3,845 research outputs found
Optical meta-atom for localization of light with quantized energy
The capacity to confine light into a small region of space is of paramount
importance in many areas of modern science. Here, we suggest a mechanism to
store a quantized "bit" of light - with a very precise amount of energy - in an
open core-shell plasmonic structure ("meta-atom") with a nonlinear optical
response. Notwithstanding the trapped light state is embedded in the radiation
continuum, its lifetime is not limited by the radiation loss. Interestingly, it
is shown that the interplay between the nonlinear response and volume plasmons
enables breaking fundamental reciprocity restrictions, and coupling very
efficiently an external light source to the meta-atom. The collision of an
incident optical pulse with the meta-atom may be used to release the trapped
radiation "bit".Comment: Article in press in Nature Communications (29/09/2015). Attached:
Supplementary Movies 1 and 2 (small size version
Learning Task Priorities from Demonstrations
Bimanual operations in humanoids offer the possibility to carry out more than
one manipulation task at the same time, which in turn introduces the problem of
task prioritization. We address this problem from a learning from demonstration
perspective, by extending the Task-Parameterized Gaussian Mixture Model
(TP-GMM) to Jacobian and null space structures. The proposed approach is tested
on bimanual skills but can be applied in any scenario where the prioritization
between potentially conflicting tasks needs to be learned. We evaluate the
proposed framework in: two different tasks with humanoids requiring the
learning of priorities and a loco-manipulation scenario, showing that the
approach can be exploited to learn the prioritization of multiple tasks in
parallel.Comment: Accepted for publication at the IEEE Transactions on Robotic
Geometry-aware Manipulability Learning, Tracking and Transfer
Body posture influences human and robots performance in manipulation tasks,
as appropriate poses facilitate motion or force exertion along different axes.
In robotics, manipulability ellipsoids arise as a powerful descriptor to
analyze, control and design the robot dexterity as a function of the
articulatory joint configuration. This descriptor can be designed according to
different task requirements, such as tracking a desired position or apply a
specific force. In this context, this paper presents a novel
\emph{manipulability transfer} framework, a method that allows robots to learn
and reproduce manipulability ellipsoids from expert demonstrations. The
proposed learning scheme is built on a tensor-based formulation of a Gaussian
mixture model that takes into account that manipulability ellipsoids lie on the
manifold of symmetric positive definite matrices. Learning is coupled with a
geometry-aware tracking controller allowing robots to follow a desired profile
of manipulability ellipsoids. Extensive evaluations in simulation with
redundant manipulators, a robotic hand and humanoids agents, as well as an
experiment with two real dual-arm systems validate the feasibility of the
approach.Comment: Accepted for publication in the Intl. Journal of Robotics Research
(IJRR). Website: https://sites.google.com/view/manipulability. Code:
https://github.com/NoemieJaquier/Manipulability. 24 pages, 20 figures, 3
tables, 4 appendice
The zipper mechanism in phagocytosis: energetic requirements and variability in phagocytic cup shape
Phagocytosis is the fundamental cellular process by which eukaryotic cells
bind and engulf particles by their cell membrane. Particle engulfment involves
particle recognition by cell-surface receptors, signaling and remodeling of the
actin cytoskeleton to guide the membrane around the particle in a zipper-like
fashion. Despite the signaling complexity, phagocytosis also depends strongly
on biophysical parameters, such as particle shape, and the need for
actin-driven force generation remains poorly understood. Here, we propose a
novel, three-dimensional and stochastic biophysical model of phagocytosis, and
study the engulfment of particles of various sizes and shapes, including spiral
and rod-shaped particles reminiscent of bacteria. Highly curved shapes are not
taken up, in line with recent experimental results. Furthermore, we
surprisingly find that even without actin-driven force generation, engulfment
proceeds in a large regime of parameter values, albeit more slowly and with
highly variable phagocytic cups. We experimentally confirm these predictions
using fibroblasts, transfected with immunoreceptor FcyRIIa for engulfment of
immunoglobulin G-opsonized particles. Specifically, we compare the wild-type
receptor with a mutant receptor, unable to signal to the actin cytoskeleton.
Based on the reconstruction of phagocytic cups from imaging data, we indeed
show that cells are able to engulf small particles even without support from
biological actin-driven processes. This suggests that biochemical pathways
render the evolutionary ancient process of phagocytic highly robust, allowing
cells to engulf even very large particles. The particle-shape dependence of
phagocytosis makes a systematic investigation of host-pathogen interactions and
an efficient design of a vehicle for drug delivery possible.Comment: Accepted for publication in BMC Systems Biology. 17 pages, 6 Figures,
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