Tootfinder

Rationally Analyzing Shelby: Proving Incentive Compatibility in a Decentralized Storage Network
Michael Crystal, Guy Goren, Scott Duke Kominers
https://arxiv.org/abs/2510.11866 …

Rationally Analyzing Shelby: Proving Incentive Compatibility in a Decentralized Storage Network
Decentralized storage is one of the most natural applications built on blockchains and a central component of the Web3 ecosystem. Yet despite a decade of active development -- from IPFS and Filecoin to more recent entrants -- most of these storage protocols have received limited formal analysis of their incentive properties. Claims of incentive compatibility are sometimes made, but rarely proven. This gap matters: without well-designed incentives, a system may distribute storage but fail to tru…

Hausdorff dimension of the Wedding cake type surfaces
Bal\'azs B\'ar\'any, Manuj Verma
https://arxiv.org/abs/2510.04613 https://arxiv.org/pdf/2…

Hausdorff dimension of the Wedding cake type surfaces
In this paper, we study the Hausdorff dimension of fractal interpolation surfaces (FISs) over a triangular domain. These FISs are known as `wedding cake surfaces'. These surfaces are the attractor of some deterministic self-affine iterated function systems (IFS) on $\mathbb{R}^3$ generated by a fractal interpolation algorithm. Due to the recent seminal result of Rapaport (Adv. Math. 449 (2024) 109734), the dimension theory of self-affine IFS on $\mathbb{R}^3$ is known whenever the IFS is strong…

SingLEM: Single-Channel Large EEG Model
Jamiyan Sukhbaatar, Satoshi Imamura, Ibuki Inoue, Shoya Murakami, Kazi Mahmudul Hassan, Seungwoo Han, Ingon Chanpornpakdi, Toshihisa Tanaka
https://arxiv.org/abs/2509.17920

SingLEM: Single-Channel Large EEG Model
Current deep learning models for electroencephalography (EEG) are often task-specific and depend on large labeled datasets, limiting their adaptability. Although emerging foundation models aim for broader applicability, their rigid dependence on fixed, high-density multi-channel montages restricts their use across heterogeneous datasets and in missing-channel or practical low-channel settings. To address these limitations, we introduce SingLEM, a self-supervised foundation model that learns rob…

Predicting MacroB12: Data-Driven Assessment of Pre-PEG B12 Utility and Clinical Caveats
Carmen Fr\'ias-Ruiz (Hospital Universitario Nuestra Se\~nora de Candelaria), Jos\'e Mar\'ia G\'alvez-Navas (CIBERESP, Andalusian School of Public Health, Instituto de Investigaci\'on Biosanitaria ibs.GRANADA, University of Granada), Isabel Garc\'ia-Calcerrada (Hospital Universitario Nuestra Se\~nora de Candelaria), Silvia Heras Fl\'orez (Hospital Universitario Nuestra Se\…

Predicting MacroB12: Data-Driven Assessment of Pre-PEG B12 Utility and Clinical Caveats
MacroB12 interference presents a significant challenge in the diagnosis of Vitamin B12 status, potentially masking true deficiency. To establish robust predictors and quantify the utility of pre-polyethylene glycol (PEG) B12 levels, we conducted a retrospective analysis of 875 individuals with hypercobalaminaemia (greater than 1000 pg/mL), using multiple imputation to handle missing data. Multivariable regression modelling revealed that MacroB12 positivity (less than 30% PEG recovery) was indep…