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This work reports the investigations of the electric potential impacts on the mechanical buckling of the piezoelectric nanocomposite doubly curved shallow shells reinforced by functionally gradient graphene platelets (FGGPLs). A four-variable shear deformation shell theory is utilized to describe the components of displacement. The present nanocomposite shells are presumed to be rested on an elastic foundation and subject to electric potential and in-plane compressive loads. These shells are composed of several bonded layers. Each layer is composed of piezoelectric materials strengthened by uniformly distributed GPLs. The Halpin-Tsai model is employed to calculate the Young's modulus of each layer, whereas Poisson's ratio, mass density, and piezoelectric coefficients are evaluated based on the mixture rule. The graphene components are graded from one layer to another according to four different piecewise laws. The stability differential equations are deduced based on the principle of virtual work. To test the validity of this work, the current mechanical buckling load is analogized with that available in the literature. Several parametric investigations have been performed to demonstrate the effects of the shell geometry elastic foundation stiffness, GPL volume fraction, and external electric voltage on the mechanical buckling load of the GPLs/piezoelectric nanocomposite doubly curved shallow shells. It is found that the buckling load of GPLs/piezoelectric nanocomposite doubly curved shallow shells without elastic foundations is reduced by increasing the external electric voltage. Moreover, by increasing the elastic foundation stiffness, the shell strength is enhanced, leading to an increase in the critical buckling load.

In this article, we present a mathematical model of thermoelastic skin tissue based on a refined Lord-Shulman heat conduction theory. A small thickness of skin tissue is considered to be one-dimensional with mechanical clamped surfaces. In addition, the skin tissue's outer surface is subjected to ramp-type heating while its inner surface is adiabatic. A simple Lord-Shulman theory, as well as the classical coupled thermoelasticity, are also applied in this article. Laplace transform techniques and their inversions are calculated to return to the time domain. Numerical outcomes are represented graphically to discuss the significant impacts on the temperature, dilatation, displacement, and stress distributions. Such results provide a more comprehensive and better insight for understanding the behavior of skin tissue during the temperature distribution of a specific boundary condition.

Background and Aim: Predicting culprit lesions in acute coronary syndrome (ACS) could be a challenge. The aim of this study was to assess the accuracy of regional wall motion abnormalities (RWMA) using various echocardiographic techniques and ECG changes in predicting the culprit coronary lesion in a group of patients with ACS., Methods: In 80 consecutive patients with ACS (age 55·7 ± 9·4 years, 77% male, 15% with CCS Angina III), an echocardiographic examination of left ventricle (LV) RWMA, tissue Doppler imaging (TDI) and speckle tracking myocardial strain and strain rate (SR) were performed before intervention., Results: Of the 80 patients, one-vessel stenosis (>70%) was present in 53 (66%), two-vessel disease in 12 (15%) and multivessel disease in 15 patients (19%). About 51% of patients had hypertension, 40% diabetes and 23% dyslipidaemia. There was no relationship between individual segmental RWMA and SR. Mean regional SR, but not peak strain, correlated with culprit lesion branch: left anterior descending - LAD (r = 0·35, P = 0·005), circumflex LCx (r = 0·32, P = 0·03) and right coronary RCA (r = 0·37, P = 0·01). Only ECG changes in the LAD territory (r = 0·26, P = 0·04) correlated with the culprit lesion. SR of LAD territories ≤-0·74 was 71% sensitive and 70% specific (AUC = 0·70, CI = 0·67-0·93, P = 0·01), SR of LCx territories of ≤-0·67 was 75% sensitive and 63% specific (AUC = 0·72, CI = 0·58-0·87, P = 0·02) and SR of RCA territories ≤-0·83 was 73% sensitive and 71% specific (AUC = 0·80, CI = 0·66-0·93, P = 0·001) in predicting significant stenosis. SR was more accurate than all other techniques in predicting the culprit lesion., Conclusion: In ACS, mean regional speckle tracking SR is more sensitive than peak strain, TDI, ECG changes and wall motion abnormalities in detecting significant coronary artery stenosis., (© 2019 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.)