Results 181 to 190 of about 2,729,090 (299)
As food insecurity and global food demands surge, artificial intelligence (AI)‐based technologies offer promising opportunities to reduce food loss and waste. In this perspective, current AI adoption across the food supply chain is assessed using various academic, industry, and policy sources.
Akansha Prasad +5 more
wiley +1 more source
Development and validation of a brief Nutrition Security Screener (NSS) for clinical and public health settings. [PDF]
Craig HC +14 more
europepmc +1 more source
Scientific opportunities for food and nutrition security [PDF]
Robin Fears +2 more
openaire +3 more sources
The Collective Power of Bacteria as a Blueprint for Emergent Intelligence
Small cells, powerful collectives. Bacteria demonstrate how sophisticated behaviors can emerge from many simple individuals working together. We explore the remarkable world of bacterial communities and the mechanisms that underpin their complex emergent behaviors, enabling impressive adaptability, robustness, and responsiveness to changing ...
Johanna A. Blee +2 more
wiley +1 more source
Fall armyworm infestation, maize production and nutrition security: Evidence from Uganda. [PDF]
Chisanga B, Kassie M.
europepmc +1 more source
This review highlights recent advances in automated iPSC culture systems integrating robotics, advanced imaging, artificial intelligence, and process control. These technologies improve reproducibility, scalability, and quality in cell expansion, differentiation, and real‐time monitoring, while emerging AI‐enabled and closed‐loop approaches offer new ...
Hyoryong Lee +3 more
wiley +1 more source
Food and Nutrition Security in the context of structural inequities: insights from Brazilian favelas. [PDF]
Rocha LL +4 more
europepmc +1 more source
A distributed wireless sensing framework enables noninvasive monitoring of plant salinity stress through leaf reflectance measurements acquired with portable optical sensors. The collected data are processed using TinyML‐based neural network models deployed at the edge, enabling accurate, real‐time, and low‐cost classification of salinity levels, while
Ali Ahmad +4 more
wiley +1 more source
Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman +1 more
wiley +1 more source

