7,020 research outputs found
On the theory of polarization transfer in inhomogeneous magnetized plasmas
Polarization transfer theory in inhomogeneous magnetized plasmas with mode couplin
Formation of Non-reciprocal Bands in Magnetized Diatomic Plasmonic Chains
We show that non-reciprocal bands can be formed in a magnetized periodic
chain of spherical plasmonic particles with two particles per unit cell.
Simplified form of symmetry operators in dipole approximations are used to
demonstrate explicitly the relation between spectral non-reciprocity and broken
spatial-temporal symmetries. Due to hybridization among plasmon modes and free
photon modes, strong spectral non-reciprocity appears in region slightly below
the lightline, where highly directed guiding of energy can be supported. The
results may provide a clear guidance on the design of one-way waveguides
Structure of the chromosphere-corona transition region
Structure and energy distribution of chromosphere-corona transition regio
Anomalous Light Scattering by Topological -symmetric Particle Arrays
Robust topological edge modes may evolve into complex-frequency modes when a
physical system becomes non-Hermitian. We show that, while having negligible
forward optical extinction cross section, a conjugate pair of such complex
topological edge modes in a non-Hermitian -symmetric system can
give rise to an anomalous sideway scattering when they are simultaneously
excited by a plane wave. We propose a realization of such scattering state in a
linear array of subwavelength resonators coated with gain media. The prediction
is based on an analytical two-band model and verified by rigorous numerical
simulation using multiple-multipole scattering theory. The result suggests an
extreme situation where leakage of classical information is unnoticeable to the
transmitter and the receiver when such a -symmetric unit is
inserted into the communication channel.Comment: 16 pages, 8 figure
Lateral migration of a 2D vesicle in unbounded Poiseuille flow
The migration of a suspended vesicle in an unbounded Poiseuille flow is
investigated numerically in the low Reynolds number limit. We consider the
situation without viscosity contrast between the interior of the vesicle and
the exterior. Using the boundary integral method we solve the corresponding
hydrodynamic flow equations and track explicitly the vesicle dynamics in two
dimensions. We find that the interplay between the nonlinear character of the
Poiseuille flow and the vesicle deformation causes a cross-streamline migration
of vesicles towards the center of the Poiseuille flow. This is in a marked
contrast with a result [L.G. Leal, Ann. Rev. Fluid Mech. 12,
435(1980)]according to which the droplet moves away from the center (provided
there is no viscosity contrast between the internal and the external fluids).
The migration velocity is found to increase with the local capillary number
(defined by the time scale of the vesicle relaxation towards its equilibrium
shape times the local shear rate), but reaches a plateau above a certain value
of the capillary number. This plateau value increases with the curvature of the
parabolic flow profile. We present scaling laws for the migration velocity.Comment: 11 pages with 4 figure
BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection
You Only Look Once (YOLO)-based object detectors have shown remarkable
accuracy for automated brain tumor detection. In this paper, we develop a novel
BGF-YOLO architecture by incorporating Bi-level Routing Attention (BRA),
Generalized feature pyramid networks (GFPN), and Fourth detecting head into
YOLOv8. BGF-YOLO contains an attention mechanism to focus more on important
features, and feature pyramid networks to enrich feature representation by
merging high-level semantic features with spatial details. Furthermore, we
investigate the effect of different attention mechanisms and feature fusions,
detection head architectures on brain tumor detection accuracy. Experimental
results show that BGF-YOLO gives a 4.7% absolute increase of mAP
compared to YOLOv8x, and achieves state-of-the-art on the brain tumor detection
dataset Br35H. The code is available at https://github.com/mkang315/BGF-YOLO
Two-dimensional Vesicle dynamics under shear flow: effect of confinement
Dynamics of a single vesicle under shear flow between two parallel plates is
studied using two-dimensional lattice-Boltzmann simulations. We first present
how we adapted the lattice-Boltzmann method to simulate vesicle dynamics, using
an approach known from the immersed boundary method. The fluid flow is computed
on an Eulerian regular fixed mesh while the location of the vesicle membrane is
tracked by a Lagrangian moving mesh. As benchmarking tests, the known vesicle
equilibrium shapes in a fluid at rest are found and the dynamical behavior of a
vesicle under simple shear flow is being reproduced. Further, we focus on
investigating the effect of the confinement on the dynamics, a question that
has received little attention so far. In particular, we study how the vesicle
steady inclination angle in the tank-treading regime depends on the degree of
confinement. The influence of the confinement on the effective viscosity of the
composite fluid is also analyzed. At a given reduced volume (the swelling
degree) of a vesicle we find that both the inclination angle, and the membrane
tank-treading velocity decrease with increasing confinement. At sufficiently
large degree of confinement the tank-treading velocity exhibits a
non-monotonous dependence on the reduced volume and the effective viscosity
shows a nonlinear behavior.Comment: 12 pages, 8 figure
Asymptotic properties of order statistics correlation coefficient in the normal cases
We have previously proposed a novel order statistics correlation coefficient (OSCC), which possesses some desirable advantages when measuring linear and monotone nonlinear associations between two signals. However, the understanding of this new coefficient is far from complete. A lot of theoretical questions, such as the expressions of its distribution and moments, remain to be addressed. Motivated by this unsatisfactory situation, in this paper we prove that for samples drawn from bivariate normal populations, the distribution of OSCC is asymptotically equivalent to that of the Pearson's product moment correlation coefficient (PPMCC). We also reveal its close relationships with the other two coefficients, namely, Gini correlation (GC) and Spearman's rho (SR). Monte Carlo simulation results agree with the theoretical findings. © 2008 IEEE.published_or_final_versio
- …