98 research outputs found
Topological Floquet edge states in periodically curved waveguides
We study the Floquet edge states in arrays of periodically curved optical
waveguides described by the modulated Su-Schrieffer-Heeger model. Beyond the
bulk-edge correspondence, our study explores the interplay between band
topology and periodic modulations. By analysing the quasi-energy spectra and
Zak phase, we reveal that, although topological and non-topological edge states
can exist for the same parameters, \emph{they can not appear in the same
spectral gap}. In the high-frequency limit, we find analytically all boundaries
between the different phases and study the coexistence of topological and
non-topological edge states. In contrast to unmodulated systems, the edge
states appear due to either band topology or modulation-induced defects. This
means that periodic modulations may not only tune the parametric regions with
nontrivial topology, but may also support novel edge states.Comment: 11 pages, 5 figure
Floquet-surface bound states in the continuum in a resonantly driven 1D tilted defect-free lattice
We study the Floquet-surface bound states embedded in the continuum (BICs)
and bound states out the continuum (BOCs)in a resonantly driven 1D tilted
defect-free lattice. In contrast to fragile single-particle BICs assisted by
specially tailored potentials, we find that Floquet-surface BICs, stable
against structural perturbations, can exist in a wide range of parameter space.
By using a multiple-time-scale asymptotic analysis in the high-frequency limit,
the appearance of Floquet-surface bound states can be analytically explained by
effective Tamm-type defects at boundaries induced by the resonance between the
periodic driving and tilt. The phase boundary of existing Floquet-surface
states is also analytically given. Based on the repulsion effect of surface
states, we propose to detect transition points and measure the number of
Floquet-surface bound states by quantum walk. Our work opens a new door to
experimental realization of BICs in quantum system.Comment: 8 pages, 4 figures. submitted to Phys.Rev.
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
In this paper, we propose a novel network, SVDFormer, to tackle two specific
challenges in point cloud completion: understanding faithful global shapes from
incomplete point clouds and generating high-accuracy local structures. Current
methods either perceive shape patterns using only 3D coordinates or import
extra images with well-calibrated intrinsic parameters to guide the geometry
estimation of the missing parts. However, these approaches do not always fully
leverage the cross-modal self-structures available for accurate and
high-quality point cloud completion. To this end, we first design a Self-view
Fusion Network that leverages multiple-view depth image information to observe
incomplete self-shape and generate a compact global shape. To reveal highly
detailed structures, we then introduce a refinement module, called
Self-structure Dual-generator, in which we incorporate learned shape priors and
geometric self-similarities for producing new points. By perceiving the
incompleteness of each point, the dual-path design disentangles refinement
strategies conditioned on the structural type of each point. SVDFormer absorbs
the wisdom of self-structures, avoiding any additional paired information such
as color images with precisely calibrated camera intrinsic parameters.
Comprehensive experiments indicate that our method achieves state-of-the-art
performance on widely-used benchmarks. Code will be available at
https://github.com/czvvd/SVDFormer.Comment: Accepted by ICCV 202
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis
Current methodologies in point cloud analysis predominantly explore 3D
geometries, often achieved through the introduction of intricate learnable
geometric extractors in the encoder or by deepening networks with repeated
blocks. However, these approaches inevitably lead to a significant number of
learnable parameters, resulting in substantial computational costs and imposing
memory burdens on CPU/GPU. Additionally, the existing strategies are primarily
tailored for object-level point cloud classification and segmentation tasks,
with limited extensions to crucial scene-level applications, such as autonomous
driving. In response to these limitations, we introduce PointeNet, an efficient
network designed specifically for point cloud analysis. PointeNet distinguishes
itself with its lightweight architecture, low training cost, and plug-and-play
capability, effectively capturing representative features. The network consists
of a Multivariate Geometric Encoding (MGE) module and an optional
Distance-aware Semantic Enhancement (DSE) module. The MGE module employs
operations of sampling, grouping, and multivariate geometric aggregation to
