Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Optimization of Water-Nitrogen-Salinity Management for Improving Yield, Quality, and Resource Use Efficiency of Pigment Pepper Under Brackish Water Irrigation in Arid Regions. [PDF]
Yang X +5 more
europepmc +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
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
The response of wheat yield, water productivity, and partial factor productivity of nitrogen to straw return and biochar application: a global meta-analysis. [PDF]
Yang Z +7 more
europepmc +1 more source
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
Spatiotemporal complementarity synergistically drives high productivity in intercropping systems: a comparison of grain maize and fresh maize intercropped with soybean. [PDF]
Li J, Kong M, Zhang D, Huang M, Hao K.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Restoration pathways reshape forest structure and multifunctionality in subtropical plantations and secondary forests. [PDF]
Wu J, Xiang Q, Wang X, Zhou S, Lei J.
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
Ride the green: How does the national carbon market affect corporate breakthrough green innovation? [PDF]
Zhang L, Song Y.
europepmc +1 more source

