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In this article, a size-dependent generalized thermoelasticity model is established to appraise the small-scale effect on thermoelastic vibrations of Euler-Bernoulli nanobeams. Small-scale effect on the structure and heat conduction is captured by exploiting nonlocal strain gradient theory (NSGT) and nonclassical heat conduction model of Guyer and Krumhansl (GK model). NSGT enables the model to account for both nonlocal and strain gradient effects on structure, and GK formulation empowers the model to incorporate both nonlocal and lagging effect into heat conduction equation. The normalized forms of size-dependent equations of motion and heat conduction are provided by introducing some dimensionless parameters. This system of normalized differential equations is then solved with the aid of the Laplace transform to determine thermoelastic responses of nanobeams. Through various examples, a complete parametric study is conducted to clarify the pivotal role of nonclassical scale parameters in thermoelastic behavior of nanobeams. Comparing the results extracted based on various relative magnitudes of nonlocal and strain gradient length scale parameters implies that NSGT is capable of expounding both hardening and softening phenomenon in nanoscale structures. The outcomes also reveal that GK model anticipates less energy dissipation. [ABSTRACT FROM AUTHOR]

Business process management (BPM) has been the main driver behind company optimization and operational efficiency. However, the digitization era we live in necessitates that organizations be agile and adaptable. Delivering unprecedented rates of automation-fueled agility is necessary to be a part of this digital revolution. On the other hand, BPM automation cannot be done only by concentrating on procedure space and traditional planning methodologies. With the introduction of BPM, where the deployment of BPM with cloud computing has undergone enormous development lately, cloud computing has been considered a particularly active topic of study. Cloud computing points to the provision of dependable computing environments based on improved infrastructure availability and service quality without imposing a significant cost load. This research aims to discover the relationship between technical factors, financial factors, environmental factors, security of the cloud-based information systems, and the agile development of industrial BPM (IBPM). The present study aims to fill this gap and show how partial least squares structural equation modeling (SEM) can be employed in this field. Importance–performance map analysis (IPMA) evaluated the importance and performance of factors in the SEM. IPMA enables the identification of factors with relatively low performance but relatively high importance in shaping dependent variables. The empirical findings showed that four key factors (technical, financial, environmental, and security) positively influence the agile development of IBPM. [ABSTRACT FROM AUTHOR]