arXiv subjects

Haiyang Yan

Publications and source records attributed to Haiyang Yan.

7 recordsLinked to original sources

arXiv2026

X-Hinges: 3D Printing Self-Sensing Compliant Mechanisms for Continuous and Multi-DOF Motion Sensing

We present X-Hinges, a design and fabrication method for self-sensing compliant mechanisms based on multi-material FDM 3D printing. By co-printing two conductive filaments of different conductivities within a compliant body, we embed resistive sensing elements directly during fabrication without post-assembly, enabling continuous motion sensing across multiple degrees of freedom in a single print. The structure supports three degrees of freedom, each equipped with a dedicated sensing element configuration for multi-DOF motion estimation. We develop a precision data acquisition system and data-driven regression models that enable continuous, real-time motion sensing. We also introduce an interactive design tool for customizing the geometry, mechanical properties, degrees of freedom, and sensing configurations of X-Hinges. The tool also supports augmenting existing 3D models with self-sensing structures, endowing ordinary objects with continuous multi-DOF sensing capabilities. Finally, we present a set of application examples demonstrating the capability of X-Hinges for fabricating personalized interactive interfaces.

cs.HC↗

arXiv2026

NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation

Accurate 3D neuron segmentation in fluorescence microscopy is critical for neuroscience. However, the sparse and elongated morphology of neurons poses significant challenges to existing segmentation methods. These methods struggle to preserve both local details and global topology, leading to fragmented results. To address this, we propose NeuroRefiner, a multi-agent system that formalizes the human expert workflow involving iterative global observation and local editing. Specifically, NeuroRefiner comprises three collaborative agents dedicated to diagnosing topological errors, generating correction instructions, and validating refinement quality. To facilitate agent instruction-guided segmentation refinement, we propose TopoRefineNet, a dedicated 3D U-Net-based tool that leverages cross-modality feature fusion to generate refined masks. Through multi-round agent reasoning and voxel-level editing, NeuroRefiner produces topologically more accurate segmentations with enhanced interpretability. Experiments on the BigNeuron, CWMBS, and ZBFWB datasets demonstrate that NeuroRefiner outperforms state-of-the-art methods, notably achieving a 3.02% improvement in F1 score on the challenging ZBFWB dataset.

cs.CV↗

arXiv2026

Probe-EM: Targeted Neuron Tracing via Training-Free Semantic Verification

Establishing large-scale, high-resolution neural connectivity maps is fundamental to elucidating the structural basis of brain function. However, when processing terabyte- or petabyte-scale electron microscopy data, over-segmentation inherent in automated reconstruction algorithms remains a critical bottleneck, requiring extensive manual proofreading spanning person-years. To alleviate the heavy reliance on annotated data and the limited flexibility of conventional tracing methods, we propose a training-free, targeted neuron tracing framework. Specifically, we introduce a skeleton-guided Heuristic Spatial Search paradigm that leverages geometric priors to iteratively reconstruct neuronal morphologies through a probing-verification cycle. To achieve robust zero-shot semantic verification, we further develop a Dimension-Aware Semantic Verification strategy built upon the foundation model NeuroSAM 2. This strategy resolves intra-slice splits via Planar Ensemble Consensus and inter-slice splits via Axial Spatio-Temporal Propagation. Notably, we integrate the proposed workflow into the Neuroglancer visualization platform, enabling an interactive human-in-the-loop proofreading system. Experimental results demonstrate that the proposed method outperforms supervised baselines and reduces manual proofreading time by 33.4%. The source code is publicly available at https://github.com/HeadLiuYun/Probe-EM.

