Results 81 to 90 of about 48,695 (259)
Introduction Although the use of mobile health (mHealth) to promote tobacco control and smoking cessation interventions has been available in developed countries, their use in low- and middle-income countries (i.e. in China) is lacking.
Xiaoxiao Chen+ +9 more
doaj +1 more source
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
THE RELATIONSHIP BETWEEN EXPOSURE TO TEXTISM AND SPELLING COMPETENCY
The purpose of the study was to investigate the relationship between exposure to textism and spelling competency. A quasi-experimental research design was used to determine how the independent variable (exposure to textism) influenced the dependent ...
Sekgalabje Isaiah Ramaoka +2 more
doaj +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
BackgroundSleep disturbances and low physical activity are common among breast cancer (BC) survivors and are associated with increased morbidity and mortality.
Chi-shan Tsai +8 more
doaj +1 more source

