Results 221 to 230 of about 143,034 (298)

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

open access: yesAdvanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica   +38 more
wiley   +1 more source

Cross‐Sectoral AI Integration Is Essential to Tackling Food Waste and Food Insecurity: A Roadmap for Developing Resilient Food Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Editorial: Innovation, technology and sustainability in sport management and education. [PDF]

open access: yesFront Sports Act Living
Van Den Berg L   +4 more
europepmc   +1 more source

Who Owns the Output? Authorship, Creative Labour, and Innovation Capability in Human‐AI Collaboration

open access: yesAI &Innovation, EarlyView.
ABSTRACT Generative AI is radically transforming how creative authorship is understood, attributed, and governed across the world’s cultural and creative industries. As AI systems increasingly produce outputs that organisations and audiences recognise as creative, foundational assumptions about who authors creative work, who receives credit for it, and
Ololade A. Shonubi
wiley   +1 more source

Causal analysis of trade loss from pathogens: A global study of foot and mouth disease impacts on meat exports

open access: yesAmerican Journal of Agricultural Economics, EarlyView.
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

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