cs.CV↗

arXiv2026

Symphony: A Cognitively-Inspired Multi-Agent System for Long-Video Understanding

Despite rapid developments and widespread applications of MLLM agents, they still struggle with long-form video understanding (LVU) tasks, which are characterized by high information density and extended temporal spans. Recent research on LVU agents demonstrates that simple task decomposition and collaboration mechanisms are insufficient for long-chain reasoning tasks. Moreover, directly reducing the time context through embedding-based retrieval may lose key information of complex problems. In this paper, we propose Symphony, a multi-agent system, to alleviate these limitations. By emulating human cognition patterns, Symphony decomposes LVU into fine-grained subtasks and incorporates a deep reasoning collaboration mechanism enhanced by reflection, effectively improving the reasoning capability. Additionally, Symphony provides a VLM-based grounding approach to analyze LVU tasks and assess the relevance of video segments, which significantly enhances the ability to locate complex problems with implicit intentions and large temporal spans. Experimental results show that Symphony achieves state-of-the-art performance on LVBench, LongVideoBench, VideoMME, and MLVU, with a 5.0% improvement over the prior state-of-the-art method on LVBench. Code is available at https://github.com/Haiyang0226/Symphony.

cs.CV↗

arXiv2018

New Experimental Limits on Exotic Spin-Spin-Velocity-Dependent Interactions By Using SmCo$_5$ Spin Sources

We report the latest results of searching for possible new macro-scale spin-spin-velocity-dependent forces (SSVDFs) based on specially designed iron-shielded SmCo$_5$ (ISSC) spin sources and a spin exchange relaxation free (SERF) co-magnetometer. The ISSCs have high net electron spin densities of about $1.7\times 10^{21}$ cm$^{-3}$, which mean high detecting sensitivity; and low magnetic field leakage of about $\sim$mG level due to iron shielding, which means low detecting noise. With help from the ISSCs, the high sensitivity SERF co-magnetometer, and the similarity analysis method, new constraints on SSVDFs with forms of $V_{6+7}$, $V_8$, $V_{15}$, and $V_{16}$ have been obtained, which represent the tightest limits in force range of 5 cm -- 1 km to the best of our knowledge.

hep-ex↗

arXiv2012

Laboratory Search for Spin-dependent Short-range Force from Axion-Like-Particles using Optically Polarized 3He gas

The possible existence of short-range forces between unpolarized and polarized spin-1/2 particles has attracted the attention of physicists for decades. These forces are predicted in various theories and provide a possible new source for parity (P) and time reversal (T) symmetry violation. We use an ensemble of polarized 3He gas in a cell with a 250 um thickness glass window to search for a force from scalar boson exchange over a sub-millimeter ranges. This interaction would produce a NMR frequency shift as an unpolarized mass is moved near and far from the polarized ensemble. We report a new upper bound on the product g_{s}g_{p}^{n} of the scalar couplings to the fermions in the unpolarized mass, and the pseudoscalar coupling of the polarized neutron in the 3He nucleus for force ranges from 1e-4 to 1e-2 m, which corresponds to a mass range of 2e-3 to 2e-5 eV for the scalar boson.

nucl-ex↗

arXiv2007

The Neutron Energy Spectrum Study from the Phase II Solid Methane Moderator at the LENS Neutron Source

Neutron energy spectrum measurements from a solid methane moderator were performed at the Low Energy Neutron Source (LENS) at Indiana University Cyclotron Facility (IUCF) to verify our neutron scattering model of solid methane. The time-of-flight method was used to measure the energy spectrum of the moderator in the energy range of 0.1$meV\sim$ 1$eV$. Neutrons were counted with a high efficiency $^{3}{He}$ detector. The solid methane moderator was operated in phase II temperature and the energy spectra were measured at the temperatures of 20K and 4K. We have also tested our newly-developed scattering kernels for phase II solid methane by calculating the neutron spectral intensity expected from the methane moderator at the LENS neutron source using MCNP (Monte Carlo N-particle Transport Code). Within the expected accuracy of our approximate approach, our model predicts both the neutron spectral intensity and the optimal thickness of the moderator at both temperatures. The predictions are compared to the measured energy spectra. The simulations agree with the measurement data at both temperatures.

nucl-ex↗