The standard Yee algorithm is widely used in computational electromagnetics because of its simplicity and divergence free nature. A generalization of the classical Yee scheme to 3D unstructured meshes is adopted, based on the use of a Delaunay primal mesh and its high quality Voronoi dual. This allows the problem of accuracy losses, which are normally associated with the use of the standard Yee scheme and a staircased representation of curved material interfaces, to be circumvented. The 3D dual mesh leapfrog-scheme which is presented has the ability to model both electric and magnetic anisotropic lossy materials. This approach enables the modelling of problems, of current practical interest, involving structured composites and metamaterials.
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http://dx.doi.org/10.1007/s00466-016-1295-x | DOI Listing |
Nat Commun
November 2024
Institut de Génétique et de Biologie Moléculaire et Cellulaire, Integrated Structural Biology Department, Illkirch, France.
The ribosome maturation factor Rea1 (or Midasin) catalyses the removal of assembly factors from large ribosomal subunit precursors and promotes their export from the nucleus to the cytosol. Rea1 consists of nearly 5000 amino-acid residues and belongs to the AAA+ protein family. It consists of a ring of six AAA+ domains from which the ≈1700 amino-acid residue linker emerges that is subdivided into stem, middle and top domains.
View Article and Find Full Text PDFIEEE Trans Pattern Anal Mach Intell
December 2024
Policy diversity, encompassing the variety of policies an agent can adopt, enhances reinforcement learning (RL) success by fostering more robust, adaptable, and innovative problem-solving in the environment. The environment in which standard RL operates is usually modeled with a Markov Decision Process (MDP) as the theoretical foundation. However, in many real-world scenarios, the rewards depend on an agent's history of states and actions leading to a non-MDP.
View Article and Find Full Text PDFAdv Sci (Weinh)
October 2024
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150001, China.
Nat Commun
July 2024
Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Noord-Holland, the Netherlands.
Legged robots are well-suited for deployment in unstructured environments but require a unique control scheme specific for their design. As controllers optimised in simulation do not transfer well to the real world (the infamous sim-to-real gap), methods enabling quick learning in the real world, without any assumptions on the specific robot model and its dynamics, are necessary. In this paper, we present a generic method based on Central Pattern Generators, that enables the acquisition of basic locomotion skills in parallel, through very few trials.
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