Dual perfect bases and dual perfect graphs
, 2015 We introduce the notion of dual perfect bases and dual perfect graphs. We show that every integrable highest, weight module V-q, (A) over a quantum generalized Kac-Moody algebra U-q (g) has a dual perfect basis and its dual perfect graph is isomorphic to
Kahng, Byeong Hoon +3 more
core
Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets
Advanced Intelligent Discovery, EarlyView.An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh +4 more
wiley +1 more source
Comparative Evaluation of VisuALL Virtual Reality Perimetry and Humphrey Visual Field Testing in Glaucoma Patients. [PDF]
Clin OphthalmolWeng PJ, Asrani S, Wen JC.
europepmc +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms. [PDF]
Philos Trans A Math Phys Eng SciMinenkova A, Mograby G, Zhan H.
europepmc +1 more source
Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage
Advanced Intelligent Discovery, EarlyView.We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen +5 more
wiley +1 more source
Why is it easier to predict the epidemic curve than to reconstruct the underlying contact network? [PDF]
J Math BiolKeliger D, Horváth I.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Prediction Model for Overall Survival in Patients with Epithelial Ovarian Cancer Undergoing Surgery and Systemic Therapy Based on the 2010-2021 SEER Database. [PDF]
Int J Womens HealthShi H, Zhan S, An Y, He M, Xu Z.
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source