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