Globular clusters (GCs) formed when the Milky Way experienced a phase of rapid assembly.
We use the wealth of information contained in the Galactic GC population to quantify the …

Multiple codes are available to derive atmospheric parameters and individual chemical
abundances from high-resolution spectra of AFGKM stars. Almost all spectroscopists have …

With the advances in artificial intelligence (AI), data‐driven algorithms are becoming
increasingly popular in the medical domain. However, due to the nonlinear and complex …

Exhaled breath analysis has become more and more popular as a supplementary tool for
medical diagnosis. However, the number of variables that have to be taken into account …

Measuring and assessing the cognitive load associated with different tasks is crucial for
many applications, from the design of instructional materials to monitoring the mental well …

The SARS-CoV-2 virus like many other viruses has transformed in a continual manner to
give rise to new variants by means of mutations commonly through substitutions and indels …

Deep neural networks usually require large labeled datasets to construct accurate models;
however, in many real-world scenarios, such as medical image segmentation, labeling data …

Tests of general relativity with gravitational waves typically introduce parameters for putative
deviations and combine information from multiple events by characterizing the population …

We propose a highly efficient and accurate numerical scheme named the truncated atomic
plane wave method to determine the subband structure of twisted bilayer graphene (TBG) …

We develop a supervised machine learning algorithm that is able to learn topological
phases of finite condensed-matter systems from bulk data in real lattice space. The algorithm …