lightweightly capture and adaptively aggregate multivariate geometric features,
providing a comprehensive depiction of 3D geometries. The DSE module, designed
for real-world autonomous driving scenarios, enhances the semantic perception
of point clouds, particularly for distant points. Our method demonstrates
flexibility by seamlessly integrating with a classification/segmentation head
or embedding into off-the-shelf 3D object detection networks, achieving notable
performance improvements at a minimal cost. Extensive experiments on
object-level datasets, including ModelNet40, ScanObjectNN, ShapeNetPart, and
the scene-level dataset KITTI, demonstrate the superior performance of
PointeNet over state-of-the-art methods in point cloud analysis
High-frequency stimulation of nucleus accumbens changes in dopaminergic reward circuit
Deep brain stimulation (DBS) of the nucleus accumbens (NAc) is a potential remedial therapy for drug craving and relapse, but the mechanism is poorly understood. We investigated changes in neurotransmitter levels during high frequency stimulation (HFS) of the unilateral NAc on morphine-induced rats. Sixty adult Wistar rats were randomized into five groups: the control group (administration of saline), the morphine-only group (systematic administration of morphine without electrode implantation), the morphine-sham-stimulation group (systematic administration of morphine with electrode implantation but not given stimulation), the morphine-stimulation group (systematic administration of morphine with electrode implantation and stimulation) and the saline-stimulation group (administration of saline with electrode implantation and stimulation). The stimulation electrode was stereotaxically implanted into the core of unilateral NAc and microdialysis probes were unilaterally lowered into the ipsilateral ventral tegmental area (VTA), NAc, and ventral pallidum (VP). Samples from microdialysis probes in the ipsilateral VTA, NAc, and VP were analyzed for glutamate (Glu) and caminobutyric acid (GABA) by high-performance liquid chromatography (HPLC). The levels of Glu were increased in the ipsilateral NAc and VP of morphine-only group versus control group, whereas Glu levels were not significantly changed in the ipsilateral VTA. Furthermore, the levels of GABA decreased significantly in the ipsilateral NAc, VP, and VTA of morphineonly group when compared with control group. The profiles of increased Glu and reduced GABA in morphine-induced rats suggest that the presence of increased excitatory neurotransmission in these brain regions. The concentrations of the Glu significantly decreased while the levels of GABA increased in ipsilateral VTA, NAc, and VP in the morphine-stimulation group compared with the morphine-only group. No significant changes were seen in the morphine-sham stimulation group compared with the morphine-only group. These findings indicated that unilateral NAc stimulation inhibits the morphineinduced rats associated hyperactivation of excitatory neurotransmission in the mesocorticolimbic reward circuit
Dietary fiber intake and non-alcoholic fatty liver disease: The mediating role of obesity
Background and aimsDietary pattern rich in fiber is negatively associated with the risk of non-alcoholic fatty liver disease (NAFLD). Meanwhile, obesity is a known predisposing factor for NAFLD. Nutrient-focused research can enhance the mechanistic understanding of dietary effects. We thus hypothesized that higher dietary fiber intake was associated with lower risk of NAFLD through the mediating role of obesity.MethodsIn this nationwide cross-sectional study, dietary fiber was surveyed using two 24-h recalls. NAFLD and clinically significant fibrosis (CSF) were determined by vibration-controlled transient elastography. Multivariable logistic and linear regression were applied to investigate the association of dietary fiber with NAFLD, CSF, and liver function parameters. We used counterfactual-based mediation analysis to estimate the direct and indirect effect of dietary fiber on NAFLD.ResultsOf the 3,974 participants, ~36.86% and 7.78% of participants were diagnosed with NAFLD and CSF. Compared with participants among the lowest tertile, the highest tertile of dietary fiber consumption was associated with lower odds of NAFLD (OR = 0.81; 95% CI: 0.66–0.98; Poverall = 0.019). Dietary fiber intake appeared to be linked with lower odds of CSF (ORTertile3vs.Tertile1 = 0.81; 95% CI: 0.58–1.14; Poverall = 0.107). Mediation analysis showed that obesity fully mediated the association of dietary fiber with NAFLD. Dietary fiber was associated with improved hepatic parameters.ConclusionsThe findings indicated that increasing dietary fiber intake could confer a greater benefit to protect against NAFLD. Translating these findings regarding dietary fiber into dietary advice might be an attractive strategy for NAFLD prevention
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