Results 51 to 60 of about 3,063 (257)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Exact certification in global polynomial optimization via sums-of-squares of rational functions with rational coefficients

Journal of Symbolic Computation, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Erich L. Kaltofen, Bin Li, Zhengfeng Yang, Lihong Zhi   +3 more
openaire   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
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

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
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

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang, Zichao Wang, Zhiwei He, Qingquan Wei, Yong Zuo, Linzhen Nie, Zhishuai Yin   +6 more
wiley   +1 more source

Redistributive land reforms, agricultural productivity, and structural change: New cross‐national evidence

American Journal of Agricultural Economics, EarlyView.
Abstract Large‐scale land reforms constitute a substantial redistribution of wealth and reallocation of agricultural land, which is a major form of asset and production input in developing countries. While land redistribution (from the rich to the poor) remains a highly controversial issue, extensive evidence on its effect is limited.
Devashish Mitra, Abdulaziz B. Shifa, Lan Anh Tong, Mehmet A. Ulubasoglu   +3 more
wiley   +1 more source

Choice experiments on land managers' participation in environmental programs: A systematic review and meta‐analysis of estimate validity

American Journal of Agricultural Economics, EarlyView.
Abstract Discrete choice experiments are increasingly being used to estimate land managers' willingness to accept participation in incentive‐based environmental programs. This is a specific application of discrete choice experiments: the estimation of willingness to accept for a private good (program participation) where respondents have to make trade ...
Anastasio J. Villanueva, Angel Perni, Jesus Barreiro‐Hurle   +2 more
wiley   +1 more source

Coefficient functions of the Ehrhart quasi-polynomials of rational polygons

, 2008
5 pages, 2 figures, 2008 International Conference on Information Theory and Statistical Learning (ITSL'08), held in Las Vagas, NV, July ...
openaire   +3 more sources

Upper bounds for the number of factors for a class of polynomials with rational coefficients [PDF]

Acta Arithmetica, 2004
Let \(f(X),g(X)\in{\mathbb Q}[X]\) be two relatively prime polynomials, with \(\deg(f) < \deg(g)\). Using Hilbert's irreducibility theorem, \textit{M. Cavachi} [J. Number Theory 82, 96--99 (2000; Zbl 0985.12001)] proved that the polynomial \(f(X)+pg(X)\) is irreducible for infinitely many rational primes \(p\). Later on, \textit{M. Cavachi, M. Vâjâitu}
openaire   +1 more source