Tootfinder

Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
Nolbert Morales, Edward A. Turner
https://arxiv.org/abs/2508.12424 https://

Generalized Quasispecies Model with Time Delays and Periodic Fluctuations in Replication
In this research, we present a generalized quasispecies model in which population growth is governed by an arbitrary nonlinear function incorporating time delays. We begin by demonstrating that, under the constant population constraint, the dynamics of the system with time delays remain confined to the invariant manifold for both forward and backward time evolution. Furthermore, we establish that in this modified quasispecies model, defined on a single-peak fitness landscape, in the presence of…

Airborne acoustic emission enables sub-scanline keyhole porosity quantification and effective process characterization for metallic laser powder bed fusion
Haolin Liu, David Guirguis, Xuzhe Zeng, Logan Maurer, Vigknesh Rajan, Niloofar Sanaei, Chi-Ta Yang, Jack L. Beuth, Anthony D. Rollett, Levent Burak Kara
https://arxiv.org/abs/2508.13492…

Airborne acoustic emission enables sub-scanline keyhole porosity quantification and effective process characterization for metallic laser powder bed fusion
Keyhole-induced (KH) porosity, which arises from unstable vapor cavity dynamics under excessive laser energy input, remains a significant challenge in laser powder bed fusion (LPBF). This study presents an integrated experimental and data-driven framework using airborne acoustic emission (AE) to achieve high-resolution quantification of KH porosity. Experiments conducted on an LPBF system involved in situ acquisition of airborne AE and ex situ porosity imaging via X-ray computed tomography (XCT…

Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
Niloofar Ramezani, Martin Slawski
https://arxiv.org/abs/2507.20079 https://

Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
Beta regression is commonly employed when the outcome variable is a proportion. Since its conception, the approach has been widely used in applications spanning various scientific fields. A series of extensions have been proposed over time, several of which address variable selection and penalized estimation, e.g., with an $\ell_1$-penalty (LASSO). However, a theoretical analysis of this popular approach in the context of Beta regression with high-dimensional predictors is lacking. In this pape…

NLAFormer: Transformers Learn Numerical Linear Algebra Operations
Zhantao Ma, Yihang Gao, Michael K. Ng
https://arxiv.org/abs/2508.19557 https://arxiv.org/…

NLAFormer: Transformers Learn Numerical Linear Algebra Operations
Transformers are effective and efficient at modeling complex relationships and learning patterns from structured data in many applications. The main aim of this paper is to propose and design NLAFormer, which is a transformer-based architecture for learning numerical linear algebra operations: pointwise computation, shifting, transposition, inner product, matrix multiplication, and matrix-vector multiplication. Using a linear algebra argument, we demonstrate that transformers can express such o…

Layered Normalized Min-Sum Decoding with Bit Flipping for FDPC Codes
Niloufar Hosseinzadeh, Mohsen Moradi, Hessam Mahdavifar
https://arxiv.org/abs/2510.01019 https://

Layered Normalized Min-Sum Decoding with Bit Flipping for FDPC Codes
Fair-density parity-check (FDPC) codes have been recently introduced demonstrating improved performance compared to low-density parity-check (LDPC) codes standardized in 5G systems particularly in high-rate regimes. In this paper, we introduce a layered normalized min-sum (LNMS) message-passing decoding algorithm for the FDPC codes. We also introduce a syndrome-guided bit flipping (SGBF) method to enhance the error-correction performance of our proposed decoder. The LNMS decoder leverages confl…