Modélisation de l'effet de la structure spatiale à l'intérieur du peuplement sur la succession de forêts boréales mixtes

La configuration spatiale des arbres individuels peut affecter leur croissance et leur survie à une échelle fine et modifier la composition et la structure de la forêt à l'échelle du paysage. Ainsi, la compréhension de la dynamique spatiale des peuplements est cruciale pour la gestion forestière. L'utilisation de SORTIE-ND, un simulateur forestier spatialement explicite et individu-centré, permet de prédire la croissance, la mortalité et le recrutement d'arbres individuels à l'échelle du peuplement en recréant la dynamique des trouées. Notre recherche vise à déterminer les changements dans la structure spatiale des peuplements forestiers à l'aide de SORTIE-ND et à évaluer la précision du modèle en comparant la structure spatiale des peuplements simulés et observés. Les simulations seront effectuées et validées avec deux ensembles de données empiriques provenant de peuplements situés dans la forêt boréale mixte de l'est du Canada. Ces peuplements se sont formés après huit feux de forêt depuis 1760 et représentent une chronoséquence de 249 ans de succession forestière, qui serviront de données d'entrée et de validation pour les modèles. Nous avons calculé une fonction L homogène de la structure spatiale pour chaque peuplement simulé (avec des conditions initiales basées sur des données empiriques de peuplements plus jeunes), et comparé avec la fonction L non homogène des données observées pour vérifier si le modèle SORTIE-ND est capable de produire une structure spatiale similaire à celle observée. Pour les trois espèces les plus communes (Abies balsamea, Populus tremuloides et Picea glauca) dans les peuplements observés, SORTIE-ND a pu reproduire les patrons spatiaux observés pour les espèces individuelles et les paires d’espèces. Cependant, l’étude ne portait pas sur toutes les espèces des forêts boréales mixtes et des recherches futures sur la performance du modèle pour d’autres espèces devraient être réalisées

Cation Exchange Sorption of Some Metal Ions from Aqueous Ammonium Acetate Medium: Separation of Ce(IV) from Ce(III), La(III) & Other Metal Ions

438-44

Uncertainty-aware predictions of molecular X-ray absorption spectra using neural network ensembles

As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important for their robust application. Uncertainty aware machine learning methods have been used in select applications, but largely for scalar properties. In this work, we showcase an exemplary study in which neural network ensembles are used to predict the X-ray absorption spectra of small molecules, as well as their point-wise uncertainty, from local atomic environments. The performance of the resulting surrogate clearly demonstrates quantitative correlation between errors relative to ground truth and the predicted uncertainty estimates. Significantly, the model provides an upper bound on the expected error. Specifically, an important quality of this uncertainty-aware model is that it can indicate when the model is predicting on out-of-sample data. This allows for its integration with large scale sampling of structures together with active learning or other techniques for structure refinement. Additionally, our models can be generalized to larger molecules than those used for training, and also successfully track uncertainty due to random distortions in test molecules. While we demonstrate this workflow on a specific example, ensemble learning is completely general. We believe it could have significant impact on ML-enabled forward modeling of a broad array of molecular and materials properties.Comment: 24 pages, 16 figure

Cobalt(III), Nickel(II) and zlnc(II) complexes with 4-(2-pyridylazo) resorcinol (PAR)

Bull. Chem. Soc. Ethiop., 4(1), 61-65 (1990)

Cobalt(III), Nickel(II) and zlnc(II) complexes with 4-(2-pyridylazo) resorcinol (PAR)

Bull. Chem. Soc. Ethiop., 4(1), 61-65 (1990)

Obstacle Avoidance in a Dynamic Environment: A Collision Cone Approach

A novel collision cone approach is proposed as an aid to collision detection and avoidance between irregularly shaped moving objects with unknown trajectories. It is shown that the collision cone can be effectively used to determine whether collision between a robot and an obstacle (both moving in a dynamic environment) is imminent. No restrictions are placed on the shapes of either the robot or the obstacle, i.e., they can both be of any arbitrary shape. The collision cone concept is developed in a phased manner starting from existing analytical results-available in aerospace literature-that enable prediction of collision between two moving point objects. These results are extended to predict collision between a point and a circular object, between a point and an irregularly shaped object, between two circular objects, and finally between two irregularly shaped objects. Using the collision cone approach, several strategies that the robot can follow in order to avoid collision, are presented. A discussion on how the shapes of the robot and obstacles can be approximated in order to reduce computational burden is also presented. A number of examples are given to illustrate both collision prediction and avoidance strategies of the robot

Guidance for Precision Three-Dimensional Maneuvers Through Orifices Using Safe-Passage Cones

This paper proposes a safe-passage cone-based guidance strategy developed in a relative velocity framework to enable a generic aerial robot execute a precision three-dimensional maneuver through a narrow orifice in a wall. The relative sizes of the robot and the orifice are such that the orifice is only slightly larger than the robot. The orifice is approximated as an elliptical shape, and analytical nonlinear guidance laws incorporating state-based switching are derived. It is demonstrated that the guidance laws developed can be used to maneuver the robot through both fixed and moving orifices as well as in scenarios when the orifice is closing with time

Collision Cones for Quadric Surfaces

The problem of collision prediction in dynamic environments appears in several diverse fields, which include robotics, air vehicles, underwater vehicles, and computer animation. In this paper, collision prediction of objects that move in 3-D environments is considered. Most work on collision prediction assumes objects to be modeled as spheres. However, there are many instances of object shapes where an ellipsoidal or a hyperboloid-like bounding box would be more appropriate. In this paper, a collision cone approach is used to determine collision between objects whose shapes can be modeled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained in the form of analytical expressions in the relative velocity space. For objects of arbitrary shapes, exact representations of planar sections of the 3-D collision cone are obtained

Generalization of the collision cone approach for motion safety in 3-D environments

Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies