Results 161 to 170 of about 2,162,054 (361)

DECOMPOSING RED MEAT, POULTRY, AND FISH EXPENDITURES INTO AGE, TIME, AND COHORT EFFECTS [PDF]

This paper decomposes red meat, poultry, and fish consumption into cohort, age, and time effects. Younger cohorts spend less in real terms than older cohorts. These findings suggest strong implications for future consumption and nutrient intakes in the U.
Blisard, Noel, Harris, James Michael
core   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Family Food Consumption Studies [PDF]

Public Health Reports (1896-1970), 1952
openaire   +2 more sources

Farm Commodity Policy and Obesity [PDF]

Many commentators have claimed that farm subsidies have contributed significantly to the “obesity epidemic” by making fattening foods relatively cheap and abundant and, symmetrically, that taxing “unhealthy” commodities or subsidizing “healthy ...
Alston, Julian M., Okrent, Abigail M.
core   +1 more source

A Bespoke Programmable Interpenetrating Elastomer Network Composite Laryngeal Stent for Expedited Paediatric Laryngotracheal Reconstruction

Advanced Functional Materials, EarlyView.
A programmable interpenetrating double‐network architecture, created via 3D‐TIPS printing and resin infusion, synergistically combines thermoplastic and thermosetting elastomers to balance structural rigidity and surface softness—crucial for paediatric laryngeal stents.
Elizabeth F. Maughan, Lei Wu, Dong Zhang, Linxiao Wu, Graca Ferreira Vaz Pinto Mendes, Wanqiao J. Tu, Heping Ma, Toby J. Proctor, Colin R. Butler, Thomas Kjærgaard, Mark W. Lowdell, Martin A. Birchall, Robert E. Hynds, Richard Hewitt, Wenhui Song   +14 more
wiley   +1 more source

Consumption of Pork Products: Now and to the Year 2020 [PDF]

Data from the recent USDA's food consumption surveys are used to describe pork consumption patterns, to estimate a censored demand system for pork cuts, and to forecast pork consumption.
Davis, Christopher G., Lin, Biing-Hwan, Yen, Steven T.   +2 more
core   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

American Opinions of GM Food: Awareness, Knowledge, and Implications for Education [PDF]

Consumer/Household Economics, Food Consumption/Nutrition/Food Safety,
Hallman, William K., Hebden, W. Carl
core   +1 more source

European consumers preference and willingness to pay for food products labelled as obtained by a circular farming system -in relation to environmental attitudes and consumption behaviours

, 2023
Selene Ivette Ornelas Herrera, Zein Kallas   +1 more
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source