Evidence of Finite Magneto-electric Coupling in SmFeO3 – PbTiO3 Solid Solutions

Present work investigates the detailed multiferroic properties of Pb1 − xSmxTi1−xFexO3, (x = 0.21, 0.22, 0.23, 0.24 and 0.25) synthesize through solid state reaction route. The structural, dielectric, ferroelectric and magnetic properties were measured. A sincere study is carried out to detect the magneto-electric coupling in all the samples through magneto-dielectric, magnetization after electric poling and magneto-pe response. The maximum value of coupling coefficient (γ) and magneto-dielectric response (MDR) of sample x = 0.24 has shown by magneto-dielectric properties and magnetization after electric poling whereas magneto-pe has shown that all the samples possess multiferroic nature.

Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)–systolic time interval (STI), RRI–diastolic time interval (DTI), HR-corrected QT interval (QTcI)–STI, QTcI–DTI, Tpeak–Tend interval (TpeI)–STI, TpeI–DTI, Tpe/QT interval (Tpe/QTI)–STI, and Tpe/QTI–DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD—mild-to-moderate CHD group, severe CHD—chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD—CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.

Magneto-electric coupling constants in piezoelectric/piezomaganetic layered composite

During the last few years, piezoelectric/piezomagnetic composites have been studied due to the numerous applications related to the coupling between these materials and the fields. In the present work, two theoretical models for calculating the magneto/electric coupling factor of the composite with 2-2 connectivity, are presented. Using the asymptotic homogenization method, the effective coefficients of a periodic magneto–electro–elastic layered composite can be obtained in matrix form. By using this matrix, a two-layered composite formed by BaTiO3 and CoFe2O4 are studied, and expressions for the effective coefficients are obtained. The effective magneto/electric coupling factor as a function of the piezoelectric volumetric fraction are found from these particular coefficients. In addition, a dynamic model of the multilayer piezoelectric/piezomagnetic composite is discussed. The dynamical model has been used to determinate the magnetoelectric coupling constants.