arXiv preprints from January 1, 2026 through September 27, 2026 — 07:04:44 EST
Exposure to psychoactive substances during pregnancy, such as cannabis, can disrupt neurodevelopment and alter large-scale brain networks, yet identifying their neural signatures remains challenging. We introduced KOCOBrain: KuramotO COupled Brain Graph Network; a unified graph neural network framework that integrates structural and...
Human vision combines low-resolution "gist" information from the visual periphery with sparse but high-resolution information from fixated locations to construct a coherent understanding of a visual scene. In this paper, we introduce MetamerGen, a tool for generating scenes that are aligned with latent human scene representations....
A dual pre-Poisson algebra is an algebraic structure that integrates a permutative algebra and a Leibniz algebra under certain compatibility conditions. As the Koszul dual notion of the pre-Poisson algebra, this structure serves as a natural generalization of the Poisson algebra. In this paper, we commence a study on dual pre-Poisson...
In this paper, we introduce a framework for contextual distributionally robust optimization (DRO) that considers the causal and continuous structure of the underlying distribution by developing interpretable and tractable decision rules that prescribe decisions using covariates. We first introduce the causal Sinkhorn discrepancy...
Anomalous Hall effect studies on ultrathin Si(50Angstrom)/Fe(t_Fe) bilayers were performed at 300 K. Giant enhancements of about 60 times in saturation anomalous Hall resistivity and 265 times in anomalous Hall coefficient (R_s) were observed upon decreasing the Fe layer thickness t_Fe from 200 to 10 Angstrom. The R_s observed for...
Circular cross-section plasma is the most basic form of tokamak plasma and the fundamental configuration for magnetic confinement fusion experiments. Based on the HL-2A limiter discharge experiments, the magnetohydrodynamic (MHD) equilibrium and MHD instability of circular cross-section tokamak plasmas are investigated in this work....
A continuous route from a disordered soup of simple chemical feedstocks to a functional protocell -- a compartment that metabolizes, grows, and propagates -- remains elusive. Here, we show that a homogeneous aqueous chemical mixture containing phosphorus, iron, molybdenum salts and formaldehyde spontaneously self-organizes into...
The ability to engineer optimized protein variants has transformative potential for biotechnology and medicine. Prior sequence-based optimization methods struggle with the high-dimensional complexities due to the epistasis effect and the disregard for structural constraints. To address this, we propose HADES, a Bayesian optimization...
We present the neutral gas morphology of four galaxies from z = 0.22 to 0.47 obtained with the COSMOS HI Large Extragalactic Survey (CHILES). The HI is resolved at the highest redshift with the 7.5 arcsec beam of CHILES and 43 kpc linear scale, with all four galaxies having extended HI. Three are massive galaxies (Mstellar > 3 e10...
In services such as retail audits and urban infrastructure monitoring, a platform dispatches rewarded, location-based micro-tasks to mobile workers traveling along personal origin-destination (OD) trips under hard time budgets. As requests with time constraints arrive online over a finite horizon, the platform must decide which...
Matthew de Brecht raised the question of whether countable frames are continuous lattices. We prove that the continuity of a countable frame implies the quasicontinuity of its corresponding spectrum in the dual specialization order. We further show that this question admits a positive answer if the frame's spectrum is a $T_1$ space or...
We isolate the limit-stage filter construction needed for countable-support symmetric iterations built from standard successor-step symmetric systems. At successor stages we take the $ω_1$-completion of the usual successor-stage symmetry filter. At limit stages of uncountable cofinality, countable supports are bounded and the...
LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and adaptability. They typically under-model dynamic environmental information and assume largely static scenes and casts, offering insufficient support for multi-character orchestration, scene...
Contrastive learning has become a leading self- supervised approach to representation learning across domains, including vision, multimodal settings, graphs, and federated learning. However, recent studies have shown that contrastive learning is susceptible to backdoor and data poisoning attacks. In these attacks, adversaries can...
The speed of sound refers to the rate at which information travels from one point to another. It is a positive quantity and bounded by causality. It is defined as the rate of change of pressure with respect to the system's density. In this article, we derive a covariant equation for the sound wave and demonstrate how the wave equation...
Early diagnosis of melanoma, which can save thousands of lives, relies heavily on the analysis of dermoscopic images. One crucial diagnostic criterion is the identification of unusual pigment network (PN). However, distinguishing between regular (typical) and irregular (atypical) PN is challenging. This study aims to automate the PN...
Accurately assessing model confidence is essential for deploying large language models (LLMs) in mission-critical factual domains. While retrieval-augmented generation (RAG) is widely adopted to improve grounding, confidence calibration in RAG settings remains poorly understood. We conduct a systematic study across four benchmarks,...
Time-varying dielectric metasurfaces that support sharp optical resonances with nontrivial electromagnetic field distributions constitute a unique platform for realizing temporal interfaces for metasurface-guided waves (MGWs). Rapidly changing metasurface resonance enables frequency conversion and temporal scattering of a concurrently...
Simultaneous Machine Translation (SiMT) requires high-quality translations under strict real-time constraints, which traditional policies with only READ/WRITE actions cannot fully address. We extend the action space of SiMT with four adaptive actions: Sentence_Cut, Drop, Partial_Summarization and Pronominalization, which enable...
SiO2/Fe/SiO2 sandwich structure films fabricated by sputtering were studied by varying the Fe layer thickness (t_Fe). The structural and microstructural studies on the samples showed that the Fe layer has grown in nanocrystalline form with (110) texture and that the two SiO2 layers are amorphous. Magnetic measurements performed with...
Personalized large language models (LLMs) adapt model behavior to individual users to enhance user satisfaction, yet personalization can inadvertently distort factual reasoning. We show that when personalized LLMs face factual queries, there exists a phenomenon where the model generates answers aligned with a user's prior history...
Physics-informed extreme learning machines (PIELMs) typically impose boundary and initial conditions through penalty terms, yielding only approximate satisfaction that is sensitive to user-specified weights and can propagate errors into the interior solution. This work introduces Null-Space Projected PIELM (NP-PIELM), achieving exact...
Massively Multiplayer Online (MMO) game servers must handle thousands of simultaneous players while maintaining sub-100ms response times. When server load exceeds capacity, traditional approaches either uniformly throttle all message types regardless of importance (damaging gameplay) or apply fixed heuristic rules that fail to adapt...
Solid-state electrolytes (SSEs) are attractive for next-generation lithium-ion batteries due to improved safety and stability but their low room-temperature ionic conductivity hinders practical application. Experimental synthesis and testing of new SSEs remain time-consuming and resource intensive. Machine learning (ML) offers an...
We attempt to mitigate the persistent tradeoff between risk and return in medium- to long-term portfolio management. This paper proposes a novel LLM-guided no-regret portfolio allocation framework that integrates online learning dynamics, market sentiment indicators, and large language model (LLM)-based hedging to construct...