NEW THEORETICAL APPROACHES IN COMPUTATIONAL BIOMECHANICS
Reverse engineering is the processes of extracting knowledge or design information from a product, often involving the analysis of its components and workings in detail. In vertebrate biology, one of the most important processes is the comparison of the well-known design of bony structures between actual species to detect ecomorphological patterns (diet, locomotion, etc.) and use them to infer them in fossil extinct taxa. In line with this, I published several works using the equations of continuum mechanics to develop a theoretical framework to enable comparison of different FEA models of different species: Marcé-Nogué et al. (2013) or Gil et al. (2015). With these works, I established a robust theoretical framework using the continuum mechanics equations for comparing models. Previously, other researchers presented some works in this line, but they have always been based on trial-error methods instead of using the core equations of the Finite Element Method and demonstrating them mathematically.
I also created new post-processing methodologies in order to quantify the FEA results for comparative purposes and being capable to mix them with other morphological methods such as, geometrical morphometry (which studies the variation in shape) or multivariate statistics (which enables to differentiate species or ecological behaviours such as diet or locomotion): Combining geometric morphometrics in Fortuny et al. (2011), presenting new single measurements from FEA models that represent the relative strength of each model or proposing the concept of “Quasi-ideal Mesh” to facilitate the statistics in FEA models because not all the FEA meshes are adequate for this purpose (Marcé-Nogué et al. 2016) or proposing a new method named the intervals’ method Marcé-Nogué et al. (2017). These post-process methods are specially interesting because they can be used as an input data for the use of both supervised and non-supervised machine-learning (ML) algorithms. The use of ML is a powerful way that allow to classify sets of data as well as a predictor and has an incredible potential in inferring behaviours of extinct taxa. I started to develop ML in my methods with success: Püschel et al. (2018), Marcé-Nogué et al. (2020) or Püschel et al. (2020). are exemples to how we can infer the ecological traits of fossil taxa using machine learning in biomechanical and morphological data.
I also created new post-processing methodologies in order to quantify the FEA results for comparative purposes and being capable to mix them with other morphological methods such as, geometrical morphometry (which studies the variation in shape) or multivariate statistics (which enables to differentiate species or ecological behaviours such as diet or locomotion): Combining geometric morphometrics in Fortuny et al. (2011), presenting new single measurements from FEA models that represent the relative strength of each model or proposing the concept of “Quasi-ideal Mesh” to facilitate the statistics in FEA models because not all the FEA meshes are adequate for this purpose (Marcé-Nogué et al. 2016) or proposing a new method named the intervals’ method Marcé-Nogué et al. (2017). These post-process methods are specially interesting because they can be used as an input data for the use of both supervised and non-supervised machine-learning (ML) algorithms. The use of ML is a powerful way that allow to classify sets of data as well as a predictor and has an incredible potential in inferring behaviours of extinct taxa. I started to develop ML in my methods with success: Püschel et al. (2018), Marcé-Nogué et al. (2020) or Püschel et al. (2020). are exemples to how we can infer the ecological traits of fossil taxa using machine learning in biomechanical and morphological data.
In general, the methods I developed include two important points: firstly, novelty, creativity and originality in the way to analyse FEA models, which open many new relevant possibilities for the scientific community. And my contributions were not only used in the field biomechanics, because these new methods introduce potential approaches that can be used in other fields of computational mechanics. Secondly, I have critically evaluated and imposed useful solutions to a variety of topics that impeded reliable FEA, including inaccurate assumptions about the particularities of the FEA mesh, the consequences of employing unrealistic thickness parameters in plane models and those related to bad mathematical formulation in evaluating allometry. Nowadays I am using them in most of my recent works and I create a unique and singular personality to the research I am doing, being the only one in the world capable to compare quantitatively more than 20 different species in a morphological context. I am also currently publishing the results of new research done in other fields such as locomotion in vertebrates (Püschel et al. 2018, 2020), other families such as ungulates (Zhou et al. 2019) or biomechanics in invertebrates (Esteve et al. 2021) demonstrating that the methodology is valid in other different fields of morphological and biomechanical analysis.
SELECTED REFERENCES
- Marcé-Nogué, J., Püschel, T. A., Daasch, A. & Kaiser, T. M. (2020). Broad scale morpho-functional traits of the mandible suggest no hard food adaptation in the hominin lineage. Scientific Reports. 10:6793 (url)
- Püschel, T. A., Marcé-Nogué, J., Gladman, J., Patel, B., Almécija, S. & Sellers, W. I. (2020). Getting its feet on the ground: elucidating Paralouatta's semi-terrestriality using the virtual morpho-functional toolbox. Frontiers in Earth Science. 8:79 (url)
- Zhou, Z., Winkler, D. E., Fortuny, J., Kaiser, T. M & Marcé-Nogué, J. (2019). Why ruminating ungulates chew sloppily: Biomechanics discern a phylogenetic pattern. PLoS One. 14(4), e0214510 (url)
- Püschel, T. A., Marcé-Nogué, J., Gladman, J. T., Bobe, R., & Sellers, W. I. (2018). Inferring locomotor behaviours in Miocene New World monkeys using finite element analysis, geometric morphometrics and machine-learning classification techniques applied to talar morphology. Journal of The Royal Society Interface, 15(146), 20180520.