Results 161 to 170 of about 37,638 (267)
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Pathways to Formalization: Going beyond the Formality Dichotomy
Too often, academics and policy makers interpret formality as a binary choice and formalization as an irreversible process. Yet, formalization has many facets and shades on the business and labor fronts, and firms may not be able or willing to formalize ...
Chacaltana, Juan +3 more
core
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Strengthening aianza formalization support
posterA comprehensive guide about coalition models and ...
Pedreira, Victor Matias
core
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Rule-based formalization of eligibility criteria for clinical trials (abstract)
In this extended abstract, we propose a rule-based formalization of eligibility criteria for clinical trials. The rule-based formalization is implemented by using the logic programming language Prolog.
Ten Teije, A. (author) +2 more
core
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon +3 more
wiley +1 more source
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
Algorithmic formalization: impacts on administrative processes
This paper investigates the influence of algorithms on the administrative processes within public organizations, utilizing the foundational theory of formalization from Walsh and Dewar (1987) as a framework.
Cordella, Antonio, Gualdi, Francesco
core +1 more source

