Foreign labor, peer‐networking and agricultural efficiency in the Italian dairy sector
Abstract While the presence of immigrants in the agricultural sector is widely acknowledged, the empirical evidence on its economic consequences is lacking, especially from a microeconomic perspective. Using the Farm Accountancy Data Network panel data for Italian dairy farms in the period 2008–2018, the present study investigates the relationship ...
Federico Antonioli +2 more
wiley +1 more source
Bridging HIV prevention and sexual reproductive health services in the context of multi-method PrEP: a qualitative study exploring provider perceptions in South Africa. [PDF]
Musvipwa FM +8 more
europepmc +1 more source
The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen +6 more
wiley +1 more source
Production scheduling with multi-robot task allocation in a real industry 4.0 setting. [PDF]
Shakeri Z +4 more
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
A hybrid multi-level ant colony optimization framework for integrated production scheduling and vehicle routing. [PDF]
Ashour M +3 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Research on low carbon welding scheduling based on production process. [PDF]
Meng RH +6 more
europepmc +1 more source
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Static scheduling method for aircraft flat-tail assembly production based on improved bi-level genetic algorithm. [PDF]
Li T, Hua M, Wang J, Qin W.
europepmc +1 more source

