Results 71 to 80 of about 384,609 (355)

The Impacts of Health and Environmental Information Nudges on Meat Choices: Where Does Goat Meat Fit?

open access: yesAgribusiness, EarlyView.
ABSTRACT Amidst a recent surge in US goat meat imports to meet growing demand, this study contributes to the meat demand literature by examining consumer preferences for goat meat, a relatively healthy and environmentally friendly alternative to other popular meats.
Binod Khanal   +2 more
wiley   +1 more source

Swedish Consumers' Willingness‐to‐Pay for Plant‐Based Proteins in Pasta Sauce: Preferences and Policy Scenarios

open access: yesAgribusiness, EarlyView.
ABSTRACT This paper explores Swedish consumers' protein preferences by estimating the willingness‐to‐pay (WTP) for minced meat and plant‐based proteins in pasta sauce from an in‐store experiment (n = 206) and an online discrete choice experiment (n = 517). On average, the WTP was highest for minced meat.
Emilia Mattsson   +3 more
wiley   +1 more source

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

open access: yesAdvanced 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   +1 more
wiley   +1 more source

Controls on the composition of hydroxylated isoprenoidal glycerol dialkyl glycerol tetraethers (isoGDGTs) in cultivated ammonia-oxidizing Thaumarchaeota [PDF]

open access: yesBiogeosciences
Membrane lipids of ammonia-oxidizing Thaumarchaeota, in particular isoprenoidal glycerol dialkyl glycerol tetraethers (isoGDGTs) and hydroxylated isoGDGTs (OH-isoGDGTs), have been used as biomarkers and as proxies in various environments.
D. Varma   +8 more
doaj   +1 more source

A Molecular Approach to Explore the Background Benthic Fauna Around a Hydrothermal Vent and Their Larvae: Implications for Future Mining of Deep-Sea SMS Deposits

open access: yesFrontiers in Marine Science, 2020
Seafloor massive sulfide (SMS) deposits are commonly found at hydrothermal vents and recently gained the special interest of mining industries. These deposits contain valuable metals and methods are currently developed to mine deep sea SMS deposits ...
Lise Klunder   +8 more
doaj   +1 more source

Portrait of Philip H. Glatfelter in Glatfelter Hall

open access: yes, 2006
The first floor lobby of Glatfelter Hall is home to a Ned Bittinger oil painting portrait of Philip H. Glatfelter, the namesake of the building. Bittinger was commissioned in 1988 to paint the portraits of several Gettysburg College benefactors. Philip H.
Burg, Rachel L.
core  

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

open access: yesAdvanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

open access: yesAdvanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang   +4 more
wiley   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi   +5 more
wiley   +1 more source

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