Biomechanical analysis of pelvic floor dysfunction requires knowledge of certain biomechanical parameters, such as muscle fiber direction, in order to adequately model function. Magnetic resonance (MR) diffusion tensor imaging (DTI) provides an estimate of overall muscle fiber directionality based on the mathematical description of water diffusivity. This work aimed at evaluating the concurrence between pubovisceralis muscle fiber representations obtained from DTI, and the maximum principal stress lines obtained through the finite element method. Seven datasets from axial T2-weighted images were used to build numerical models, and muscle fiber orientation estimated from the DT images. The in-plane projections of the first eigenvector of both vector fields describing muscle fiber orientation were extracted and compared. The directional consistency was evaluated by calculating the angle between the normalized vectors for the entire muscle and also for the right and left insertions, middle portions, and anorectal area. The values varied between 28° ± 6 (right middle portion) and 34° ± 9 (anorectal area), and were higher than the angular precision of the DT estimates, evaluated using wild bootstrapping analysis. Angular dispersion ranged from 17° ± 4 (left middle portion) to 23° ± 5 (anorectal area). Further studies are needed to examine acceptability of these differences when integrating the vectors estimated from DTI in the numerical analysis.

Background: Assessing carbon storage and sequestration is key for de ning effective conservation actions to mitigate climate change. Forest species changes have direct impacts on carbon stocks and may lead to undesirable climate trade-offs. In this paper, we measure aboveground biomass (AGB) and the impact of forest changes on climate regulation through three land policy scenarios by 2030 in continental Portugal.Results: We found that a High intervention scenario, supported by an important increase in "Other coniferous trees" class, will provide 29.5% more of carbon sequestration, whereas a Low intervention scenario, in which there is a moderate increase in all forest classes, will result in an increase of 5.7%. A business as usual (BAU) scenario, supported by an increase in eucalyptus forests and a decrease in autochthonous species, will decrease carbon sequestration (-2.7%), particularly Lisboa, Algarve and Norte regions. Economic valuation shows that the High intervention scenario will generate the highest economic outcome for climate regulation by 2030. Conclusion:This study provides a spatial-based methodology for monitoring carbon sequestration and new insights about the impact of policies for Green House Gas (GHG) mitigation, supporting the 2030 Sustainable Development Goals achievement.

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