Results 201 to 210 of about 106,296 (285)
Red meat from animals offered a grass diet increases platelet n–3 PUFA in healthy consumers [PDF]
Alison J. McAfee+8 more
openalex +1 more source
This paper describes the basis for AInsectID Version 1, a GUI‐operable open‐source insect species identification, color processing, and image analysis software. This paper discusses our methods of algorithmic development, coupled to rigorous machine training used to enable high levels of validation accuracy.
Haleema Sadia, Parvez Alam
wiley +1 more source
The inclusion of habits in the stage model of self-regulated behavior change: an investigation of life events and red meat consumption in the UK. [PDF]
Whittle C+3 more
europepmc +1 more source
Red meat and colorectal cancer: a critical summary of prospective epidemiologic studies [PDF]
Dominik D. Alexander, Colleen A. Cushing
openalex +1 more source
Sampling a design space to target a class of possible desirable outcomes, creating an artificial intuition, can accelerate future optimizations to those targets. This is tested experimentally with parameterization to achieve various geometries of freestanding structures using direct ink write (DIW) 3D printing.
Erick J. Braham+4 more
wiley +1 more source
Metabolomics-based biomarkers of fermented dairy and red meat intake: a randomized controlled trial in healthy adults. [PDF]
La Barbera G+3 more
europepmc +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
The Association between the Substitution of Red Meat with Legumes and the Risk of Primary Liver Cancer in the UK Biobank: A Cohort Study. [PDF]
Bock N+4 more
europepmc +1 more source
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar+3 more
wiley +1 more source