What if the mechanical properties of a cell could be programmed like the components of a machine? Researchers at the ...

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a ...

A study published in Nature Physics provides new molecular-level evidence from simulations that liquid water is not a single uniform substance, but a constantly shifting mixture of two distinct ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. The ...

Chinese scientists have shattered long-held beliefs about certain three-dimensional crystals by discovering and controlling ultratiny "linear" walls inside them, whose thickness and width are around ...

Researchers developed a machine-learning model that can predict the structures of transition states of chemical reactions in less than a second, with high accuracy. Their model could make it easier ...

The dimensionality of a system profoundly influences its physical behaviour, leading to the emergence of different states of matter in many-body quantum systems. In lower dimensions, fluctuations ...

Abstract: Subspace learning has been widely applied for feature extraction of hyperspectral images (HSIs) and achieved great success. However, the current methods still leave two problems that need to ...

Recent rapid advances in spatiotemporal optical pulses demand accurate characterization of the spatiotemporal structure of the produced light fields. We report an automated close-loop characterization ...

Frequent epileptic seizures cause damage to the human brain, resulting in memory impairment, mental decline, and so on. Therefore, it is important to detect epileptic seizures and provide medical ...