This study highlights non-linear center-of-pressure features that enhance clinical assessment of fall risk in older adults, ...

A recent publication from IMDEA Materials Institute and the Technical University of Madrid (UPM) presents a major step ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...

Scientists have developed a new method to measure ocean surface currents over large areas in greater detail than ever before. Called GOFLOW (Geostationary Ocean Flow), the approach applies deep ...

Nine machine learning models—decision tree, random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), support vector machine, elastic net, logistic ...

Stock Price Prediction, Deep Learning, LSTM, GRU, Attention Mechanism, Financial Time Series Share and Cite: Kirui, D. (2026) ...

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

Researchers have developed an intelligent monitoring pipe that combines optical sensing with machine learning algorithms to monitor and predict 3D soil settlement. With more development, the system ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

A quantum system built from just nine atoms has outperformed classical artificial intelligence models containing thousands of ...

Can living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir ...