In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu +6 more
wiley +1 more source
SHAP-based explainable AI framework for autism severity classification using 3D motor biomarkers. [PDF]
Fırat Y.
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Artificial intelligence models for point-of-care ultrasound diagnostics in dogs. [PDF]
Martinez R +7 more
europepmc +1 more source
Who Are the Consumers of European Farmers' Markets? A Cross‐Country Analysis
ABSTRACT With substantial growth in the number of farmers' markets (FMs) in developed countries, the number of consumers visiting FMs is also increasing. This study comparatively assesses the consumers of FMs in three European countries where FMs traditionally play a distinctive role in food supply chains.
Áron Török +6 more
wiley +1 more source
THE AMOUNT OF TRANSMITTED INFORMATION IN CONFUSION MATRIX
TAROW INDOW, SAKIKO SONO
openaire +2 more sources
U.S. Consumer Preferences for Cage‐Free Eggs and Hen Housing Policies
ABSTRACT Farm animal welfare (FAW) continues to be a divisive issue in the egg industry. In the United States, 10 states and most major retailers have implemented policies or voluntary pledges to transition to 100% cage‐free egg sales. We use best‐worst scaling and discrete choice experiments to evaluate U.S.
Vincenzina Caputo +3 more
wiley +1 more source
Slope stability prediction via TrAdaBoost transfer learning: integrating physics and data into a double-driven framework. [PDF]
Ren M +5 more
europepmc +1 more source
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Semi-Quantitative Detection of Borax Adulteration in Wheat Flour Based on Microwave Non-Destructive Testing and Machine Learning. [PDF]
Kang M, Yang J, Ren Y, Bai X.
europepmc +1 more source

