Results 211 to 220 of about 45,005 (294)

Novel Distribution-Free Eigenspace Framework via Truncated Singular Value Decomposition for High-Resolution Dengue Clusters [PDF]

Muhammad Fayyaz, Alamgir Khalil, Hameed Ali, Zeineb Klai, Sami Ullah, Abdulrahman Obaid Alshammari   +5 more
openalex   +1 more source

Analyzing individual rent price ratios in eastern German agricultural land markets: A GAMLSS approach

Agribusiness, EarlyView.
Abstract This study explores the rent price ratio in agricultural land markets, crucial for evaluating market efficiency, policy needs, and farmer decision‐making. Traditionally, the analyses faced challenges due to the absence of concurrent sale and rent data for the same land, potentially leading to biased results.
Marius Michels, Cord‐Friedrich von Hobe, Miryam Sarah Merk, Thomas Kneib, Oliver Musshoff   +4 more
wiley   +1 more source

Predicting plant trait dynamics from genetic markers. [PDF]

Nat Plants
Hobby D, Tong H, Heuermann M, Mbebi AJ, Laitinen RAE, Dell'Acqua M, Altmann T, Nikoloski Z.   +7 more
europepmc   +1 more source

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

Comparison of Low-Rank Denoising Methods for Dynamic Deuterium MRSI at 7 T. [PDF]

NMR Biomed
Duguid A, Niess F, Bogner W, Hingerl L, Bader V, Frese S, Osburg A, Lanz B, Alves B, Cudalbu C, Robinson SD, Eckstein K, Strasser B.   +12 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

A reduced basis decomposition approach to efficient data collection in pairwise comparison studies. [PDF]

Comput Stat
Jiang J, Marsh J, Seymour R.
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Recent Trends in Metabolomics by NMR Spectroscopy

Angewandte Chemie, EarlyView.
AI tools were applied to analyze more than 5 000 publications indexed in Scopus (2018–2025), identifying key trends and research directions in NMR‐based metabolomics. The artificial intelligence‐assisted workflow classified papers into six main fields of application, human health, food and nutrition, veterinary science, plants, environment, and ...
Giorgio Di Paco, Gaia Meoni, Veronica Ghini, Alessia Vignoli, Leonardo Tenori, Paola Turano, Claudio Luchinat   +6 more
wiley   +2 more sources

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source