Search results for "multiscale"
showing 10 items of 78 documents
Global patterns and drivers of alpine plant species richness
2021
B.J.-A. was funded by the Marie Curie Clarín-COFUND program of the Principality of Asturias-EU (ACB17-26) and the Spanish Research Agency (AEI/10.13039/501100011033).
The Importance of Cerebellar Connectivity on Simulated Brain Dynamics
2020
The brain shows a complex multiscale organization that prevents a direct understanding of how structure, function and dynamics are correlated. To date, advances in neural modeling offer a unique opportunity for simulating global brain dynamics by embedding empirical data on different scales in a mathematical framework. The Virtual Brain (TVB) is an advanced data-driven model allowing to simulate brain dynamics starting from individual subjects' structural and functional connectivity obtained, for example, from magnetic resonance imaging (MRI). The use of TVB has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting…
Remote sensing image segmentation by active queries
2012
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…
Multiscale modeling on biological systems
2018
P 042 - Gait complexity quantified using inertial measurement units in children with cerebral palsy
2018
Abstract Children with cerebral palsy (CP) have gait impairments, and their gait is affected by concurrent tasks. We used inertial measurement units (IMU) to quantify CP-related gait complexity alterations, and identify effects of dual tasks on gait variability from 12 children with CP and 23 typically developed (TD) controls. The data were collected for normal and dual-tasks (motor; carrying a tray, cognitive; word naming) during walking. Step duration and adjusted multiscale entropy (MSE) index were computed. In overall, children with CP had shorter step duration and greater gait complexity than TD. Gait complexity was higher in vertical direction during the cognitive than normal and moto…
Adversarial reverse mapping of equilibrated condensed-phase molecular structures
2020
A tight and consistent link between resolutions is crucial to further expand the impact of multiscale modeling for complex materials. We herein tackle the generation of condensed molecular structures as a refinement -- backmapping -- of a coarse-grained structure. Traditional schemes start from a rough coarse-to-fine mapping and perform further energy minimization and molecular dynamics simulations to equilibrate the system. In this study we introduce DeepBackmap: A deep neural network based approach to directly predict equilibrated molecular structures for condensed-phase systems. We use generative adversarial networks to learn the Boltzmann distribution from training data and realize reve…
Modeling of biomolecular machines in non-equilibrium steady states
2021
Numerical computations have become a pillar of all modern quantitative sciences. Any computation involves modeling--even if often this step is not made explicit--and any model has to neglect details while still being physically accurate. Equilibrium statistical mechanics guides both the development of models and numerical methods for dynamics obeying detailed balance. For systems driven away from thermal equilibrium such a universal theoretical framework is missing. For a restricted class of driven systems governed by Markov dynamics and local detailed balance, stochastic thermodynamics has evolved to fill this gap and to provide fundamental constraints and guiding principles. The next step…
Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability
2021
Switching between different levels of resolution is essential for multiscale modeling, but restoring details at higher resolution remains challenging. In our previous study we have introduced deepBackmap: a deep neural-network-based approach to reverse-map equilibrated molecular structures for condensed-phase systems. Our method combines data-driven and physics-based aspects, leading to high-quality reconstructed structures. In this work, we expand the scope of our model and examine its chemical transferability. To this end, we train deepBackmap solely on homogeneous molecular liquids of small molecules, and apply it to a more challenging polymer melt. We augment the generator's objective w…
Efficient unsupervised clustering for spatial bird population analysis along the Loire river
2015
International audience; This paper focuses on application and comparison of Non Linear Dimensionality Reduction (NLDR) methods on natural high dimensional bird communities dataset along the Loire River (France). In this context, biologists usually use the well-known PCA in order to explain the upstream-downstream gradient.Unfortunately this method was unsuccessful on this kind of nonlinear dataset.The goal of this paper is to compare recent NLDR methods coupled with different data transformations in order to find out the best approach. Results show that Multiscale Jensen-Shannon Embedding (Ms JSE) outperform all over methods in this context.
A 3D multi-physics boundary element computational framework for polycrystalline materials micro-mechanics
2021
A recently developed novel three-dimensional (3D) computational framework for the analysis of polycrystalline materials at the grain scale is described in this lecture. The framework is based on the employment of: i) 3D Laguerre-Voronoi tessellations for the representation of the micro-morphology of polycrystalline materials; ii) boundary integral equations for the representation of the mechanics of the individual grains; iii) suitable cohesive traction-separation laws for the representation of the multi-physics behavior of the interfaces (either inter-granular or trans-granular) within the aggregate, which are the seat of damage initiation and evolution processes, up to complete decohesion…