Deep learning (DL) architecture, which exploits multiple hidden layers to learn hierarchical
representations automatically from massive input data, presents a promising tool for …

A confidence interval is an interval estimate of a parameter of a population calculated from a
sample drawn from the population. Bootstrapping method, which involves producing several …

Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess
the level of confidence during prediction, as ML models are not inherently physical and can …

Research and development in nuclear reactor physics and thermal-hydraulics continue to
be vital parts of nuclear science and technology in Japan. The Fukushima accident not only …

Monitoring the health of lithium-ion batteries' internal components as they age is crucial for
optimizing cell design and usage control strategies. However, quantifying component-level …

The angiopoietin-Tie signaling pathway is an important vascular signaling pathway involved
in angiogenesis, vascular stability, and quiescence. Dysregulation in the pathway is linked …

Abstract Machine learning (ML) models are valuable research tools for making accurate
predictions. However, ML models often unreliably extrapolate outside their training data. The …

The assessment of temporal changes in glacier response due to climatic change is critical
from the hydrological perspective. The present study aims to identify temporal changes in …

This research advances urban resilience assessment beyond conventional social,
economic, environmental, and institutional dimensions by introducing a hybrid framework …

Bee farming and beehealth are threatened by climate change, agricultural and
agrochemicals intensification, and bee pests and diseases. Among these threats, bee pests …