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Related Articles from SNS
TRUST-SCF: Transformer-based Risk Understanding and Scoring for Transactional Supply Chain Finance
arXiv:2606.08140v1 Announce Type: new Abstract: Supply Chain Finance (SCF) and LendTech platforms need credit scoring systems that respond to evolving transaction behavior, repayment delays, and active exposure. We propose TRUST-SCF, a transformer-based framework for transaction-level risk prediction and dynamic credit scoring. Each user history is represented as a sequence of transaction tokens containing utilization, repayment delay and transaction position.
Augmented Roothaan-Hall Hessian Applied to Spin-Restricted Open-Shell Density-Functional Theory
arXiv:2606.03709v1 Announce Type: new Abstract: We generalize the augmented Roothaan-Hall (ARH) Hessian formalism to the self-consistent field (SCF) optimization of spin-restricted open-shell (RO) wavefunctions, encompassing high-spin, low-spin, and two-determinant electronic states. A detailed ARH formulation is presented. We demonstrate that ARH is a highly efficient optimization algorithm for rapidly identifying accurate SCF minima, primarily owing to its systematic construction of an...
FBH1 Reverses Stalled Replication Forks via Sequential Unwinding of Nascent Strands
Replication fork reversal is a DNA damage tolerance mechanism important for genome stability that entails annealing of parental DNA to push the fork backwards. F-box helicase 1 (FBH1) is a 3'-5' ssDNA translocase and SCF (SKP-CUL1-F-box) E3 ubiquitin ligase that catalyzes fork reversal and limits aberrant recombination, yet how its helicase activity drives strand annealing is unknown. Here, using single-molecule and biochemical assays, we show that SCFFBH1 reverses forks through a two-stage...
Stanley Cup Final preview: Key players, goalie con...
From a starting point of 16 teams, the 2026 Stanley Cup playoff field is now down to two. The Carolina Hurricanes blew past their competition in the Eastern Conference, needing only 13 games to win three series. The Vegas Golden Knights needed 16 games to get past their three opponents, but that included a four-game sweep of the top-seeded Colorado Avalanche.
Derivative Informed Learning of Exchange-Correlation Functionals
arXiv:2606.04279v1 Announce Type: new Abstract: Machine-learned (ML) exchange-correlation (XC) functionals aim to replace human-designed density functional approximations by learning directly from reference data, but they still do not consistently outperform traditional $\mathcal{O}(N^4)$-scaling hybrid functionals. We study a hybrid-distillation setting in which $\mathcal{O}(N^3)$-scaling ML-XC functionals are trained to reproduce B3LYP/def2-SVP targets. We introduce Derivative Informed...
Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations
arXiv:2606.00401v1 Announce Type: cross Abstract: Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architectures. In the context of the LimitX project, we propose a data-driven framework to accelerate these calculations.
Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations
arXiv:2606.00401v1 Announce Type: new Abstract: Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architectures. In the context of the LimitX project, we propose a data-driven framework to accelerate these calculations.