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Osmotic forces modify lipid membrane fluctuations
Amaresh Sahu
https://arxiv.org/abs/2510.10352 https://arxiv.org/pdf/2510.10352

Osmotic forces modify lipid membrane fluctuations
In hydrodynamic descriptions of lipid bilayers, the membrane is often approximated as being impermeable to the surrounding, solute-containing fluid. However, biological and in vitro lipid membranes are influenced by their permeability and the resultant osmotic forces -- whose effects remain poorly understood. Here, we study the dynamics of a fluctuating, planar lipid membrane that is ideally selective: fluid can pass through it, while the electrically-neutral solutes cannot. We find that the ca…

Leave No TRACE: Black-box Detection of Copyrighted Dataset Usage in Large Language Models via Watermarking
Jingqi Zhang, Ruibo Chen, Yingqing Yang, Peihua Mai, Heng Huang, Yan Pang
https://arxiv.org/abs/2510.02962

Leave No TRACE: Black-box Detection of Copyrighted Dataset Usage in Large Language Models via Watermarking
Large Language Models (LLMs) are increasingly fine-tuned on smaller, domain-specific datasets to improve downstream performance. These datasets often contain proprietary or copyrighted material, raising the need for reliable safeguards against unauthorized use. Existing membership inference attacks (MIAs) and dataset-inference methods typically require access to internal signals such as logits, while current black-box approaches often rely on handcrafted prompts or a clean reference dataset for…

Voice-guided Orchestrated Intelligence for Clinical Evaluation (VOICE): A Voice AI Agent System for Prehospital Stroke Assessment
Julian Acosta, Scott Adams, Julius Kernbach, Romain Hardy, Sung Eun Kim, Luyang Luo, Xiaoman Zhang, Shreya Johri, Mohammed Baharoon, Pranav Rajpurkar
https://arxiv.org/abs/2507.22898

Voice-guided Orchestrated Intelligence for Clinical Evaluation (VOICE): A Voice AI Agent System for Prehospital Stroke Assessment
We developed a voice-driven artificial intelligence (AI) system that guides anyone - from paramedics to family members - through expert-level stroke evaluations using natural conversation, while also enabling smartphone video capture of key examination components for documentation and potential expert review. This addresses a critical gap in emergency care: current stroke recognition by first responders is inconsistent and often inaccurate, with sensitivity for stroke detection as low as 58%, c…

Membership Inference Attacks on LLM-based Recommender Systems
Jiajie He, Yuechun Gu, Min-Chun Chen, Keke Chen
https://arxiv.org/abs/2508.18665 https://arxi…

Membership Inference Attacks on LLM-based Recommender Systems
Large language models (LLMs) based Recommender Systems (RecSys) can flexibly adapt recommendation systems to different domains. It utilizes in-context learning (ICL), i.e., the prompts, to customize the recommendation functions, which include sensitive historical user-specific item interactions, e.g., implicit feedback like clicked items or explicit product reviews. Such private information may be exposed to novel privacy attack. However, no study has been done on this important issue. We desig…

Memorization in Fine-Tuned Large Language Models
Danil Savine, Muni Sreenivas Pydi, Jamal Atif, Olivier Capp\'e
https://arxiv.org/abs/2507.21009 https://

Memorization in Fine-Tuned Large Language Models
This study investigates the mechanisms and factors influencing memorization in fine-tuned large language models (LLMs), with a focus on the medical domain due to its privacy-sensitive nature. We examine how different aspects of the fine-tuning process affect a model's propensity to memorize training data, using the PHEE dataset of pharmacovigilance events. Our research employs two main approaches: a membership inference attack to detect memorized data, and a generation task with prompted pref…

Aerophilic Debubbling
Bert J. C. Vandereydt, Saurabh Nath, Kripa K. Varanasi
https://arxiv.org/abs/2509.12523 https://arxiv.org/pdf/2509.12523

Aerophilic Debubbling
In this letter, we characterize quantitatively the complex phenomenon of debubbling via aerophilic membranes by examining local interactions at the scale of single bubbles. We identify three asymptotic limits of evacuation dictated by Rayleigh, Ohnesorge and Darcy dynamics, the physics of which we capture using simple scaling laws. We show that beyond a threshold permeability, bubble evacuations become constant in time - a feature we understand as an inertio-capillary limit. Our experiments rev…

Thickness Dependence and Fundamental Limitations for Ion Permeation in Nanoscale Films
Jay Prakash Singh, Konstantin I. Morozov, Viatcheslav Freger
https://arxiv.org/abs/2509.14725

Thickness Dependence and Fundamental Limitations for Ion Permeation in Nanoscale Films
Nanoscale films play a central role in biology and osmotic separations. Their water/salt selectivity is often regarded as intrinsic property, favoring thinner membranes for faster permeation. Here we highlight and quantify a fundamental limitation arising from the dependence of ion self-energy on film thickness, governed by its ratio to Bjerrum length. The resulting relation factors out this dependence from intrinsic ion permeability, which agrees well with available data and enables evaluation…