arXiv subjects

Junxiang Wu

Publications and source records attributed to Junxiang Wu.

5 recordsLinked to original sources

arXiv2026

Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity

Label Distribution Learning (LDL) models supervision as an instance-wise probability distribution, enabling fine-grained learning under inherent ambiguity, but its success relies on high-fidelity label distributions that are costly to obtain and thus often noisy. Motivated by privacy-sensitive applications, we study Federated Label Distribution Learning (Fed-LDL), where data isolation further induces heterogeneous annotation quality across clients, making local updates unevenly reliable and breaking sample-size-based aggregation (e.g., FedAvg). To address this trust dilemma, we propose FedQual, a quality-aware Fed-LDL framework with two coupled mechanisms: (i) quality-adaptive client training guided by a global semantic anchor that calibrates low-quality clients while preserving high-quality autonomy, and (ii) reliability-aware server aggregation that reweights client contributions by effective reliable information rather than raw sample size. To enable rigorous evaluation, we construct four new Fed-LDL benchmarks (FER-LDL, FI-LDL, PIPAL-LDL, and KADID-LDL) with controlled annotation quality disparity. We further provide a theoretical guarantee showing that under heterogeneous supervision quality, client-specific calibration is strictly better than any uniform calibration. Extensive experiments on the proposed benchmarks demonstrate the effectiveness of FedQual.

cs.LG↗

arXiv2026

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning

Federated Multi-Label Learning is a distributed paradigm where multiple clients possess heterogeneous multi-label data and perform collaborative learning under privacy constraints without sharing raw data. However, modeling label correlations under heterogeneous distributions remains challenging. Due to client-specific label spaces and varying co-occurrence patterns, correlations learned by individual clients inevitably deviate from the global structure, a phenomenon we term label correlation drift. To address this, we propose FedHarmony, a framework that harmonizes heterogeneous label correlations across clients. It introduces consensus correlation, capturing agreement among other clients and serving as a global teacher to correct biased local estimates. During aggregation, FedHarmony evaluates each client by both data size and correlation quality, assigning weights accordingly. Moreover, we develop an accelerated optimization algorithm for FedHarmony and theoretically establish faster convergence without sacrificing accuracy. Experiments on real-world federated multi-label datasets show that FedHarmony consistently outperforms state-of-the-art methods.

cs.LG↗

arXiv2026

Simulation of complex DNA damage enhancement and biological effect validation for Proton-CAT

Proton therapy has been rapidly advancing due to its excellent conformal index, but its relatively low relative biological effect (RBE) has somewhat limited its therapeutic efficacy for certain tumors. To address this, we previously proposed a nitrogen-targeting Proton-Carbon-Alpha-Therapy (Proton-CAT) enhancement method. In this letter, we present combined multi-scale DNA damage simulations and in vitro cell experiments, further investigating the mechanism of the Proton-CAT. It has been show that $^{15}$N enrichment significantly enhances complex DNA damage induced by high linear energy transfer(LET) particles within tumor regions. Under 30\% $^{15}$N conditions, $\alpha$ and $^{12}$C particle induced DSB++ increased by 175.19\% and 52.94\%, respectively. Furthermore, in vitro cell experiments using $^{15}$N-glutamine ($^{15}$N-Glu) as the $^{15}$N carrier indicated that high concentrations of $^{15}$N-Glu did not bring about significant cytotoxicity. Following 2 Gy irradiation, the cell viability in the 500 $\mu$g/mL $^{15}$N-Glu treated group exhibited a net reduction of about 15.41\% compared to the control group.This indicates that the enhanced effect of Proton-CAT primarily stems from increased complex DNA damage. This work provides a theoretical basis and multi-scale research framework for the development of the Proton-CAT.

physics.med-ph↗

arXiv2024

Proton-CAT: a Novel Strategy for Enhanced Proton Therapy

We present a nitrogen-targeting-Proton-Carbon-Alpha-Therapy method, abbreviated as Proton-CAT, which partially converts protons into carbon-12 and $α$ particles through nuclear reactions between protons and nitrogen-15. Monte Carlo simulations validated the effectiveness of the Proton-CAT, and the study specifically focused on the distribution of relative energy deposition. The results indicated that the presence of nitrogen-15 enhanced the maximum dose level of protons, resulting in more effective damage confined to tumor cells. Statistical analysis of secondary ions has shown that the Proton-CAT significantly increases the production efficiencies of carbon-12 and $α$ particles. Furthermore, it has been revealed that elevating the nitrogen-15 concentration significantly boosts the dose of carbon and $α$ particles within the tumor region. The present work would contribute to the future development of proton therapy.

physics.med-ph↗

arXiv2024

Effect of the ${\rm^{15}N(p,α)^{12}C}$ reaction on the kinetic energy release of water molecule fragmentation

In this work, we investigated the effect of ${\rm^{15}N(p,α)^{12}C}$ reaction produced by the collision between proton and ammonia monohydrate on the kinetic energy release (KER) of water molecule fragmentation. After the occurrence of the nuclear reaction, it was found that the charge states $q$ and the flight speeds $v$ are the main factors affecting the KER of water molecule fragmentation. With the value of $q/v$ increases, the KER distribution gets wider and the peak position changes more pronounced. The energy gained by each fragment is related to the mass of the fragment and the distance of the fragment from the nuclear reaction. In this study, the fragments with smaller masses and the distances far away from the nuclear reaction get higher energies. The fragments of water molecules getting higher energy may induce other factors affecting the radiotherapy effect, which needs more detailed investigations in the future.

physics.chem-ph↗