Results 31 to 40 of about 13,970 (183)
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang +6 more
wiley +1 more source
Beyond the Ban—Shedding Light on Smallholders' Price Vulnerability in Indonesia's Palm Oil Industry
ABSTRACT The Indonesian government imposed a palm oil export ban in April 2022 to address rising cooking oil prices. This study explores oil palm smallholders' vulnerability to the policy using descriptive statistics, Lasso, and post‐Lasso OLS regressions.
Charlotte‐Elena Reich +3 more
wiley +1 more source
This review summarizes key advances from 2024 to 2025 that are reshaping esophageal cancer surgery toward a strategy‐oriented, personalized paradigm through the integration of immunotherapy, population aging, and intelligent technologies. Adjuvant nivolumab after neoadjuvant chemoradiotherapy remains the only perioperative approach with durable benefit,
Shuichiro Oya +2 more
wiley +1 more source
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
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 +1 more
wiley +1 more source
Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks
Bayesian Networks (BNs) represent conditional probability relations among a set of random variables (nodes) in the form of a directed acyclic graph (DAG), and have found diverse applications in knowledge discovery.
Kucukyavuz, Simge +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
An Algorithmic Theory of Dependent Regularizers, Part 1: Submodular Structure [PDF]
We present an exploration of the rich theoretical connections between several classes of regularized models, network flows, and recent results in submodular function theory.
Koepke, Hoyt, Meila, Marina
core
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
ABSTRACT This study presents a strong framework for the detection and classification of Submerged Cultural Heritage Assets (SCHA) in shallow marine environments using the integration of multibeam echosounder and airborne LiDAR bathymetry with object‐based image analysis and fuzzy logic–based classification.
Łukasz Janowski +4 more
wiley +1 more source

