Tootfinder

Generalized splitting of algebras with application to a bialgebra structure of Leibniz algebras induced from averaging Lie bialgebras
Chengming Bai, Li Guo, Guilai Liu, Quan Zhao
https://arxiv.org/abs/2509.14137

Generalized splitting of algebras with application to a bialgebra structure of Leibniz algebras induced from averaging Lie bialgebras
The classical notion of splitting a binary quadratic operad $\mathcal{P}$ gives the notion of pre-$\mathcal{P}$-algebras characterized by $\mathcal{O}$-operators, with pre-Lie algebras as a well-known example. Pre-$\mathcal{P}$-algebras give a refinement of the structure of $\mathcal{P}$-algebras and is critical in the Manin triple approach to bialgebras for $\mathcal{P}$-algebras. Motivated by the new types of splitting appeared in recent studies, this paper aims to extend the classical notion…

Breaking Reward Collapse: Adaptive Reinforcement for Open-ended Medical Reasoning with Enhanced Semantic Discrimination
Yizhou Liu, Jingwei Wei, Zizhi Chen, Minghao Han, Xukun Zhang, Keliang Liu, Lihua Zhang
https://arxiv.org/abs/2508.12957

Breaking Reward Collapse: Adaptive Reinforcement for Open-ended Medical Reasoning with Enhanced Semantic Discrimination
Reinforcement learning (RL) with rule-based rewards has demonstrated strong potential in enhancing the reasoning and generalization capabilities of vision-language models (VLMs) and large language models (LLMs), while reducing computational overhead. However, its application in medical imaging remains underexplored. Existing reinforcement fine-tuning (RFT) approaches in this domain primarily target closed-ended visual question answering (VQA), limiting their applicability to real-world clinical…

HeteroRAG: A Heterogeneous Retrieval-Augmented Generation Framework for Medical Vision Language Tasks
Zhe Chen, Yusheng Liao, Shuyang Jiang, Zhiyuan Zhu, Haolin Li, Yanfeng Wang, Yu Wang
https://arxiv.org/abs/2508.12778

HeteroRAG: A Heterogeneous Retrieval-Augmented Generation Framework for Medical Vision Language Tasks
Medical large vision-language Models (Med-LVLMs) have shown promise in clinical applications but suffer from factual inaccuracies and unreliable outputs, posing risks in real-world diagnostics. While retrieval-augmented generation has emerged as a potential solution, current medical multimodal RAG systems are unable to perform effective retrieval across heterogeneous sources. The irrelevance of retrieved reports affects the factuality of analysis, while insufficient knowledge affects the credib…

BELT: Block Encoding of Linear Transformation on Density Matrices
Fuchuan Wei, Rundi Lu, Yuguo Shao, Junfeng Li, Jin-Peng Liu, Zhengwei Liu
https://arxiv.org/abs/2508.12858 http…

BELT: Block Encoding of Linear Transformation on Density Matrices
Linear maps that are not completely positive play a crucial role in the study of quantum information, yet their non-completely positive nature renders them challenging to realize physically. The core difficulty lies in the fact that when acting such a map $\mathcal{N}$ on a state $ρ$, $\mathcal{N}(ρ)$ may not correspond to a valid density matrix, making it difficult to prepare directly in a physical system. We introduce Block Encoding of Linear Transformation (BELT), a systematic protocol tha…

😅 Wearable sensor could help patients with bipolar disorder track medication levels through sweat
https://medicalxpress.com/news/2025-07-wearable-sensor-patients-bipolar-disorder.html

Wearable sensor could help patients with bipolar disorder track medication levels through sweat
Although lithium is highly effective in treating bipolar disorder, the chemical has a narrow therapeutic window—too high a dose can be toxic to patients, causing kidney damage, thyroid damage, or even death, while too low a dose renders the treatment ineffective.

Shi-type and Hamilton-type gradient estimates for a general parabolic equation under compact Finsler $CD(-K,N)$ geometric flows
Yijie Miao, Bin Shen
https://arxiv.org/abs/2506.14776

Shi-type and Hamilton-type gradient estimates for a general parabolic equation under compact Finsler $CD(-K,N)$ geometric flows
Recently, the Li-Yau-type gradient estimates for positive solutions to parabolic equations \begin{equation} \partial_t u=Δu+\mathcal{R}_1u+\mathcal{R}_2u^α+\mathcal{R}_3u(\log u)^β,\notag \end{equation} under the general compact Finsler $CD(-K,N)$ geometric flow are studied. Here $\mathcal{R}_1$,$\mathcal{R}_2$,$\mathcal{R}_3$ $\in$ $ C^{1}(M,[0,T])$, $α$ and $β$ are both positive constants, $T$ is the maximal existence time for the flow. However, compared with the Riemannian ca…

MExplore: an entity-based visual analytics approach for medical expertise acquisition
Xiao Pang, Yan Huang, Chang Liu, JiYuan Liu, MingYou Liu
https://arxiv.org/abs/2507.12337

MExplore: an entity-based visual analytics approach for medical expertise acquisition
Acquiring medical expertise is a critical component of medical education and professional development. While existing studies focus primarily on constructing medical knowledge bases or developing learning tools based on the structured, private healthcare data, they often lack methods for extracting expertise from unstructured medical texts. These texts constitute a significant portion of medical literature and offer greater flexibility and detail compared to structured data formats. Furthermore…

Pathwise regularity of solutions for a class of elliptic SPDEs with symmetric L\'evy noise
Juan J. Jim\'enez
https://arxiv.org/abs/2507.12656 https…

Pathwise regularity of solutions for a class of elliptic SPDEs with symmetric Lévy noise
In this article, we investigate the existence and uniqueness of random-field solutions to the elliptic SPDE $-\mathcal{L}u=\dotξ$ on a bounded domain $D$ with Dirichlet boundary conditions $u=0$ on $\partial D$, driven by symmetric Lévy noise $\dotξ$. Under general sufficient conditions on the coefficients of the second-order operator $\mathcal{L}$, we prove the existence of a mild solution via the corresponding Green's function and show that the same framework applies to the spectral fracti…

An Efficient Medical Image Classification Method Based on a Lightweight Improved ConvNeXt-Tiny Architecture
Jingsong Xia, Yue Yin, Xiuhan Li
https://arxiv.org/abs/2508.11532 htt…

An Efficient Medical Image Classification Method Based on a Lightweight Improved ConvNeXt-Tiny Architecture
Intelligent analysis of medical imaging plays a crucial role in assisting clinical diagnosis. However, achieving efficient and high-accuracy image classification in resource-constrained computational environments remains challenging. This study proposes a medical image classification method based on an improved ConvNeXt-Tiny architecture. Through structural optimization and loss function design, the proposed method enhances feature extraction capability and classification performance while redu…

Codimensions-Two Submanifolds Contained in the Light-like Hypercylinder $\mathcal{LC}^n\times\mathbb R$
Ali Gineli, Hazal Y\"ur\"uk, Nurettin Cenk Turgay
https://arxiv.org/abs/2508.11653

Codimensions-Two Submanifolds Contained in the Light-like Hypercylinder $\mathcal{LC}^n\times\mathbb R$
In this paper, we investigate space-like codimension-two submanifolds of the Lorentz-Minkowski space $\mathbb{E}_1^{n+2}$ constrained to lie on the light-like hypercylinder $\mathcal{LC}^n \times \mathbb{R}$ over the light cone $\mathcal{LC}^n$. By constructing a geometrically defined global frame field on the submanifold, we analyze the geometric interpretations of the associated extrinsic invariants by providing characterizations of (pseudo-)isotropic and pseudo-umbilical submanifolds, as wel…