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…

On exponential separation of analytic self-conformal sets on the real line
Bal\'azs B\'ar\'any, Istv\'an Kolossv\'ary, Sascha Troscheit
https://arxiv.org/abs/2509.07888

On exponential separation of analytic self-conformal sets on the real line
In a recent article, Rapaport showed that the there is no dimension drop for exponentially separated analytic IFSs on the real line. We show that the set of such exponentially separated IFSs in the space of analytic IFSs contains an open and dense set in the $\mathcal{C}^2$ topology. Moreover, we give a sufficient condition for the IFS to be exponentially separated which allows us to construct explicit examples which are exponentially separated. The key technical tool is the introduction of the…

Self-heating in SIS Mixers: Experimental Evidence and Theoretical Modeling
Wenlei Shan, Shohei Ezaki
https://arxiv.org/abs/2509.04521 https://arxiv.org/pdf…

Self-heating in SIS Mixers: Experimental Evidence and Theoretical Modeling
This work investigates the relationship between self-heating and the characteristic features observed in the current-voltage characteristics (IVCs) of superconductor-insulator-superconductor (SIS) junctions. Finite-element analysis is employed to evaluate the steady-state temperature distribution around SIS junctions, explicitly accounting for the temperature dependence of the thermal conductivities of the constituent materials. This approach enables flexible estimation of self-heating under va…

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…

Error estimates of linear decoupled structure-preserving incremental viscosity splitting methods for the Cahn--Hilliard--Navier--Stokes system
Baolin Kuang, Hongfei Fu, Xiaoli Li
https://arxiv.org/abs/2508.01141

Error estimates of linear decoupled structure-preserving incremental viscosity splitting methods for the Cahn--Hilliard--Navier--Stokes system
We propose first- and second-order time discretization schemes for the coupled Cahn--Hilliard--Navier--Stokes model, leveraging the incremental viscosity splitting (IVS) method. The schemes combine the scalar auxiliary variable method and the zero-energy-contribution approach, resulting in a linear, decoupled numerical framework. At each time step, they only require to solve a sequence of constant-coefficient equations, along with a linear equation with one unknown, making the algorithms comput…

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…