of PEO. The band gap shifted from 4.78 eV to 4.612 eV for PEO-doped with 4 wt.% SnTiO3. The nature of electronic transitions in the pure and the composite material were studied on the basis of Tauc's model, while optical εi examination was also carried out to calculate the optical band gap.
Atrial flutter (AFL) is a common arrhythmia with two significant mechanisms, namely, focal (FAFL) and macroreentry (MAFL). Discrimination of the AFL mechanism through noninvasive techniques can improve radiofrequency ablation efficacy. This study aims to differentiate the AFL mechanism using a 12-lead surface electrocardiogram. P-P interval series variability is hypothesized to be different in FAFL and MAFL and may be useful for discrimination. 12-lead ECG signals were collected from 46 patients with known AFL mechanisms. Features for a proposed classifier are extracted through descriptive statistics of the interval series. On the other hand, the class ratio of MAFL and FAFL was 41 : 5, respectively, which was highly imbalanced. To resolve this, different data augmentation techniques (SMOTE, modified-SMOTE, and smoothed-bootstrap) have been applied on the interval series to generate synthetic interval series and minimize imbalance. Modification is introduced in the classic SMOTE technique (modified-SMOTE) to properly produce data samples from the original distribution. The characteristics of modified-SMOTE are found closer to the original dataset than the other two techniques based on the four validation criteria. The performance of the proposed model has been evaluated by three linear classifiers, namely, linear discriminant analysis (LDA), logistic regression (LOG), and support vector machine (SVM). Filter and wrapper methods have been used for selecting relevant features. The best average performance was achieved at 400% augmentation of the FAFL interval series (90.24% sensitivity, 49.50% specificity, and 76.88% accuracy) in the LOG classifier. The variation of consecutive P-wave intervals has been shown as an effective concept that differentiates FAFL from MAFL through the 12-lead surface ECG.