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This paper outlines a computational model for the analysis of the piezoelectric behaviour of the vertebral body remodelling process. Particular attention is paid to the algorithms for the simulation of the stress energy density for each point of the geometry and the distribution of the density in the bone. In addition, the model takes into account the piezoelectric effect and the anisotropy (transversal isotropy) of the bone. A model for internal anisotropic piezoelectric bone remodelling of a human vertebra is discussed in detail. The model consists of the implementation of an algorithm which includes the elastic and electric variables in a single equation using boundary element method. The presented results show a good agreement with biological data and the model does not include any electric additional charge.

Even though machine learning (ML) applications are not novel, they have gained popularity partly due to the advance in computing processing. This study explores the adoption of ML methods in marketing applications through a bibliographic review of the period 2008-2022. In this period, the adoption of ML in marketing has grown significantly. This growth has been quite heterogeneous, varying from the use of classical methods such as artificial neural networks to hybrid methods that combine different techniques to improve results. Generally, maturity in the use of ML in marketing and increasing specialization in the type of problems that are solved were observed. Strikingly, the types of ML methods used to solve marketing problems vary wildly, including deep learning, supervised learning, reinforcement learning, unsupervised learning, and hybrid methods. Finally, we found that the main marketing problems solved with machine learning were related to consumer behavior, recommender systems, forecasting, marketing segmentation, and text analysis-content analysis.